gcmfaces/0000755000435400001440000000000012375431052012207 5ustar gforgetusersgcmfaces/gcmfaces_misc/0000755000435400001440000000000012375431055014775 5ustar gforgetusersgcmfaces/gcmfaces_misc/ccaa.m0000644000435400001440000000007611600706727016046 0ustar gforgetusers%abbreviation for clear all; close all; clear all; close all; gcmfaces/gcmfaces_misc/convertR8toR4.m0000644000435400001440000000046411600706727017623 0ustar gforgetusersfunction []=convertR8toR4(fileIn,fileOut); %object: read R8 fileIn, write R4 fileOut %inputs: fileIn and fileOut tmp1=dir(fileIn); tmp1=tmp1.bytes/8; fid=fopen(fileIn,'r','b'); tmp2=fread(fid,tmp1,'float64'); fclose(fid); fid=fopen(fileOut,'w','b'); fwrite(fid,tmp2,'float32'); fclose(fid); gcmfaces/gcmfaces_misc/depthStretch.m0000644000435400001440000000204111600706727017612 0ustar gforgetusersfunction [z]=depthStretch(d,varargin) %object: compute stretched depth coordinate %inputs: d is the depth vector (>=0) %optional: depthStretchLim are the stretching depth limits ([0 500 6000] by default) % %this routine maps %[depthStretchLim(1) depthStretchLim(2)] to [1 0] %[depthStretchLim(2) depthStretchLim(3)] to [0 -1] if nargin>1; depthStretchLim=varargin{1}; else; depthStretchLim=[0 500 6000]; end; zStretchLim=[1 0 -1]; %make sure depth is positive d=abs(d); %initialize stretched vertical coordinate z=zeros(size(d)); %values between 0 and depthStretchLim(2) get half the range of z tmp1=find(d<=depthStretchLim(2)); tmp2=(depthStretchLim(2)-d(tmp1))./(depthStretchLim(2)-depthStretchLim(1))... .*(zStretchLim(1)-zStretchLim(2))+zStretchLim(2); z(tmp1)=tmp2; %values between depthStretchLim(2) and depthStretchLim(3) get the other half z range tmp1=find(d>depthStretchLim(2)); tmp2=(d(tmp1)-depthStretchLim(2))./(depthStretchLim(3)-depthStretchLim(2))... .*(zStretchLim(3)-zStretchLim(2))+zStretchLim(2); z(tmp1)=tmp2; gcmfaces/gcmfaces_misc/sym_g.m0000644000435400001440000000331212266577513016301 0ustar gforgetusersfunction [field_out]=sym_g(field_in,sym_in,op_in); %apply symmetry in the complex plane to field_in(z) % where field_in and z are in the complex arrays. %then, depending on op_in, we apply a compensating operation % %format of field_in: % z(1,:) is z=-1+?i, z(end,:) is z=1+?i % z(:,1) is z=?-i, z(:,end) is z=?+i % %sym_in: 1,2,3,4 are reflexions about x=0,y=0,x=y,x=-y % 4+nRot is rotation by nRot*pi/2 % 0 just returns the input field as output %op_in: 1 apply the opposite complex operation field_out=field_in; if isempty(whos('op_in')); op_in=0; end; if sym_in==0; %do nothing elseif sym_in==1; field_out=flipdim(field_in,1); if op_in==1; field_out=-real(field_out)+i*imag(field_out); end; elseif sym_in==2; field_out=flipdim(field_in,2); if op_in==1; field_out=real(field_out)-i*imag(field_out); end; elseif sym_in==3; field_out=permute(field_in,[2,1,3,4]); if op_in==1; field_out=imag(field_out)+i*real(field_out); end; elseif sym_in==4; field_out=flipdim(permute(flipdim(field_in,1),[2,1,3,4]),1); if op_in==1; field_out=-imag(field_out)-i*real(field_out); end; elseif sym_in>=5&sym_in<=7; for icur=1:sym_in-4; field_out=flipdim(permute(field_out,[2,1,3,4]),1); if op_in==1; field_out=i*field_out; end; end else; fprintf('error in sym_g2\n'); return; end; %for test case: %-------------- %xx=[1:10]'*ones(1,10); yy=xx'; %zz=zeros(10,10); zz(1:2,1:3)=1; zz(8,9)=2; zz(2,6:8)=-1; zz(7,3)=-2; %sym_g(zz,1); %etc %with the following uncommented: %------------------------------- %figure; %subplot(2,2,1); imagesc(field_in); %subplot(2,2,4); imagesc(field_out); %xlabel('y'); xlabel('x'); gcmfaces/gcmfaces_misc/convertR4toR4nonan.m0000644000435400001440000000053211600706727020645 0ustar gforgetusersfunction []=convertR4toR4nonan(fileIn,fileOut); %object: read R4 fileIn, replace NaN with 0, write R4 fileOut %inputs: fileIn and fileOut tmp1=dir(fileIn); tmp1=tmp1.bytes/4; fid=fopen(fileIn,'r','b'); tmp2=fread(fid,tmp1,'float32'); fclose(fid); tmp2(find(isnan(tmp2)))=0; fid=fopen(fileOut,'w','b'); fwrite(fid,tmp2,'float32'); fclose(fid); gcmfaces/gcmfaces_misc/diff_mat.m0000644000435400001440000000626011625550015016723 0ustar gforgetusersfunction [report0]=diff_mat(file1,dir2,varargin); %object: compute the %rms difference between fields in two mat files %inputs: file1 is the file to compare with a reference % dir2 is the reference file directory %optional: file2 is the reference file (file1 by default) %output: cell array containing the % rms difference display per field if nargin>2; file2=varargin{1}; else; file2=file1; end; new=open(file1); old=open([dir2 file2]); %new list of fields: %=================== IInew=fieldnames(new); NInew=length(IInew); %extend to structure fields: JJ={}; for ii=1:NInew; tmp0=IInew{ii}; tmp1=getfield(new,tmp0); if isstruct(tmp1); tmp2=fieldnames(tmp1); for jj=1:length(tmp2); JJ{length(JJ)+1}=[tmp0 '.' tmp2{jj}]; end; else; JJ{length(JJ)+1}=tmp0; end; end; %overwrite list of fields: IInew=JJ; NInew=length(IInew); %old list of fields: %=================== IIold=fieldnames(old); NIold=length(IIold); %extend to structure fields: JJ={}; for ii=1:NIold; tmp0=IIold{ii}; tmp1=getfield(old,tmp0); if isstruct(tmp1); tmp2=fieldnames(tmp1); for jj=1:length(tmp2); JJ{length(JJ)+1}=[tmp0 '.' tmp2{jj}]; end; else; JJ{length(JJ)+1}=tmp0; end; end; %overwrite list of fields: IIold=JJ; NIold=length(IIold); %compare new to old fields: %========================== report0={}; report1={}; for ii=1:NInew; test0=isempty(find(strcmp(IIold,IInew{ii}))); test1=strfind(IInew{ii},'gcm2faces'); if test0; txt0=sprintf(['new contains ' IInew{ii} ' BUT ref does not']); report1{length(report1)+1,1}=txt0; elseif test1; txt0=sprintf(['test of ' IInew{ii} ' was omitted']); report1{length(report1)+1,1}=txt0; else; tmp0=IInew{ii}; tmp00=strfind(tmp0,'.'); if isempty(tmp00); %get the field: tmp1=getfield(new,IInew{ii}); tmp2=getfield(old,IInew{ii}); elseif length(tmp00)==1; %get the sub field: tmp11=IInew{ii}(1:tmp00-1); tmp1=getfield(new,tmp11); tmp2=getfield(old,tmp11); tmp11=IInew{ii}(tmp00+1:end); tmp1=getfield(tmp1,tmp11); tmp2=getfield(tmp2,tmp11); else; error(sprintf('cannot compare %s',tmp0)); end; %do the comparison: if isa(tmp1,'double')|isa(tmp1,'gcmfaces'); %add blanks for display: tmp11=ceil(length(tmp0)/10)*10-length(tmp0); tmp11=char(32*ones(1,tmp11)); %compute difference: tmp22=nanstd(tmp1(:))^2; if tmp22==0; tmp22=nanmean( tmp1(:).^2 ); end; tmp22=100*sqrt(nanmean( (tmp1(:)-tmp2(:)).^2 )./tmp22); %full text for display: txt0=[tmp0 tmp11]; %txt0=sprintf('%s differs by %i%% from %s',txt0,round(tmp22),[dir2 file2]); txt0=sprintf('%s diff by %i%%',txt0,round(tmp22)); %do display: if tmp22~=0; fprintf([txt0 '\n']); end; %add to report: report0{length(report0)+1,1}=txt0; end; end; end; %compare old field to new fields: %================================ report2={}; for ii=1:NIold; test0=~isempty(find(strcmp(IInew,IIold{ii}))); if ~test0; txt0=sprintf(['ref contains ' IIold{ii} ' BUT new does not']); report2{length(report2)+1,1}=txt0; end; end; %combine the various reports: %============================ report0={report0{:} report1{:}}'; report0={report0{:} report2{:}}'; gcmfaces/gcmfaces_misc/disp_budget_mean_zonal.m0000644000435400001440000000327012276600407021650 0ustar gforgetusersfunction []=disp_budget_mean_zonal(lat,budg,uni,tit); %object : plot a budget from budget_integr %inputs: lat is the latitude vector % budg is the result of budget_integr (in e.g. m^3/s) % uni is the unit to be displayed % tit is the variable description to be displayed %display: cumulative sum of budg*median(dt) gcmfaces_global; global myparms; %scaled the budget terms, and integrate in time: nyears=[myparms.yearInAve(2)-myparms.yearInAve(1)]; dt=365*86400*nyears; cont=sum(dt*budg(1,:,:),3); hdiv=sum(dt*budg(2,:,:),3); zdiv=sum(dt*budg(3,:,:),3); %do the plotting: plot(lat,cont,'b','LineWidth',1); hold on; plot(lat,zdiv,'r','LineWidth',1); plot(lat,hdiv,'g','LineWidth',1); plot(lat,cont-zdiv-hdiv,'k','LineWidth',1); %finish the plot: tmp1=max(abs(cont)); tmp2=max(abs(zdiv)); tmp3=max(tmp1,tmp2)*1.5; if tmp3~=0&std(lat)~=0; axis([min(lat) max(lat) -tmp3 tmp3]); end; grid on; legend('content','vert. div.','hor. div.','residual','Orientation','horizontal'); res=sqrt(mean((cont-zdiv-hdiv).^2)); title(sprintf('Budget %s scaled by %d years; in %s; residual : %0.1e',tit,nyears,uni,res)); %set the axis range : symmetric about 0 and rounded up aa=axis; tmp1=max(abs(hdiv)); tmp2=ceil(log10(tmp1)); tmp2=10^tmp2; tmp3=2*tmp2*round(tmp1/tmp2*10)/10; if ~isnan(tmp3); aa(3:4)=tmp3*[-1 1]; end; axis(aa); %print to screen: if ~isempty(strfind(tit,'Mass')); tmp0='Mass'; elseif ~isempty(strfind(tit,'Heat')); tmp0='Heat'; elseif ~isempty(strfind(tit,'Salt')); tmp0='Salt'; else; tmp0='????'; end; tmp1=round(log10(sqrt(mean((cont).^2)))); tmp2=round(log10(sqrt(mean((cont-zdiv-hdiv).^2)))); fprintf('%5s budget [log10(cont) | log10(res)] %3i | %3i\n',tmp0,tmp1,tmp2); gcmfaces/gcmfaces_misc/figureL.m0000644000435400001440000000021212023440611016527 0ustar gforgetusers %figure; set(gcf,'Units','Normalized','Position',[0.1 0.2 0.8 0.8]); figure; set(gcf,'Units','Normalized','Position',[0. 0.2 0.4 0.8]); gcmfaces/gcmfaces_misc/runmean.m0000644000435400001440000000526511626253126016627 0ustar gforgetusersfunction [fldOut]=runmean(fldIn,halfWindow,dim,varargin); %object: compute running mean window ('rmw') over a dimension %input: fldIn is the field to which the rmw will be applied % halfWindow is the half width of the rmw % dim is the dimension over which the rmw will be applied %optional: doCycle states whether the boundary condition is cyclic (1) or % not (0; default). If doCycle==0, the no. of averaged points % decreases from 1+2*halfWindow to halfWindow at the edges, % and we mask all of those edge points with NaNs. %output: fldOut is the resulting field % %notes: - NaNs are discarded in the rmw, implying that an average is % computed if the rmw contains at least 1 valid point. % - setting halfWindow to 0 implies fldOut=fldIn. %determine and check a couple things fld_isa_gcmfaces=isa(fldIn,'gcmfaces'); if fld_isa_gcmfaces; if dim<3; error('for gcmfaces objects runmean excludes dim=1 or 2'); end; end; if nargin==3; doCycle=0; else; doCycle=varargin{1}; end; %switch to array format if needed if fld_isa_gcmfaces; fldIn=convert2array(fldIn); end; %switch dim to first dimension sizeIn=size(fldIn); perm1to2=[1:length(sizeIn)]; perm1to2=[dim perm1to2(find(perm1to2~=dim))]; perm2to1=[[1:dim-1]+1 1 [dim+1:length(sizeIn)]]; sizeIn2=sizeIn(perm1to2); fldIn=permute(fldIn,perm1to2); sizeCur=size(fldIn); if ~doCycle; %add NaNs at both edges sizeCur(1)=sizeCur(1)+2*halfWindow; fldIn2=NaN*ones(sizeCur); fldIn2(halfWindow+1:end-halfWindow,:,:,:)=fldIn; fldIn=fldIn2; clear fldIn2; end; %create mask and remove NaNs: fldMsk=~isnan(fldIn); fldIn(isnan(fldIn))=0; fldCnt=0*fldIn; %apply the running mean fldOut=zeros(sizeCur); for tcur=-halfWindow:halfWindow %To have halfWindow*2 coeffs rather than halfWindow*2+1, centered to the current %point, it is convenient to reduce the weight of the farthest points to 1/2. %This became necessary to get proper annual means, from monthly data, with halfWindow=6. if abs(tcur)==halfWindow; fac=1/2; else; fac=1; end; tmp1=circshift(fldIn,[tcur zeros(1,length(sizeCur)-1)]); fldOut=fldOut+fac*tmp1; tmp1=circshift(fldMsk,[tcur zeros(1,length(sizeCur)-1)]); fldCnt=fldCnt+fac*tmp1; end fldCnt(fldCnt<2*halfWindow)=NaN; fldOut=fldOut./fldCnt; if ~doCycle; fldOut=fldOut(halfWindow+1:end-halfWindow,:,:,:); %consistent with old version bug (one point offset) % fldOut=fldOut(halfWindow:end-halfWindow,:,:,:); end; %switch dimensions order back to original order fldOut=permute(fldOut,perm2to1); %switch back to gcmfaces format if needed if fld_isa_gcmfaces; fldOut=convert2array(fldOut); end; gcmfaces/gcmfaces_misc/input_list_check.m0000644000435400001440000000435712357056601020513 0ustar gforgetusersfunction []=input_list_check(myFunction,myNargin); %object: print warning/error messages related to % changes in arguments lists (June 2011). %inputs: myFunction: name of the calling routine % myNargin: number of arguments passed to the calling routine if strcmp(myFunction,'convert2gcmfaces')&myNargin~=1; warning('inputCheck:convert2gcmfaces',... ['As of june 2011, convert2gcmfaces.m expects only \n' ... ' one input argument. The others were dismissed.\n' ... ' Type ''help convert2gcmfaces'' for details.']); end; if strcmp(myFunction,'convert2array')&myNargin~=1; warning('inputCheck:convert2array',... ['As of june 2011, convert2array.m expects only \n' ... ' one input argument. The other ones are dismissed.\n' ... ' Type ''help convert2array'' for details.']); end; if strcmp(myFunction,'convert2pcol')&myNargin~=3; warning('inputCheck:convert2pcol',... ['As of june 2011, convert2pcol.m expects only \n' ... ' three input arguments. The other ones are dismissed.\n' ... ' Type ''help convert2pcol'' for details.']); end; if strcmp(myFunction,'plot_one_field')&myNargin~=2; error('inputCheck:plot_one_field',... ['As of june 2011, plot_one_field.m is a \n' ... 'function with two input argument. \n'... 'Type ''help plot_one_field'' for details.\n']); end; if strcmp(myFunction,'plot_std_field')&myNargin~=1; error('inputCheck:plot_std_field',... ['As of june 2011, plot_std_field.m is a \n' ... 'function with one input argument. \n'... 'Type ''help plot_std_field'' for details.\n']); end; if strcmp(myFunction,'basic_diags_compute_v3_or_v4')&myNargin~=1; error('inputCheck:basic_diags_compute_v3_or_v4',... ['As of june 2011, basic_diags_compute_v3_or_v4.m is a \n' ... 'function with one input argument. \n'... 'Type ''help basic_diags_compute_v3_or_v4'' for details.\n']); end; if strcmp(myFunction,'basic_diags_display_v3_or_v4')&myNargin~=1; error('inputCheck:basic_diags_display_v3_or_v4',... ['As of june 2011, basic_diags_display_v3_or_v4.m is a \n' ... 'function with one input argument. \n'... 'Type ''help basic_diags_display_v3_or_v4'' for details.\n']); end; gcmfaces/gcmfaces_misc/disp_budget_mean_mask.m0000644000435400001440000000323512072655270021463 0ustar gforgetusersfunction []=disp_budget_mean_mask(tim,budg,uni,tit); %object : plot a budget from budget_integr %inputs: tim is the time vector (in days) % budg is the result of budget_integr (in e.g. m^3/s) % uni is the unit to be displayed % tit is the variable description to be displayed %display: cumulative sum of budg*median(dt) %scale the budget terms, and integrate in time: dt=365.25*median(diff(tim));%in days if isnan(dt); dt=1; end;%assume annual mean dt=dt*86400;%in seconds cont=dt*cumsum(budg(1,:)); hdiv=dt*cumsum(budg(2,:)); zdiv=dt*cumsum(budg(3,:)); %do the plotting: plot(tim,cont,'b','LineWidth',1); hold on; plot(tim,zdiv,'r','LineWidth',1); plot(tim,hdiv,'g','LineWidth',1); plot(tim,cont-zdiv-hdiv,'k','LineWidth',1); %finish the plot: tmp1=max(abs(cont)); tmp2=max(abs(zdiv)); tmp3=max(tmp1,tmp2)*1.5; if tmp3~=0&std(tim)~=0; axis([min(tim) max(tim) -tmp3 tmp3]); end; grid on; legend('content','vert. div.','hor. div.','residual','Orientation','horizontal'); res=sqrt(mean((cont-zdiv-hdiv).^2)); title(sprintf('Budget %s; in %s; residual : %0.1e',tit,uni,res)); %set the axis range : symmetric about 0 and rounded up aa=axis; tmp1=max(abs(cont)); tmp2=ceil(log10(tmp1)); tmp2=10^tmp2; tmp3=2*tmp2*round(tmp1/tmp2*10)/10; if ~isnan(tmp3); aa(3:4)=tmp3*[-1 1]; end; axis(aa); %print to screen: if ~isempty(strfind(tit,'Mass')); tmp0='Mass'; elseif ~isempty(strfind(tit,'Heat')); tmp0='Heat'; elseif ~isempty(strfind(tit,'Salt')); tmp0='Salt'; else; tmp0='????'; end; tmp1=round(log10(sqrt(mean((cont).^2)))); tmp2=round(log10(sqrt(mean((cont-zdiv-hdiv).^2)))); fprintf('%5s budget [log10(cont) | log10(res)] %3i | %3i\n',tmp0,tmp1,tmp2); gcmfaces/gcmfaces_misc/density.m0000644000435400001440000000612311625550015016627 0ustar gforgetusersfunction [RHOP,RHOIS,RHOR] = density(TN,SN,GDEPT,ZREF) % [RHOP,RHOIS,RHOR] = density(Tpot,S,P,PREF) % % Adapted from OPA, subroutine EOS.F (bferron@ifremer.fr) % % ROUTINE EOS % ******************* % % PURPOSE : % ------- % COMPUTE THE POTENTIAL DENSITY RHOP, IN SITU DENSITY RHOIS, AND, IF A % REFERENCE LEVEL PREF IS SPECIFIED, THE DENSITY RHOR REFERENCED TO PREF % FROM POTENTIAL TEMPERATURE AND SALINITY FIELDS. % % IMPORTANT NOTE: This version minimize the deviations of in-situ % density compared to the UNESCO equation within % [0-4500]dbars!!!!!! It is the version used in OPA % (differences < 2e-4 kg/m3) % Below 6000 dbar , differences are > 1e-3 kg/m-3 % % METHOD : % ------ % JACKETT AND McDOUGALL (1994) EQUATION OF STATE % ********************* % THE IN SITU DENSITY IS COMPUTED DIRECTLY AS A FUNCTION OF % POTENTIAL TEMPERATURE RELATIVE TO THE SURFACE, SALT AND PRESSURE % % % RHO(T,S,P) % % WITH PRESSURE P DECIBARS % POTENTIAL TEMPERATURE T DEG CELSIUS % SALINITY S PSU % DENSITY RHO KG/M**3 % % CHECK VALUE: RHO = 1.04183326 KG/M**3 FOR P=10000 DBAR, % T = 40 DEG CELCIUS, S=40 PSU % % % JACKETT AND McDOUGALL (1994) FORMULATION %-------------------------------------------- % %... potential temperature, salinity and depth ZT = TN; ZS = SN; if size(TN,2)>1 & size(TN,1)>1 & size(TN,1)==length(GDEPT) ZH = GDEPT*ones(1,size(ZT,2)); % comented 13/04/99 for WHP Thorpe calc. elseif size(TN,2)>1 & size(TN,1)>1 & size(TN,2)==length(GDEPT) ZH = ones(size(ZT,1),1) *GDEPT'; elseif sum(size(TN))==2 ZH = ones(size(TN))*GDEPT; else ZH = GDEPT; % Added 13/04/99 for WHP Thorpe calc. end %... square root salinity ZSR= sqrt(ZS); %... compute density pure water at atm pressure ZR1= ((((6.536332E-9*ZT-1.120083E-6).*ZT+1.001685E-4).*ZT ... -9.095290E-3).*ZT+6.793952E-2).*ZT+999.842594; %... seawater density atm pressure ZR2= (((5.3875E-9*ZT-8.2467E-7).*ZT+7.6438E-5).*ZT ... -4.0899E-3).*ZT+0.824493; ZR3= (-1.6546E-6*ZT+1.0227E-4).*ZT-5.72466E-3; ZR4= 4.8314E-4; % %... potential density (referenced to the surface) RHOP= (ZR4*ZS + ZR3.*ZSR + ZR2).*ZS + ZR1; % %... add the compression terms ZE = (-3.508914E-8*ZT-1.248266E-8).*ZT-2.595994E-6; ZBW= ( 1.296821E-6*ZT-5.782165E-9).*ZT+1.045941E-4; ZB = ZBW + ZE .* ZS; % ZD = -2.042967E-2; ZC = (-7.267926E-5*ZT+2.598241E-3).*ZT+0.1571896; ZAW= ((5.939910E-6*ZT+2.512549E-3).*ZT-0.1028859).*ZT-4.721788; ZA = ( ZD*ZSR + ZC).*ZS + ZAW; % ZB1= (-0.1909078*ZT+7.390729).*ZT-55.87545; ZA1= ((2.326469E-3*ZT+1.553190).*ZT-65.00517).*ZT+1044.077; ZKW= (((-1.361629E-4*ZT-1.852732E-2).*ZT-30.41638).*ZT ... +2098.925).*ZT+190925.6; ZK0= (ZB1.*ZSR + ZA1).*ZS + ZKW; % %... in situ density RHOIS = RHOP ./ (1.0-ZH./(ZK0-ZH.*(ZA-ZH.*ZB))); %... density referenced to level ZREF if nargin==4 RHOR = RHOP ./ (1.0-ZREF./(ZK0-ZREF.*(ZA-ZREF.*ZB))); end gcmfaces/gcmfaces_misc/depthStretchPlot.m0000644000435400001440000000274111600706727020460 0ustar gforgetusersfunction [varargout]=depthStretchPlot(plotName,plotData,varargin); %object: front end to plot/pcolor/etc. using a stretched depth coordinate (see depthStretch.m) %inputs: plotName is the name of the plotting routine (e.g. 'pcolor') % plotData is the list or arguments to pass over to the plotting routine % in a cell array (e.g. {depth,time,temperature}), with the % depth coordinate coming second (as usual for plot/pcolor/etc.) %optional: depthTics is the vector of yTics depths % depthStretchLim are the stretching depth limits ([0 500 6000] by default) % to pass over to depthStretch (type 'help depthStretch' for details). % %notes: the depth coordinate must be first in plotData %get depthStretchDef if provided if nargin>2; depthTics=varargin{1}; else; depthTics=[0:100:500 750 1000:500:6000]; end; if nargin>3; depthStretchDef=varargin{2}; else; depthStretchDef=[0 500 6000]; end; %replace it with stretched coordinate: plotData{2}=depthStretch(abs(plotData{2}),depthStretchDef); %do the very plot: eval(['h=' plotName '(plotData{:});']); %take care of depth tics in stretched coordinate: depthTics=sort(depthTics,'descend'); depthTicsLabel=[]; for kkk=1:length(depthTics) depthTicsLabel=strvcat(depthTicsLabel,num2str(depthTics(kkk))); end depthTics=depthStretch(depthTics,depthStretchDef); set(gca,'YTick',depthTics); set(gca,'YTickLabel',depthTicsLabel); %output plot handle: if nargout>0; varargout={h}; end; gcmfaces/gcmfaces_misc/annualmean.m0000644000435400001440000000416412023434027017267 0ustar gforgetusersfunction [myMean,myAnom]=annualmean(myTimes,myFld,myYear); %object: compute an annual mean for myYear (= 'first','last',n (int) or 'all') % of a gcmfaces or array object (myFld) provided at myTimes (in years) %input: myTimes,myFld,myYear %output: myMean if the corresponding time mean % (optional: myAnom is myFld-myMean) % %algorithm : % - determine the number of records in one year (lYear) % - determine the number of full years (nYears) % - prepare list of records to average (depending on myYear, lYear and nYears) % - in case when lYear<2 we use records as years % %by assumption: % - the time dimension is last in myFld, and matches the length of myTimes %determine the number of records in one year (lYear) tmp1=mean(myTimes(2:end)-myTimes(1:end-1)); lYear=round(1/tmp1); %in case when lYear<2 we use records as years if ~(lYear>=2); lYear=1; myTimes=[1:length(myTimes)]; end; %determine the number of full years (nYears) nYears=floor(length(myTimes)/lYear); %determine records that correspond to myYear, which % may be 'first','last',n (an integer) or 'all' if ischar(myYear); if strcmp(myYear,'first'); recInAve=[1:lYear]; elseif strcmp(myYear,'last'); recInAve=[1:lYear]+(nYears-1)*lYear; elseif strcmp(myYear,'all'); recInAve=[1:nYears*lYear]; else; error('inconsistent specification of myYear'); end; elseif (myYear>=1)&(myYear<=nYears); recInAve=[1:lYear]+(myYear-1)*lYear; else; error('inconsistent specification of myYear'); end; nRecs=length(recInAve); %determine last dimension, which need to match the length myTimes if strcmp(class(myFld),'gcmfaces'); nDim=size(myFld{1}); else; nDim=size(myFld); end; if length(myTimes)>1; if nDim(end)~=length(myTimes); error('last dimension should match the length of myTimes'); end; nDim=length(nDim); tt=''; for jj=1:nDim-1; tt=[tt ':,']; end; else; nDim=length(nDim)+1; tt=''; for jj=1:nDim-1; tt=[tt ':,']; end; end; %compute time mean: eval(['myMean=mean(myFld(' tt 'recInAve),nDim);']); %compute anomaly: if nargout>1; myAnom=myFld-repmat(myMean,[ones(1:nDim-1) length(myTimes)]); end; gcmfaces/gcmfaces_misc/write2tex.m0000644000435400001440000001215712365534166017124 0ustar gforgetusersfunction []=write2tex(myFile,myStep,varargin); %object: create/increment/complete/compile a tex file from within matlab %input: myFile is the file name % myStep is the operation to perform on the tex file % 0 create file starting with title page (see myText) % 1 add section or subsection (see myLev) % 2 add a figure plus caption (see myFig) % 3 add a paragraph % 4 finish file % 5 compile (latex x 2 then dvipdf) % 6 remove temporary files (incl. *fig*.ps) %optional myText is a cell array of text lines (for myStep=1 to 2) % myLev is the title level (for myStep=1) % 1=section, 2=subsection (not yet implemented) % myFig is a figure handle (for myStep=2) if isempty(myFile); %if no file name, then do nothing return; end; if iscell(myFile); %extecute alternative command (myFile{1}) passing rest as arguments eval([myFile{1} '(myFile{2:end});']); return; end; myText=[]; myLev=[]; myFig=[]; myRdm=[]; if myStep<4; myText=varargin{1}; end; if myStep==0; myRdm=varargin{2}; elseif myStep==1; myLev=varargin{2}; elseif myStep==2; myFig=varargin{2}; end; %create file starting with write2tex.header if myStep==0; test0=dir(myFile); if ~isempty(test0); test0=input(['you are about to overwrite ' myFile ' !!! \n type 1 to proceed, 0 to stop \n']); else; test0=1; end; if ~test0; return; else; fid=fopen(myFile,'w'); fprintf(fid,'\\documentclass[12pt]{beamer}\n'); fprintf(fid,'%%a nice series of examples for the beamer class:\n'); fprintf(fid,'%%http://www.informatik.uni-freiburg.de/~frank/ENG/beamer/example/beamer-class-example-en-5.html\n'); fprintf(fid,'\\usepackage{multicol}\n'); fprintf(fid,'\n'); fprintf(fid,'\\newcommand\\Fontvi{\\fontsize{6}{7.2}\\selectfont}\n'); fprintf(fid,'\n'); fprintf(fid,'\\begin{document} \n\n'); fprintf(fid,'\\title{\n'); for ii=1:length(myText); fprintf(fid,[myText{ii} '\\\\ \n']); end; fprintf(fid,'}\n\n'); fprintf(fid,'\\date{\\today}\n\n'); fprintf(fid,'\\frame{\\titlepage}\n\n'); fprintf(fid,'\\frame{\n'); fprintf(fid,'\\frametitle{Table of contents}\n'); fprintf(fid,'\\begin{multicols}{2}\n'); fprintf(fid,'\\Fontvi\n'); fprintf(fid,'\\tableofcontents\n'); fprintf(fid,'\\end{multicols}\n'); fprintf(fid,'} \n\n'); if ~isempty(myRdm); fprintf(fid,'\\frame{\n'); fprintf(fid,'\\section{README}\n'); fprintf(fid,'\\Fontvi\n'); for pp=1:length(myRdm); fprintf(fid,[myRdm{pp} '\n\n']); end; fprintf(fid,'} \n\n'); end; fclose(fid); end; myFigNumTex=0; mySection=''; eval(['save ' myFile(1:end-4) '.mat myFigNumTex mySection;']); end; %open file and go to last line fid=fopen(myFile,'a+'); eval(['load ' myFile(1:end-4) '.mat;']); %add title or section page (see myLev) if myStep==1; mySection=myText; if myLev==1; fprintf(fid,'\\section{\n'); else; fprintf(fid,'\\subsection{\n'); end; fprintf(fid,mySection); fprintf(fid,'} \n\n'); end; %add a figure plus caption (see myFig) if myStep==2; figure(myFig); drawnow; myFigNumTex=myFigNumTex+1; nn=strfind(myFile,filesep); if ~isempty(nn); dirTex=myFile(1:nn(end)); fileTex=myFile(nn(end)+1:end-4); else; dirTex='./'; fileTex=myFile(1:end-4) end; %print the very figure print(myFig,'-depsc',[dirTex fileTex '.fig' num2str(myFigNumTex)]); close; %add figure to text file fprintf(fid,'\\frame{ \n'); fprintf(fid,['\\frametitle{' mySection '} \n']); fprintf(fid,'\\begin{figure}[tbh] \\centering \n'); % fprintf(fid,'\\includegraphics[width=\\textwidth,height=0.9\\textheight]'); fprintf(fid,'\\includegraphics[width=0.75\\textwidth]'); fprintf(fid,['{' fileTex '.fig' num2str(myFigNumTex) '}\n']); fprintf(fid,'\\caption{'); for ii=1:length(myText); fprintf(fid,[myText{ii} '\n']); end; fprintf(fid,'} \\end{figure} \n'); fprintf(fid,'} \n\n'); end; %add a paragraph if myStep==3; for ii=1:length(myText); fprintf(fid,[myText{ii} '\n']); end; end; %finish file if myStep==4; fprintf(fid,'\n\n \\end{document} \n\n'); end; %close file fprintf(fid,'\n\n'); fclose(fid); eval(['save ' myFile(1:end-4) '.mat myFigNumTex mySection;']); %compile if myStep==5; dirOrig=pwd; nn=strfind(myFile,filesep); if ~isempty(nn); cd(myFile(1:nn(end))); fileTex=myFile(nn(end)+1:end-4); else; fileTex=myFile(1:end-4); end; system(['latex ' fileTex]); system(['latex ' fileTex]); system(['dvipdf ' fileTex]); cd(dirOrig); end; %compile if myStep==6&ispc; fprintf('warning : compiling tex to pdf is bypassed on PCs\n'); end; if myStep==6&~ispc; dirOrig=pwd; nn=strfind(myFile,filesep); if ~isempty(nn); cd(myFile(1:nn(end))); fileTex=myFile(nn(end)+1:end-4); else; fileTex=myFile(1:end-4); end; delete([fileTex '.fig*']); delete([fileTex '.aux']); delete([fileTex '.log']); delete([fileTex '.out']); delete([fileTex '.dvi']); cd(dirOrig); end; gcmfaces/gcmfaces_misc/gcmfaces_msg.m0000644000435400001440000000675411650105265017601 0ustar gforgetusersfunction [msgOut]=gcmfaces_msg(msgIn,headerOut,widthOut); %object: print formatted message to screen %input: msgIn is a char or a cell array of char %optional: headerOut is the header(default: no header if % myenv.verbose<2; calling tree if myenv.verbose>=2) % widthOut is the line width (75 by default) %output: msgOut is a char where line breaks were set % so that all lines have approx. the same width. %note: could also introduce form feeds (page break for print) or %test case: % msgIn={'xxxx \ryy\tzz\n' ['1 ' char(9) '2' char(10) '3' char(11) '4' char(12) '5']} % widthOut=3; % gcmfaces_msg(msgIn,widthOut); gcmfaces_global; if isempty(who('headerOut'))&myenv.verbose<2; headerOut=''; elseif isempty(who('headerOut'))&myenv.verbose>=2; %pause before each event if myenv.verbose>=3; fprintf('\n > hit return to continue <\n'); pause; end; % [ST,I]=dbstack; headerOut={'gcmfaces message from '}; if isempty(ST); headerOut={headerOut{:} 'main workspace'}; else; for ii=length(ST):-1:2; tmp1=[char(45)*ones(1,length(ST)-ii+1)]; headerOut={headerOut{:} [tmp1 ST(ii).name ' at line ' num2str(ST(ii).line)]}; end; end; m=0; for ii=1:length(headerOut); m=max(m,length(headerOut{ii})); end; tmpOut=45*ones(1,m+2); for ii=1:length(headerOut); n=length(headerOut{ii}); tmpOut=[tmpOut char(10) '|' headerOut{ii} 32*ones(1,m-n) '|']; end; tmpOut=[tmpOut char(10) 45*ones(1,m+2) char(10)]; headerOut=tmpOut; end; if isempty(who('widthOut')); widthOut=75; end; %step 1: reformat msgIn to one char line, if needed %======= %1.1) make cell array if ischar(msgIn)&size(msgIn,2)>1; nLinesIn=size(msgIn,1); tmpIn={}; for ii=1:nLinesIn; tmpIn{ii}=msgIn(ii,:); end; msgIn=tmpIn; end; if iscell(msgIn)&size(msgIn,2)>1; msgIn=msgIn'; end; %2.2) cat to one char line msgIn=strcat(cell2mat(msgIn')); %step 2: deformat text -- rm/replace control characters from caller %======= %2.1) matlab control characters ii=strfind(msgIn,'\n'); for jj=ii; msgIn=[msgIn(1:jj-1) ' ' msgIn(jj+2:end)]; end; ii=strfind(msgIn,'\r'); for jj=ii; msgIn=[msgIn(1:jj-1) ' ' msgIn(jj+2:end)]; end; ii=strfind(msgIn,'\t'); for jj=ii; msgIn=[msgIn(1:jj-1) ' ' msgIn(jj+2:end)]; end; ii=strfind(msgIn,'\b'); for jj=ii; msgIn=[msgIn(1:jj-1) ' ' msgIn(jj+2:end)]; end; ii=strfind(msgIn,'\f'); for jj=ii; msgIn=[msgIn(1:jj-1) ' ' msgIn(jj+2:end)]; end; %2.2) ANSI C control characters tmp1=msgIn; tmp2=double(tmp1); %substitute some with a space jj=find(tmp2>8&tmp2<13); tmp1(jj)=32; %remove the others jj=find(tmp2>=32); tmp1=tmp1(jj); msgIn=char(tmp1); %2.3) double spaces ii=strfind(msgIn,' '); while ~isempty(ii); jj=ii(1); msgIn=[msgIn(1:jj-1) ' ' msgIn(jj+2:end)]; ii=strfind(msgIn,' '); end; %step 3: reformat text -- according to to gcmfaces_msg standards %======= ii=strfind(msgIn,' '); if isempty(ii); ii=[ii length(msgIn)+1]; end; if ii(end)~=length(msgIn); ii=[ii length(msgIn)+1]; end; if ii(1)~=1; ii=[0 ii]; end; msgOut=headerOut; nn=0; for jj=1:length(ii)-1; kk=[ii(jj)+1 :ii(jj+1)-1]; tmp1=msgIn(kk); if nn+length(tmp1)+1<=widthOut; msgOut=[msgOut tmp1 ' ']; nn=nn+length(tmp1)+1; else; msgOut=[msgOut char(10)]; nn=0; msgOut=[msgOut ' ' tmp1 ' '];%start new line with two spaces nn=nn+length(tmp1)+1; end; end; msgOut=[msgOut char(10)]; nn=0; %step 4: print to screen %======= fprintf(msgOut); gcmfaces/gcmfaces_misc/imagescnan.m0000644000435400001440000003427711334543422017271 0ustar gforgetusersfunction [H,HNAN] = imagescnan(varargin) %IMAGESCNAN Scale data and display as image with uncolored NaNs. % % SYNTAX: % imagescnan(U) % imagescnan(U,...,'NanColor',CNAN) % imagescnan(U,...,'NanMask',MNAN) % imagescnan(U,...,IOPT) % imagescnan(X,Y,U,...) % [H,HNAN] = imagescnan(...); % % INPUT: % U - 2 dimensional N-by-M image or N-by-M-by-3 RGB image. % X - 2 extrema X-axis data; or the M values; or the N-by-M values % as obtained from MESHGRID (see DESCRIPTION below). % DEFAULT: [1 N] % Y - 2 extrema X-axis data; or the N values; or the N-by-M values % as obtained from MESHGRID (see DESCRIPTION below). % DEFAULT: [1 M] % CNAN - Color for the NaNs elements. May be a char specifier or an [R % G B] triplet specifying the color. % DEFAULT: invisible (axes background color) % MNAN - Elements to be ignored besides not finite values. May be an % scalar or a logical M-by-N matrix indicating the elements to % be ignored. % DEFAULT: [] % IOPT - IMAGE function normal optional pair arguments like % ('Parent',H) or/and CLIM like optional last argument as in % IMAGESC. % DEFAULT: none % % OUTPUT (all optional): % H - Image handle % HNAN - Handle of every ignored (NaN) value colored patch. % % DESCRIPTION: % MATLAB function IMAGESC does not work properly with NaNs. This % programs deals with this problem by including colored patches over % this elements and maybe others specyfied by the user with MNAN. % % Besides, those functions does not work properly with X,Y values % variable interval, but this functions does it by generating a whole % new image of several rectangular patches, but whose centers may not % lay in the specified coordinate (see NOTE below). This functionality % is experimental and not recommended (see ADDITIONAL NOTES inside this % program). % % In previous release, 2-dim input images were transformed into a % 3-dim RGB image. This is not used anymore (see ADDITIONAL NOTES % inside this file). % % NOTE: % * Optional inputs use its DEFAULT value when not given or []. % * Optional outputs may or not be called. % * If X is a two element vector, min(X) will be the coordinate of the % first column and max(X) of the last column. % * If Y is a two element vector, min(Y) will be the coordinate of the % first row and max(Y) of the last row. % * If vector X-axis is decreasing U=fliplr(U) will be used. % * If vector Y-axis is decreasing U=flipud(U) will be used. % * When X or Y do not have a constant increasing/decreasing step, the % vertices of the color rectangules are set in the middle of each % pair of coordinates. For this reason its center may not lay on the % specified coordinate, except on the coordinates at the edges where % it always lays on the center. % * To get a non-scaled image (IMAGE instead of IMAGESC) use: % >> H = imagescnan(...); % >> set(H,'CDataMapping','direct') % * ADDITIONAL NOTES are included inside this file. % % EXAMPLE: % % Compares with normal IMAGESC: % N = 100; % PNaNs = 0.10; % U = peaks(N); % U(round(1 + (N^2-1).*rand(N^2*PNaNs,1))) = NaN; % Adds NaNs % subplot(221), imagesc(U) % title('With IMAGESC: ugly NaNs') % subplot(222), imagescnan(U) % title('With IMAGESCNAN: uncolored NaNs') % % Compares with SPY: % subplot(223), spy(isnan(U)) % title('SPY(isnan(U))') % subplot(224), imagescnan(isnan(U),'NaNMask',0), axis equal tight % title('SPY with IMAGESCNAN') % % SEE ALSO: % IMAGE, IMAGESC, COLORBAR, IMREAD, IMWRITE % and % CMAPPING, CBFREEZE by Carlos Vargas % at http://www.mathworks.com/matlabcentral/fileexchange % % % --- % MFILE: imagescnan.m % VERSION: 2.1 (Aug 20, 2009) (download) % MATLAB: 7.7.0.471 (R2008b) % AUTHOR: Carlos Adrian Vargas Aguilera (MEXICO) % CONTACT: nubeobscura@hotmail.com % ADDITIONAL NOTES: % * I keep getting a kind of BUG with the edges of the patched NaNs. I % added two NOTE inside this program that may fix this problem. % Another way is to convert the intensity matrix U into RGB colors by % using the CMAPPING function, as used by the first version of this % program. % * Besides, if the matrix is too large, sometimes there is an % undocumented failure while drawing the patch NaNs. Is recommended % to use U = cmapping(U,[],'k','discrete') instead, and change the % CLIM to [min(U(:)) max(U(:))]. % * The use of not homogeneous step interval X,Y axes is not % recommended because the program tries to put its value in the % middle of the colored rectangule (as IMAGESC does) and soetimes the % result may not be what the user wants. So this is for experimental % use only. % REVISIONS: % 1.0 Released. (Jun 30, 2008) % 1.1 Fixed bug when CAXIS used. Colorbar freezed colormap. Fixed % bug in color vector input (Found by Greg King) and now % accets RGB image as input. (Jul 14, 2008) % 2.0 Totally rewritten code. Do not converts to RGB anymore. Do not % freezes the colormap anymore. Do not output any colorbar. New % X and Y variable steps accepted input. Now uses patches. (Jun % 08, 2009) % 2.1 Fixed bug with RGB input. Added a NOTE about the use of % CMAPPING. (Aug 20, 2009) % DISCLAIMER: % imagescnan.m is provided "as is" without warranty of any kind, under % the revised BSD license. % Copyright (c) 2008,2009 Carlos Adrian Vargas Aguilera % INPUTS CHECK-IN % ------------------------------------------------------------------------- % Initializes: X = []; Y = []; CNAN = []; MNAN = []; ha = []; % Checks number of inputs: if nargin<1 error('CVARGAS:imagescnan:notEnoughInputs',... 'At least 1 input is required.') elseif nargout>2 error('CVARGAS:imagescnan:tooManyOutputs',... 'At most 2 outputs are allowed.') end % Gets X,Y,U: if ((nargin==1) || (nargin==2)) U = varargin{1}; varargin(1) = []; else if (isnumeric(varargin{1}) && isnumeric(varargin{2}) && ... isnumeric(varargin{3})) X = varargin{1}; Y = varargin{2}; U = varargin{3}; varargin(1:3) = []; else U = varargin{1}; varargin(1) = []; end end % Check U: ndim = ndims(U); if (ndim==2) [M,N] = size(U); O = 1; elseif (ndim==3) [M,N,O] = size(U); if (O~=3) error('CVARGAS:imagescnan:incorrectRgbImage',... 'RGB image must be of size M-by-N-by-3.') end else error('CVARGAS:imagescnan:incorrectImageSize',... 'Image must be 2-dimensional or a 3-dim RGB image.') end % Check X: aequal = true; % Equal intervals on x-axis? dX = []; if isempty(X) X = [1 N]; else if (ndims(X)>2) error('CVARGAS:imagescnan:incorrectXDims',... 'X must be a vector or a matrix as a result of MESHGRID.') end if any(~isfinite(X(:))) error('CVARGAS:imagescnan:incorrectXValue',... 'X elements must be numeric and finite.') end [Mx,Nx] = size(X); if ((Mx*Nx)==2) if X(2)(eps*max(abs(dX(:)))*1000)) error('CVARGAS:imagescnan:incorrectXMatrix',... 'X matrix must be as generated by MESHGRID.') end X = X(1,:); elseif (~any([Mx Nx]==1) && ~((Mx*Nx)==N)) error('CVARGAS:imagescnan:incorrectXSize',... 'X must be an scalar or a matrix.') end % Forces ascending x-axis: [X,I] = sort(X(:).'); for k = 1:O % Fixed bug Aug 2009 U(:,:,k) = U(:,I,k); end clear I % Checks equal intervals: dX = diff(X); if any(abs(dX(1)-dX(2:end))>(eps*max(dX)*1000)) if aequal aequal = false; end else X = [X(1) X(end)]; dX = []; end end end % Check Y: dY = []; if isempty(Y) Y = [1 M]; else if (ndims(Y)>2) error('CVARGAS:imagescnan:incorrectYDims',... 'Y must be a vector or a matrix as a result of MESHGRID.') end if any(~isfinite(Y(:))) error('CVARGAS:imagescnan:incorrectYValue',... 'Y elements must be numeric and finite.') end [My,Ny] = size(Y); if ((My*Ny)==2) if Y(2)(eps*max(abs(dY(:)))*1000)) error('CVARGAS:imagescnan:incorrectYMatrix',... 'Y matrix must be as generated by MESHGRID.') end Y = Y(:,1); elseif (~any([My Ny]==1) && ~((My*Ny)==M)) error('CVARGAS:imagescnan:incorrectYSize',... 'Y must be an scalar or a matrix.') end % Forces ascending y-axis: [Y,I] = sort(Y(:).'); for k = 1:O % Fixed bug Aug 2009 U(:,:,k) = U(I,:,k); end clear I % Checks equal intervals: dY = diff(Y); if any(abs(dY(1)-dY(2:end))>(eps*max(dY)*1000)) if aequal aequal = false; end else Y = [Y(1) Y(end)]; dY = []; end end end % Checks varargin: ind = []; Nopt = length(varargin); for k = 1:Nopt-1 if (~isempty(varargin{k}) && ischar(varargin{k})) if strncmpi(varargin{k},'NanColor',4) CNAN = varargin{k+1}; ind = [ind k k+1]; elseif strncmpi(varargin{k},'NanMask',4) MNAN = varargin{k+1}; ind = [ind k k+1]; elseif (strncmpi(varargin{k},'Parent',2) && isempty(CNAN)) try CNAN = get(varargin{k+1},'Color'); ha = varargin{k+1}; catch error('CVARGAS:imagescnan:incorrectParentHandle',... '''Parent'' must be a valid axes handle.') end end end end varargin(ind) = []; Nargin = length(varargin); % Check ha: if isempty(ha) ha = gca; end % Check CNAN: if isempty(CNAN) CNAN = get(ha,'Color'); elseif ischar(CNAN) switch lower(CNAN) case 'y', CNAN = [1 1 0]; case 'm', CNAN = [1 0 0]; case 'c', CNAN = [0 1 1]; case 'r', CNAN = [1 0 0]; case 'g', CNAN = [0 1 0]; case 'b', CNAN = [0 0 1]; case 'w', CNAN = [1 1 1]; case 'k', CNAN = [0 0 0]; otherwise error('CVARGAS:imagescnan:incorrectNancString',... 'Color string must be a valid color identifier. One of ''ymcrgbwk''.') end elseif isnumeric(CNAN) && (length(CNAN)==3) CNAN = CNAN(:).'; % Forces row vector. else error('CVARGAS:imagescnan:incorrectNancInput',... 'Not recognized CNAN input.') end % Check MNAN: if isempty(MNAN) MNAN = any(~isfinite(U),3); else if (ndims(MNAN)==2) [Mm,Nm] = size(MNAN); if ((Mm*Nm)==1) MNAN = (any(~isfinite(U),3) | any(U==MNAN,3)); elseif ((Mm==M) && (Nm==N) && islogical(MNAN)) MNAN = (any(~isfinite(U),3) | MNAN); else error('CVARGAS:imagescnan:incorrectNanmSize',... 'MNAN must be an scalar or a logical matrix of size M-by-N.') end else error('CVARGAS:imagescnan:incorrectNanmDims',... 'MNAN must be an scalar or a matrix.') end end % ------------------------------------------------------------------------- % MAIN % ------------------------------------------------------------------------- % Generates the image: if aequal % IMAGESC way. H = imagesc(X,Y,U,varargin{:}); else % PATCH way. % Check clim: if (rem(Nargin,2)==1) clim = varargin{end}; varargin(end) = []; if ((length(clim)~=2) || (clim(1)>clim(2))) error('CVARGAS:imagescnan:incorrectClimInput',... 'clim must be a 2 element increasing vector.') end else clim = []; end % Generates vertices between coordinates (coordinates may not be at the % center of these vertices): if (length(X)~=N) X = (0:N-1)*((X(2)-X(1))/(N-1)) + X(1); end if (length(Y)~=M) Y = (0:M-1)*((Y(2)-Y(1))/(M-1)) + Y(1); end if isempty(dX) dX = diff(X); end if isempty(dY) dY = diff(Y); end [X,Y] = meshgrid([X(1)-dX(1)/2 X+dX([1:N-1 N-1])/2],... [Y(1)-dY(1)/2 Y+dY([1:M-1 M-1])/2]); % Generates faces: ind = (1:(M+1)*N)'; ind(M+1:M+1:end) = []; % Generates patches: H = patch(... 'Vertices' ,[X(:) Y(:)],... 'Faces' ,[ind ind+1 ind+M+2 ind+M+1],... 'FaceVertexCData',U(:),... 'FaceColor' ,'flat',... 'EdgeColor' ,'none',... % NOTE: Sometimes this is not required. varargin{:}); set(ha,... 'YDir' ,'reverse',... 'View' ,[0 90],... 'Box' ,'on',... 'Layer','top') axis(ha,'tight') % Sets clim: if ~isempty(clim) set(ha,'CLim',clim) else set(ha,'CLimMode','auto') end end % Adds NaNs patches: if any(MNAN(:)) if aequal % dX and dY is constant: [MNAN,NNAN] = ind2sub([M,N],find(MNAN)); Nnan = length(MNAN); dX = (X(2)-X(1))/(N-1)/2; dY = (Y(2)-Y(1))/(M-1)/2; HNAN = patch(repmat((X(1)+(NNAN(:)'-1)*(2*dX)),4,1) + ... (repmat([-1 1 1 -1]'*dX,1,Nnan)),... repmat((Y(1)+(MNAN(:)'-1)*(2*dY)),4,1) + ... (repmat([1 1 -1 -1]'*dY,1,Nnan)),... CNAN,... 'EdgeColor',CNAN,... 'EdgeColor','none',... varargin{1:Nargin-rem(Nargin,2)}); else % dX and/or dY is not constant: MNAN = find(MNAN); HNAN = patch(... 'Vertices' ,[X(:) Y(:)],... 'Faces' ,[ind(MNAN) ind(MNAN)+1 ind(MNAN)+M+2 ind(MNAN)+M+1],... 'FaceColor' ,CNAN,... 'EdgeColor' ,'none',... 'EdgeColor',CNAN,... % NOTE: may be better? varargin{:}); end else HNAN = []; end % OUTPUTS CHECK-OUT % ------------------------------------------------------------------------- % Clears outputs?: if (nargout==0) clear H end % [EOF] imagescnan.mgcmfaces/gcmfaces_legacy/0000755000435400001440000000000012375431055015306 5ustar gforgetusersgcmfaces/gcmfaces_legacy/line_greatC_TUV_MASKS_test.m0000644000435400001440000000401111600767631022431 0ustar gforgetusers %test: %lons=[-81 -77]; lats=[28 27]; name='Florida Strait'; %lons=[-81 -79]; lats=[28 22]; name='Florida Strait W1'; %lons=[-76 -76]; lats=[21 8]; name='Florida Strait S1'; %lons=[-77 -77]; lats=[27 25]; name='Florida Strait E1'; %lons=[-77 -77]; lats=[25 22]; name='Florida Strait E2'; %lons=[-65 -50]; lats=[66 66]; name='Davis Strait'; %lons=[-35 -20]; lats=[67 65]; name='Denmark Strait'; %lons=[-16 -7]; lats=[65 62.5]; name='Iceland Feroe'; %lons=[-6.5 -4]; lats=[62.5 57]; name='Feroe England'; %lons=[-4 8]; lats=[57 62]; name='England Norway'; %lons=[-68 -63]; lats=[-54 -66]; name='Drake Passage'; %lons=[103 103]; lats=[-1 4]; name='Indonesia W1'; %lons=[104 109]; lats=[-3 -8]; name='Indonesia W2'; %lons=[113 118]; lats=[-8.5 -8.5]; name='Indonesia W3'; %lons=[118 127 ]; lats=[-8.5 -15]; name='Indonesia W4'; %lons=[127 127]; lats=[-25 -68]; name='Australia Antarctica'; %lons=[38 46]; lats=[-10 -22]; name='Madagascar Channel'; %lons=[46 46]; lats=[-22 -69]; name='Madagascar Antarctica'; %lons=[20 20]; lats=[-30 -69.5]; name='South Africa Antarctica'; %compute: line_cur=line_greatC_TUV_mask(lons,lats); line_cur.name=name; %check: ii=1; close all; tmp1=mygrid.hFacW{ii}(:,:,1); tmp2=line_cur.mmuIn{ii}; tmp1(~isnan(tmp2))=-1; figure; imagesc(tmp1); %axis([40 60 50 100]); %axis([50 190 40 90]); axis([230 270 0 50]); drawnow; refresh; pause; tmp1=mygrid.hFacS{ii}(:,:,1); tmp2=line_cur.mmvIn{ii}; tmp1(~isnan(tmp2))=-1; figure; imagesc(tmp1); %axis([40 60 50 100]); %axis([50 190 40 90]); axis([230 270 0 50]); drawnow; refresh; pause; [X,Y,MSK]=convert_llc2pcol(mygrid.XC,mygrid.YC,mygrid.Depth,1,1); MSK(MSK==0)=NaN; figure; pcolor(X,Y,MSK); axis([-180 180 -90 90]); shading flat; caxis([0 6000]); hold on; plot(lons(1),lats(1),'r.','MarkerSize',32); plot(lons(2),lats(2),'k.','MarkerSize',32); [X,Y,mmtIn]=convert_llc2pcol(mygrid.XC,mygrid.YC,line_cur.mmtIn,1,1); kk=find(mmtIn==1); plot(X(kk),Y(kk),'m.'); %axis([-90 -70 10 30]); %axis([90 140 -70 30]); %axis([15 30 -72 -30]); axis([-80 20 50 70]); drawnow; refresh; pause; gcmfaces/gcmfaces_legacy/grid_load_occa.m0000644000435400001440000000206711600376700020375 0ustar gforgetusers global mygrid; if isempty(mygrid); dirGrid='/net/ross/raid2/gforget/1x1_50levels/GRID/'; list0={'XC','XG','YC','YG','RC','RF','RAC','DRC','DRF',... 'DXC','DXG','DYC','DYG','hFacC','hFacS','hFacW','Depth'}; %list0={'AngleCS','AngleSN','Depth','DRC','DRF','DXC','DXG','DYC','DYG',... % 'hFacC','hFacS','hFacW','maskCtrlC','maskCtrlS','maskCtrlW',... % 'PHrefC','PHrefF','RAC','RAS','RAW','RAZ','RC','RF','XC','XG','YC','YG'}; list0={'XC','XG','YC','YG','RAC','DXC','DXG','DYC','DYG',... 'hFacC','hFacS','hFacW','Depth'}; for iFld=1:length(list0); tmp1=gcmfaces(1,'ll'); eval(['tmp2=rdmds([dirGrid ''' list0{iFld} '*'']);']); tmp1.f1=tmp2; eval(['mygrid.' list0{iFld} '=tmp1;']); end; mygrid.AngleCS=mygrid.XC; mygrid.AngleCS(:,:)=1; mygrid.AngleSN=mygrid.XC; mygrid.AngleSN(:,:)=0; list0={'RC','RF','DRC','DRF'}; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds([dirGrid ''' list0{iFld} '*'']);']); end; mygrid.hFacCsurf=mygrid.hFacC; for ff=1:mygrid.hFacC.nFaces; mygrid.hFacCsurf{ff}=mygrid.hFacC{ff}(:,:,1); end; end; gcmfaces/gcmfaces_legacy/convert_UV2UeVn.m0000644000435400001440000000014211334544171020431 0ustar gforgetusersfunction [fldUe,fldVn]=convert_UV2UeVn(fldU,fldV); [fldUe,fldVn]=calc_UEVNfromUXVY(fldU,fldV); gcmfaces/gcmfaces_legacy/nanrunmean.m0000644000435400001440000000171311600706724017626 0ustar gforgetusers%this function does a running mean along dimension dim_cur, %averaging over indices [-nb_cur:nb_cur] % function [field_out]=nanrunmean(field_in,nb_cur,dim_cur); if nb_cur~=0 size_cur=size(field_in); perm1to2=[1:length(size_cur)]; perm1to2=[dim_cur perm1to2(find(perm1to2~=dim_cur))]; perm2to1=[[1:dim_cur-1]+1 1 [dim_cur+1:length(size_cur)]]; size_cur2=size_cur(perm1to2); field_in2=permute(field_in,perm1to2); field_mask2=1*~isnan(field_in2); field_in2(isnan(field_in2))=0; field_out2=zeros(size_cur2); count_out2=zeros(size_cur2); for tcur=-nb_cur:nb_cur tmp1=[tcur:tcur-1+size_cur2(1)]; tmp2=find(tmp1>=1&tmp1<=size_cur2(1)); field_out2(tmp2,:)=field_out2(tmp2,:)+field_in2(tmp1(tmp2),:); count_out2(tmp2,:)=count_out2(tmp2,:)+field_mask2(tmp1(tmp2),:); end tmp1=find(count_out2>0); field_out2(tmp1)=field_out2(tmp1)./count_out2(tmp1); field_out2(count_out2==0)=NaN; field_out=permute(field_out2,perm2to1); else field_out=field_in; end%if nb_cur~=0 gcmfaces/gcmfaces_legacy/grid_load_96x23.m0000644000435400001440000000170711600376700020263 0ustar gforgetusers global mygrid; if isempty(mygrid); dirGrid='/net/altix3700/raid4/gforget/mysetups/ecco_v4/RUNS/GRIDmds/'; list0={'XC','XG','YC','YG','RC','RF','RAC','DRC','DRF',... 'DXC','DXG','DYC','DYG','hFacC','hFacS','hFacW','Depth'}; %list0={'AngleCS','AngleSN','Depth','DRC','DRF','DXC','DXG','DYC','DYG',... % 'hFacC','hFacS','hFacW','maskCtrlC','maskCtrlS','maskCtrlW',... % 'PHrefC','PHrefF','RAC','RAS','RAW','RAZ','RC','RF','XC','XG','YC','YG'}; list0={'XC','XG','YC','YG','RAC','DXC','DXG','DYC','DYG',... 'hFacC','hFacS','hFacW','Depth','AngleCS','AngleSN'}; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds_compact2llc([dirGrid ''' list0{iFld} '*'']);']); end; list0={'RC','RF','DRC','DRF'}; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds([dirGrid ''' list0{iFld} '*'']);']); end; mygrid.hFacCsurf=mygrid.hFacC; for ff=1:mygrid.hFacC.nFaces; mygrid.hFacCsurf{ff}=mygrid.hFacC{ff}(:,:,1); end; end; gcmfaces/gcmfaces_legacy/diffsmooth2Dstraight.m0000644000435400001440000000012411334544171021555 0ustar gforgetusersfunction [fld]=diffsmooth2Dstraight(varargin); [fld]=diffsmooth2D(varargin{:}); gcmfaces/gcmfaces_legacy/runmean_cycle.m0000644000435400001440000000140411600706724020305 0ustar gforgetusers%this function does a running mean along dimension dim_cur, %averaging over indices [-nb_cur:nb_cur] % function [field_out]=runmean_cycle(field_in,nb_cur,dim_cur); if nb_cur~=0 size_cur=size(field_in); perm1to2=[1:length(size_cur)]; perm1to2=[dim_cur perm1to2(find(perm1to2~=dim_cur))]; perm2to1=[[1:dim_cur-1]+1 1 [dim_cur+1:length(size_cur)]]; size_cur2=size_cur(perm1to2); field_in2=permute(field_in,perm1to2); field_out2=zeros(size_cur2); count_out2=0; for tcur=-nb_cur:nb_cur field_out2=field_out2+circshift(field_in2,[tcur zeros(1,length(size_cur2)-1)]); count_out2=count_out2+1; end field_out2=field_out2/count_out2; %field_out=field_in-permute(field_out2,perm2to1); field_out=permute(field_out2,perm2to1); else field_out=field_in; end%if nb_cur~=0 gcmfaces/gcmfaces_legacy/line_greatC_TUV_MASKS_v4_until_evol4.m0000644000435400001440000000454111600767631024337 0ustar gforgetusersfunction [LINES_out]=line_greatC_TUV_MASKS(varargin); if nargin==1; doDisplay=varargin{1}; else; doDisplay=0; end; global mygrid; for iy=1:21; switch iy; case 1; lons=[-173 -164]; lats=[65.5 65.5]; name='Bering Strait'; case 2; lons=[-5 -5]; lats=[34 40]; name='Gibraltar'; case 3; lons=[-81 -77]; lats=[28 27]; name='Florida Strait'; case 4; lons=[-81 -79]; lats=[28 22]; name='Florida Strait W1'; case 5; lons=[-76 -76]; lats=[21 8]; name='Florida Strait S1'; case 6; lons=[-77 -77]; lats=[27 25]; name='Florida Strait E1'; case 7; lons=[-77 -77]; lats=[25 22]; name='Florida Strait E2'; case 8; lons=[-65 -50]; lats=[66 66]; name='Davis Strait'; case 9; lons=[-35 -20]; lats=[67 65]; name='Denmark Strait'; case 10; lons=[-16 -7]; lats=[65 62.5]; name='Iceland Feroe'; case 11; lons=[-6.5 -4]; lats=[62.5 57]; name='Feroe England'; case 12; lons=[-4 8]; lats=[57 62]; name='England Norway'; case 13; lons=[-68 -63]; lats=[-54 -66]; name='Drake Passage'; case 14; lons=[103 103]; lats=[-1 4]; name='Indonesia W1'; case 15; lons=[104 109]; lats=[-3 -8]; name='Indonesia W2'; case 16; lons=[113 118]; lats=[-8.5 -8.5]; name='Indonesia W3'; case 17; lons=[118 127 ]; lats=[-8.5 -15]; name='Indonesia W4'; case 18; lons=[127 127]; lats=[-25 -68]; name='Australia Antarctica'; case 19; lons=[38 46]; lats=[-10 -22]; name='Madagascar Channel'; case 20; lons=[46 46]; lats=[-22 -69]; name='Madagascar Antarctica'; case 21; lons=[20 20]; lats=[-30 -69.5]; name='South Africa Antarctica'; end; %compute: line_cur=line_greatC_TUV_mask(lons,lats); line_cur.name=name; if doDisplay; ii=5; tmp1=mygrid.hFacW{ii}(:,:,1); tmp2=line_cur.mmuIn{ii}; tmp1(~isnan(tmp2))=-1; figure; imagesc(tmp1); tmp1=mygrid.hFacS{ii}(:,:,1); tmp2=line_cur.mmvIn{ii}; tmp1(~isnan(tmp2))=-1; figure; imagesc(tmp1); [X,Y,MSK]=convert_llc2pcol(mygrid.XC,mygrid.YC,mygrid.Depth,1,1); MSK(MSK==0)=NaN; figure; pcolor(X,Y,MSK); axis([-180 180 -90 90]); shading flat; caxis([0 6000]); hold on; plot(lons(1),lats(1),'r.','MarkerSize',32); plot(lons(2),lats(2),'k.','MarkerSize',32); [X,Y,mmtIn]=convert_llc2pcol(mygrid.XC,mygrid.YC,line_cur.mmtIn,1,1); kk=find(mmtIn==1); plot(X(kk),Y(kk),'m.'); %[X,Y,mmtOut]=convert_llc2pcol(mygrid.XC,mygrid.YC,line_cur.mmtOut,1,1); %kk=find(mmtOut==1); plot(X(kk),Y(kk),'cx'); end; if iy==1; LINES_out=line_cur; else; LINES_out(iy)=line_cur; end; end; gcmfaces/gcmfaces_legacy/line_zonal_TUV_mask.m0000644000435400001440000000215111601141417021355 0ustar gforgetusersfunction [line_out]=line_zonal_TUV_mask(lat_in); global mygrid; y=mygrid.YC; yP1=exch_T_N(y); %T part: yy=lat_in; mm=yP1<=yy; mm(isnan(mm))=0; for iF=1:y.nFaces; eval(['tmp1=mm.f' num2str(iF) ';']); tmp2=circshift(tmp1,[-1 0])+circshift(tmp1,[1 0])+... circshift(tmp1,[0 -1])+circshift(tmp1,[0 1]); tmp2(tmp1>0)=0; tmp2(tmp2~=0)=1; tmp2(tmp2==0)=NaN; eval(['mm.f' num2str(iF) '=tmp2(2:end-1,2:end-1);']); end; mmt=mm; %UV part: nn=exch_T_N(mmt); mm=yP1<=yy; mm(isnan(mm))=0; mmu=y; mmv=y; for iFace=1:y.nFaces; iF=num2str(iFace); eval(['tmp_u=mm.f' iF '(1:end-1,:)==1&nn.f' iF '(2:end,:)==1;']); eval(['tmp_u2=mm.f' iF '(2:end,:)==1&nn.f' iF '(1:end-1,:)==1;']); tmp_u=1*(tmp_u(1:end-1,2:end-1)-tmp_u2(1:end-1,2:end-1)); eval(['mmu.f' iF '=tmp_u;']); eval(['tmp_v=mm.f' iF '(:,1:end-1)==1&nn.f' iF '(:,2:end)==1;']); eval(['tmp_v2=mm.f' iF '(:,2:end)==1&nn.f' iF '(:,1:end-1)==1;']); tmp_v=1*(tmp_v(2:end-1,1:end-1)-tmp_v2(2:end-1,1:end-1)); eval(['mmv.f' iF '=tmp_v;']); end; mmu(mmu==0)=NaN; mmv(mmv==0)=NaN; %store: line_out=struct('mmt',mmt,'mmu',mmu,'mmv',mmv,'lat',lat_in); gcmfaces/gcmfaces_legacy/convert_compact2llc.m0000644000435400001440000000012511334544171021423 0ustar gforgetusersfunction [v1]=convert_compact2llc(varargin); [v1]=convert2gcmfaces(varargin{:}); gcmfaces/gcmfaces_legacy/diffsmooth2Dstraight_extrapolate.m0000644000435400001440000000015311334544171024167 0ustar gforgetusersfunction [fld]=diffsmooth2Dstraight_extrapolate(varargin); [fld]=diffsmooth2D_extrap_fwd(varargin{:}); gcmfaces/gcmfaces_legacy/myverticaldeform.m0000644000435400001440000000111111600706724021030 0ustar gforgetusersfunction [varout]=myverticaldeform(varin) %varin : profondeur en m (positif) %varout : z correspondant (negatif), avec % deformation selon le niveau %var de sortie : varout=zeros(size(varin)); %valeurs limite : %val_lim=500;fprintf('deform v:500m\n'); val_lim=500; %val_lim=250; fprintf('deform v:250m\n'); %val_lim=-0.0001; val_lim2=2000; %valeurs inferieures a 500m : tmp1=find(varin<=val_lim); tmp2=-100*varin(tmp1)/val_lim; varout(tmp1)=tmp2; %valeurs superieurs a 500m : tmp1=find(varin>val_lim); tmp2=-100-200*(varin(tmp1)-val_lim)./(val_lim2-val_lim); varout(tmp1)=tmp2; gcmfaces/gcmfaces_legacy/line_zonal_TUV_MASKS.m0000644000435400001440000000032211601141417021276 0ustar gforgetusersfunction [LINES_out]=line_zonal_TUV_MASKS(Y_in); global mygrid; for iy=1:length(Y_in); line_cur=line_zonal_TUV_mask(Y_in(iy)); if iy==1; LINES_out=line_cur; else; LINES_out(iy)=line_cur; end; end; gcmfaces/gcmfaces_legacy/rdmds_compact2llc.m0000644000435400001440000000013111334544171021051 0ustar gforgetusersfunction [fldOut]=rdmds_compact2llc(varargin); [fldOut]=rdmds2gcmfaces(varargin{:}); gcmfaces/gcmfaces_legacy/nanrunmean_cycle.m0000644000435400001440000000164011600706724021004 0ustar gforgetusers%this function does a running mean along dimension dim_cur, %averaging over indices [-nb_cur:nb_cur] % function [field_out]=nanrunmean_cycle(field_in,nb_cur,dim_cur); if nb_cur~=0 size_cur=size(field_in); perm1to2=[1:length(size_cur)]; perm1to2=[dim_cur perm1to2(find(perm1to2~=dim_cur))]; perm2to1=[[1:dim_cur-1]+1 1 [dim_cur+1:length(size_cur)]]; size_cur2=size_cur(perm1to2); field_in2=permute(field_in,perm1to2); field_mask2=1*~isnan(field_in2); field_out2=zeros(size_cur2); count_out2=zeros(size_cur2); for tcur=-nb_cur:nb_cur tmp1=circshift(field_in2,[tcur zeros(1,length(size_cur2)-1)]); tmp2=find(~isnan(tmp1.*field_in2)); field_out2(tmp2)=field_out2(tmp2)+tmp1(tmp2); count_out2(tmp2)=count_out2(tmp2)+1; end tmp1=find(count_out2>0); field_out2(tmp1)=field_out2(tmp1)./count_out2(tmp1); field_out2(count_out2==0)=NaN; field_out=permute(field_out2,perm2to1); else field_out=field_in; end%if nb_cur~=0 gcmfaces/gcmfaces_legacy/grid_load_90x50.m0000644000435400001440000000171511600376700020254 0ustar gforgetusers global mygrid; if isempty(mygrid); dirGrid='/net/altix3700/raid4/gforget/mysetups/ecco_v4/RUNS/GRIDmds_90x50/'; list0={'XC','XG','YC','YG','RC','RF','RAC','DRC','DRF',... 'DXC','DXG','DYC','DYG','hFacC','hFacS','hFacW','Depth'}; %list0={'AngleCS','AngleSN','Depth','DRC','DRF','DXC','DXG','DYC','DYG',... % 'hFacC','hFacS','hFacW','maskCtrlC','maskCtrlS','maskCtrlW',... % 'PHrefC','PHrefF','RAC','RAS','RAW','RAZ','RC','RF','XC','XG','YC','YG'}; list0={'XC','XG','YC','YG','RAC','DXC','DXG','DYC','DYG',... 'hFacC','hFacS','hFacW','Depth','AngleCS','AngleSN'}; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds_compact2llc([dirGrid ''' list0{iFld} '*'']);']); end; list0={'RC','RF','DRC','DRF'}; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds([dirGrid ''' list0{iFld} '*'']);']); end; mygrid.hFacCsurf=mygrid.hFacC; for ff=1:mygrid.hFacC.nFaces; mygrid.hFacCsurf{ff}=mygrid.hFacC{ff}(:,:,1); end; end; gcmfaces/gcmfaces_legacy/verticalplot.m0000644000435400001440000000405111600706724020172 0ustar gforgetusers%22/11/2003 %auteur : Gael Forget %version : beta %objet : a la realsiation d'un plot xz ou yz, on utilise %des echelles differentes au dessus/en dessous de 500m %remarque : old version etait spacifique a chaque type % de plot, cette nouvelle se vaut generique... function [varargout]=verticalplot(typeplot,cur_x,cur_z,varargin); %variables d'entree : %1) typeplot est le nom du type de plot (px : pcolor) %2) cur_x et cur_z sont les chamsp x et z %3) varargin sont les autres options a passer a la routine de plot %nouvelles ordonnees : xplot2=cur_x; yplot2=myverticaldeform(cur_z); %************************************ %gestion des vars de sortie (partie 1) tmptxt=''; if nargout==1 tmptxt='[tmp1]='; elseif nargout>1 tmptxt='[tmp1'; for kkk=2:nargout tmptxt=[tmptxt ',tmp' num2str(kkk)]; end tmptxt=[tmptxt ']=']; end %************************************ %le plot en lui meme : eval([tmptxt typeplot '(xplot2,yplot2,varargin{:});']); %************************************ %gestion des vars de sortie (partie 2) if nargout>=1 for kkk=1:nargout eval(['varargout(kkk) = {tmp' num2str(kkk) '};']) end end %************************************ %reglage des ytics : newtick=[floor(min(min(cur_z))) ceil(max(max(cur_z)))]; if (newtick(1)<=500)&(newtick(2)>500) tmp1=100*floor(newtick(1)/100); tmp2=ceil(newtick(2)/500)*500; %newtick=[0:1000:6000]; %newtick=[tmp1:50:250]; newtick=[ newtick(1:end) [500:500:tmp2]]; %newtick=[tmp1:100:500]; newtick=[ newtick(1:end-1) [500:500:tmp2]]; newtick=[tmp1:100:1000]; newtick=[ newtick(1:end-1) [1000:500:6000]]; elseif (newtick(1)<=500) tmp1=floor(newtick(1)/50)*50; tmp2=ceil(newtick(2)/50)*50; newtick=[tmp1:50:tmp2]; else tmp1=floor(newtick(1)/500)*500; tmp2=ceil(newtick(2)/500)*500; newtick=[tmp1:500:tmp2]; end %on les range dans l'ordre approprie : newtick=flipdim(newtick,2); %format texte : newticklabel=[]; for kkk=1:length(newtick) newticklabel=strvcat(newticklabel,num2str(newtick(kkk))); end %mise a jour des yticks : newtick=myverticaldeform(newtick); set(gca,'YTick',newtick); set(gca,'YTickLabel',newticklabel); gcmfaces/gcmfaces_legacy/convert_llc2pcol.m0000644000435400001440000000013011334544171020726 0ustar gforgetusersfunction [X,Y,fld]=convert_llc2pcol(varargin); [X,Y,fld]=convert2pcol(varargin{:}); gcmfaces/gcmfaces_legacy/diffsmooth2Dstraight_extrapolate_inverse.m0000644000435400001440000000016311334544171025723 0ustar gforgetusersfunction [fld]=diffsmooth2Dstraight_extrapolate_inverse(varargin); [fld]=diffsmooth2D_extrap_inv(varargin{:}); gcmfaces/gcmfaces_legacy/line_greatC_TUV_mask.m0000644000435400001440000000711711601141417021446 0ustar gforgetusersfunction [line_out]=line_greatC_TUV_mask(lonPair_in,latPair_in); global mygrid; %get carthesian coordinates: %... of grid lon=mygrid.XC; lat=mygrid.YC; x=cos(lat*pi/180).*cos(lon*pi/180); y=cos(lat*pi/180).*sin(lon*pi/180); z=sin(lat*pi/180); %... and of end points x0=cos(latPair_in*pi/180).*cos(lonPair_in*pi/180); y0=cos(latPair_in*pi/180).*sin(lonPair_in*pi/180); z0=sin(latPair_in*pi/180); %get the rotation matrix: %1) rotate around x axis to put first point at z=0 theta=atan2(-z0(1),y0(1)); R1=[[1;0;0] [0;cos(theta);sin(theta)] [0;-sin(theta);cos(theta)]]; tmp0=[x0;y0;z0]; tmp1=R1*tmp0; x1=tmp1(1,:); y1=tmp1(2,:); z1=tmp1(3,:); x0=x1; y0=y1; z0=z1; %2) rotate around z axis to put first point at y=0 theta=atan2(x0(1),y0(1)); R2=[[cos(theta);sin(theta);0] [-sin(theta);cos(theta);0] [0;0;1]]; tmp0=[x0;y0;z0]; tmp1=R2*tmp0; x1=tmp1(1,:); y1=tmp1(2,:); z1=tmp1(3,:); x0=x1; y0=y1; z0=z1; %3) rotate around y axis to put second point at z=0 theta=atan2(-z0(2),-x0(2)); R3=[[cos(theta);0;-sin(theta)] [0;1;0] [sin(theta);0;cos(theta)]]; tmp0=[x0;y0;z0]; tmp1=R3*tmp0; x1=tmp1(1,:); y1=tmp1(2,:); z1=tmp1(3,:); x0=x1; y0=y1; z0=z1; %apply rotation to grid: tmpx=convert2array(x); tmpy=convert2array(y); tmpz=convert2array(z); tmp1=find(~isnan(tmpx)); tmpx2=tmpx(tmp1); tmpy2=tmpy(tmp1); tmpz2=tmpz(tmp1); tmp2=[tmpx2';tmpy2';tmpz2']; tmp3=R3*R2*R1*tmp2; tmpx2=tmp3(1,:); tmpy2=tmp3(2,:); tmpz2=tmp3(3,:); tmpx(tmp1)=tmpx2; tmpy(tmp1)=tmpy2; tmpz(tmp1)=tmpz2; x=convert2array(tmpx); y=convert2array(tmpy); z=convert2array(tmpz); %compute the great circle mask: zz=exch_T_N(z); mm=zz<=0; mm(isnan(mm))=0; for iF=1:y.nFaces; eval(['tmp1=mm.f' num2str(iF) ';']); tmp2=circshift(tmp1,[-1 0])+circshift(tmp1,[1 0])+... circshift(tmp1,[0 -1])+circshift(tmp1,[0 1]); tmp2(tmp1>0)=0; tmp2(tmp2~=0)=1; tmp2(tmp2==0)=NaN; eval(['mm.f' num2str(iF) '=tmp2(2:end-1,2:end-1);']); end; %UV part: mmt=mm; nn=exch_T_N(mmt); mm=zz<=0; mm(isnan(mm))=0; mmu=mmt; mmv=mmt; for iFace=1:y.nFaces; iF=num2str(iFace); eval(['tmp_u=mm.f' iF '(1:end-1,:)==1&nn.f' iF '(2:end,:)==1;']); eval(['tmp_u2=mm.f' iF '(2:end,:)==1&nn.f' iF '(1:end-1,:)==1;']); tmp_u=1*(tmp_u(1:end-1,2:end-1)-tmp_u2(1:end-1,2:end-1)); eval(['mmu.f' iF '=tmp_u;']); eval(['tmp_v=mm.f' iF '(:,1:end-1)==1&nn.f' iF '(:,2:end)==1;']); eval(['tmp_v2=mm.f' iF '(:,2:end)==1&nn.f' iF '(:,1:end-1)==1;']); tmp_v=1*(tmp_v(2:end-1,1:end-1)-tmp_v2(2:end-1,1:end-1)); eval(['mmv.f' iF '=tmp_v;']); end; mmu(mmu==0)=NaN; mmv(mmv==0)=NaN; for kk=1:3; %select field to treat: switch kk; case 1; mm=mmt; case 2; mm=mmu; case 3; mm=mmv; end; %split in two contours: theta=[]; theta(1)=atan2(y0(1),x0(1)); theta(2)=atan2(y0(2),x0(2)); tmpx=convert2array(x); tmpy=convert2array(y); tmpz=convert2array(z); tmptheta=atan2(tmpy,tmpx); tmpm=convert2array(mm); tmpmIn=tmpm; tmpmOut=tmpmIn; if theta(2)<0; tmp00=find(tmptheta<=theta(2)); tmptheta(tmp00)=tmptheta(tmp00)+2*pi; theta(2)=theta(2)+2*pi; end; tmpmIn(find(tmptheta>theta(2)|tmptheta=theta(1)))=NaN; mmIn=convert2array(tmpmIn); mmOut=convert2array(tmpmOut); %ensure that we select the shorther segment as mmIn: if theta(2)-theta(1)>pi; tmp1=mmIn; mmIn=mmOut; mmOut=tmp1; end; %store result: switch kk; case 1; mmtIn=mmIn; mmtOut=mmOut; case 2; mmuIn=mmIn; mmuOut=mmOut; case 3; mmvIn=mmIn; mmvOut=mmOut; end; end; %output: line_out=struct('mmt',mmt,'mmtIn',mmtIn,'mmtOut',mmtOut,... 'mmu',mmu,'mmuIn',mmuIn,'mmuOut',mmuOut,... 'mmv',mmv,'mmvIn',mmvIn,'mmvOut',mmvOut,... 'lonPair',lonPair_in,'latPair',latPair_in); gcmfaces/ecco_v4/0000755000435400001440000000000012375431055013534 5ustar gforgetusersgcmfaces/ecco_v4/cost_seaicearea.m0000644000435400001440000001707312365532071017033 0ustar gforgetusersfunction []=cost_seaicearea(dirModel,dirMat,doComp,dirTex,nameTex); %object: compute cost function term for sea ice data %inputs: dimodel is the model directory % dirMat is the directory where diagnozed .mat files will be saved % -> set it to '' to use the default [dirModel 'mat/'] % doComp is a switch (1->compute; 0->display) %optional: dirTex is the directory where tex and figures files are created % (if not specified then display all results to screen instead) % nameTex is the tex file name (default : 'myPlots') if isempty(dirMat); dirMat=[dirModel 'mat/']; else; dirMat=[dirMat '/']; end; if isempty(dir(dirMat)); mkdir([dirMat]); end; %determine if and where to create tex and figures files dirMat=[dirMat '/']; if isempty(who('dirTex')); addToTex=0; else; if ~ischar(dirTex); error('mis-specified dirTex'); end; addToTex=1; if isempty(who('nameTex')); nameTex='myPlots'; end; fileTex=[dirTex nameTex '.tex']; end; %grid, params and inputs gcmfaces_global; global myparms; if ~isfield(mygrid,'XC'); grid_load('./GRID/',5,'compact'); end; if ~isfield(mygrid,'LATS_MASKS'); gcmfaces_lines_zonal; end; if isfield(myparms,'yearsta'); yearsta=myparms.yearsta; yearend=myparms.yearend; else; yearsta=1992; yearend=2011; end; [lonPairs,latPairs,names] = line_greatC_TUV_MASKS_core2_antarctic; lonLims=[lonPairs(1:5,1);lonPairs(1,1)]; if doComp; %grid, params and inputs fld_err=ones(90,1170); fld_err=convert2gcmfaces(fld_err); fld_w=fld_err.^-2; dirData='/net/nares/raid11/ecco-shared/ecco-version-4/input/'; fileModel=dir([dirModel 'barfiles/gbar_area*data']); fileModel=['barfiles/' fileModel.name]; nyears=yearend-yearsta+1; nmonths=12*nyears; %misfits : fld_dif=convert2gcmfaces(NaN*ones(90,90*13,nmonths)); fld_nsidc=convert2gcmfaces(NaN*ones(90,90*13,nmonths)); %monthly mean climatology : climMod=convert2gcmfaces(zeros(90,90*13,12)); climObs=convert2gcmfaces(zeros(90,90*13,12)); climMsk=convert2gcmfaces(zeros(90,90*13,12)); climNb=convert2gcmfaces(zeros(90,90*13,12)); %monthly integrals : IceAreaNorthMod=NaN*zeros(1,nmonths); IceAreaNorthObs=NaN*zeros(1,nmonths); IceAreaSouthMod=NaN*zeros(6,nmonths); IceAreaSouthObs=NaN*zeros(6,nmonths); %computational loop : for ycur=yearsta:yearend; tic; for mcur=1:12; mm=(ycur-yearsta)*12+mcur; fld_dat=read_bin([dirData 'input_nsidc_all/nsidc79_monthly_' num2str(ycur)],mcur,0); fld_dat=fld_dat.*mygrid.mskC(:,:,1);%land mask fld_dat(find(fld_dat<-99))=NaN;%missing data msk=1+0*fld_dat;%combined mask fld_mod=read_bin([dirModel fileModel],mm,0); fld_mod=fld_mod.*msk;%mask consistent with fld_dat %misfits : fld_dif(:,:,mm)=fld_mod-fld_dat; fld_nsidc(:,:,mm)=fld_dat; %climatology : tmp1=msk; tmp1(isnan(tmp1))=0; climMsk(:,:,mcur)=climMsk(:,:,mcur)+tmp1; tmp1=fld_mod; tmp1(isnan(tmp1))=0; climMod(:,:,mcur)=climMod(:,:,mcur)+tmp1; tmp1=fld_dat; tmp1(isnan(tmp1))=0; climObs(:,:,mcur)=climObs(:,:,mcur)+tmp1; %integrals : fld=fld_mod.*mygrid.RAC.*(mygrid.YC>0); IceAreaNorthMod(mm)=nansum(fld); fld=fld_dat.*mygrid.RAC.*(mygrid.YC>0); IceAreaNorthObs(mm)=nansum(fld); fld=fld_mod.*mygrid.RAC.*(mygrid.YC<0); IceAreaSouthMod(1,mm)=nansum(fld); fld=fld_dat.*mygrid.RAC.*(mygrid.YC<0); IceAreaSouthObs(1,mm)=nansum(fld); for kk=1:5; tmpmsk=0.*mygrid.XC; if lonLims(kk+1) > lonLims(kk) tmpmsk(find(mygrid.XC >= lonLims(kk) & mygrid.XC < lonLims(kk+1)))=1.; else tmpmsk(find(mygrid.XC >= lonLims(kk) & mygrid.XC <= 180.))=1.; tmpmsk(find(mygrid.XC >= -180. & mygrid.XC < lonLims(kk+1)))=1.; end tmpmsk=tmpmsk.*(mygrid.YC<0); % fld=fld_mod.*mygrid.RAC.*tmpmsk; IceAreaSouthMod(kk+1,mm)=nansum(fld); % fld=fld_dat.*mygrid.RAC.*tmpmsk; IceAreaSouthObs(kk+1,mm)=nansum(fld); end end; toc; end; %misfits : mis_rms=sqrt(nanmean(fld_dif.^2,3)); obs_std=nanstd(fld_nsidc,[],3); mod_std=nanstd(fld_nsidc+fld_dif,[],3); %climatology : for mcur=1:12; tmp1=climMsk(:,:,mcur); tmp1(tmp1==0)=NaN; climNb(:,:,mcur)=tmp1; climMod(:,:,mcur)=climMod(:,:,mcur)./tmp1; climObs(:,:,mcur)=climObs(:,:,mcur)./tmp1; end; clear climMsk; if ~isdir([dirMat 'cost/']); mkdir([dirMat 'cost/']); end; eval(['save ' dirMat '/cost/cost_seaicearea.mat fld_err mis_rms obs_std mod_std IceArea* clim*;']); else;%display previously computed results if isdir([dirMat 'cost/']); dirMat=[dirMat 'cost/']; end; eval(['load ' dirMat '/cost_seaicearea.mat;']); %variance maps: figure; m_map_gcmfaces(mis_rms,0,{'myCaxis',[0:0.1:1.]}); myCaption={'modeled-observed rms -- sea ice concentration'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(obs_std,0,{'myCaxis',[0:0.1:1.]}); myCaption={'observed std -- sea ice concentration'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(mod_std,0,{'myCaxis',[0:0.1:1.]}); myCaption={'modelled std -- sea ice concentration'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %arctic maps figureL; subplot(2,2,1); m_map_gcmfaces(climMod(:,:,3),2,{'myCaxis',[0:0.1:1.]}); subplot(2,2,2); m_map_gcmfaces(climObs(:,:,3),2,{'myCaxis',[0:0.1:1.]}); subplot(2,2,3); m_map_gcmfaces(climMod(:,:,9),2,{'myCaxis',[0:0.1:1.]}); subplot(2,2,4); m_map_gcmfaces(climObs(:,:,9),2,{'myCaxis',[0:0.1:1.]}); myCaption={'ECCO (left) and NSIDC (right, gsfc bootstrap) ice concentration in March (top) and September (bottom).'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %southern ocean maps figureL; subplot(2,2,1); m_map_gcmfaces(climMod(:,:,3),3,{'myCaxis',[0:0.1:1.]}); subplot(2,2,2); m_map_gcmfaces(climObs(:,:,3),3,{'myCaxis',[0:0.1:1.]}); subplot(2,2,3); m_map_gcmfaces(climMod(:,:,9),3,{'myCaxis',[0:0.1:1.]}); subplot(2,2,4); m_map_gcmfaces(climObs(:,:,9),3,{'myCaxis',[0:0.1:1.]}); myCaption={'ECCO (left) and NSIDC (right, gsfc bootstrap) ice concentration in March (top) and September (bottom).'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %northern/southern integrals ny=length(IceAreaNorthMod)/12; yy=yearsta+[0:ny-1]; figureL; subplot(1,2,1); plot(yy,IceAreaNorthMod(3:12:end),'LineWidth',2); hold on; plot(yy,IceAreaNorthObs(3:12:end),'r','LineWidth',2); plot(yy,IceAreaNorthMod(9:12:end),'LineWidth',2); plot(yy,IceAreaNorthObs(9:12:end),'r','LineWidth',2); axis([yearsta yearsta+ny-1 0 20e12]); ylabel('m^2'); title('Northern Hemisphere'); subplot(1,2,2); plot(yy,IceAreaSouthMod(1,3:12:end),'LineWidth',2); hold on; plot(yy,IceAreaSouthObs(1,3:12:end),'r','LineWidth',2); plot(yy,IceAreaSouthMod(1,9:12:end),'LineWidth',2); plot(yy,IceAreaSouthObs(1,9:12:end),'r','LineWidth',2); axis([yearsta yearsta+ny-1 0 20e12]); ylabel('m^2'); title('Southern Hemisphere'); myCaption={'ECCO (blue) and NSIDC (red, gsfc bootstrap) ice concentration in March and September',... 'in Northern Hemisphere (left) and Southern Hemisphere (right)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %southern basin integrals for mm=[3 9]; figureL; for ii=1:6; subplot(3,2,ii); if ii==1; iiTxt='Entire Southern Ocean'; else; iiTxt=sprintf('%dE to %dE',lonLims(ii-1),lonLims(ii)); end; plot(yy,IceAreaSouthMod(ii,mm:12:end),'LineWidth',2); hold on; plot(yy,IceAreaSouthObs(ii,mm:12:end),'r','LineWidth',2); aa=axis; aa(1:2)=[yearsta yearsta+ny-1]; axis(aa); ylabel('m^2'); title(iiTxt); end; if mm==3; mmTxt='March'; elseif mm==9; mmTxt='September'; else; '???'; end; myCaption={'ECCO (blue) and NSIDC (red, gsfc bootstrap) ice concentration in ',mmTxt,' per Southern Ocean sector'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; gcmfaces/ecco_v4/cost_altimeter_disp.m0000644000435400001440000001266512365532071017760 0ustar gforgetusersfunction []=cost_altimeter_disp(dirMat,choicePlot,suf,dirTex,nameTex); %object: plot the various sea level statistics % (std model-obs, model, obs, leading to cost function terms) %inputs: dirMat is the model run directory % choicePlot is 1 (rms) 2 (prior uncertainty) or 3 (cost) % suf is 'modMobs', 'obs' or 'mod' %optional: dirTex is the directory where tex and figures files are created % (if not specified then display all results to screen instead) % nameTex is the tex file name (default : 'myPlots') gcmfaces_global; %backward compatibility test test1=~isempty(dir([dirMat 'basic_diags_ecco_mygrid.mat'])); test2=~isempty(dir([dirMat 'diags_grid_parms.mat'])); if ~test1&~test2; error('missing diags_grid_parms.mat') elseif test2; nameGrid='diags_grid_parms.mat'; else; nameGrid='basic_diags_ecco_mygrid.mat'; end; %here we always reload the grid from dirMat to make sure the same one is used throughout eval(['load ' dirMat nameGrid ';']); %determine if and where to create tex and figures files dirMat=[dirMat '/']; if isempty(who('dirTex')); addToTex=0; else; if ~ischar(dirTex); error('mis-specified dirTex'); end; addToTex=1; if isempty(who('nameTex')); nameTex='myPlots'; end; fileTex=[dirTex nameTex '.tex']; end; %%%%%%%%%%%%%%% %define pathes: %%%%%%%%%%%%%%% if isempty(dirMat); dirMat=[dirModel 'mat/']; else; dirMat=[dirMat '/']; end; runName=pwd; tmp1=strfind(runName,filesep); runName=runName(tmp1(end)+1:end); %%%%%%%%%%%%%%%%% %do computations: %%%%%%%%%%%%%%%%% if isdir([dirMat 'cost/']); dirMat=[dirMat 'cost/']; end; eval(['load ' dirMat 'cost_altimeter_' suf '.mat myflds;']); %mask for plotting if isfield(myflds,'msk_100pts'); MSK=myflds.msk_100pts; else; MSK=mygrid.mskC(:,:,1); end; %hack to omit any masking : MSK(:)=1; if strcmp(suf,'modMobs'); tit='modeled-observed'; elseif strcmp(suf,'obs'); tit='observed'; elseif strcmp(suf,'mod'); tit='modeled'; else; error('unknown field'); end if choicePlot==1; tit=[tit ' log(variance)']; uni='(m$^2$)'; elseif choicePlot==2; tit=' log(prior error variance)'; uni='(m$^2$)'; else; tit=[tit ' cost']; uni=''; end; if choicePlot==1;%rms if strcmp(suf,'modMobs'); cc=[-0.4:0.05:-0.25 -0.2:0.03:-0.05 -0.03:0.01:0.03 0.05:0.03:0.2 0.25:0.05:0.4]; figure; m_map_gcmfaces(100*MSK.*myflds.dif_mdt,0,{'myCaxis',100*cc}); drawnow; myCaption={'mean dynamic topography misfit (cm)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; cc=[-4:0.2:-1]-0.5; figure; m_map_gcmfaces(log10(MSK.*(myflds.rms_sladiff_smooth.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- sea level anomaly ',uni,' -- large space/time scales'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; cc=[-4:0.2:-1]; figure; m_map_gcmfaces(log10(MSK.*(myflds.rms_sladiff_point.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- sea level anomaly ',uni,' -- pointwise'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; if 0; figure; m_map_gcmfaces(log10(MSK.*(myflds.rms_sladiff_point35d.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- sea level anomaly ',uni,' -- large time scales'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(log10(MSK.*(myflds.rms_sladiff_35dMsmooth.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- sea level anomaly ',uni,' -- point35d minus lsc'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(log10(MSK.*(myflds.rms_sladiff_pointMpoint35d.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- sea level anomaly ',uni,' -- point minus point35d'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; elseif choicePlot==2;%uncertainty fields cc=[0:0.005:0.02 0.03:0.01:0.05 0.06:0.02:0.1 0.14:0.03:0.2 0.25:0.05:0.4]; figure; m_map_gcmfaces(100*myflds.sig_mdt,0,{'myCaxis',100*cc}); drawnow; myCaption={'mean dynamic topography prior uncertainty (cm)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; cc=[-4:0.2:-1]-0.5; figure; m_map_gcmfaces(log10(MSK.*(myflds.sig_sladiff_smooth.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- sea level anomaly ',uni,' -- large space/time scales'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; cc=[-4:0.2:-1]; figure; m_map_gcmfaces(log10(MSK.*(myflds.sig_sladiff_point.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- sea level anomaly ',uni,' -- pointwise'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; else;%cost cc=[0:0.005:0.02 0.03:0.01:0.05 0.06:0.02:0.1 0.14:0.03:0.2 0.25:0.05:0.4]*100; figure; m_map_gcmfaces(MSK.*((myflds.dif_mdt.^2)./(myflds.sig_mdt.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- mean dynamic topography ',uni}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(MSK.*((myflds.rms_sladiff_smooth.^2)./(myflds.sig_sladiff_smooth.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- sea level anomaly ',uni,' -- large space/time scales'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(MSK.*((myflds.rms_sladiff_point.^2)./(myflds.sig_sladiff_point.^2)),0,{'myCaxis',cc}); drawnow; myCaption={tit,'-- sea level anomaly ',uni,' -- pointwise'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; gcmfaces/ecco_v4/cost_xx.m0000644000435400001440000000706612365532071015411 0ustar gforgetusersfunction []=cost_xx(dirModel,dirMat,doComp,dirTex,nameTex); %object: compute cost function term for atmospheric controls %inputs: dirModel is the model directory % dirMat is the directory where diagnozed .mat files will be saved % -> set it to '' to use the default [dirModel 'mat/'] % doComp is a switch (1->compute; 0->display) %optional: dirTex is the directory where tex and figures files are created % (if not specified then display all results to screen instead) % nameTex is the tex file name (default : 'myPlots') if isempty(dirMat); dirMat=[dirModel 'mat/']; else; dirMat=[dirMat '/']; end; if isempty(dir(dirMat)); mkdir([dirMat]); end; %determine if and where to create tex and figures files dirMat=[dirMat '/']; if isempty(who('dirTex')); addToTex=0; else; if ~ischar(dirTex); error('mis-specified dirTex'); end; addToTex=1; if isempty(who('nameTex')); nameTex='myPlots'; end; fileTex=[dirTex nameTex '.tex']; end; for ii=1:6; switch ii; case 1; xxName='atemp'; sigName='cap_sigma_tmp2m_degC_eccollc.bin'; cc=2; uni='K'; case 2; xxName='aqh'; sigName='cap_sigma_spfh2m_eccollc.bin'; cc=2; uni='g/kg'; case 3; xxName='tauu'; sigName='cap_sigma_ustr_eccollc.bin'; cc=0.04; uni='N/m2'; case 4; xxName='tauv'; sigName='cap_sigma_vstr_eccollc.bin'; cc=0.04; uni='N/m2'; case 5; xxName='lwdown'; sigName='cap_sigma_dlw_eccollc.bin'; cc=20; uni='W/m2'; case 6; xxName='swdown'; sigName='cap_sigma_dsw_eccollc.bin'; cc=40; uni='W/m2'; end; if doComp; %load grid gcmfaces_global; if ~isfield(mygrid,'XC'); grid_load('./GRID/',5,'compact'); end; if ~isfield(mygrid,'LATS_MASKS'); gcmfaces_lines_zonal; end; dirSig='/net/nares/raid11/ecco-shared/ecco-version-4/input/input_all_from_pleiades/'; %read model cost output tmp1=dir([dirModel 'ADXXfiles/xx_' xxName '.effective.*data']); tmp2=size(convert2gcmfaces(mygrid.XC)); fld_xx=read2memory([dirModel 'ADXXfiles/' tmp1.name],[tmp2 tmp1.bytes/tmp2(1)/tmp2(2)/4]); fld_xx=convert2gcmfaces(fld_xx); %does not work when adjoint overwrites xx*effective*meta fld_xx=rdmds2gcmfaces([dirModel 'ADXXfiles/xx_' xxName '.effective.*']); fld_sig=read_bin([dirSig sigName],1,0); if strcmp(xxName,'aqh'); fld_xx=fld_xx*1000; fld_sig=fld_sig*1000; end; %compute xx stats fld_rms=sqrt(mean(fld_xx.^2,3)); fld_mean=mean(fld_xx,3); fld_std=std(fld_xx,[],3); %mask fld_rms=fld_rms.*mygrid.mskC(:,:,1); fld_sig=fld_sig.*mygrid.mskC(:,:,1); fld_mean=fld_mean.*mygrid.mskC(:,:,1); fld_std=fld_std.*mygrid.mskC(:,:,1); clear fld_xx; if ~isdir([dirMat 'cost/']); mkdir([dirMat 'cost/']); end; eval(['save ' dirMat '/cost/cost_xx_' xxName '.mat fld_* cc uni;']); else;%display previously computed results global mygrid; if ~isdir([dirMat 'cost/']); dirMat=[dirMat 'cost/']; end; eval(['load ' dirMat '/cost_xx_' xxName '.mat;']); figure; m_map_gcmfaces(fld_sig,0,{'myCaxis',[0:0.05:0.5 0.6:0.1:1 1.25]*cc}); myCaption={['prior uncertainty -- ' xxName ' (' uni ')']}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(fld_rms,0,{'myCaxis',[0:0.05:0.5 0.6:0.1:1 1.25]*cc}); myCaption={['rms adjustment -- ' xxName ' (' uni ')']}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(fld_std,0,{'myCaxis',[0:0.05:0.5 0.6:0.1:1 1.25]*cc}); myCaption={['std adjustment -- ' xxName ' (' uni ')']}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(fld_mean,0,{'myCaxis',[-0.5:0.05:0.5]*cc}); myCaption={['mean adjustment -- ' xxName ' (' uni ')']}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end;%for ii=1:6; gcmfaces/ecco_v4/cost_read.m0000644000435400001440000000450412103041413015640 0ustar gforgetusersfunction [cost]=cost_read(dir0,file0,list0); %object: read a cost function file such as costfunction0000 %input: dir0 is the model run directory name % file0 (optional) is the cost function file name (costfunction0000 or % or costfunction0001 etc ). If file0 is not specified, % of specified as '' then it will be automatically be set % by inspecting dir0 (assuming there is only one in dir0) % list0 (optional) is a cell array of cost term names %output : if list0 is NOT specified, then cost is a structure vector % of cost(kk).fc, cost(kk).no, cost(kk).fc % if list0 is specified, then cost is the vector of cost terms if isempty(who('file0')); file0=''; end; if isempty(who('list0')); list0=''; end; %take care of file name: dir0=[dir0 '/']; if isempty(file0); file0=dir([dir0 'costfunction0*']); if length(file0)>1&nargin>1; fprintf('several costfunction0??? files were found:\n'); {file0(:).name}' error('please be more specific'); end; file0=file0.name; end; file0=[dir0 file0]; %read costfunction0??? file: fid=fopen(file0); tmp2=''; while 1; tline = fgetl(fid); if ~ischar(tline), break, end if isempty(tmp2); tmp2=[tline ' ; ']; else; tmp2=[tmp2 ' ' tline ' ; ']; end; end fclose(fid); %get cost from file (already in text form in memory): cost=[]; cost2=[]; kk=0; tmp1=[-3 strfind(tmp2,' ; ')]; for ii=1:length(tmp1)-1; tmp3=tmp2(tmp1(ii)+4:tmp1(ii+1)); jj=strfind(tmp3,'='); jj=jj(end)+1; tmp_name=tmp3(1:jj-2); tmp_val=tmp3(jj:end-1); % tmp_val(strfind(tmp_val,'D'))='e'; tmp_val(strfind(tmp_val,'+'))=''; eval(['tmp_val=[ ' tmp_val ' ];']); tmp_val(tmp_val==0)=NaN; % if ~isnan(tmp_val(1)); kk=kk+1; if kk==1; cost.name=strtrim(tmp_name); cost.fc=tmp_val(1); cost.no=tmp_val(2); else; cost(kk).name=strtrim(tmp_name); cost(kk).fc=tmp_val(1); cost(kk).no=tmp_val(2); end; end; end; %output vector of cost? if ~isempty(list0); cost_bak=cost; nn=length(list0); cost=NaN*zeros(nn,1); list1={cost_bak(:).name}; for kk=1:nn; jj=find(strcmp(list1,list0{kk})); if length(jj)>1; error([list0{kk} ' is not specific enough']); elseif length(jj)==1; %cost(kk,:)=[cost_bak(jj).fc cost_bak(jj).no]; cost(kk)=cost_bak(jj).fc; end; end; end; gcmfaces/ecco_v4/v4_basin.m0000644000435400001440000000553412365534162015430 0ustar gforgetusersfunction [varargout]=v4_basin(nameBasin,varargin); %object: obtain the mask of an ocean basin % %input: nameBasin name of the basin of interest (atl, pac, ind, arctic, etc.) %optional: msk0 value for the masked region (0 by default) % %output: mskC mask for tracer points (msk0=outside basin; 1=inside basin) %optional: mskW,mskS mask for velocity points (0=oustide/land; 1/2=edge; 1=inside) if nargin==2; msk0=varargin{1}; else; msk0=0; end; gcmfaces_global; dir0=which('gcmfaces_demo'); tmp1=strfind(dir0,filesep); dir0=[dir0(1:tmp1(end)) 'sample_input/OCCAetcONv4GRID/']; msk=read_bin([dir0 'basin_masks_eccollc_90x50.bin'],0,1); %list of available basins: list0={ 'pac','atl','ind','arct','bering',... 'southChina','mexico','okhotsk','hudson','med',... 'java','north','japan','timor','eastChina','red','gulf',... 'baffin','gin','barents'}; %list of selected basins: if ischar(nameBasin); nameBasin={nameBasin}; end; list1={}; for ii=1:length(nameBasin); if strcmp(nameBasin{ii},'atlExt'); list1={list1{:},'atl','mexico','hudson','med','north','baffin','gin'}; elseif strcmp(nameBasin{ii},'pacExt'); list1={list1{:},'pac','bering','okhotsk','japan','eastChina'}; elseif strcmp(nameBasin{ii},'indExt'); list1={list1{:},'ind','southChina','java','timor','red','gulf'}; else; list1={list1{:},nameBasin{ii}}; end; end %derive tracer points mask: mskC=0*msk; for ii=1:length(list1); jj=find(strcmp(list1{ii},list0)); if ~isempty(jj); mskC(find(msk==jj))=1; end; end; %determine velocity points masks, if needed: if nargout>1; %flag velocity points according to neighboring pair: fld=3*mskC+1*(~isnan(mygrid.mskC(:,:,1))); FLD=exch_T_N(fld); fldW=fld; fldS=fld; for iF=1:FLD.nFaces; tmpA=FLD{iF}(2:end-1,2:end-1); tmpB=FLD{iF}(1:end-2,2:end-1); fldW{iF}=(tmpA+tmpB)/2; tmpA=FLD{iF}(2:end-1,2:end-1); tmpB=FLD{iF}(2:end-1,1:end-2); fldS{iF}=(tmpA+tmpB)/2; end; %compute corresponding masks: mskW=0*mskC; mskW(find(fldW==4))=1;%inside points mskW(find(fldW==2.5))=0.5;%basin edge points mskS=0*mskC; mskS(find(fldS==4))=1;%inside points mskS(find(fldS==2.5))=0.5;%basin edge points %for checking: if 0; mskWout=0*mskC; mskWout(find(fldW==1))=1;%outside points mskWout(find(fldW==2.5))=0.5;%basin edge points mskSout=0*mskC; mskSout(find(fldS==1))=1;%outside points mskSout(find(fldS==2.5))=0.5;%basin edge points end; end; %replace 0 with msk0: mskC(find(mskC==0))=msk0; if nargout>1; mskW(find(mskW==0))=msk0; mskS(find(mskS==0))=msk0; end; %output(s): if nargout==1; varargout={mskC}; else; varargout={mskC,mskW,mskS}; end; %for checking: if 0; figure; msk0=1*(msk0>0); msk0(find(msk0==0))=NaN; subplot(2,1,1); imagescnan(convert2array(msk0)'); axis xy; caxis([-1 2]); subplot(2,1,2); imagescnan(convert2array(mskC.*msk0)'); axis xy; caxis([-1 2]); drawnow; end; gcmfaces/ecco_v4/read_grace_fld.m0000644000435400001440000000073012161145421016603 0ustar gforgetusersfunction [fld,fldsm]=read_grace_fld(fname); %[fld]=read_grace_fld('GRACE_CSR_Error.asc'); fid=fopen(fname,'rt'); fgetl(fid); fgetl(fid); fld4columns=zeros(1e5,4); ii=1; while ~feof(fid); fld4columns(ii,:)=str2num(fgetl(fid)); ii=ii+1; end; fclose(fid); ii=find(fld4columns(:,2)>0&fld4columns(:,2)<360); jj=(fld4columns(ii,1)+89.5)*360+fld4columns(ii,2)+0.5; fld=NaN*zeros(360,180); fld(jj)=fld4columns(ii,3); fldsm=NaN*zeros(360,180); fldsm(jj)=fld4columns(ii,4); gcmfaces/ecco_v4/cost_summary.m0000644000435400001440000001205011625547244016442 0ustar gforgetusersfunction []=cost_summary(dir0,file0,cost0); %object: display summary of the various cost terms from costfunction0??? file %input: dir0 is the model run directory name % file0 is the costfunction0??? file name (if '' then it will % be detected -- assuming there is only one in dir0) % cost0 is a reference value that will be used for normalization (1e8 by default) %note: hard coded ... mainly because multipliers are not in costfunction0??? file if isempty(cost0); cost0=1e8; end; %take care of file name: dir0=[dir0 '/']; if isempty(file0); file0=dir([dir0 'costfunction0*']); if length(file0)>1&nargin>1; fprintf('several costfunction0??? files were found:\n'); {file0(:).name}' error('please be more specific'); end; file0=file0.name; end; file0=[dir0 file0]; %read costfunction0??? file: fid=fopen(file0); tmp2=''; while 1; tline = fgetl(fid); if ~ischar(tline), break, end if isempty(tmp2); tmp2=[tline ' ; ']; else; tmp2=[tmp2 ' ' tline ' ; ']; end; end fclose(fid); %list of cost function terms and multipliers: (after apr1alpha/part2) mylist={'fc','f_temp','f_salt','f_sst','f_tmi',... 'argo_pacific_MITprof_latest_4mygridprof_T','argo_pacific_MITprof_latest_4mygridprof_S',... 'argo_atlantic_MITprof_latest_4mygridprof_T','argo_atlantic_MITprof_latest_4mygridprof_S',... 'argo_indian_MITprof_latest_4mygridprof_T','argo_indian_MITprof_latest_4mygridprof_S',... 'seals_MITprof_latest_4mygridprof_T','seals_MITprof_latest_4mygridprof_S',... 'WOD09_CTD_4mygridprof_T','WOD09_CTD_4mygridprof_S','WOD09_XBT_4mygridprof_T',... 'area','area2sst','sshv4-mdt','sshv4-lsc',... 'sshv4-tp','sshv4-ers','sshv4-gfo',... 'sstv4-amsre-lsc','sstv4-amsre'}; mymult=[[0 0.15 0.15 2 2] [2 2 2 2 2 2 1 1 2 2 2] [0 50 200 40] 0.25*[1 1 1] 25 1]; %before apr1alpha part 2 %mylist={'fc','f_temp','f_salt','f_sst','f_tmi',... % 'argo_pacific_MITprof_latest_4mygridprof_T','argo_pacific_MITprof_latest_4mygridprof_S',... % 'argo_atlantic_MITprof_latest_4mygridprof_T','argo_atlantic_MITprof_latest_4mygridprof_S',... % 'argo_indian_MITprof_latest_4mygridprof_T','argo_indian_MITprof_latest_4mygridprof_S',... % 'seals_MITprof_latest_4mygridprof_T','seals_MITprof_latest_4mygridprof_S','XBT_v5_4mygridprof_T',... % 'area','area2sst','sshv4-mdt','sshv4-lsc','sstv4-amsre-lsc',... % 'sshv4-tp','sshv4-ers','sshv4-gfo','sstv4-amsre'}; %mymult0=[[0 0.5 0.5 1 1] [2 2 2 2 2 2 1 1 2] [2 50 10 10 10] [1 1 1 1]];%during no1beta part 4 %mymult1=[[0 0.15 0.15 1 1] [2 2 2 2 2 2 1 1 2] [1 50 100 20 50] 0.25*[1 1 1 1]];%during nov1beta part 5 %mymult=[[0 0.15 0.15 1 1] [2 2 2 2 2 2 1 1 2] [1 50 100 20 50] 0.25*[1 1 1 1]];%during apr1alpha/part1 %get cost from file (already in text form in memory): mycost=[]; mycost2=[]; kk=0; tmp1=[-3 strfind(tmp2,' ; ')]; for ii=1:length(tmp1)-1; tmp3=tmp2(tmp1(ii)+4:tmp1(ii+1)); jj=strfind(tmp3,'='); jj=jj(end)+1; tmp_name=tmp3(1:jj-2); tmp_val=tmp3(jj:end-1); % jj=strfind(tmp_name,'gencost'); if ~isempty(jj); tmp_name=deblank(tmp_name(1:jj-2)); end; jj=find(~isspace(tmp_name)); tmp_name=tmp_name(jj); %if isempty(strfind(tmp_name,' prof_')); tmp_name=deblank(tmp_name); end; % tmp_val(strfind(tmp_val,'D'))='e'; tmp_val(strfind(tmp_val,'+'))=''; eval(['tmp_val=[ ' tmp_val ' ];']); tmp_val(tmp_val==0)=NaN; % if ~isnan(tmp_val(1))&sum(strcmp(tmp_name,mylist))>0; tmp_mult=mymult(find(strcmp(tmp_name,mylist))); kk=kk+1; if kk==1; mycost.name={tmp_name}; mycost.fc=tmp_val(1); mycost.no=tmp_val(2); mycost.mult=tmp_mult; mycost2.name=tmp_name; mycost2.fc=tmp_val(1); mycost2.no=tmp_val(2); mycost2.mult=tmp_mult; else; mycost.name(kk)={tmp_name}; mycost.fc(kk)=tmp_val(1); mycost.no(kk)=tmp_val(2); mycost.mult(kk)=tmp_mult; mycost2(kk).name=tmp_name; mycost2(kk).fc=tmp_val(1); mycost2(kk).no=tmp_val(2); mycost2(kk).mult=tmp_mult; end; end; end; %check that I recover the total: tmp1=100*sum(mycost.fc.*mycost.mult/mycost.fc(1)); fprintf('offline/online cost ratio is %3.3f%%\n',tmp1); %share for each cost term: myshare=mycost.fc.*mycost.mult; myshare=100*myshare/sum(myshare); %groups of cost terms: %myshare2=[sum(myshare(2:3)) sum(myshare([4 5 21 22])) sum(myshare(14:15)) sum(myshare([16:20])) sum(myshare(6:13))]'; fprintf('%15s contributes %3.2f%% \n','T/S atlas',sum(myshare(2:3))); fprintf('%15s contributes %3.2f%% \n','SST',sum(myshare([4 5 24 25]))); fprintf('%15s contributes %3.2f%% \n','ice conc',sum(myshare(17:18))); fprintf('%15s contributes %3.2f%% \n','SSH',sum(myshare(19:23))); fprintf('%15s contributes %3.2f%% \n','in situ',sum(myshare(6:16))); %plot the various contributions: % myplot=myshare; aa=[0 1.5 0 length(myplot)+1]; % figure; barh(myshare); axis(aa); grid on; hold on; title('cost terms contribution in %'); myplot=mycost.fc.*mycost.mult/cost0; aa=[0 10 0 length(myplot)+1]; myplot(1)=mycost.fc(1)/cost0; %to plot fc despite mult=0 figure; barh(myplot); axis(aa); grid on; hold on; title(sprintf('cost terms divided by %0.3g',cost0)); for ii=1:length(myplot); xx=myplot(ii)+0.01; yy=ii-0.4; text(xx,yy,mycost.name(ii),'Interpreter','none'); end; gcmfaces/ecco_v4/gcmfaces_remap.m0000644000435400001440000000433111747566713016663 0ustar gforgetusersfunction []=gcmfaces_remap(dirIn,fileIn,gridIn,dirOut,fileOut); %object: use bin average to remap a lat-lon grid product to a gcmfaces grid %inputs: dirIn is the input directory % fileIn is the input file name without the final four year characters % (e.g. 'SST_monthly_r2_' to process 'SST_monthly_r2_1992' etc.) % gridIn states the originating grid. It can be set to % 1 implying that the grid is [0.5:359.5] & [-89.5:89.5] % 2 implying that the grid is [0.5:359.5] & [-79.5:79.5] % 3 implying that the grid is [.125:.25:360-.125] & [-90+.125:.25:90-.125] % {x,y} where x and y are the position arrays % dirOut and filOut are the corresponding output names % %assumption: mygrid has been read using grid_load % for the input grid, lon must be 0-360 (see gcmfaces_remap_2d) global mygrid mytri; %create triangulation gcmfaces_bindata; %list files to be processed listFiles=dir([dirIn fileIn '*']); %case of user defined grid if iscell(gridIn); x=gridIn{1}; y=gridIn{2}; [nx,ny]=size(x); mis=0; else; %standard cases if gridIn==1;%gloabl 1 degree grid x=[0.5:359.5]'*ones(1,180); y=ones(360,1)*[-89.5:89.5]; [nx,ny]=size(x); mis=0; elseif gridIn==2;%ECCO 1 degree grid x=[0.5:359.5]'*ones(1,160); y=ones(360,1)*[-79.5:79.5]; [nx,ny]=size(x); mis=0; elseif gridIn==3;%1/4 degree grid (e.g. REMSS) x=[.125:.25:360-.125]'*ones(1,180*4); y=ones(360*4,1)*[-90+.125:.25:90-.125]; [nx,ny]=size(x); mis=-9999; else; error('unknown grid'); end; end; %process one file after the other for ii=1:length(listFiles); yy=listFiles(ii).name(end-3:end); fprintf(['processing ' fileIn ' for year ' yy '\n']); nt=listFiles(ii).bytes/nx/ny/4; if round(nt)~=nt; error('inconsistent sizes'); end; %read data fld=reshape(read2memory([dirIn listFiles(ii).name],[nx*ny*nt 1]),[nx ny nt]); %mask land fld(fld==mis)=NaN; %map to v4 grid FLD=convert2array(zeros(360,360,nt)); for tt=1:nt; FLD(:,:,tt)=gcmfaces_remap_2d(x,y,fld(:,:,tt),3); end; %set missing value FLD(find(isnan(FLD)))=mis; %write data write2file([dirOut fileOut yy],convert2gcmfaces(FLD)); end; gcmfaces/ecco_v4/rads_noice_mad_plot.m0000644000435400001440000000726112151726162017703 0ustar gforgetusersfunction [zBefore,zAfter]=rads_noice_mad_plot(choiceData); if isempty(who('doTesting')); doTesting=0; end; doPlot=0; %directories dirMad='/net/nares/raid10/gforget/2013mayInputs/rads/rads_ice_not_flagged/' dirRads='/bay/scratch2/RADS_alongtrk_v4_ice_not_flagged_2013/' dirOutput='./'; topexfile = 'tj_daily_ssh_v4_r1'; ersfile = 'en_daily_ssh_v4_r1'; gfofile = 'g1_daily_ssh_v4_r1'; dirIce='/net/nares/raid11/ecco-shared/ecco-version-4/input/input_nsidc_all/'; fileIce='nsidc79_daily'; nday=zeros(20,1); for yy=1992:2012; tmp1=dir([dirRads topexfile '_' num2str(yy)]); nday(yy-1991)=tmp1.bytes/90/1170/4; end; years=[1992:2012]; dayMax=datenum(years(end)+1,1,1)-datenum(years(1),1,1); gcmfaces_global; eval(['fileData=' choiceData ';']); slaBefore=zeros(90*1170,dayMax); slaAfter=slaBefore; for yy=years; fprintf(['reading ' fileData '_' num2str(yy) '\n']); day1=1+datenum(yy,1,1)-datenum(years(1),1,1); dayN=datenum(yy+1,1,1)-datenum(years(1),1,1); % fld=read2memory([dirRads fileData '_' num2str(yy)],[90*1170 1+dayN-day1]); fld(fld<-999)=NaN; slaBefore(:,day1:dayN)=fld; % fld=read2memory([dirMad fileData '_mad_' num2str(yy)],[90*1170 1+dayN-day1]); fld(fld<-999)=NaN; slaAfter(:,day1:dayN)=fld; end; %global+time mean stats : cntNbs=[sum(~isnan(slaBefore(:))) sum(~isnan(slaAfter(:)))]; cntNbs(3)=100*(1-cntNbs(2)/cntNbs(1)); stdNbs=[nanstd(slaBefore(:)) nanstd(slaAfter(:))]; stdNbs(3)=100*(1-stdNbs(2)/stdNbs(1)); fid = fopen([dirMad fileData '_mad_stats.txt'],'w'); fprintf(fid,' instr : %s \n',fileData); fprintf(fid,' # samples : %d \n',cntNbs(1)); fprintf(fid,' %% mad reject : %3.2f \n',cntNbs(3)); fclose(fid); %global mean stats : stdBefore=nanstd(slaBefore,[],1); stdAfter=nanstd(slaAfter,[],1); cntBefore=sum(~isnan(slaBefore),1); cntAfter=sum(~isnan(slaAfter),1); stdBefore=runmean(stdBefore,17,2); stdAfter=runmean(stdAfter,17,2); cntBefore=runmean(cntBefore,17,2); cntAfter=runmean(cntAfter,17,2); %zonal mean stats : msk=mygrid.mskC(:,:,1); z=nanstd(slaBefore,[],2); z=convert2gcmfaces(reshape(z,[90 1170])); zBefore=z;%output slaBeforeStd=calc_zonmean_T(msk.*z); z=nanstd(slaAfter,[],2); z=convert2gcmfaces(reshape(z,[90 1170])); zAfter=z;%output slaAfterStd=calc_zonmean_T(msk.*z); z=sum(~isnan(slaBefore),2); z=convert2gcmfaces(reshape(z,[90 1170])); slaBeforeCnt=calc_zonmean_T(msk.*z); z=sum(~isnan(slaAfter),2); z=convert2gcmfaces(reshape(z,[90 1170])); slaAfterCnt=calc_zonmean_T(msk.*z); %plotting: figureL; % x=mygrid.LATS; subplot(3,2,1); plot(x,slaBeforeStd); hold on; plot(x,slaAfterStd,'r'); axis([-90 90 0 30]); title('std before (b) and after (r)'); ylabel('cm'); xlabel('lat'); subplot(3,2,3); plot(x,slaBeforeCnt); hold on; plot(x,slaAfterCnt,'r'); axis([-90 90 0 1e3]) title('count before (b) and after (r)'); ylabel('# obs'); xlabel('lat'); subplot(3,2,5); plot(x,100*(1-slaAfterStd./slaBeforeStd),'k'); hold on; plot(x,100*(1-slaAfterCnt./slaBeforeCnt),'m'); axis([-90 90 0 20]) title('std (k) and count (m) reduction : 100*(1-after/before)'); ylabel('%'); xlabel('lat'); % x=[1:dayMax]; subplot(3,2,2); plot(x,stdBefore); hold on; plot(x,stdAfter,'r'); axis([0 8e3 0 20]); title('std before (b) and after (r)'); ylabel('cm'); xlabel('lat'); subplot(3,2,4); plot(x,cntBefore); hold on; plot(x,cntAfter,'r'); axis([0 8e3 0 2e4]); title('count before (b) and after (r)'); ylabel('# obs'); xlabel('lat'); subplot(3,2,6); plot(x,100*(1-stdAfter./stdBefore),'k'); hold on; plot(x,100*(1-cntAfter./cntBefore),'m'); axis([0 8e3 0 20]); title('std (k) and count (m) reduction : 100*(1-after/before)'); ylabel('%'); xlabel('lat'); % saveas(gcf,[dirMad fileData '_mad_stats'],'fig'); eval(['print -djpeg90 ' dirMad fileData '_mad_stats.jpg']); gcmfaces/ecco_v4/v4_read_data.m0000644000435400001440000000111312365534162016225 0ustar gforgetusersfunction [fld]=v4_read_data(fileName,irec); %usage: fld=v4_read_data(fileName,irec); 'fast' read of 2D fields no irec in all [fileName '*.data'] gcmfaces_global; dir0=strfind(fileName,filesep); if isempty(dir0); dir0='./'; else; dir0=fileName(1:dir0(end)); end; fileList=dir([fileName '.data']); nn=length(fileList); fld=zeros(90,1170,nn); for ii=1:nn; fid_cur=fopen([dir0 fileList(ii).name],'r','b'); recl=90*1170*4; position0=recl*(irec-1); status=fseek(fid_cur,position0,'bof'); fld(:,:,ii)=fread(fid_cur,[90 1170],'float32'); fclose(fid_cur); end; fld=convert2gcmfaces(fld); gcmfaces/ecco_v4/cost_altimeter.m0000644000435400001440000002523212365532071016733 0ustar gforgetusersfunction []=cost_altimeter(dirModel,dirMat); %object: compute or plot the various sea level statistics % (std model-obs, model, obs, leading to cost function terms) %inputs: dirModel is the model run directory % dirMat is the directory where diagnozed .mat files will be saved % -> set it to '' to use the default [dirModel 'mat/'] % doComp is the switch from computation to plot doComp=1; if doComp==1; doSave=1; doPlot=0; else; doSave=0; doPlot=1; end; doPrint=0; for doDifObsOrMod=1:3; if doDifObsOrMod==1; suf='modMobs'; elseif doDifObsOrMod==2; suf='obs'; else; suf='mod'; end; %%%%%%%%%%% %load grid: %%%%%%%%%%% gcmfaces_global; if ~isfield(mygrid,'XC'); grid_load('./GRID/',5,'compact'); end; if ~isfield(mygrid,'LATS_MASKS'); gcmfaces_lines_zonal; end; %%%%%%%%%%%%%%% %define pathes: %%%%%%%%%%%%%%% dirSigma='/net/nares/raid11/ecco-shared/ecco-version-4/input/input_err/'; %nameSigma={'sigma_MDT_glob_eccollc.bin','sigma_SLA_smooth_eccollc.bin','sigma_SLA_PWS07r2_glob_eccollc.bin'}; maxLatObs=66 nameSigma={'sigma_MDT_glob_eccollc.bin','slaerr_largescale_r4.err','slaerr_gridscale_r4.err'}; maxLatObs=90 if isempty(dirMat); dirMat=[dirModel 'mat/']; else; dirMat=[dirMat '/']; end; if isempty(dir(dirMat)); mkdir([dirMat]); end; if ~isdir([dirMat 'cost/']); mkdir([dirMat 'cost/']); end; runName=pwd; tmp1=strfind(runName,filesep); runName=runName(tmp1(end)+1:end); %%%%%%%%%%%%%%%%% %do computations: %%%%%%%%%%%%%%%%% if doComp==0; eval(['load ' dirMat 'cost/cost_altimeter_' suf '.mat myflds;']); else; tic; %mdt cost function term (misfit plot) dif_mdt=rdmds2gcmfaces([dirModel 'barfiles/mdtdiff_smooth']); sig_mdt=read_bin([dirSigma nameSigma{1}],1,0); sig_mdt(find(sig_mdt==0))=NaN; %store: myflds.dif_mdt=dif_mdt; myflds.sig_mdt=sig_mdt; %skip blanks: tmp1=dir([dirModel 'barfiles/sladiff_smooth*data']); nrec=tmp1.bytes/90/1170/4; ttShift=17; %skip 1992 listRecs=[1+365-ttShift:17+365*18-ttShift]; nRecs=length(listRecs); TT=1993+[0:nRecs-1]/365.25; toc; tic; %pointwise/1day terms: sladiff_point=repmat(0*mygrid.RAC,[1 1 nRecs]); count_point=sladiff_point; for ii=1:3; if ii==1; myset='tp'; elseif ii==2; myset='gfo'; else; myset='ers'; end; %topex pointwise misfits: if doDifObsOrMod==1; sladiff_tmp=cost_altimeter_read([dirModel 'barfiles/sladiff_' myset '_raw'],ttShift+listRecs); elseif doDifObsOrMod==2; sladiff_tmp=cost_altimeter_read([dirModel 'barfiles/slaobs_' myset '_raw'],ttShift+listRecs); else; sladiff_tmp=cost_altimeter_read([dirModel 'barfiles/sladiff_' myset '_raw'],ttShift+listRecs); sladiff_tmp=sladiff_tmp+cost_altimeter_read([dirModel 'barfiles/slaobs_' myset '_raw'],ttShift+listRecs); end; %add to overall data set: sladiff_point=sladiff_point+sladiff_tmp; count_point=count_point+(sladiff_tmp~=0); %finalize data set: sladiff_tmp(sladiff_tmp==0)=NaN; %compute rms: count_tmp=sum(~isnan(sladiff_tmp),3); count_tmp(find(count_tmp<10))=NaN; msk_tmp=1+0*count_tmp; eval(['myflds.rms_' myset '=sqrt(nansum(sladiff_tmp.^2,3)./count_tmp);']); eval(['myflds.std_' myset '=nanstd(sladiff_tmp,0,3).*msk_tmp;']); end; %finalize overall data set: count_point(count_point==0)=NaN; sladiff_point=sladiff_point./count_point; %compute overall rms,std: count_tmp=sum(~isnan(sladiff_point),3); count_tmp(find(count_tmp<10))=NaN; msk_tmp=1+0*count_tmp; myflds.rms_sladiff_point=sqrt(nansum(sladiff_point.^2,3)./count_tmp); myflds.std_sladiff_point=nanstd(sladiff_point,0,3).*msk_tmp; % msk_point=1*(count_point>0); %fill blanks: warning('off','MATLAB:divideByZero'); msk=mygrid.mskC(:,:,1); msk(find(abs(mygrid.YC)>maxLatObs))=NaN; myflds.xtrp_rms_sladiff_point=diffsmooth2D_extrap_inv(myflds.rms_sladiff_point,msk); myflds.xtrp_std_sladiff_point=diffsmooth2D_extrap_inv(myflds.std_sladiff_point,msk); warning('on','MATLAB:divideByZero'); %get weight: sig_sladiff_point=read_bin([dirSigma nameSigma{3}],1,0); sig_sladiff_point(find(sig_sladiff_point==0))=NaN; myflds.sig_sladiff_point=sig_sladiff_point; %computational mask : only points that were actually observed, and in 35d average msk_point35d=cost_altimeter_read([dirModel 'barfiles/sladiff_raw'],listRecs); msk_point35d=1*(msk_point35d~=0); tmp1=sum(msk_point35d==0&msk_point~=0); tmp2=sum(msk_point35d~=0&msk_point~=0); fprintf('after masking : %d omitted, %d retained \n',tmp1,tmp2); msk_point=msk_point.*msk_point35d; msk_point(msk_point==0)=NaN; %plotting mask : regions of less than 100 observations are omitted msk_100pts=1*(nansum(msk_point,3)>=100); msk_100pts(msk_100pts==0)=NaN; %store myflds.msk_100pts=msk_100pts; toc; tic; %lsc cost function term: if doDifObsOrMod==1; sladiff_smooth=cost_altimeter_read([dirModel 'barfiles/sladiff_smooth'],listRecs); elseif doDifObsOrMod==2; sladiff_smooth=cost_altimeter_read([dirModel 'barfiles/slaobs_smooth'],listRecs); else; sladiff_smooth=cost_altimeter_read([dirModel 'barfiles/sladiff_smooth'],listRecs); sladiff_smooth=sladiff_smooth+cost_altimeter_read([dirModel 'barfiles/slaobs_smooth'],listRecs); end; %mask missing points: sladiff_smooth(sladiff_smooth==0)=NaN; sladiff_smooth=sladiff_smooth.*msk_point; count_tmp=sum(~isnan(sladiff_smooth),3); count_tmp(find(count_tmp<10))=NaN; msk_tmp=1+0*count_tmp; %compute rms: rms_sladiff_smooth=msk_tmp.*sqrt(nanmean(sladiff_smooth.^2,3)); std_sladiff_smooth=msk_tmp.*nanstd(sladiff_smooth,0,3); %get weight: sig_sladiff_smooth=read_bin([dirSigma nameSigma{2}],1,0); sig_sladiff_smooth(find(sig_sladiff_smooth==0))=NaN; %store: myflds.rms_sladiff_smooth=rms_sladiff_smooth; myflds.std_sladiff_smooth=std_sladiff_smooth; myflds.sig_sladiff_smooth=sig_sladiff_smooth; toc; tic; %pointwise/point35days cost function term: if doDifObsOrMod==1; sladiff_point35d=cost_altimeter_read([dirModel 'barfiles/sladiff_raw'],listRecs); elseif doDifObsOrMod==2; sladiff_point35d=cost_altimeter_read([dirModel 'barfiles/slaobs_raw'],listRecs); else; sladiff_point35d=cost_altimeter_read([dirModel 'barfiles/sladiff_raw'],listRecs); sladiff_point35d=sladiff_point35d+cost_altimeter_read([dirModel 'barfiles/slaobs_raw'],listRecs); end; %mask missing points: sladiff_point35d(sladiff_point35d==0)=NaN; sladiff_point35d=sladiff_point35d.*msk_point; count_tmp=sum(~isnan(sladiff_point35d),3); count_tmp(find(count_tmp<10))=NaN; msk_tmp=1+0*count_tmp; %compute rms: rms_sladiff_point35d=msk_tmp.*sqrt(nanmean(sladiff_point35d.^2,3)); std_sladiff_point35d=msk_tmp.*nanstd(sladiff_point35d,0,3); %store: myflds.rms_sladiff_point35d=rms_sladiff_point35d; myflds.std_sladiff_point35d=std_sladiff_point35d; if 0; %difference between scales rms_sladiff_35dMsmooth=msk_tmp.*sqrt(nanmean((sladiff_point35d-sladiff_smooth).^2,3)); std_sladiff_35dMsmooth=msk_tmp.*nanstd((sladiff_point35d-sladiff_smooth),0,3); %store: myflds.rms_sladiff_35dMsmooth=rms_sladiff_35dMsmooth; myflds.std_sladiff_35dMsmooth=std_sladiff_35dMsmooth; %difference between scales rms_sladiff_pointMpoint35d=msk_tmp.*sqrt(nanmean((sladiff_point-sladiff_point35d).^2,3)); std_sladiff_pointMpoint35d=msk_tmp.*nanstd((sladiff_point-sladiff_point35d),0,3); %store: myflds.rms_sladiff_pointMpoint35d=rms_sladiff_pointMpoint35d; myflds.std_sladiff_pointMpoint35d=std_sladiff_pointMpoint35d; end; %compute zonal mean/median: for ii=1:4; switch ii; case 1; tmp1='mdt'; cost_fld=(mygrid.mskC(:,:,1).*myflds.dif_mdt./myflds.sig_mdt).^2; case 2; tmp1='lsc'; cost_fld=(mygrid.mskC(:,:,1).*myflds.rms_sladiff_smooth./myflds.sig_sladiff_smooth).^2; case 3; tmp1='point35d'; cost_fld=(mygrid.mskC(:,:,1).*myflds.rms_sladiff_point35d./myflds.sig_sladiff_point).^2; case 4; tmp1='point'; cost_fld=(mygrid.mskC(:,:,1).*myflds.rms_sladiff_point./myflds.sig_sladiff_point).^2; end; cost_zmean=calc_zonmean_T(cost_fld); eval(['mycosts_mean.' tmp1 '=cost_zmean;']); cost_zmedian=calc_zonmedian_T(cost_fld); eval(['mycosts_median.' tmp1 '=cost_zmedian;']); end; toc; %write to disk: if doSave; eval(['save ' dirMat 'cost/cost_altimeter_' suf '.mat myflds mycosts_mean mycosts_median;']); end; end;%if doComp if doPlot; cc=[-0.4:0.05:-0.25 -0.2:0.03:-0.05 -0.03:0.01:0.03 0.05:0.03:0.2 0.25:0.05:0.4]; figure; m_map_gcmfaces(myflds.dif_mdt,0,{'myCaxis',cc}); drawnow; cc=[0:0.005:0.02 0.03:0.01:0.05 0.06:0.02:0.1 0.14:0.03:0.2 0.25:0.05:0.4]; figure; m_map_gcmfaces(myflds.rms_sladiff_smooth,0,{'myCaxis',cc}); drawnow; figure; m_map_gcmfaces(myflds.rms_sladiff_point35d,0,{'myCaxis',cc}); drawnow; figure; m_map_gcmfaces(myflds.rms_sladiff_point,0,{'myCaxis',cc}); drawnow; end; if doPlot&doPrint; dirFig='../figs/altimeter/'; ff0=gcf-4; for ff=1:4; figure(ff+ff0); saveas(gcf,[dirFig runName '_' suf num2str(ff)],'fig'); eval(['print -depsc ' dirFig runName '_' suf num2str(ff) '.eps;']); eval(['print -djpeg90 ' dirFig runName '_' suf num2str(ff) '.jpg;']); end; end; end;%for doDifObsOrMod=1:3; function [fldOut]=cost_altimeter_read(fileIn,recIn); nrec=length(recIn); global mygrid; siz=[size(convert2gcmfaces(mygrid.XC)) nrec]; lrec=siz(1)*siz(2)*4; myprec='float32'; fldOut=zeros(siz); fid=fopen([fileIn '.data'],'r','b'); for irec=1:nrec; status=fseek(fid,(recIn(irec)-1)*lrec,'bof'); fldOut(:,:,irec)=fread(fid,siz(1:2),myprec); end; fldOut=convert2gcmfaces(fldOut); gcmfaces/ecco_v4/cost_sst.m0000644000435400001440000001521312365532071015554 0ustar gforgetusersfunction []=cost_sst(dirModel,dirMat,doComp,dirTex,nameTex); %object: compute cost function term for sst data %inputs: dimodel is the model directory % dirMat is the directory where diagnozed .mat files will be saved % -> set it to '' to use the default [dirModel 'mat/'] % doComp is a switch (1->compute; 0->display) %optional: dirTex is the directory where tex and figures files are created % (if not specified then display all results to screen instead) % nameTex is the tex file name (default : 'myPlots') if isempty(dirMat); dirMat=[dirModel 'mat/']; else; dirMat=[dirMat '/']; end; if isempty(dir(dirMat)); mkdir([dirMat]); end; %determine if and where to create tex and figures files dirMat=[dirMat '/']; if isempty(who('dirTex')); addToTex=0; else; if ~ischar(dirTex); error('mis-specified dirTex'); end; addToTex=1; if isempty(who('nameTex')); nameTex='myPlots'; end; fileTex=[dirTex nameTex '.tex']; end; if doComp; %grid, params and inputs gcmfaces_global; global myparms; if ~isfield(mygrid,'XC'); grid_load('./GRID/',5,'compact'); end; if ~isfield(mygrid,'LATS_MASKS'); gcmfaces_lines_zonal; end; if isfield(myparms,'yearFirst'); yearFirst=myparms.yearFirst; yearLast=myparms.yearLast; else; yearFirst=1992; yearLast=2011; end; dirData='/net/nares/raid11/ecco-shared/ecco-version-4/input/'; subdirReynolds='input_sst_reynolds_v4/'; nameReynolds='reynolds_oiv2_r1'; subdirRemss='input_sst_remss_v4/'; nameRemss='tmi_amsre_oisst_r1'; subdirL2p='input_sst_amsre_daily/'; nameL2p='tmi_amsre_l2p_r1'; if 0;%old versions nameReynolds='v4_reynolds_monthly'; nameRemss='v4_TMI_AMSRE_sst_monav'; nameL2p='amsre_r2'; yearLast=2010; end; dirErr='/net/nares/raid11/ecco-shared/ecco-version-4/input/input_all_from_pleiades/'; fld_err=read2memory([dirErr '/sigma_half.bin'],[90 1170]); fld_err=convert2gcmfaces(fld_err); fld_w=fld_err.^-2; fileModel=dir([dirModel 'barfiles/tbar*data']); fileModel=['barfiles/' fileModel.name]; %computational loop mod_m_rey=repmat(NaN*mygrid.mskC(:,:,1),[1 1 12*(yearLast-yearFirst+1)]); mod_m_remss=repmat(NaN*mygrid.mskC(:,:,1),[1 1 12*(yearLast-yearFirst+1)]); % zm_mod=repmat(ones(length(mygrid.LATS),1),[1 12*(yearLast-yearFirst+1)]); zm_rey=repmat(ones(length(mygrid.LATS),1),[1 12*(yearLast-yearFirst+1)]); zm_mod_m_rey=repmat(ones(length(mygrid.LATS),1),[1 12*(yearLast-yearFirst+1)]); zm_remss=repmat(ones(length(mygrid.LATS),1),[1 12*(yearLast-yearFirst+1)]); zm_mod_m_remss=repmat(ones(length(mygrid.LATS),1),[1 12*(yearLast-yearFirst+1)]); % for ycur=yearFirst:yearLast; fprintf(['starting ' num2str(ycur) '\n']); tic; for mcur=1:12; %load Reynolds SST file0=[dirData subdirReynolds nameReynolds '_' num2str(ycur)]; if ~isempty(dir(file0)); fld_rey=read_bin(file0,mcur,0); else; fld_rey=NaN*mygrid.mskC(:,:,1); end; fld_rey(find(fld_rey==0))=NaN; fld_rey(find(fld_rey<-99))=NaN; %load Remss SST file0=[dirData subdirRemss nameRemss '_' num2str(ycur)]; if ~isempty(dir(file0)); fld_remss=read_bin(file0,mcur,0); else; fld_remss=NaN*mygrid.mskC(:,:,1); end; fld_remss(find(fld_remss==0))=NaN; fld_remss(find(fld_remss<-99))=NaN; %load model SST mm=(ycur-yearFirst)*12+mcur; fld_mod=read_bin([dirModel fileModel],mm,1).*mygrid.mskC(:,:,1); %store misfit maps mod_m_rey(:,:,mm)=fld_mod-fld_rey; mod_m_remss(:,:,mm)=fld_mod-fld_remss; %comp zonal means zm_mod(:,mm)=calc_zonmean_T(fld_mod.*mygrid.mskC(:,:,1)); msk=mygrid.mskC(:,:,1); msk(fld_rey==0)=NaN; zm_rey(:,mm)=calc_zonmean_T(fld_rey.*msk); zm_mod_m_rey(:,mm)=calc_zonmean_T(fld_mod-fld_rey.*msk); msk=mygrid.mskC(:,:,1); msk(fld_remss==0)=NaN; zm_remss(:,mm)=calc_zonmean_T(fld_remss.*msk); zm_mod_m_remss(:,mm)=calc_zonmean_T(fld_mod-fld_remss.*msk); end; toc; end; %compute rms maps rms_to_rey=sqrt(nanmean(mod_m_rey.^2,3)); rms_to_remss=sqrt(nanmean(mod_m_remss.^2,3)); if ~isdir([dirMat 'cost/']); mkdir([dirMat 'cost/']); end; eval(['save ' dirMat '/cost/cost_sst.mat fld_err rms_* zm_*;']); else;%display previously computed results global mygrid; if isdir([dirMat 'cost/']); dirMat=[dirMat 'cost/']; end; eval(['load ' dirMat '/cost_sst.mat;']); if ~isempty(who('fld_rms')); figure; m_map_gcmfaces(fld_rms,0,{'myCaxis',[0:0.2:1.2 1.5:0.5:3 4:1:6 8 10]/2}); myCaption={'modeled-observed rms -- sea surface temperature (K)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; else; figure; m_map_gcmfaces(rms_to_rey,0,{'myCaxis',[0:0.2:1.2 1.5:0.5:3 4:1:6 8 10]/2}); myCaption={'modeled-Reynolds rms -- sea surface temperature (K)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(rms_to_remss,0,{'myCaxis',[0:0.2:1.2 1.5:0.5:3 4:1:6 8 10]/2}); myCaption={'modeled-REMSS rms -- sea surface temperature (K)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; ny=size(zm_rey,2)/12; [xx,yy]=meshgrid(1992+([1:ny*12]-0.5)/12,mygrid.LATS); figureL; obs=zm_rey; obsCycle=sst_cycle(obs); mod=zm_rey+zm_mod_m_rey; modCycle=sst_cycle(mod); mis=zm_mod_m_rey; misCycle=sst_cycle(mis); subplot(3,1,1); pcolor(xx,yy,obs-obsCycle); shading flat; caxis([-1 1]*1); colorbar; set(gca,'FontSize',14); set(gca,'XTick',[]); ylabel('latitude'); title('Reynolds sst anomaly'); subplot(3,1,2); pcolor(xx,yy,mod-modCycle); shading flat; caxis([-1 1]*1); colorbar; set(gca,'FontSize',14); set(gca,'XTick',[]); ylabel('latitude'); title('ECCO sst anomaly'); subplot(3,1,3); pcolor(xx,yy,mis-misCycle); shading flat; caxis([-1 1]*1); colorbar; set(gca,'FontSize',14); ylabel('latitude'); title('ECCO-Reynolds sst misfit'); myCaption={'ECCO and Reynolds zonal mean sst anomalies (K)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figureL; obs=zm_remss; obsCycle=sst_cycle(obs); mod=zm_remss+zm_mod_m_remss; modCycle=sst_cycle(mod); mis=zm_mod_m_remss; misCycle=sst_cycle(mis); subplot(3,1,1); pcolor(xx,yy,obs-obsCycle); shading flat; caxis([-1 1]*1); colorbar; set(gca,'FontSize',14); set(gca,'XTick',[]); ylabel('latitude'); title('REMSS sst anomaly'); subplot(3,1,2); pcolor(xx,yy,mod-modCycle); shading flat; caxis([-1 1]*1); colorbar; set(gca,'FontSize',14); set(gca,'XTick',[]); ylabel('latitude'); title('ECCO sst anomaly'); subplot(3,1,3); pcolor(xx,yy,mis-misCycle); shading flat; caxis([-1 1]*1); colorbar; set(gca,'FontSize',14); ylabel('latitude'); title('ECCO-REMSS sst misfit'); myCaption={'ECCO and REMSS zonal mean sst anomalies (K)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; function [zmCycle]=sst_cycle(zmIn); ny=size(zmIn,2)/12; zmCycle=NaN*zeros(179,12); for mm=1:12; zmCycle(:,mm)=nanmean(zmIn(:,mm:12:ny*12),2); end; zmCycle=repmat(zmCycle,[1 ny]); gcmfaces/ecco_v4/map_grace.m0000644000435400001440000000334512161145421015625 0ustar gforgetusers xC1=[0.5:359.5]'*ones(1,180); yC1=ones(360,1)*[-89.5:89.5]; v4_reclen=convert2gcmfaces(mygrid.RAC); v4_reclen=size(v4_reclen); v4_reclen=v4_reclen(1)*v4_reclen(2); dir_out='./'; %output directory dir_in='./'; %input directory file_pref='GRACE_CSR_withland_'; %load error field [fieldErr_nosmooth,fieldErr]=read_grace_fld([dir_in 'GRACE_CSR_Error.asc']); %process grace fields for yy=1992:2012; for mm=1:12; tt=sprintf('%4i%02i',yy,mm); file0=dir([dir_in file_pref tt '.asc']); if ~isempty(file0); %read file0=file0.name; field0=read_grace_fld([dir_in file0]); %map x=[xC1-360;xC1]; y=[yC1;yC1]; z=[field0;field0]; x=[x x x]; y=[y-180 y y+180]; z=[flipdim(z,2) z flipdim(z,2)]; field1=0*mygrid.XC; for ii=1:5; xi=mygrid.XC{ii}; yi=mygrid.YC{ii}; zi = interp2(x',y',z',xi,yi); %zi = griddata(x,y,z,xi,yi); field1{ii}=zi; end; %mask the model poles tmp1=find(mygrid.RAC<8e8&mygrid.YC>0); field1(tmp1)=NaN; tmp1=find(mygrid.RAC<2e8&mygrid.YC<0); field1(tmp1)=NaN; else; fprintf(['did not find : ' file_pref tt '.asc \n']); field1=NaN*mygrid.RAC; end; %use -999 for mask field1(isnan(field1))=-999; %write to file if mm==1; fid=fopen([dir_out file_pref num2str(yy)],'w','b'); end; fwrite(fid,convert2gcmfaces(field1),'float32'); if mm==12; fclose(fid); end; end; end; %process error estimate z=[fieldErr;fieldErr]; z=[flipdim(z,2) z flipdim(z,2)]; field1=0*mygrid.XC; for ii=1:5; xi=mygrid.XC{ii}; yi=mygrid.YC{ii}; zi = interp2(x',y',z',xi,yi); %zi = griddata(x,y,z,xi,yi); field1{ii}=zi; end; %mask the model poles tmp1=find(mygrid.RAC<8e8&mygrid.YC>0); field1(tmp1)=NaN; tmp1=find(mygrid.RAC<2e8&mygrid.YC<0); field1(tmp1)=NaN; %use 0 for mask field1(isnan(field1))=0; %write to file write2file([dir_out file_pref 'err'],convert2gcmfaces(field1)); gcmfaces/ecco_v4/rads_noice_mad.m0000644000435400001440000001601412145162164016640 0ustar gforgetusersfunction []=rads_noice_mad(choiceData,l0,L0,doTesting,doNoice); %object : outlier (& ice if doNoice) data flagging for altimetry %inputs : choiceData is 'topexfile','ersfile' or 'gfofile' % l0 is the box longitude (l0+-10 will be treated) % L0 is the box latitude (L0+-10 will be treated) % doTesting (0 by default) is a testing option % doNoice (0 by default) activate the flagging % of all ice covered points (based on nsidc) % if isempty(who('doTesting')); doTesting=0; end; if isempty(who('doNoice')); doNoice=0; end; %directories dirData='/bay/scratch2/RADS_alongtrk_v4_ice_flagged_2013/'; topexfile = 'tj_daily_ssh_v4_r1'; ersfile = 'en_daily_ssh_v4_r1'; gfofile = 'g1_daily_ssh_v4_r1'; dirIce='/net/nares/raid11/ecco-shared/ecco-version-4/input/input_nsidc_all/'; fileIce='nsidc79_daily'; dirOutput='./'; %testing switches if doTesting; l0=-170; L0=-80; choiceData='gfofile'; end; %select region gcmfaces_global; XC=convert2gcmfaces(mygrid.XC.*mygrid.mskC(:,:,1)); XC=XC(:); YC=convert2gcmfaces(mygrid.YC.*mygrid.mskC(:,:,1)); YC=YC(:); ii=find(XC>=l0-10&XC<=l0+10&YC>=L0-10&YC<=L0+10); ni=length(ii); nt=7671;%corresponds to 1992-2012 %load data eval(['fileData=' choiceData ';']); allData=zeros(ni,nt); allIce=zeros(ni,nt); ndata=0; for yy=1992:2012; fprintf(['reading ' fileData '_' num2str(yy) '\n']); tmp1=dir([dirData fileData '_' num2str(yy)]); tmp0=tmp1.bytes/90/1170/4; tmp1=read2memory([dirData fileData '_' num2str(yy)],[90*1170 tmp0]); allData(:,ndata+[1:tmp0])=tmp1(ii,:); if doNoice; tmp1=read2memory([dirIce fileIce '_' num2str(yy)],[90*1170 tmp0]); allIce(:,ndata+[1:tmp0])=tmp1(ii,:); end; ndata=ndata+tmp0; end; allData(allData<-999)=NaN; allData=allData/100; allIce(allIce<-999)=NaN; allIce=allIce; if ndata~=nt; error('nt was mispecified'); end; %if doTesting; eval(['save ' dirOutput 'rads_noice_mad.demo.mat allData allIce ndata;']); end; %if doTesting; eval(['load ' dirOutput 'rads_noice_mad.demo.mat allData allIce ndata;']); end; %only keep ice free data points noiceData=allData; noiceData(allIce>0)=NaN; iceRejectPerc=100*(1-nansum(~isnan(noiceData(:)))/nansum(~isnan(allData(:)))); %the outliers filtering medianData=nanmedian(noiceData,2)*ones(1,nt);%center of distribution madData=1.4826*mad(noiceData,1,2);%width of the distribution cutoff=4*madData*ones(1,nt);%a factor 4 corresponds to a typical cost of 16 goodData=noiceData; goodData(abs(noiceData-medianData)>cutoff)=NaN; madRejectPerc=100*(1-nansum(~isnan(goodData(:)))/nansum(~isnan(noiceData(:)))); %output result [iceRejectPerc madRejectPerc] %note : original testing was done with gfofile, l0=-170; L0=-80; % including ice points madRejectPerc is ~ 3.9% % excluding ice points madRejectPerc drops to 0.33% if ~doTesting; eval(['save ' dirOutput fileData 'l0is' num2str(l0) 'L0is' num2str(L0) ... ' ii goodData madData medianData iceRejectPerc madRejectPerc choiceData l0 L0 doNoice']); end; %------- testing case -----% if doTesting; %note : original testing was done with gfofile, l0=-170; L0=-80; % the last point (see next line) happened to work as an example jj=find(~isnan(madData)); %do example of mad detection of ice covered points as outliers at one grid point kk=jj(end); xc_kk=XC(ii(kk)); yc_kk=YC(ii(kk)); all_kk=allData(kk,:); median_kk=nanmedian(all_kk);%center of distribution mad_kk=1.4826*mad(all_kk,1,2);%width of distribution cutoff_kk=4*mad_kk*ones(1,nt);%a factor 4 corresponds to a typical cost of 16 good_kk=all_kk; good_kk(abs(good_kk-median_kk)>cutoff_kk)=NaN; reject_kk=100*(1-nansum(~isnan(good_kk))/nansum(~isnan(all_kk))); %compute the various statistics msk=1+0*allIce; msk(isnan(allData))=NaN; %in the testing case we dont filter out the ice points : msk(allIce>0)=NaN; stdOut=nanstd(msk.*allData,0,2);%sample standard deviation iqrOut=0.7413*iqr(msk.*allData,2);%intequartile range estimate of std madOut=1.4826*mad(msk.*allData,1,2);%median absolute difference estimate of std jj=find(~isnan(stdOut)); %plot region if L0>60; myproj=2; elseif L0<-60; myproj=3; else; myproj=1; end; figureL; m_map_gcmfaces(mygrid.Depth,myproj,{'myCaxis',[0 6e3]}); colormap('gray'); colorbar off; m_map_gcmfaces({'plot',XC(ii),YC(ii),'m.'},myproj,{'doHold',1}); m_map_gcmfaces({'plot',xc_kk,yc_kk,'k.','MarkerSize',24},myproj,{'doHold',1}); saveas(gcf,[dirOutput 'outliers_0'],'fig'); eval(['print -djpeg90 ' dirOutput 'outliers_0.jpg']); eval(['print -depsc ' dirOutput 'outliers_0.eps']); %plot sensitivity of std estimates to outliers figureL; set(gca,'FontSize',16); plot(stdOut(jj),'.-'); hold on; plot(madOut(jj),'r.-'); plot(iqrOut(jj),'g.-'); legend('SSTD','MAD*1.4826','IQR*0.7413'); xlabel('grid point index'); ylabel('estimated standard deviation'); saveas(gcf,[dirOutput 'outliers_1'],'fig'); eval(['print -djpeg90 ' dirOutput 'outliers_1.jpg']); eval(['print -depsc ' dirOutput 'outliers_1.eps']); %plot distributions for the overall region figureL; subplot(3,1,1); set(gca,'FontSize',16); %all data points tmp1=allData(jj,:); hist(tmp1(:),[-1.5:0.02:1.5]); aa=axis; aa(1:2)=[-1 1]; axis(aa); title('all data points'); %and the corresponding normal distribution [xx,yy]=normal_distribution([-1.5:0.02:1.5],tmp1(:)); hold on; plot(xx,yy,'m','LineWidth',0.5); % subplot(3,1,2); set(gca,'FontSize',16); tmp1=noiceData(jj,:); hist(tmp1(:),[-1.5:0.02:1.5]); aa=axis; aa(1:2)=[-1 1]; axis(aa); title('ice free data points'); [xx,yy]=normal_distribution([-1.5:0.02:1.5],tmp1(:)); hold on; plot(xx,yy,'m','LineWidth',0.5); subplot(3,1,3); set(gca,'FontSize',16); tmp1=allData(jj,:); tmp1(~isnan(noiceData(jj,:)))=NaN; hist(tmp1(:),[-1.5:0.02:1.5]); aa=axis; aa(1:2)=[-1 1]; axis(aa); title('icy data points'); [xx,yy]=normal_distribution([-1.5:0.02:1.5],tmp1(:)); hold on; plot(xx,yy,'m','LineWidth',0.5); saveas(gcf,[dirOutput 'outliers_2'],'fig'); eval(['print -djpeg90 ' dirOutput 'outliers_2.jpg']); eval(['print -depsc ' dirOutput 'outliers_2.eps']); figureL; subplot(2,1,1); set(gca,'FontSize',16); hist(all_kk,[-1.5:0.02:1.5]); aa=axis; aa(1:2)=[-1 1]; axis(aa); title('before MAD detection'); %and the corresponding normal distribution [xx,yy]=normal_distribution([-1.5:0.02:1.5],all_kk(:)); hold on; plot(xx,yy,'m','LineWidth',2); subplot(2,1,2); set(gca,'FontSize',16); hist(good_kk,[-1.5:0.02:1.5]); aa=axis; aa(1:2)=[-1 1]; axis(aa); title('after MAD detection'); %and the corresponding normal distribution [xx,yy]=normal_distribution([-1.5:0.02:1.5],all_kk(:)); hold on; plot(xx,yy,'m','LineWidth',2); saveas(gcf,[dirOutput 'outliers_3'],'fig'); eval(['print -djpeg90 ' dirOutput 'outliers_3.jpg']); eval(['print -depsc ' dirOutput 'outliers_3.eps']); end; function [xx,yy]=normal_distribution(xx,data); dx=diff(xx); dx=median(dx); %dx=unique(dx); if length(dx)>1; error('plot_normal_distribution expect regular spacing\n'); end; mm=nanmedian(data); ss=1.4826*mad(data,1); nn=sum(~isnan(data)); %for testing : mm=0.2; ss=0.1; nn=100; xx=xx+mm;%reset xx to center of distribution yy=nn*dx/ss/sqrt(2*pi)*exp(-0.5*xx.*xx/ss/ss);%compute distribution %for testing : sum(yy)/nn gcmfaces/ecco_v4/extend_xx.m0000644000435400001440000000446712365534162015735 0ustar gforgetusersfunction []=extend_xx(dirIn,dirOut,ndayIn,nyearOut); %object: extend atmospheric controls to additional years %inputs: dirIn is the input directory % dirOut is the output directory % ndayIn is the control vector frecuency, in days % nyearOut is the extended number of years % %note: we will take the time mean seasonal cycle, and transition % to it linearly over the last year that was already covered %example: %dirIn='/net/weddell/raid3/gforget/ecco_v4/output_files2/apr1alpha_it9/'; %dirOut='/net/weddell/raid3/gforget/ecco_v4/input_files2/apr1alpha_it9_extended_xx/'; %extend_xx(dirIn,dirOut,14,20); gcmfaces_global; %first copy time independent controls listCp={'diffkr','kapgm','kapredi','salt','theta'}; for ii=1:length(listCp); fileIn=dir([dirIn 'ADXXfiles/xx_' listCp{ii} '.00*data']); copyfile([dirIn 'ADXXfiles/' fileIn.name] , [dirOut fileIn.name]); end; %then extend the time dependent ones for ii=1:7; switch ii; case 1; xxName='atemp'; case 2; xxName='aqh'; case 3; xxName='tauu'; case 4; xxName='tauv'; case 5; xxName='lwdown'; case 6; xxName='swdown'; case 7; xxName='precip'; end; %read model cost output fld_xx=rdmds2gcmfaces([dirIn 'ADXXfiles/xx_' xxName '.00*']); %determine already covered time period nrec=size(fld_xx{1},3); nyearIn=nrec*ndayIn/365; nrecInOneYear=round(365/ndayIn); nrecOut=nrecInOneYear*nyearOut+1; %determine seasonal cycle season_xx=0*fld_xx(:,:,1:nrecInOneYear); for tt=1:nrecInOneYear; season_xx(:,:,tt)=mean(fld_xx(:,:,tt:nrecInOneYear:nrec),3); end; %determine transition factor (fld_xx -> season_xx) nrec0=nrecInOneYear*(floor(nyearIn)-1); fac=([1:nrecOut]-nrec0)/(nrec-nrec0); fac=max(min(fac,1),0); %build extended time series more_xx=zeros(fld_xx(:,:,1),nrecOut); more_xx(:,:,1:nrec0)=fld_xx(:,:,1:nrec0); for tt=nrec0+1:nrecOut; ttt=mod(tt,nrecInOneYear); if ttt==0; ttt=nrecInOneYear; end; if tt17)=18;%reset indices to proper basin %fld(fld>17&mygrid.XC>-40)=19;%reset indices to proper basin %msk1=v4_basin_one(1); msk2=v4_basin_one(2); %fld(fld<10&(msk1==1|msk2==1))=20;%add new basin index gcmfaces_global; if numBasin==1; lonList=[10 19 60 60 ]; latList=[60 80 81 60]; elseif numBasin==2; lonList=[60 100 110 60]; latList=[81 80 60 60]; else; error('unknown basin'); end; lonList=[lonList lonList(1)]; latList=[latList latList(1)]; msk=mygrid.mskC(:,:,1); for iy=1:length(lonList)-1; lonPair=lonList(iy:iy+1); latPair=latList(iy:iy+1); lon=mygrid.XC; lat=mygrid.YC; x=cos(lat*pi/180).*cos(lon*pi/180); y=cos(lat*pi/180).*sin(lon*pi/180); z=sin(lat*pi/180); x0=cos(latPair*pi/180).*cos(lonPair*pi/180); y0=cos(latPair*pi/180).*sin(lonPair*pi/180); z0=sin(latPair*pi/180); %get the rotation matrix: %1) rotate around x axis to put first point at z=0 theta=atan2(-z0(1),y0(1)); R1=[[1;0;0] [0;cos(theta);sin(theta)] [0;-sin(theta);cos(theta)]]; tmp0=[x0;y0;z0]; tmp1=R1*tmp0; x1=tmp1(1,:); y1=tmp1(2,:); z1=tmp1(3,:); x0=x1; y0=y1; z0=z1; %2) rotate around z axis to put first point at y=0 theta=atan2(x0(1),y0(1)); R2=[[cos(theta);sin(theta);0] [-sin(theta);cos(theta);0] [0;0;1]]; tmp0=[x0;y0;z0]; tmp1=R2*tmp0; x1=tmp1(1,:); y1=tmp1(2,:); z1=tmp1(3,:); x0=x1; y0=y1; z0=z1; %3) rotate around y axis to put second point at z=0 theta=atan2(-z0(2),-x0(2)); R3=[[cos(theta);0;-sin(theta)] [0;1;0] [sin(theta);0;cos(theta)]]; tmp0=[x0;y0;z0]; tmp1=R3*tmp0; x1=tmp1(1,:); y1=tmp1(2,:); z1=tmp1(3,:); x0=x1; y0=y1; z0=z1; %apply rotation to grid: tmpx=convert2array(x); tmpy=convert2array(y); tmpz=convert2array(z); tmp1=find(~isnan(tmpx)); tmpx2=tmpx(tmp1); tmpy2=tmpy(tmp1); tmpz2=tmpz(tmp1); tmp2=[tmpx2';tmpy2';tmpz2']; tmp3=R3*R2*R1*tmp2; tmpx2=tmp3(1,:); tmpy2=tmp3(2,:); tmpz2=tmp3(3,:); tmpx(tmp1)=tmpx2; tmpy(tmp1)=tmpy2; tmpz(tmp1)=tmpz2; x=convert2array(tmpx); y=convert2array(tmpy); z=convert2array(tmpz); %compute the great circle mask: mskCint=1*(z>0); %increment msk: msk(mskCint>0)=0; end; gcmfaces/ecco_v4/cost_bp.m0000644000435400001440000000604312365532071015345 0ustar gforgetusersfunction []=cost_bp(dirModel,dirMat,doComp,dirTex,nameTex); %object: compute cost function term for grace data %inputs: dimodel is the model directory % dirMat is the directory where diagnozed .mat files will be saved % -> set it to '' to use the default [dirModel 'mat/'] % doComp is a switch (1->compute; 0->display) %optional: dirTex is the directory where tex and figures files are created % (if not specified then display all results to screen instead) % nameTex is the tex file name (default : 'myPlots') if isempty(dirMat); dirMat=[dirModel 'mat/']; else; dirMat=[dirMat '/']; end; if isempty(dir(dirMat)); mkdir([dirMat]); end; %determine if and where to create tex and figures files dirMat=[dirMat '/']; if isempty(who('dirTex')); addToTex=0; else; if ~ischar(dirTex); error('mis-specified dirTex'); end; addToTex=1; if isempty(who('nameTex')); nameTex='myPlots'; end; fileTex=[dirTex nameTex '.tex']; end; if doComp; %load grid gcmfaces_global; if ~isfield(mygrid,'XC'); grid_load('./GRID/',5,'compact'); end; if ~isfield(mygrid,'LATS_MASKS'); gcmfaces_lines_zonal; end; %read model cost output fld_dat=rdmds2gcmfaces([dirModel 'barfiles/bpdatanom_smooth']); fld_dif=rdmds2gcmfaces([dirModel 'barfiles/bpdifanom_smooth']); %mask: fld_msk=rdmds2gcmfaces([dirModel 'barfiles/bpdatanom_raw']); fld_msk(find(fld_msk~=0))=1; fld_msk(find(fld_msk==0))=NaN; fld_dif=fld_dif.*fld_msk; fld_dat=fld_dat.*fld_msk; fld_mod=fld_dat+fld_dif;%compute model values %read uncertainty fields fld_err=read2memory('/net/nares/raid11/ecco-shared/ecco-version-4/input/input_grace/GRACE_CSR_withland_err',[90 1170]); fld_err=convert2gcmfaces(fld_err); fld_err(find(fld_err==0))=NaN; %compute weight fld_w=fld_err.^-2; %compute cost fld_cost=mk3D(fld_w,fld_dif).*(fld_dif.^2); fld_cost=nanmean(fld_cost,3); fld_dif=nanstd(fld_dif,[],3); fld_mod=nanstd(fld_mod,[],3); fld_dat=nanstd(fld_dat,[],3); if ~isdir([dirMat 'cost/']); mkdir([dirMat 'cost/']); end; eval(['save ' dirMat '/cost/cost_bp.mat fld_err fld_dif fld_mod fld_dat fld_cost;']); else;%display previously computed results global mygrid; if isdir([dirMat 'cost/']); dirMat=[dirMat 'cost/']; end; eval(['load ' dirMat '/cost_bp.mat;']); %figure; m_map_gcmfaces(fld_cost,0,{'myCaxis',[0:0.2:1.2 1.5:0.5:3 4:1:6 8 10]}); figure; m_map_gcmfaces(fld_dif,0,{'myCaxis',[0:0.2:1.2 1.5:0.5:3 4:1:6 8 10]}); myCaption={'modeled-observed rms -- bottom pressure (cm)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(fld_mod,0,{'myCaxis',[0:0.2:1.2 1.5:0.5:3 4:1:6 8 10]}); myCaption={'rms modeled -- bottom pressure (cm)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(fld_dat,0,{'myCaxis',[0:0.2:1.2 1.5:0.5:3 4:1:6 8 10]}); myCaption={'rms observed -- bottom pressure (cm)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figure; m_map_gcmfaces(fld_cost,0,{'myCaxis',[0:0.2:1.2 1.5:0.5:3 4:1:6 8 10]}); myCaption={'Cost function'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; gcmfaces/ecco_v4/alldiag_load.m0000644000435400001440000000634612273015477016322 0ustar gforgetusersfunction [alldiag]=alldiag_load(dirMat,nameMat,varargin); %object: load single record files off basic_diags_ecco, and assemble time records %inputs: dirMat is the model run sub-directory where the matlab files are (e.g. 'mat/') % nameMat is the mat files name (e.g. 'basic_diags_ecco_A_*.mat') %optional: nameDiag is the name of the diagnostic of interest % subListTimes is a vector to reduce listTimes to listTimes(subListTimes) if nargin>2; nameDiag=varargin{1}; else; nameDiag=''; end; if nargin>3; subListTimes=varargin{2}; else; subListTimes=[]; end; %model run paramters (from basic_diags_ecco_mygrid.mat) global myparms; %get list of files listFiles=dir([dirMat '/' nameMat]); %get time steps and sort listFiles listSteps=[]; for tt=1:length(listFiles); nn=listFiles(tt).name; ii=strfind(nn,'_'); ii=ii(end); listSteps=[listSteps;str2num(nn(ii+1:end-4))]; end; [listSteps,ii]=sort(listSteps); listFiles=listFiles(ii); %compute approximate times (in years -- using 365.25 as year length) listTimes=myparms.yearFirst(1)+listSteps*myparms.timeStep/86400/365.25; %initialize alldiag alldiag=load([dirMat listFiles(1).name]); listDiags=fieldnames(alldiag); %restrict list of diags to load if ~isempty(nameDiag); if iscell(nameDiag); listDiags=nameDiag; else; listDiags={nameDiag}; end; end; %restrict list of times if ~isempty(subListTimes); listSteps=listSteps(subListTimes); listTimes=listTimes(subListTimes); listFiles=listFiles(subListTimes); alldiag=load([dirMat listFiles(1).name]); end; %extend time dimension listNdim=ones(1,length(listDiags)); listTT={}; listDD=''; for ii=1:length(listDiags); %list diags in text string listDD=[listDD listDiags{ii} ''',''']; %get data: eval(['tmp1=alldiag.' listDiags{ii} ';']); %determine the time dimension: if strcmp(class(tmp1),'gcmfaces'); nDim=size(tmp1{1}); else; nDim=size(tmp1); end; if ~isempty(find(nDim==0)); nDim=0; elseif nDim(end)==1; nDim=length(nDim)-1; else; nDim=length(nDim); end; %store nDim for use below listNdim(ii)=nDim; tt=''; for jj=1:nDim; tt=[tt ':,']; end; listTT{ii}=['(' tt 'tt)']; %extend time dimension: if nDim>0; tmp2=ones(1,nDim+1); tmp2(end)=length(listSteps); tmp2=repmat(tmp1,tmp2); eval(['alldiag.' listDiags{ii} '=tmp2;']); end; end; %finalize text-list of variables to load listDD=['''' listDD(1:end-2)]; %loop and concatenate for tt=2:length(listSteps); eval(['tmpdiag=load([dirMat listFiles(tt).name],' listDD ');']); for ii=1:length(listDiags); nDim=listNdim(ii); if nDim>0; eval(['alldiag.' listDiags{ii} listTT{ii} '=tmpdiag.' listDiags{ii} ';']); end; end; end; %clean empty diags up for ii=1:length(listDiags); eval(['tmp1=isempty(alldiag.' listDiags{ii} ');']); if tmp1; alldiag=rmfield(alldiag,listDiags{ii}); end; end; %remove diags that were not selected (and therefore not concatenated) tmpDiags=fieldnames(alldiag); for ii=1:length(tmpDiags); if ~sum(sum(strcmp(tmpDiags{ii},listDiags))); alldiag=rmfield(alldiag,tmpDiags{ii}); end; end; %complement alldiag alldiag.listSteps=listSteps; alldiag.listTimes=listTimes; alldiag.listDiags=listDiags; %squeeze for ii=1:length(alldiag.listDiags); eval(['alldiag.' listDiags{ii} '=squeeze(alldiag.' listDiags{ii} ');']); end; gcmfaces/ecco_v4/rads_noice_mad_recompose.m0000644000435400001440000000545712151725735020733 0ustar gforgetusersfunction []=rads_noice_mad_recompose(choiceData,years,doTesting); if isempty(who('doTesting')); doTesting=0; end; doPlot=0; %directories dirMad='./'; dirRads='/bay/scratch2/RADS_alongtrk_v4_ice_flagged_2013/'; dirOutput='./'; topexfile = 'tj_daily_ssh_v4_r1'; ersfile = 'en_daily_ssh_v4_r1'; gfofile = 'g1_daily_ssh_v4_r1'; dirIce='/net/nares/raid11/ecco-shared/ecco-version-4/input/input_nsidc_all/'; fileIce='nsidc79_daily'; nday=zeros(20,1); for yy=1992:2012; tmp1=dir([dirRads topexfile '_' num2str(yy)]); nday(yy-1991)=tmp1.bytes/90/1170/4; end; %testing switches if doTesting; years=[2009:2010]; choiceData='gfofile'; end; gcmfaces_global; eval(['fileData=' choiceData ';']); reject.l0=[-170:20:170]'*ones(1,9); reject.L0=ones(18,1)*[-80:20:80]; reject.remain=NaN*zeros(18,9,20); reject.iceRejectPerc=NaN*zeros(18,9,20); reject.madRejectPerc=NaN*zeros(18,9,20); for yy=years; fprintf(['reading ' fileData '_' num2str(yy) '\n']); tmp1=dir([dirRads fileData '_' num2str(yy)]); nrec=tmp1.bytes/90/1170/4; if yy==1992; rec00=0; else; rec00=sum(nday(1:yy-1992)); end; rec0=rec00+1; rec1=rec00+nrec; goodData=NaN*zeros(105300,nrec); for L0=[-80:20:80]; for l0=[-170:20:170]; %select region XC=convert2gcmfaces(mygrid.XC.*mygrid.mskC(:,:,1)); XC=XC(:); YC=convert2gcmfaces(mygrid.YC.*mygrid.mskC(:,:,1)); YC=YC(:); ii=find(XC>=l0-10&XC<=l0+10&YC>=L0-10&YC<=L0+10); ni=length(ii); %read region tile=load([dirMad fileData 'l0is' num2str(l0) 'L0is' num2str(L0)]); %add to accounting at proper location [i0,j0]=find(reject.l0==l0&reject.L0==L0); y0=yy-1991; reject.remain(i0,j0,y0)=sum(~isnan(tile.goodData(:))); reject.iceRejectPerc(i0,j0,y0)=tile.iceRejectPerc; reject.madRejectPerc(i0,j0,y0)=tile.madRejectPerc; %add to goodData at proper location if length(ii)~=length(tile.ii); error('inconsistent size'); end; if max(abs(ii-tile.ii))~=0; error('inconsistent size'); end; goodData(ii,:)=tile.goodData(:,rec0:rec1); end; end; goodData=goodData*100; goodData(isnan(goodData))=-9999; if doPlot; fld=read2memory([dirRads fileData '_' num2str(yy)]); fld=convert2gcmfaces(reshape(fld,[90 1170 nrec])); FLD=convert2gcmfaces(reshape(goodData,[90 1170 nrec])); FLD(FLD<-999)=NaN; fld(fld<-999)=NaN; % figureL; msk=mygrid.mskC(:,:,1); x=mygrid.LATS; subplot(3,1,1); z=calc_zonmean_T(msk.*nanstd(fld,[],3)); plot(x,z); hold on; z=calc_zonmean_T(msk.*nanstd(FLD,[],3)); plot(x,z,'r'); subplot(3,1,2); z=calc_zonmean_T(msk.*sum(~isnan(fld),3)); plot(x,z); hold on; z=calc_zonmean_T(msk.*sum(~isnan(FLD),3)); plot(x,z,'r'); subplot(3,1,3); z=calc_zonmean_T(msk.*nanstd(FLD,[],3)./nanstd(fld,[],3)); plot(x,z); hold on; z=calc_zonmean_T(msk.*sum(~isnan(FLD),3)./sum(~isnan(fld),3)); plot(x,z,'r'); % keyboard; end; fid=fopen([dirOutput fileData '_mad_' num2str(yy)],'w','b'); fwrite(fid,goodData,'float32'); fclose(fid); end; gcmfaces/gcmfaces_exch/0000755000435400001440000000000012375431055014771 5ustar gforgetusersgcmfaces/gcmfaces_exch/exch_UV_N_cube.m0000644000435400001440000001112211712423607017756 0ustar gforgetusersfunction [FLDU,FLDV]=exch_UV_N_llc(fldU,fldV,varargin); if nargin==3; N=varargin{1}; else; N=1; end; %fill interior of extended arrays FLDUtmp=exch_T_N(fldU,N); FLDVtmp=exch_T_N(fldV,N); for iFace=1:fldU.nFaces; FLDUtmp{iFace}(1:N,:,:)=NaN; FLDUtmp{iFace}(end-N+1:end,:,:)=NaN; FLDUtmp{iFace}(:,1:N,:)=NaN; FLDUtmp{iFace}(:,end-N+1:end,:)=NaN; FLDVtmp{iFace}(1:N,:,:)=NaN; FLDVtmp{iFace}(end-N+1:end,:,:)=NaN; FLDVtmp{iFace}(:,1:N,:)=NaN; FLDVtmp{iFace}(:,end-N+1:end,:)=NaN; end; FLDU=FLDUtmp; FLDV=FLDVtmp; %now add the one extra point we need for U and V [FLDUtmp,FLDVtmp]=exch_UV(fldU,fldV); %then add the remaining rows and columns... %U face 1 tmp1=permute(FLDVtmp.f5(:,end-N:end-1,:),[2 1 3]); FLDU.f1(1:N,N+1:end-N,:)=flipdim(tmp1,2); tmp1=FLDUtmp.f2(1:N,:,:); FLDU.f1(end-N+1:end,N+1:end-N,:)=tmp1; % tmp1=FLDUtmp.f6(:,end-N+1:end,:); FLDU.f1(N+1:end-N+1,1:N,:)=tmp1; tmp1=permute(-FLDVtmp.f3(1:N,:,:),[2 1 3]); FLDU.f1(N+1:end-N+1,end-N+1:end,:)=flipdim(tmp1,1); %V face 1 tmp1=permute(-FLDUtmp.f5(:,end-N+1:end,:),[2 1 3]); FLDV.f1(1:N,N+1:end-N+1,:)=flipdim(tmp1,2); tmp1=FLDVtmp.f2(1:N,:,:); FLDV.f1(end-N+1:end,N+1:end-N+1,:)=tmp1; % tmp1=FLDVtmp.f6(:,end-N:end-1,:); FLDV.f1(N+1:end-N,1:N,:)=tmp1; tmp1=permute(FLDUtmp.f3(1:N,:,:),[2 1 3]); FLDV.f1(N+1:end-N,end-N+1:end,:)=flipdim(tmp1,1); %U face 2 tmp1=FLDUtmp.f1(end-N:end-1,:,:); FLDU.f2(1:N,N+1:end-N,:)=tmp1; tmp1=permute(FLDVtmp.f4(:,1:N,:),[2 1 3]); FLDU.f2(end-N+1:end,N+1:end-N,:)=flipdim(tmp1,2); % tmp1=permute(-FLDVtmp.f6(end-N+1:end,:,:),[2 1 3]); FLDU.f2(N+1:end-N+1,1:N,:)=flipdim(tmp1,1); tmp1=FLDUtmp.f3(:,1:N,:); FLDU.f2(N+1:end-N+1,end-N+1:end,:)=tmp1; %V face 2 tmp1=FLDVtmp.f1(end-N+1:end,:,:); FLDV.f2(1:N,N+1:end-N+1,:)=tmp1; tmp1=permute(-FLDUtmp.f4(:,1:N,:),[2 1 3]); FLDV.f2(end-N+1:end,N+1:end-N+1,:)=flipdim(tmp1,2); % tmp1=permute(FLDUtmp.f6(end-N:end-1,:,:),[2 1 3]); FLDV.f2(N+1:end-N,1:N,:)=flipdim(tmp1,1); tmp1=FLDVtmp.f3(:,1:N,:); FLDV.f2(N+1:end-N,end-N+1:end,:)=tmp1; %U face 3 tmp1=permute(FLDVtmp.f1(:,end-N:end-1,:),[2 1 3]); FLDU.f3(1:N,N+1:end-N,:)=flipdim(tmp1,2); tmp1=FLDUtmp.f4(1:N,:,:); FLDU.f3(end-N+1:end,N+1:end-N,:)=tmp1; % tmp1=FLDUtmp.f2(:,end-N+1:end,:); FLDU.f3(N+1:end-N+1,1:N,:)=tmp1; tmp1=permute(-FLDVtmp.f5(1:N,:,:),[2 1 3]); FLDU.f3(N+1:end-N+1,end-N+1:end,:)=flipdim(tmp1,1); %V face 3 tmp1=permute(-FLDUtmp.f1(:,end-N+1:end,:),[2 1 3]); FLDV.f3(1:N,N+1:end-N+1,:)=flipdim(tmp1,2); tmp1=FLDVtmp.f4(1:N,:,:); FLDV.f3(end-N+1:end,N+1:end-N+1,:)=tmp1; % tmp1=FLDVtmp.f2(:,end-N:end-1,:); FLDV.f3(N+1:end-N,1:N,:)=tmp1; tmp1=permute(FLDUtmp.f5(1:N,:,:),[2 1 3]); FLDV.f3(N+1:end-N,end-N+1:end,:)=flipdim(tmp1,1); %U face 4 tmp1=FLDUtmp.f3(end-N:end-1,:,:); FLDU.f4(1:N,N+1:end-N,:)=tmp1; tmp1=permute(FLDVtmp.f6(:,1:N,:),[2 1 3]); FLDU.f4(end-N+1:end,N+1:end-N,:)=flipdim(tmp1,2); % tmp1=permute(-FLDVtmp.f2(end-N+1:end,:,:),[2 1 3]); FLDU.f4(N+1:end-N+1,1:N,:)=flipdim(tmp1,1); tmp1=FLDUtmp.f5(:,1:N,:); FLDU.f4(N+1:end-N+1,end-N+1:end,:)=tmp1; %V face 4 tmp1=FLDVtmp.f3(end-N+1:end,:,:); FLDV.f4(1:N,N+1:end-N+1,:)=tmp1; tmp1=permute(-FLDUtmp.f6(:,1:N,:),[2 1 3]); FLDV.f4(end-N+1:end,N+1:end-N+1,:)=flipdim(tmp1,2); % tmp1=permute(FLDUtmp.f2(end-N:end-1,:,:),[2 1 3]); FLDV.f4(N+1:end-N,1:N,:)=flipdim(tmp1,1); tmp1=FLDVtmp.f5(:,1:N,:); FLDV.f4(N+1:end-N,end-N+1:end,:)=tmp1; %U face 5 tmp1=permute(FLDVtmp.f3(:,end-N:end-1,:),[2 1 3]); FLDU.f5(1:N,N+1:end-N,:)=flipdim(tmp1,2); tmp1=FLDUtmp.f6(1:N,:,:); FLDU.f5(end-N+1:end,N+1:end-N,:)=tmp1; % tmp1=FLDUtmp.f4(:,end-N+1:end,:); FLDU.f5(N+1:end-N+1,1:N,:)=tmp1; tmp1=permute(-FLDVtmp.f1(1:N,:,:),[2 1 3]); FLDU.f5(N+1:end-N+1,end-N+1:end,:)=flipdim(tmp1,1); %V face 5 tmp1=permute(-FLDUtmp.f3(:,end-N+1:end,:),[2 1 3]); FLDV.f5(1:N,N+1:end-N+1,:)=flipdim(tmp1,2); tmp1=FLDVtmp.f6(1:N,:,:); FLDV.f5(end-N+1:end,N+1:end-N+1,:)=tmp1; % tmp1=FLDVtmp.f4(:,end-N:end-1,:); FLDV.f5(N+1:end-N,1:N,:)=tmp1; tmp1=permute(FLDUtmp.f1(1:N,:,:),[2 1 3]); FLDV.f5(N+1:end-N,end-N+1:end,:)=flipdim(tmp1,1); %U face 6 tmp1=FLDUtmp.f5(end-N:end-1,:,:); FLDU.f6(1:N,N+1:end-N,:)=tmp1; tmp1=permute(FLDVtmp.f2(:,1:N,:),[2 1 3]); FLDU.f6(end-N+1:end,N+1:end-N,:)=flipdim(tmp1,2); % tmp1=permute(-FLDVtmp.f4(end-N+1:end,:,:),[2 1 3]); FLDU.f6(N+1:end-N+1,1:N,:)=flipdim(tmp1,1); tmp1=FLDUtmp.f1(:,1:N,:); FLDU.f6(N+1:end-N+1,end-N+1:end,:)=tmp1; %V face 6 tmp1=FLDVtmp.f5(end-N+1:end,:,:); FLDV.f6(1:N,N+1:end-N+1,:)=tmp1; tmp1=permute(-FLDUtmp.f2(:,1:N,:),[2 1 3]); FLDV.f6(end-N+1:end,N+1:end-N+1,:)=flipdim(tmp1,2); % tmp1=permute(FLDUtmp.f4(end-N:end-1,:,:),[2 1 3]); FLDV.f6(N+1:end-N,1:N,:)=flipdim(tmp1,1); tmp1=FLDVtmp.f1(:,1:N,:); FLDV.f6(N+1:end-N,end-N+1:end,:)=tmp1; gcmfaces/gcmfaces_exch/exch_Z_ll.m0000644000435400001440000000055612024523407017056 0ustar gforgetusersfunction [FLD]=exch_Z_ll(fld); %[FLD]=exch_Z_llc(fld); %adds vorticity points (to north and east of center points) for %lat-lon grid gcmfaces_global; FLD=exch_T_N(fld,1); FLD{1}=FLD{1}(2:end,2:end,:,:); if mygrid.domainPeriodicity(1); FLD{1}(end,end,:,:)=FLD{1}(1,end,:,:); elseif mygrid.domainPeriodicity(2); FLD{1}(end,end,:,:)=FLD{1}(end,1,:,:); end; gcmfaces/gcmfaces_exch/exch_UV_N_ll.m0000644000435400001440000000022511367364525017462 0ustar gforgetusersfunction [FLDU,FLDV]=exch_UV_N_ll(fldU,fldV,varargin); if nargin==2; N=varargin{1}; else; N=1; end; FLDU=exch_T_N(fldU,N); FLDV=exch_T_N(fldV,N); gcmfaces/gcmfaces_exch/exch_T_N_cube.m0000644000435400001440000000463411367364525017652 0ustar gforgetusersfunction [FLD]=exch_T_N_cube(fld,varargin); if nargin==2; N=varargin{1}; else; N=1; end; FLD=fld; s=size(FLD.f1); s(1:2)=s(1:2)+2*N; FLD.f1=NaN*zeros(s); s=size(FLD.f2); s(1:2)=s(1:2)+2*N; FLD.f2=NaN*zeros(s); s=size(FLD.f3); s(1:2)=s(1:2)+2*N; FLD.f3=NaN*zeros(s); s=size(FLD.f4); s(1:2)=s(1:2)+2*N; FLD.f4=NaN*zeros(s); s=size(FLD.f5); s(1:2)=s(1:2)+2*N; FLD.f5=NaN*zeros(s); s=size(FLD.f6); s(1:2)=s(1:2)+2*N; FLD.f6=NaN*zeros(s); n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); for k3=1:n3; for k4=1:n4; %f1245=[fld{1}(:,:,k3,k4);fld{2}(:,:,k3,k4);sym_g(fld{4}(:,:,k3,k4),7,0);sym_g(fld{5}(:,:,k3,k4),7,0)]; %f3=fld{3}(:,:,k3,k4); f3=[sym_g(f3,5,0);f3;sym_g(f3,7,0);sym_g(f3,6,0)]; %initial rotation for SIDE faces: f1=fld.f1(:,:,k3,k4); f2=fld.f2(:,:,k3,k4); f4=sym_g(fld.f4(:,:,k3,k4),7,0); f5=sym_g(fld.f5(:,:,k3,k4),7,0); nan1=NaN*ones(size(FLD.f1,1),N); nan2=NaN*ones(N,N); %face 1: F1=[f5(end-N+1:end,:);f1;f2(1:N,:)]; f3=sym_g(fld.f3(:,:,k3,k4),5,0); f6=fld.f6(:,:,k3,k4); F1=[[nan2;f6(:,end-N+1:end);nan2] F1 [nan2;f3(:,1:N);nan2]]; %face 2: F2=[f1(end-N+1:end,:);f2;f4(1:N,:)]; f3=fld.f3(:,:,k3,k4); f6=sym_g(fld.f6(:,:,k3,k4),5,0); F2=[[nan2;f6(:,end-N+1:end);nan2] F2 [nan2;f3(:,1:N);nan2]]; %face 4: F4=[f2(end-N+1:end,:);f4;f5(1:N,:)]; f3=sym_g(fld.f3(:,:,k3,k4),7,0); f6=sym_g(fld.f6(:,:,k3,k4),6,0); F4=[[nan2;f6(:,end-N+1:end);nan2] F4 [nan2;f3(:,1:N);nan2]]; %face 5: F5=[f4(end-N+1:end,:);f5;f1(1:N,:)]; f3=sym_g(fld.f3(:,:,k3,k4),6,0); f6=sym_g(fld.f6(:,:,k3,k4),7,0); F5=[[nan2;f6(:,end-N+1:end);nan2] F5 [nan2;f3(:,1:N);nan2]]; %face 3: f3=fld.f3(:,:,k3,k4); F3=FLD.f3(:,:,k3,k4); F3(1+N:end-N,1+N:end-N)=f3; F3=sym_g(F3,5,0); F3(1+N:end-N,1:N)=f1(:,end-N+1:end); F3=sym_g(F3,7,0); F3(1+N:end-N,1:N)=f2(:,end-N+1:end); F3=sym_g(F3,7,0); F3(1+N:end-N,1:N)=f4(:,end-N+1:end); F3=sym_g(F3,5,0); F3=sym_g(F3,6,0); F3(1+N:end-N,1:N)=f5(:,end-N+1:end); F3=sym_g(F3,6,0); %face 6: f6=fld.f6(:,:,k3,k4); F6=FLD.f6(:,:,k3,k4); F6(1+N:end-N,1+N:end-N)=f6; F6(1+N:end-N,end-N+1:end)=f1(:,1:N); F6=sym_g(F6,5,0); F6(1+N:end-N,end-N+1:end)=f2(:,1:N); F6=sym_g(F6,7,0); F6=sym_g(F6,6,0); F6(1+N:end-N,end-N+1:end)=f4(:,1:N); F6=sym_g(F6,6,0); F6=sym_g(F6,7,0); F6(1+N:end-N,end-N+1:end)=f5(:,1:N); F6=sym_g(F6,5,0); %final rotation for SIDE faces: F4=sym_g(F4,5,0); F5=sym_g(F5,5,0); %store: FLD.f1(:,:,k3,k4)=F1; FLD.f2(:,:,k3,k4)=F2; FLD.f3(:,:,k3,k4)=F3; FLD.f4(:,:,k3,k4)=F4; FLD.f5(:,:,k3,k4)=F5; FLD.f6(:,:,k3,k4)=F6; end; end; gcmfaces/gcmfaces_exch/exch_UV_N_llpc.m0000644000435400001440000000176711712423607020010 0ustar gforgetusersfunction [FLDU,FLDV]=exch_UV_N_llpc(fldU,fldV,varargin); error('!!!exch_UV_N_llpc has not been fully tested and is probably wrong!!!\n') if nargin==3; N=varargin{1}; else; N=1; end; FLDUtmp=exch_T_N(fldU,N); FLDVtmp=exch_T_N(fldV,N); FLDU=FLDUtmp; FLDV=FLDVtmp; FLDU.f1(1:N,:,:)=FLDVtmp.f1(1:N,:,:); FLDV.f1(1:N,:,:)=-FLDUtmp.f1(1:N,:,:); FLDU.f1(:,end-N+1:end,:)=-FLDVtmp.f1(:,end-N+1:end,:); FLDV.f1(:,end-N+1:end,:)=FLDUtmp.f1(:,end-N+1:end,:); FLDU.f2(end-N+1:end,:,:)=FLDVtmp.f2(end-N+1:end,:,:); FLDV.f2(end-N+1:end,:,:)=-FLDUtmp.f2(end-N+1:end,:,:); FLDU.f2(:,end-N+1:end,:)=-FLDVtmp.f2(:,end-N+1:end,:); FLDV.f2(:,end-N+1:end,:)=FLDUtmp.f2(:,end-N+1:end,:); FLDU.f3(1:N,:,:)=FLDVtmp.f3(1:N,:,:); FLDV.f3(1:N,:,:)=-FLDUtmp.f3(1:N,:,:); FLDU.f3(:,1:N,:)=-FLDVtmp.f3(:,1:N,:); FLDV.f3(:,1:N,:)=FLDUtmp.f3(:,1:N,:); FLDU.f4(1:N,:,:)=FLDVtmp.f4(1:N,:,:); FLDV.f4(1:N,:,:)=-FLDUtmp.f4(1:N,:,:); FLDU.f4(:,end-N+1:end,:)=-FLDVtmp.f4(:,end-N+1:end,:); FLDV.f4(:,end-N+1:end,:)=FLDUtmp.f4(:,end-N+1:end,:); gcmfaces/gcmfaces_exch/exch_UV_ll.m0000644000435400001440000000031011367364525017200 0ustar gforgetusersfunction [FLDU,FLDV]=exch_UV_ll(fldU,fldV); FLDUtmp=exch_T_N(fldU); FLDVtmp=exch_T_N(fldV); FLDU=FLDUtmp; FLDV=FLDVtmp; FLDU.f1=FLDUtmp.f1(2:end,2:end-1,:); FLDV.f1=FLDVtmp.f1(2:end-1,2:end,:); gcmfaces/gcmfaces_exch/exch_UV_llpc.m0000644000435400001440000000113411367364525017530 0ustar gforgetusersfunction [FLDU,FLDV]=exch_UV_llpc(fldU,fldV); FLDUtmp=exch_T_N(fldU); FLDVtmp=exch_T_N(fldV); FLDU=FLDUtmp; FLDV=FLDVtmp; FLDU.f1=FLDUtmp.f1(2:end,2:end-1,:); FLDV.f1=FLDVtmp.f1(2:end-1,2:end,:); FLDV.f1(:,end,:)=FLDUtmp.f1(2:end-1,end,:); FLDU.f2=FLDUtmp.f2(2:end,2:end-1,:); FLDU.f2(end,:,:)=FLDV.f2(end,2:end-1,:); FLDV.f2=FLDVtmp.f2(2:end-1,2:end,:); FLDV.f2(:,end,:)=FLDUtmp.f2(2:end-1,end,:); FLDU.f3=FLDUtmp.f3(2:end,2:end-1,:); FLDV.f3=FLDVtmp.f3(2:end-1,2:end,:); FLDU.f4=FLDUtmp.f4(2:end,2:end-1,:); FLDV.f4=FLDVtmp.f4(2:end-1,2:end,:); FLDV.f4(:,end,:)=FLDUtmp.f4(2:end-1,end,:); gcmfaces/gcmfaces_exch/exch_Z_cube.m0000644000435400001440000000430012024523407017354 0ustar gforgetusersfunction [FLD]=exch_Z_cub(fld); %[FLD]=exch_Z_cub(fld, [flag]); %adds vorticity points (to north and east of center points) for %cubed-sphere grid gcmfaces_global; %missing corners : assume symmetry of the grid (that may be completly wrong!) global exch_Z_assume_sym; if isempty(exch_Z_assume_sym); exch_Z_assume_sym=0; end; %determine vertical and/or time dimensions n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); %initialize FLD FLD=gcmfaces; for iF=1:mygrid.nFaces [n1,n2]=size(mygrid.XC{iF}); FLD{iF}=NaN*zeros([n1+1 n2+1 n3 n4]); end; for k3=1:n3; for k4=1:n4; for iF=1:mygrid.nFaces FLD{iF}(1:end-1,1:end-1,k3,k4)=fld{iF}(:,:,k3,k4); end %overlap in i+1 FLD.f1(end,1:end-1,k3,k4)=fld.f2(1,:,k3,k4); FLD.f2(end,2:end,k3,k4)=flipud(fld.f4(:,1,k3,k4)); FLD.f3(end,1:end-1,k3,k4)=fld.f4(1,:,k3,k4); FLD.f4(end,2:end,k3,k4)=flipud(fld.f6(:,1,k3,k4)); FLD.f5(end,1:end-1,k3,k4)=fld.f6(1,:,k3,k4); FLD.f6(end,2:end,k3,k4)=flipud(fld.f2(:,1,k3,k4)); %overlap in j+1 FLD.f1(2:end,end,k3,k4)=fliplr(fld.f3(1,:,k3,k4)); FLD.f2(1:end-1,end,k3,k4)=fld.f3(:,1,k3,k4); FLD.f3(2:end,end,k3,k4)=fliplr(fld.f5(1,:,k3,k4)); FLD.f4(1:end-1,end,k3,k4)=fld.f5(:,1,k3,k4); FLD.f5(2:end,end,k3,k4)=fliplr(fld.f1(1,:,k3,k4)); FLD.f6(1:end-1,end,k3,k4)=fld.f1(:,1,k3,k4); %missing corners : use the average value (from the 3 or 2 neighbours) zzC(1)=fld.f1(1,end,k3,k4)+fld.f3(1,end,k3,k4)+fld.f5(1,end,k3,k4); zzC(2)=fld.f2(end,1,k3,k4)+fld.f4(end,1,k3,k4)+fld.f6(end,1,k3,k4); zzC=zzC/3; %missing corners : assume symmetry of the grid (that may be completly wrong!) if exch_Z_assume_sym; zzC(1)=fld.f4(1,1,k3,k4); zzC(2)=fld.f1(1,1,k3,k4); end %- 1rst = N.W corner of face 1 FLD.f1(1,end,k3,k4)=zzC(1); FLD.f3(1,end,k3,k4)=zzC(1); FLD.f5(1,end,k3,k4)=zzC(1); %- 2nd = S.E corner of face 2 FLD.f2(end,1,k3,k4)=zzC(2); FLD.f4(end,1,k3,k4)=zzC(2); FLD.f6(end,1,k3,k4)=zzC(2); end; end; gcmfaces/gcmfaces_exch/exch_UV_cube.m0000644000435400001440000000153211367364525017516 0ustar gforgetusersfunction [FLDU,FLDV]=exch_UV_cube(fldU,fldV); FLDUtmp=exch_T_N(fldU); FLDVtmp=exch_T_N(fldV); FLDU=FLDUtmp; FLDV=FLDVtmp; FLDU.f1=FLDUtmp.f1(2:end,2:end-1,:); FLDV.f1=FLDVtmp.f1(2:end-1,2:end,:); FLDV.f1(:,end,:)=FLDUtmp.f1(2:end-1,end,:); FLDU.f2=FLDUtmp.f2(2:end,2:end-1,:); FLDU.f2(end,:,:)=FLDVtmp.f2(end,2:end-1,:); FLDV.f2=FLDVtmp.f2(2:end-1,2:end,:); FLDU.f3=FLDUtmp.f3(2:end,2:end-1,:); FLDV.f3=FLDVtmp.f3(2:end-1,2:end,:); FLDV.f3(:,end,:)=FLDUtmp.f3(2:end-1,end,:); FLDU.f4=FLDUtmp.f4(2:end,2:end-1,:); FLDU.f4(end,:,:)=FLDVtmp.f4(end,2:end-1,:); FLDV.f4=FLDVtmp.f4(2:end-1,2:end,:); %?? u FLDU.f5=FLDUtmp.f5(2:end,2:end-1,:); FLDV.f5=FLDVtmp.f5(2:end-1,2:end,:); FLDV.f5(:,end,:)=FLDUtmp.f5(2:end-1,end,:); FLDU.f6=FLDUtmp.f6(2:end,2:end-1,:); FLDU.f6(end,:,:)=FLDVtmp.f6(end,2:end-1,:); FLDV.f6=FLDVtmp.f6(2:end-1,2:end,:); %??u gcmfaces/gcmfaces_exch/exch_UV_N_llc.m0000644000435400001440000000646611712423607017631 0ustar gforgetusersfunction [FLDU,FLDV]=exch_UV_N_cube(fldU,fldV,varargin); if nargin==3; N=varargin{1}; else; N=1; end; %fill interior of extended arrays FLDUtmp=exch_T_N(fldU,N); FLDVtmp=exch_T_N(fldV,N); for iFace=1:fldU.nFaces; FLDUtmp{iFace}(1:N,:,:)=NaN; FLDUtmp{iFace}(end-N+1:end,:,:)=NaN; FLDUtmp{iFace}(:,1:N,:)=NaN; FLDUtmp{iFace}(:,end-N+1:end,:)=NaN; FLDVtmp{iFace}(1:N,:,:)=NaN; FLDVtmp{iFace}(end-N+1:end,:,:)=NaN; FLDVtmp{iFace}(:,1:N,:)=NaN; FLDVtmp{iFace}(:,end-N+1:end,:)=NaN; end; FLDU=FLDUtmp; FLDV=FLDVtmp; %now add the one extra point we need for U and V [FLDUtmp,FLDVtmp]=exch_UV(fldU,fldV); %then add the remaining rows and columns... %U face 1 tmp1=permute(FLDVtmp.f5(:,end-N:end-1,:),[2 1 3]); FLDU.f1(1:N,N+1:end-N,:)=flipdim(tmp1,2); tmp1=FLDUtmp.f2(1:N,:,:); FLDU.f1(end-N+1:end,N+1:end-N,:)=tmp1; % tmp1=permute(-FLDVtmp.f3(1:N,:,:),[2 1 3]); FLDU.f1(N+1:end-N+1,end-N+1:end,:)=flipdim(tmp1,1); %V face 1 tmp1=permute(-FLDUtmp.f5(:,end-N+1:end,:),[2 1 3]); FLDV.f1(1:N,N+1:end-N+1,:)=flipdim(tmp1,2); tmp1=FLDVtmp.f2(1:N,:,:); FLDV.f1(end-N+1:end,N+1:end-N+1,:)=tmp1; % tmp1=permute(FLDUtmp.f3(1:N,:,:),[2 1 3]); FLDV.f1(N+1:end-N,end-N+1:end,:)=flipdim(tmp1,1); %U face 2 tmp1=FLDUtmp.f1(end-N:end-1,:,:); FLDU.f2(1:N,N+1:end-N,:)=tmp1; tmp1=permute(FLDVtmp.f4(:,1:N,:),[2 1 3]); FLDU.f2(end-N+1:end,N+1:end-N,:)=flipdim(tmp1,2); % tmp1=FLDUtmp.f3(:,1:N,:); FLDU.f2(N+1:end-N+1,end-N+1:end,:)=tmp1; %V face 2 tmp1=FLDVtmp.f1(end-N+1:end,:,:); FLDV.f2(1:N,N+1:end-N+1,:)=tmp1; tmp1=permute(-FLDUtmp.f4(:,1:N,:),[2 1 3]); FLDV.f2(end-N+1:end,N+1:end-N+1,:)=flipdim(tmp1,2); % tmp1=FLDVtmp.f3(:,1:N,:); FLDV.f2(N+1:end-N,end-N+1:end,:)=tmp1; %U face 3 tmp1=permute(FLDVtmp.f1(:,end-N:end-1,:),[2 1 3]); FLDU.f3(1:N,N+1:end-N,:)=flipdim(tmp1,2); tmp1=FLDUtmp.f4(1:N,:,:); FLDU.f3(end-N+1:end,N+1:end-N,:)=tmp1; % tmp1=FLDUtmp.f2(:,end-N+1:end,:); FLDU.f3(N+1:end-N+1,1:N,:)=tmp1; tmp1=permute(-FLDVtmp.f5(1:N,:,:),[2 1 3]); FLDU.f3(N+1:end-N+1,end-N+1:end,:)=flipdim(tmp1,1); %V face 3 tmp1=permute(-FLDUtmp.f1(:,end-N+1:end,:),[2 1 3]); FLDV.f3(1:N,N+1:end-N+1,:)=flipdim(tmp1,2); tmp1=FLDVtmp.f4(1:N,:,:); FLDV.f3(end-N+1:end,N+1:end-N+1,:)=tmp1; % tmp1=FLDVtmp.f2(:,end-N:end-1,:); FLDV.f3(N+1:end-N,1:N,:)=tmp1; tmp1=permute(FLDUtmp.f5(1:N,:,:),[2 1 3]); FLDV.f3(N+1:end-N,end-N+1:end,:)=flipdim(tmp1,1); %U face 4 tmp1=FLDUtmp.f3(end-N:end-1,:,:); FLDU.f4(1:N,N+1:end-N,:)=tmp1; % tmp1=permute(-FLDVtmp.f2(end-N+1:end,:,:),[2 1 3]); FLDU.f4(N+1:end-N+1,1:N,:)=flipdim(tmp1,1); tmp1=FLDUtmp.f5(:,1:N,:); FLDU.f4(N+1:end-N+1,end-N+1:end,:)=tmp1; %V face 4 tmp1=FLDVtmp.f3(end-N+1:end,:,:); FLDV.f4(1:N,N+1:end-N+1,:)=tmp1; % tmp1=permute(FLDUtmp.f2(end-N:end-1,:,:),[2 1 3]); FLDV.f4(N+1:end-N,1:N,:)=flipdim(tmp1,1); tmp1=FLDVtmp.f5(:,1:N,:); FLDV.f4(N+1:end-N,end-N+1:end,:)=tmp1; %U face 5 tmp1=permute(FLDVtmp.f3(:,end-N:end-1,:),[2 1 3]); FLDU.f5(1:N,N+1:end-N,:)=flipdim(tmp1,2); % tmp1=FLDUtmp.f4(:,end-N+1:end,:); FLDU.f5(N+1:end-N+1,1:N,:)=tmp1; tmp1=permute(-FLDVtmp.f1(1:N,:,:),[2 1 3]); FLDU.f5(N+1:end-N+1,end-N+1:end,:)=flipdim(tmp1,1); %V face 5 tmp1=permute(-FLDUtmp.f3(:,end-N+1:end,:),[2 1 3]); FLDV.f5(1:N,N+1:end-N+1,:)=flipdim(tmp1,2); % tmp1=FLDVtmp.f4(:,end-N:end-1,:); FLDV.f5(N+1:end-N,1:N,:)=tmp1; tmp1=permute(FLDUtmp.f1(1:N,:,:),[2 1 3]); FLDV.f5(N+1:end-N,end-N+1:end,:)=flipdim(tmp1,1); gcmfaces/gcmfaces_exch/exch_T_N_llpc.m0000644000435400001440000000253011367364525017657 0ustar gforgetusersfunction [FLD]=exch_T_N_llpc(fld,varargin); if nargin==2; N=varargin{1}; else; N=1; end; FLD=fld; s=size(FLD.f1); s(1:2)=s(1:2)+2*N; FLD.f1=NaN*zeros(s); s=size(FLD.f2); s(1:2)=s(1:2)+2*N; FLD.f2=NaN*zeros(s); s=size(FLD.f3); s(1:2)=s(1:2)+2*N; FLD.f3=NaN*zeros(s); s=size(FLD.f4); s(1:2)=s(1:2)+2*N; FLD.f4=NaN*zeros(s); n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); for k3=1:n3; for k4=1:n4; %f1245=[fld{1}(:,:,k3,k4);fld{2}(:,:,k3,k4);sym_g(fld{4}(:,:,k3,k4),7,0);sym_g(fld{5}(:,:,k3,k4),7,0)]; %f3=fld{3}(:,:,k3,k4); f3=[sym_g(f3,5,0);f3;sym_g(f3,7,0);sym_g(f3,6,0)]; %initial rotation for "LATLON" faces: f1=fld.f1(:,:,k3,k4); f2=fld.f2(:,:,k3,k4); f3=sym_g(fld.f3(:,:,k3,k4),7,0); f4=sym_g(fld.f4(:,:,k3,k4),7,0); nan1=NaN*ones(size(FLD.f1,1),N); nan2=NaN*ones(N,N); %face 1: F1=[f4(end-N+1:end,:);f1;f2(1:N,:)]; ff=sym_g(f4,6,0); F1=[nan1 F1 [nan2;ff(:,1:N);nan2]]; %face 2: F2=[f1(end-N+1:end,:);f2;f3(1:N,:)]; ff=sym_g(f3,6,0); F2=[nan1 F2 [nan2;ff(:,1:N);nan2]]; %face 4: F3=[f2(end-N+1:end,:);f3;f4(1:N,:)]; ff=sym_g(f2,6,0); F3=[nan1 F3 [nan2;ff(:,1:N);nan2]]; %face 5: F4=[f3(end-N+1:end,:);f4;f1(1:N,:)]; ff=sym_g(f1,6,0); F4=[nan1 F4 [nan2;ff(:,1:N);nan2]]; %final rotation for "LATLON" faces: F3=sym_g(F3,5,0); F4=sym_g(F4,5,0); %store: FLD.f1(:,:,k3,k4)=F1; FLD.f2(:,:,k3,k4)=F2; FLD.f3(:,:,k3,k4)=F3; FLD.f4(:,:,k3,k4)=F4; end; end; gcmfaces/gcmfaces_exch/exch_Z_llc.m0000644000435400001440000000407612024523407017222 0ustar gforgetusersfunction [FLD]=exch_Z_llc(fld); %[FLD]=exch_Z_llc(fld); %adds vorticity points (to north and east of center points) for %lat-lon cap grid gcmfaces_global; %missing corners : assume symmetry of the grid (that may be completly wrong!) global exch_Z_assume_sym; if isempty(exch_Z_assume_sym); exch_Z_assume_sym=0; end; %determine vertical and/or time dimensions n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); %initialize FLD FLD=gcmfaces; for iF=1:mygrid.nFaces [n1,n2]=size(mygrid.XC{iF}); FLD{iF}=NaN*zeros([n1+1 n2+1 n3 n4]); end; for k3=1:n3; for k4=1:n4; for iF=1:mygrid.nFaces FLD{iF}(1:end-1,1:end-1,k3,k4)=fld{iF}(:,:,k3,k4); end %overlap in i+1 FLD.f1(end,1:end-1,k3,k4)=fld.f2(1,:,k3,k4); FLD.f2(end,2:end,k3,k4)=flipud(fld.f4(:,1,k3,k4)); FLD.f3(end,1:end-1,k3,k4)=fld.f4(1,:,k3,k4); FLD.f4(end,2:end,k3,k4)=NaN; FLD.f5(end,1:end-1,k3,k4)=NaN; %overlap in j+1 FLD.f1(2:end,end,k3,k4)=fliplr(fld.f3(1,:,k3,k4)); FLD.f2(1:end-1,end,k3,k4)=fld.f3(:,1,k3,k4); FLD.f3(2:end,end,k3,k4)=fliplr(fld.f5(1,:,k3,k4)); FLD.f4(1:end-1,end,k3,k4)=fld.f5(:,1,k3,k4); FLD.f5(2:end,end,k3,k4)=fliplr(fld.f1(1,:,k3,k4)); %missing corners : use the average value (from the 3 or 2 neighbours) zzC(1)=(fld.f1(1,end,k3,k4)+fld.f3(1,end,k3,k4)+fld.f5(1,end,k3,k4))/3; zzC(2)=(fld.f2(end,1,k3,k4)+fld.f4(end,1,k3,k4))/2; %missing corners : assume symmetry of the grid (that may be completly wrong!) if exch_Z_assume_sym; zzC(1)=fld.f4(1,1,k3,k4); zzC(2)=fld.f1(1,1,k3,k4); warning('exch_Z_llc filled 2 missing corners assuming uncertain symmetries!'); end %- 1rst = N.W corner of face 1 FLD.f1(1,end,k3,k4)=zzC(1); FLD.f3(1,end,k3,k4)=zzC(1); FLD.f5(1,end,k3,k4)=zzC(1); %- 2nd = S.E corner of face 2 FLD.f2(end,1,k3,k4)=zzC(2); FLD.f4(end,1,k3,k4)=zzC(2); end; end; 1; gcmfaces/gcmfaces_exch/exch_T_N_ll.m0000644000435400001440000000251412024523407017321 0ustar gforgetusersfunction [FLD]=exch_T_N_ll(fld,varargin); gcmfaces_global; if nargin==2; N=varargin{1}; else; N=1; end; if ~isfield(mygrid,'domainPeriodicity'); fprintf('\nexch_T_N_ll.m init: different 1 face configurations may \n'); fprintf(' differ with respect to domain periodicity. By default gcmfaces \n'); fprintf(' assumes 0 periodicity, except that if the first dimension has n*90 \n'); fprintf(' points it is assumed to be periodic. If this is inadequate, \n'); fprintf(' you can set domainPeriodicity yourself as explained below.\n\n'); %domainPeriodicity=[0 0];%no periodidicity %domainPeriodicity=[1 0];%1st dimension only is periodic %domainPeriodicity=[0 1];%2nd dimension only is periodic %domainPeriodicity=[1 0];%both dimensions are periodic if mod(size(fld{1},1),90)==0; mygrid.domainPeriodicity=[1 0]; else; mygrid.domainPeriodicity=[0 0]; end; end; FLD=fld; s=size(FLD.f1); s(1:2)=s(1:2)+2*N; FLD.f1=NaN*zeros(s); n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); for k3=1:n3; for k4=1:n4; f1=fld.f1(:,:,k3,k4); nan1=NaN*ones(N,size(fld.f1,2)); nan2=NaN*ones(size(FLD.f1,1),N); %face 1: if mygrid.domainPeriodicity(1); F1=[f1(end-N+1:end,:);f1;f1(1:N,:)]; else; F1=[nan1;f1;nan1]; end; if mygrid.domainPeriodicity(2); F1=[F1(:,end-N+1:end) F1 F1(:,1:N)]; else; F1=[nan2 F1 nan2]; end; %store: FLD.f1(:,:,k3,k4)=F1; end; end; gcmfaces/gcmfaces_exch/exch_T_N_llc.m0000644000435400001440000000310712266600563017472 0ustar gforgetusersfunction [FLD]=exch_T_N_llc(fld,varargin); if nargin==2; N=varargin{1}; else; N=1; end; FLD=fld; s=size(FLD.f1); s(1:2)=s(1:2)+2*N; FLD.f1=NaN*zeros(s); s=size(FLD.f2); s(1:2)=s(1:2)+2*N; FLD.f2=NaN*zeros(s); s=size(FLD.f3); s(1:2)=s(1:2)+2*N; FLD.f3=NaN*zeros(s); s=size(FLD.f4); s(1:2)=s(1:2)+2*N; FLD.f4=NaN*zeros(s); s=size(FLD.f5); s(1:2)=s(1:2)+2*N; FLD.f5=NaN*zeros(s); n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); %initial rotation for "LATLON" faces: f1=fld.f1; f2=fld.f2; f4=sym_g(fld.f4,7,0); f5=sym_g(fld.f5,7,0); nan1=NaN*ones(size(FLD.f1,1),N,n3,n4); nan2=NaN*ones(N,N,n3,n4); %face 1: F1=cat(1,f5(end-N+1:end,:,:,:),f1,f2(1:N,:,:,:)); f3=sym_g(fld.f3,5,0); F1=cat(2,nan1,F1,cat(1,nan2,f3(:,1:N,:,:),nan2)); %face 2: F2=cat(1,f1(end-N+1:end,:,:,:),f2,f4(1:N,:,:,:)); f3=fld.f3; F2=cat(2,nan1,F2,cat(1,nan2,f3(:,1:N,:,:),nan2)); %face 4: F4=cat(1,f2(end-N+1:end,:,:,:),f4,f5(1:N,:,:,:)); f3=sym_g(fld.f3,7,0); F4=cat(2,nan1,F4,cat(1,nan2,f3(:,1:N,:,:),nan2)); %face 5: F5=cat(1,f4(end-N+1:end,:,:,:),f5,f1(1:N,:,:,:)); f3=sym_g(fld.f3,6,0); F5=cat(2,nan1,F5,cat(1,nan2,f3(:,1:N,:,:),nan2)); %face 3: f3=fld.f3; F3=FLD.f3; F3(1+N:end-N,1+N:end-N,:,:)=f3; F3=sym_g(F3,5,0); F3(1+N:end-N,1:N,:,:)=f1(:,end-N+1:end,:,:); F3=sym_g(F3,7,0); F3(1+N:end-N,1:N,:,:)=f2(:,end-N+1:end,:,:); F3=sym_g(F3,7,0); F3(1+N:end-N,1:N,:,:)=f4(:,end-N+1:end,:,:); F3=sym_g(F3,5,0); F3=sym_g(F3,6,0); F3(1+N:end-N,1:N,:,:)=f5(:,end-N+1:end,:,:); F3=sym_g(F3,6,0); %final rotation for "LATLON" faces: F4=sym_g(F4,5,0); F5=sym_g(F5,5,0); %store: FLD.f1=F1; FLD.f2=F2; FLD.f3=F3; FLD.f4=F4; FLD.f5=F5; gcmfaces/gcmfaces_exch/exch_UV_llc.m0000644000435400001440000000125111367364525017350 0ustar gforgetusersfunction [FLDU,FLDV]=exch_UV_llc(fldU,fldV); FLDUtmp=exch_T_N(fldU); FLDVtmp=exch_T_N(fldV); FLDU=FLDUtmp; FLDV=FLDVtmp; FLDU.f1=FLDUtmp.f1(2:end,2:end-1,:); FLDV.f1=FLDVtmp.f1(2:end-1,2:end,:); FLDV.f1(:,end,:)=FLDUtmp.f1(2:end-1,end,:); FLDU.f2=FLDUtmp.f2(2:end,2:end-1,:); FLDU.f2(end,:,:)=FLDVtmp.f2(end,2:end-1,:); FLDV.f2=FLDVtmp.f2(2:end-1,2:end,:); FLDU.f3=FLDUtmp.f3(2:end,2:end-1,:); FLDV.f3=FLDVtmp.f3(2:end-1,2:end,:); FLDV.f3(:,end,:)=FLDUtmp.f3(2:end-1,end,:); FLDU.f4=FLDUtmp.f4(2:end,2:end-1,:); FLDV.f4=FLDVtmp.f4(2:end-1,2:end,:); FLDU.f5=FLDUtmp.f5(2:end,2:end-1,:); FLDV.f5=FLDVtmp.f5(2:end-1,2:end,:); FLDV.f5(:,end,:)=FLDUtmp.f5(2:end-1,end,:); gcmfaces/gcmfaces_smooth/0000755000435400001440000000000012375431055015353 5ustar gforgetusersgcmfaces/gcmfaces_smooth/diffsmooth2D_extrap_fwd.m0000644000435400001440000000257412006105361022301 0ustar gforgetusersfunction [FLD]=diffsmooth2D_extrap_fwd(fld,mskOut,eps); %object: extrapolate an incomplete field to create a full field, by % time-stepping a diffusion equation to near-equilibrium. %inputs: fld incomplete field of interest (masked with NaN) % mskOut land mask (1s and NaNs) for the full field (output) % eps convergence criterium %output: FLD full field global mygrid; dxC=mygrid.DXC; dyC=mygrid.DYC; rA=mygrid.RAC; dxCsm=dxC; dyCsm=dyC; %mask of points which values will evolve doStep=1*(isnan(fld)); %put first guess: x=convert2array(mygrid.XC); y=convert2array(mygrid.YC); z=convert2array(fld); m=convert2array(mskOut); tmp1=find(~isnan(z)); tmp2=find(~isnan(m)); zz=z; zz(tmp2) = griddata(x(tmp1),y(tmp1),z(tmp1),x(tmp2),y(tmp2),'nearest'); fld=convert2array(zz); %put 0 first guess if needed and switch land mask: fld(find(isnan(fld)))=0; fld=fld.*mskOut; %scale the diffusive operator: tmp0=dxCsm./dxC; tmp0(isnan(mskOut))=NaN; tmp00=nanmax(tmp0); tmp0=dyCsm./dyC; tmp0(isnan(mskOut))=NaN; tmp00=max([tmp00 nanmax(tmp0)]); smooth2D_nbt=tmp00; smooth2D_nbt=ceil(1.1*2*smooth2D_nbt^2); smooth2D_dt=1; smooth2D_T=smooth2D_nbt*smooth2D_dt; smooth2D_Kux=dxCsm.*dxCsm/smooth2D_T/2; smooth2D_Kvy=dyCsm.*dyCsm/smooth2D_T/2; %setup problem: myOp.dt=1; myOp.eps=eps; myOp.Kux=smooth2D_Kux; myOp.Kvy=smooth2D_Kvy; myOp.doStep=doStep; %time step problem: FLD=gcmfaces_timestep(myOp,fld); gcmfaces/gcmfaces_smooth/diffsmooth2Drotated.m0000644000435400001440000000217712006073741021446 0ustar gforgetusersfunction [FLD]=diffsmooth2Drotated(fld,dxLarge,dxSmall,fldRef); % %object: slanted diffusive smoother (after Weaver and Courtier 2001) % %input: fld field to be smoothed (masked with NaN) % dxLarge,dySmall smoothing scale in direction of % weak,strong fldRef gradient % fldRef tracer field which gradient defines % directions of strong,weak smoothing %output:FLD smoothed field % %asumption: dxLarge/dxSmall are given at tracer points (not U/V points) global mygrid; dxC=mygrid.DXC; dyC=mygrid.DYC; dxG=mygrid.DXG; dyG=mygrid.DYG; rA=mygrid.RAC; %scale the diffusive operator: tmp0=dxLarge./dxC; tmp0(isnan(fld))=NaN; tmp00=nanmax(tmp0); tmp0=dxLarge./dyC; tmp0(isnan(fld))=NaN; tmp00=max([tmp00 nanmax(tmp0)]); nbt=tmp00; nbt=ceil(1.1*2*nbt^2); dt=1; T=nbt*dt; %diffusion operator: kLarge=dxLarge.*dxLarge/T/2; kSmall=dxSmall.*dxSmall/T/2; [Kux,Kuy,Kvx,Kvy]=diffrotated(kLarge,kSmall,fldRef); %setup problem: myOp.dt=1; myOp.nbt=nbt; myOp.Kux=Kux; myOp.Kuy=Kuy; myOp.Kvx=Kvx; myOp.Kvy=Kvy; %time step problem: FLD=gcmfaces_timestep(myOp,fld); gcmfaces/gcmfaces_smooth/diffsmooth2D_extrap_inv.m0000644000435400001440000001071312274331524022320 0ustar gforgetusersfunction [FLD]=diffsmooth2D_extrap_inv(fld,mskOut,varargin); %object: extrapolate an incomplete field to create a full field, by % solving for a diffusion equation equilibrium state. %inputs: fld incomplete field of interest (masked with NaN) % mskOut land mask (1s and NaNs) for the full field (output) %output: FLD full field %optional: doFormMatrix (1 by default) % if set to 1 then compute the dFLDdt_op matrix % if set to 0 then use precomputed one (global dFLDdt_op) % doMSKOUT (1 by default) % if set to 1 then first detect closed regions lacking % data points to extrapolate from (e.g. abyssal canions) % and restrict mskOut to MSKOUT accordingly % if set to 0 then omit this step %principle : %in points where mskFreeze is 1 solve diffusion equation %in points where mskFreeze is 0 solve the trivial FLD=fld gcmfaces_global; if nargin==3; doFormMatrix=varargin{1}; else; doFormMatrix=1; end; if nargin==4; doMSKOUT=varargin{2}; else; doMSKOUT=1; end; if doMSKOUT; %problematic regions will show MSKOUT==0; tmp1=1+0*fld; [MSKOUT]=diffsmooth2D_extrap_inv(tmp1,mskOut,doFormMatrix,0); %if no problematic region then no need to recompute dFLDdt_op if sum(MSKOUT==0)==0; doFormMatrix=0; end; %finalize MSKOUT MSKOUT(MSKOUT==0)=NaN; MSKOUT(~isnan(MSKOUT))=1; end; dxC=mygrid.DXC; dyC=mygrid.DYC; rA=mygrid.RAC; dxCsm=dxC; dyCsm=dyC; mskFreeze=fld; mskFreeze(find(~isnan(mskFreeze)))=0; mskFreeze(find(isnan(mskFreeze)))=1; %check for domain edge points where no exchange is possible: tmp1=mskOut; tmp1(:)=1; tmp2=exch_T_N(tmp1); for iF=1:mskOut.nFaces; tmp3=mskOut{iF}; tmp4=tmp2{iF}; tmp4=tmp4(2:end-1,1:end-2)+tmp4(2:end-1,3:end)+tmp4(1:end-2,2:end-1)+tmp4(3:end,2:end-1); if ~isempty(find(isnan(tmp4)&~isnan(tmp3))); fprintf('warning: mask was modified\n'); end; tmp3(isnan(tmp4))=NaN; mskOut{iF}=tmp3; end; %put 0 first guess if needed and switch land mask: fld(find(isnan(fld)))=0; fld=fld.*mskOut; %scale the diffusive operator: tmp0=dxCsm./dxC; tmp0(isnan(mskOut))=NaN; tmp00=nanmax(tmp0); tmp0=dyCsm./dyC; tmp0(isnan(mskOut))=NaN; tmp00=max([tmp00 nanmax(tmp0)]); smooth2D_nbt=tmp00; smooth2D_nbt=ceil(1.1*2*smooth2D_nbt^2); smooth2D_dt=1; smooth2D_T=smooth2D_nbt*smooth2D_dt; smooth2D_Kux=dxCsm.*dxCsm/smooth2D_T/2; smooth2D_Kvy=dyCsm.*dyCsm/smooth2D_T/2; %form matrix problem: tmp1=convert2array(mskOut); kk=find(~isnan(tmp1)); KK=tmp1; KK(kk)=kk; KK=convert2array(KK); nn=length(kk); NN=tmp1; NN(kk)=[1:nn]; %NN=convert2array(NN); global dFLDdt_op; if doFormMatrix==1; dFLDdt_op=sparse([],[],[],nn,nn,nn*5); for iF=1:fld.nFaces; for ii=1:3; for jj=1:3; FLDones=fld; FLDones(find(~isnan(fld)))=0; FLDones{iF}(ii:3:end,jj:3:end)=1; FLDones(find(isnan(fld)))=NaN; FLDkkFROMtmp=fld; FLDkkFROMtmp(find(~isnan(fld)))=0; FLDkkFROMtmp{iF}(ii:3:end,jj:3:end)=KK{iF}(ii:3:end,jj:3:end); FLDkkFROMtmp(find(isnan(fld)))=0; FLDkkFROM=exch_T_N(FLDkkFROMtmp); FLDkkFROM(find(isnan(FLDkkFROM)))=0; for iF2=1:fld.nFaces; tmp1=FLDkkFROM{iF2}; tmp2=zeros(size(tmp1)-2); for ii2=1:3; for jj2=1:3; tmp2=tmp2+tmp1(ii2:end-3+ii2,jj2:end-3+jj2); end; end; FLDkkFROM{iF2}=tmp2; end; %clear FLDkkFROMtmp; [dTdxAtU,dTdyAtV]=calc_T_grad(FLDones,0); tmpU=dTdxAtU.*smooth2D_Kux; tmpV=dTdyAtV.*smooth2D_Kvy; [fldDIV]=calc_UV_conv(tmpU,tmpV); dFLDdt=smooth2D_dt*fldDIV./rA; dFLDdt=dFLDdt.*mskFreeze; dFLDdt=convert2array(dFLDdt); FLDkkFROM=convert2array(FLDkkFROM); FLDkkTO=convert2array(KK); tmp1=find(dFLDdt~=0&~isnan(dFLDdt)); dFLDdt=dFLDdt(tmp1); FLDkkFROM=FLDkkFROM(tmp1); FLDkkTO=FLDkkTO(tmp1); dFLDdt_op=dFLDdt_op+sparse(NN(FLDkkTO),NN(FLDkkFROM),dFLDdt,nn,nn); end; end; end; end;%if doFormMatrix==1; %figure; spy(dFLDdt_op); FLD_vec=convert2array(fld);%right hand side of FLD=fld mskFreeze_vec=convert2array(mskFreeze); FLD_vec(find(mskFreeze_vec==1))=0;%right hand side of diffusion equation FLD_vec=FLD_vec(kk); INV_op=1-mskFreeze_vec(kk); INV_op=sparse([1:nn],[1:nn],INV_op,nn,nn);%identity where mskFreeze is 0 INV_op=INV_op+dFLDdt_op;%add diffusion operator where mskFreeze is 1 INV_vec=INV_op\FLD_vec;%solve INV_fld=convert2array(mskOut); INV_fld(find(~isnan(INV_fld)))=INV_vec; FLD=convert2array(INV_fld);%reformat if doMSKOUT; FLD=FLD.*MSKOUT; end;%mask problematic regions gcmfaces/gcmfaces_smooth/diffsmooth2D.m0000644000435400001440000000142212006073741020053 0ustar gforgetusersfunction [FLD]=diffsmooth2D(fld,dxCsm,dyCsm); %object: diffusive smoother (after Weaver and Courtier 2001) % %input: fld field to be smoothed (masked with NaN) % dxCsm,dyCsm scale in first/second grid direction %output:FLD smoothed field % %asumption: dxCsm/dyCsm are given at U/V points (as DXC/DYC are) global mygrid; %scale the diffusive operator: dxC=mygrid.DXC; dyC=mygrid.DYC; tmp0=dxCsm./dxC; tmp0(isnan(fld))=NaN; tmp00=nanmax(tmp0); tmp0=dyCsm./dyC; tmp0(isnan(fld))=NaN; tmp00=max([tmp00 nanmax(tmp0)]); nbt=tmp00; nbt=ceil(1.1*2*nbt^2); dt=1; T=nbt*dt; %diffusion operator: Kux=dxCsm.*dxCsm/T/2; Kvy=dyCsm.*dyCsm/T/2; %setup problem: myOp.dt=1; myOp.nbt=nbt; myOp.Kux=Kux; myOp.Kvy=Kvy; %time step problem: FLD=gcmfaces_timestep(myOp,fld); gcmfaces/gcmfaces_smooth/diffrotated.m0000644000435400001440000000463512006073741020027 0ustar gforgetusersfunction [Kux,Kuy,Kvx,Kvy]=diffrotated(kLarge,kSmall,fldRef); % %object: compute slanted diffusive operator coefficients % %input: dxLarge,dySmall smoothing scale in direction of % weak,strong fldRef gradient % fldRef tracer field which gradient defines % directions of strong,weak smoothing %output:Kux,Kuy,Kvx,Kvy slanted diffusion operator coefficients % %asumption: dxLarge/dxSmall are given at tracer points (not U/V points) gcmfaces_global; %compute the direction of main axis: %=================================== %1) gradient at cell center [dTdxAtT,dTdyAtT]=calc_T_grad(fldRef,1); [dTdxAtT,dTdyAtT]=exch_UV_N(dTdxAtT,dTdyAtT); %2) diffusion coefficients at cell center kLargeAtT=exch_T_N(kLarge); kSmallAtT=exch_T_N(kSmall); %3) interpolate to U/V points dTdxAtU=gcmfaces; dTdxAtV=gcmfaces; dTdyAtU=gcmfaces; dTdyAtV=gcmfaces; kLargeAtU=gcmfaces; kLargeAtV=gcmfaces; kSmallAtU=gcmfaces; kSmallAtV=gcmfaces; for iF=1:mygrid.nFaces; dTdxAtU{iF}=0.5*(dTdxAtT{iF}(1:end-2,2:end-1)+dTdxAtT{iF}(2:end-1,2:end-1)); dTdyAtU{iF}=0.5*(dTdyAtT{iF}(1:end-2,2:end-1)+dTdyAtT{iF}(2:end-1,2:end-1)); kLargeAtU{iF}=0.5*(kLargeAtT{iF}(1:end-2,2:end-1)+kLargeAtT{iF}(2:end-1,2:end-1)); kSmallAtU{iF}=0.5*(kSmallAtT{iF}(1:end-2,2:end-1)+kSmallAtT{iF}(2:end-1,2:end-1)); dTdxAtV{iF}=0.5*(dTdxAtT{iF}(2:end-1,1:end-2)+dTdxAtT{iF}(2:end-1,2:end-1)); dTdyAtV{iF}=0.5*(dTdyAtT{iF}(2:end-1,1:end-2)+dTdyAtT{iF}(2:end-1,2:end-1)); kLargeAtV{iF}=0.5*(kLargeAtT{iF}(2:end-1,1:end-2)+kLargeAtT{iF}(2:end-1,2:end-1)); kSmallAtV{iF}=0.5*(kSmallAtT{iF}(2:end-1,1:end-2)+kSmallAtT{iF}(2:end-1,2:end-1)); end; %compute diffusion operator : (rotated to the direction of main axis) %=========================== %at U points dFLDn=sqrt(dTdxAtU.^2+dTdyAtU.^2); cs=dTdyAtU; sn=-dTdxAtU; cs(dFLDn>0)=cs(dFLDn>0)./dFLDn(dFLDn>0); sn(dFLDn>0)=sn(dFLDn>0)./dFLDn(dFLDn>0); if 1; FLDangleU=gcmfaces; for iF=1:mygrid.nFaces; FLDangleU{iF}=atan2(sn{iF},cs{iF}); end; end; Kux=cs.*cs.*kLargeAtU+sn.*sn.*kSmallAtU; Kuy=cs.*sn.*(-kLargeAtU+kSmallAtU); %at V points dFLDn=sqrt(dTdxAtV.^2+dTdyAtV.^2); cs=dTdyAtV; sn=-dTdxAtV; cs(dFLDn>0)=cs(dFLDn>0)./dFLDn(dFLDn>0); sn(dFLDn>0)=sn(dFLDn>0)./dFLDn(dFLDn>0); if 1; FLDangleV=fldRef; for iF=1:mygrid.nFaces; FLDangleV{iF}=atan2(sn{iF},cs{iF}); end; end; Kvy=sn.*sn.*kLargeAtV+cs.*cs.*kSmallAtV; Kvx=cs.*sn.*(-kLargeAtV+kSmallAtV); gcmfaces/gcmfaces_smooth/diffsmooth2D_div_inv.m0000644000435400001440000001104412274331524021575 0ustar gforgetusersfunction [fldUdiv,fldVdiv,fldDivPot]=diffsmooth2D_div_inv(fldU,fldV); %object: compute the divergent part of a tranport vector field % by solving a Laplace equation with Neumann B.C. % %input: fldU,fldV transport vectors (masked with NaNs) %output:fldUdiv,fldVdiv divergent part % fldDivPot Potential for the divergent flow (optional) % %note 1: here we do everything in terms of transports, so we omit all % grid factors (i.e. with dx=dy=1), and the resulting potential % has usits of transports. %note 2: this routine was derived from diffsmooth2D_extrap_inv.m but % it differs in several aspects. It : 1) omits grid factors; % 2) uses of a neumann, rather than dirichlet, boundary condition; % 3) gets the mask directly from fld. global mygrid; warning('off','MATLAB:divideByZero'); fld=calc_UV_conv(fldU,fldV,{});%no grid scaling factor in div. or transports fld=fld.*mygrid.mskC(:,:,1); fld(fld==0)=NaN; mskWet=fld; mskWet(~isnan(fld))=1; mskDry=1*isnan(mskWet); mskDry(mskDry==0)=NaN; %check for domain edge points where no exchange is possible: tmp1=mskWet; tmp1(:)=1; tmp2=exch_T_N(tmp1); for iF=1:mskWet.nFaces; tmp3=mskWet{iF}; tmp4=tmp2{iF}; tmp4=tmp4(2:end-1,1:end-2)+tmp4(2:end-1,3:end)+tmp4(1:end-2,2:end-1)+tmp4(3:end,2:end-1); if ~isempty(find(isnan(tmp4)&~isnan(tmp3))); fprintf('warning: mask was modified\n'); end; tmp3(isnan(tmp4))=NaN; mskWet{iF}=tmp3; end; %why does this matters... see set-ups with open boundary conditions... %put 0 first guess if needed and switch land mask: fld(find(isnan(fld)))=0; fld=fld.*mskWet; %define mapping from global array to (no nan points) global vector tmp1=convert2array(mskWet); kk=find(~isnan(tmp1)); nn=length(kk); KK=tmp1; KK(:)=0; KK(kk)=kk; KKfaces=convert2array(KK); %global array indices LL=tmp1; LL(:)=0; LL(kk)=[1:nn]; LLfaces=convert2array(LL); %global vector indices %note: diffsmooth2D_extrap_inv.m uses a Dirichlet boundary condition % so that it uses a nan/1 mask in KK/LL // here we use a % Neumann boundary condition so we use a 0/1 mask (see below also) %form matrix problem: A=sparse([],[],[],nn,nn,nn*5); for iF=1:fld.nFaces; for ii=1:3; for jj=1:3; %1) seed points (FLDones) and neighborhood of influence (FLDkkFROM) FLDones=fld; FLDones(:)=0; FLDones{iF}(ii:3:end,jj:3:end)=1; FLDones(KKfaces==0)=0; FLDkkFROMtmp=fld; FLDkkFROMtmp(:)=0; FLDkkFROMtmp{iF}(ii:3:end,jj:3:end)=KKfaces{iF}(ii:3:end,jj:3:end); FLDkkFROMtmp(find(isnan(fld)))=0; FLDkkFROM=exch_T_N(FLDkkFROMtmp); FLDkkFROM(isnan(FLDkkFROM))=0; for iF2=1:fld.nFaces; tmp1=FLDkkFROM{iF2}; tmp2=zeros(size(tmp1)-2); for ii2=1:3; for jj2=1:3; tmp2=tmp2+tmp1(ii2:end-3+ii2,jj2:end-3+jj2); end; end; FLDkkFROM{iF2}=tmp2; end; %2) compute effect of each point on neighboring target point: [tmpU,tmpV]=calc_T_grad(FLDones,0); %unlike calc_T_grad, we work in grid point index, so we need to omit grid factors tmpU=tmpU.*mygrid.DXC; tmpV=tmpV.*mygrid.DYC; %and accordingly we use no grid scaling factor in div. [dFLDdt]=calc_UV_conv(tmpU,tmpV,{}); %note: diffsmooth2D_extrap_inv.m uses a Dirichlet boundary condition % so that it needs to apply mskFreeze to dFLDdt // here we use a % Neumann boundary condition so we do not mask dFLDdt (see above also) %3) include seed contributions in matrix: FLDkkFROM=convert2array(FLDkkFROM); %3.1) for wet points dFLDdtWet=convert2array(dFLDdt.*mskWet); tmp1=find(dFLDdtWet~=0&~isnan(dFLDdtWet)); dFLDdtWet=dFLDdtWet(tmp1); FLDkkFROMtmp=FLDkkFROM(tmp1); FLDkkTOtmp=KK(tmp1); A=A+sparse(LL(FLDkkTOtmp),LL(FLDkkFROMtmp),dFLDdtWet,nn,nn); %3.2) for dry points (-> this part reflects the neumann boundary condition) dFLDdtDry=convert2array(dFLDdt.*mskDry); tmp1=find(dFLDdtDry~=0&~isnan(dFLDdtDry)); dFLDdtDry=dFLDdtDry(tmp1); FLDkkFROMtmp=FLDkkFROM(tmp1); A=A+sparse(LL(FLDkkFROMtmp),LL(FLDkkFROMtmp),dFLDdtDry,nn,nn); end; end; end; %to check results: %figure; spy(A); %4) solve for potential: yy=convert2array(fld); yy=yy(find(KK~=0)); xx=A\yy; yyFROMxx=A*xx; %5) prepare output: fldDivPot=0*convert2array(fld); fldDivPot(find(KK~=0))=xx; fldDivPot=convert2array(fldDivPot); [fldUdiv,fldVdiv]=calc_T_grad(fldDivPot,0); %unlike calc_T_grad, we work in grid point index, so we need to omit grid factors fldUdiv=fldUdiv.*mygrid.DXC; fldVdiv=fldVdiv.*mygrid.DYC; %to check the results: %fld1=0*convert2array(fld); fld1(find(KK~=0))=xx; %fld2=0*convert2array(fld); fld2(find(KK~=0))=yyFROMxx; %fld3=convert2array(calc_UV_conv(fldU,fldV,{}));%no grid scaling factor in div. or transports warning('on','MATLAB:divideByZero'); gcmfaces/gcmfaces_calc/0000755000435400001440000000000012375431055014744 5ustar gforgetusersgcmfaces/gcmfaces_calc/calc_boxmean_T.m0000644000435400001440000000725011746070440020022 0ustar gforgetusersfunction [varargout]=calc_boxmean_T(fld,varargin); %purpose: compute a weighted average of a field % %inputs: % (1) fld is a 3D (or 2D) field in gcmfaces format at the grid % center where missing values are assigned a NaN % (2a) 'LATS',LATS is a line vector of latitutde interval edges % (2b) 'LONS',LONS is a line vector of longitutde interval edges % (3a) 'weights',weights is a weights field. If it is not specified % then we use the grid cell volume in the weighted average. % If specifying 'weights' you likely want to set it to 0 on land. % (3b) 'level',kk is a specification of the vertical level. This % is only used when fld is a 2D field to define weights %outputs: % (1) FLD is the field/vector/value of the weighted mean. It's % size depends on the input size % (2) W is the weights for each element of FLD. It can be used to simply % compute the global weighted average as nansum(W(:).*FLD(:))/nansum(W(:)) %usage: % input 2a and/or 2b is necessary % input 3a or 3b is optional, and are mutually exclusive, except if % fld is 2D when input 3b is needed and 3a is excluded % output 2 is optional %by assumption: grid_load is done global mygrid; %get arguments for ii=1:(nargin-1)/2; tmp1=varargin{2*ii-1}; eval([tmp1 '=varargin{2*ii};']); end; %initialize output: n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); %test inputs/outputs consistency: tmp1=~isempty(whos('LONS'))+~isempty(whos('LATS')); if tmp1~=1&tmp1~=2; error('wrong input specification'); end; tmp1=~isempty(whos('weights'))+~isempty(whos('level')); if tmp1>1; error('wrong input specification'); end; if nargout>2; error('wrong output specification'); end if n3==1&isempty(whos('level'))&isempty(whos('weights')); error('wrong input specification'); end; %prepare output etc.: if ~isempty(whos('LONS'))&~isempty(whos('LATS')); %use complex valranges=LONS'*ones(size(LATS))+i*(ones(size(LONS))'*LATS); elseif ~isempty(whos('LONS')); valranges=LONS'; else; valranges=i*LATS; end; nnranges=size(valranges); nnout=max(size(valranges)-1,[1 1]); % FLD=NaN*ones([nnout n3 n4]); W=NaN*ones([nnout n3 n4]); %select weights for average: if isempty(whos('weights'))&isempty(whos('level')); weights=mygrid.hFacC.*mk3D(mygrid.RAC,mygrid.hFacC); weights=weights.*mk3D(mygrid.DRF,mygrid.hFacC); elseif ~isempty(whos('level')); weights=mygrid.hFacC(:,:,level).*mygrid.RAC*mygrid.DRF(level); end; %multiply with data mask: msk=repmat(1*~isnan(fld),[1 1 n3 n4]); weights=weights.*msk; %switch to 2D array to speed up computation: fld=convert2array(fld); n1=size(fld,1); n2=size(fld,2); fld=reshape(fld,n1*n2,n3*n4); %same for the weights: weights=reshape(convert2array(weights),n1*n2*n3,1)*ones(1,n4); weights=reshape(weights,n1*n2,n3*n4); %multiply one with the other fld=fld.*weights; %remove data mask fld(isnan(fld))=0; lonvec=reshape(convert2array(mygrid.XC),n1*n2,1); latvec=reshape(convert2array(mygrid.YC),n1*n2,1); for ix=1:nnout(1); for iy=1:nnout(2); %get list ofpoints that form a zonal band: if nnout(1)==1; mm=find(latvec>=imag(valranges(ix,iy))&latvec=real(valranges(ix,iy))&lonvec=imag(valranges(ix,iy))&latvec=real(valranges(ix,iy))&lonvec0; mskExtrap=~isnan(fldIn); for ii=1:nExtrap; mskExtrap=exch_T_N(mskExtrap); for iF=1:mskExtrap.nFaces; tmp1=mskExtrap{iF}; tmp1(isnan(tmp1))=0; tmp2=tmp1(2:end-1,2:end-1)+tmp1(1:end-2,2:end-1)+tmp1(3:end,2:end-1)+tmp1(2:end-1,1:end-2)+tmp1(2:end-1,3:end); tmp2(tmp2~=0)=1; mskExtrap{iF}=tmp2; end; end; mskExtrap(find(mskExtrap==0))=NaN; % fldIn=diffsmooth2D_extrap_inv(fldIn,mskExtrap); end; %2) extract vector of ocean points x=convert2vector(mygrid.XC); y=convert2vector(mygrid.YC); v=convert2vector(fldIn); % ii=find(~isnan(v)); ii=find(~isnan(x)); x=x(ii); y=y(ii); v=v(ii); %3) add points at lat-lon global domain edges ii=find(y>90-wRepeat); x=[x;x(ii)]; y=[y;180-y(ii)]; v=[v;v(ii)]; ii=find(y<-90+wRepeat); x=[x;x(ii)]; y=[y;-180-y(ii)]; v=[v;v(ii)]; ii=find(x>180-wRepeat&x<180); x=[x;x(ii)-360]; y=[y;y(ii)]; v=[v;v(ii)]; ii=find(x<-180+wRepeat&x>-180); x=[x;x(ii)+360]; y=[y;y(ii)]; v=[v;v(ii)]; %4) generate the interpolant F = TriScatteredInterp(x,y,v); %5) target grid fldOut = F(lon,lat); %6) optional outputs: if nargout>1; varargout={lon,lat}; end; gcmfaces/gcmfaces_calc/disp_transport.m0000644000435400001440000000673612117727165020215 0ustar gforgetusersfunction [myplot]=disp_transport(myTransports,myTimes,myTitle,varargin); %object: display transport time series and/or time mean %inputs: myTransports contains the transports as a function of depth and time % myTitle is the transport name to be displayed % myTimes is the time vector %optional: must take the following form {'name',param1,param2,...} where name may be % nmean is a running mean window length (0 by default) % ylim is the y axis range for plotting % choicePlot is the type of plot (1 by default) % 1) time series of vertical integral % 2) time series of overturning magnitude (>0) % 3) time mean profile of transport per grid point % 4) time mean profile of bottom-to-top cumulated transport global mygrid; %set more optional paramaters to default values ylim=[]; nmean=0; choicePlot=1; myUnit=[]; %set more optional paramaters to user defined values for ii=1:nargin-3; if ~iscell(varargin{ii}); warning(inputCheck:disp_transport_1',... ['disp_transport optional parameters must be spc. as cell arrays. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help disp_transport'' for details.']); elseif ~ischar(varargin{ii}{1}); warning('inputCheck:disp_transport_2',... ['disp_transport opt. param. cells must start with a char. string. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help disp_transport'' for details.']); else; if strcmp(varargin{ii}{1},'nmean')|... strcmp(varargin{ii}{1},'ylim')|... strcmp(varargin{ii}{1},'choicePlot')|... strcmp(varargin{ii}{1},'myUnit'); eval([varargin{ii}{1} '=varargin{ii}{2};']); else; warning('inputCheck:disp_transport_3',... ['unknown option ''' varargin{ii}{1} ''' was ignored']); end; end; end; nt=length(myTimes); if nt==1&size(myTransports,1)==1; myTransports=myTransports'; end; if choicePlot==2|choicePlot==4;%compute cumulative sum from bottom if size(myTransports,1)>1; fld=[flipdim(cumsum(flipdim(myTransports,1)),1);zeros(1,nt)]; else; fld=[flipdim(cumsum(flipdim(myTransports',1)),1);zeros(1,nt)]; end; else; fld=myTransports; end; if choicePlot==1; fld=nansum(fld,1); end; if choicePlot==2; fld=nanmax(abs(fld),[],1); end; if choicePlot==3; fld=nanmean(fld,2); z=squeeze(mygrid.RC); end; if choicePlot==4; fld=[nanmean(fld,2);0]; z=squeeze(mygrid.RF); end; if choicePlot==1|choicePlot==2;%time series fldmean=1e-2*round(mean(fld)*1e2); if ~isempty(myUnit); unit=[' ' myUnit]; else; unit=' Sv'; end; if nt>1; %myTitle=[myTitle ' mean = ' num2str(fldmean) unit]; if nmean>0; plot(myTimes,fld); hold on; end; fld=runmean(fld,nmean,2); myplot=plot(myTimes,fld,'LineWidth',2); title(myTitle); set(gca,'FontSize',14); grid on; if ~isempty(ylim); aa=[min(myTimes) max(myTimes) ylim]; axis(aa); end; aa=axis; xx=aa(1)+(aa(2)-aa(1))/20; yy=aa(4)-(aa(4)-aa(3))/5; cc=text(xx,yy,['(mean = ' num2str(fldmean) unit ')']); else; fprintf([myTitle '-- mean: ' num2str(fldmean) ' Sv\n']); end; elseif choicePlot==3|choicePlot==4;%time mean profile nr=length(z); kk=find(fld==0); if length(kk)>0; kk=[1:min(min(kk)+2,nr)]; else; kk=[1:nr]; end; myplot=plot(fld(kk),z(kk),'LineWidth',2); title(myTitle); set(gca,'FontSize',14); grid on; aa=axis; tmp1=max(abs(aa(1:2))); aa(1:2)=tmp1*[-1 1]; axis(aa); end; gcmfaces/gcmfaces_calc/gcmfaces_loc_tile.m0000644000435400001440000001121112273723570020543 0ustar gforgetusersfunction [varargout]=gcmfaces_loc_tile(ni,nj,varargin); %object : compute map of tile indices and (optional) associate % select location (1D vectors) with tile indices etc. %input : ni,nj is the MITgcm tile size (2 numbers total) % (optional) % AND XC,YC (vectors) % OR iTile, jTile, tileNo (vectors) % OR iTile, jTile, XC11, YC11, XCNINJ, YCNINJ (vectors) %where : % XC, YC are lon/lat of the grid point % tileNo is the grid point s tile number (assuming no blank tiles) % iTile, jTile is the grid point tile index % XC11, YC11 is lat/lon for the tile SE corner % XCNINJ, YCNINJ is lat/lon for the tile NW corner % %output : (nargin==2) tileNo is the map of tile numbers % (nargin >3) loc_tile incl. XC,YC, tileNo, XC11, YC11, XCNINJ, YCNINJ % %notes : - if XC, YC are provided as input, then loc_tile.XC, YC is nearest neighbor % - by assumption tile numbers increase from w to e (2nd dim), % then from s to n (1st dim), then with face number gcmfaces_global; global mytiles; loc_arrays={'XC','YC','XC11','YC11','XCNINJ','YCNINJ','iTile','jTile','tileNo'}; %1) check that tile arrays are up to date if isempty(mytiles); mytiles.dirGrid=mygrid.dirGrid; mytiles.nFaces=mygrid.nFaces; mytiles.fileFormat=mygrid.fileFormat; mytiles.ioSize=mygrid.ioSize; mytiles.ni=-1; mytiles.nj=-1; end; test1=strcmp(mytiles.dirGrid,mygrid.dirGrid)&(mytiles.nFaces==mygrid.nFaces)&... strcmp(mytiles.fileFormat,mygrid.fileFormat)&(sum(mytiles.ioSize~=mygrid.ioSize)==0); test2=(mytiles.ni==ni)&(mytiles.nj==nj); %2) update tile arrays if not up to date if ~test1|~test2; % mytiles.dirGrid=mygrid.dirGrid; mytiles.nFaces=mygrid.nFaces; mytiles.fileFormat=mygrid.fileFormat; mytiles.ioSize=mygrid.ioSize; % XC=mygrid.XC; YC=mygrid.YC; XC11=XC; YC11=XC; XCNINJ=XC; YCNINJ=XC; iTile=XC; jTile=XC; tileNo=XC; tileCount=0; for iF=1:XC11.nFaces; face_XC=XC{iF}; face_YC=YC{iF}; for ii=1:size(face_XC,1)/ni; for jj=1:size(face_XC,2)/nj; tileCount=tileCount+1; tmp_i=[1:ni]+ni*(ii-1); tmp_j=[1:nj]+nj*(jj-1); tmp_XC=face_XC(tmp_i,tmp_j); tmp_YC=face_YC(tmp_i,tmp_j); XC11{iF}(tmp_i,tmp_j)=tmp_XC(1,1); YC11{iF}(tmp_i,tmp_j)=tmp_YC(1,1); XCNINJ{iF}(tmp_i,tmp_j)=tmp_XC(end,end); YCNINJ{iF}(tmp_i,tmp_j)=tmp_YC(end,end); iTile{iF}(tmp_i,tmp_j)=[1:ni]'*ones(1,nj); jTile{iF}(tmp_i,tmp_j)=ones(ni,1)*[1:nj]; tileNo{iF}(tmp_i,tmp_j)=tileCount*ones(ni,nj); end; end; end; for iF=1:length(loc_arrays); eval(['mytiles.' loc_arrays{iF} '=convert2array(' loc_arrays{iF} ');']); eval(['clear ' loc_arrays{iF} ';']); end; end; %3) decide what is needed based on the number or arguments % (this needs to happen after mytiles is computed, since % I use the same variable names in that bloc and below) if nargin==2; %simply return mytiles as loc_tile tileNo=convert2array(mytiles.tileNo); varargout={tileNo}; return; elseif nargin==4; XC=varargin{1}; YC=varargin{2}; tmp1=find(XC>180); XC(tmp1)=XC(tmp1)-360; iTile=[]; jTile=[]; tileNo=[]; XC11=[]; YC11=[]; XCNINJ=[]; YCNINJ=[]; elseif nargin==5; XC=[]; YC=[]; iTile=varargin{1}; jTile=varargin{2}; tileNo=varargin{3}; XC11=[]; YC11=[]; XCNINJ=[]; YCNINJ=[]; elseif nargin==8; XC=[]; YC=[]; iTile=varargin{1}; jTile=varargin{2}; tileNo=[]; XC11=varargin{3}; YC11=varargin{4}; XCNINJ=varargin{5}; YCNINJ=varargin{6}; else; error('wrong argument list'); end; %3) find the grid points indices in array format if ~isempty(XC); %triangulate nearest neighbor tmp1=find(XC>180); XC(tmp1)=XC(tmp1)-360; ik=gcmfaces_bindata(XC,YC); else; %use mytiles as a look up table ik=zeros(size(iTile)); for ikk=1:length(iTile); if ~isempty(tileNo); tmp1=find(mytiles.iTile==iTile(ikk)&mytiles.jTile==jTile(ikk)&mytiles.tileNo==tileNo(ikk)); else; tmp1=find(mytiles.iTile==iTile(ikk)&mytiles.jTile==jTile(ikk)&... abs(mytiles.XC-XC(ikk))<1e-4&... abs(mytiles.YC-YC(ikk))<1e-4&... abs(mytiles.XC11-XC11(ikk))<1e-4&... abs(mytiles.YC11-YC11(ikk))<1e-4&... abs(mytiles.XCNINJ-XCNINJ(ikk))<1e-4&... abs(mytiles.YCNINJ-YCNINJ(ikk))<1e-4); end; if isempty(tmp1); error('grid point could not be identified from inputs'); end; ik(ikk)=tmp1(1); end; end; %4) complement location arrays and prepare output for iF=1:length(loc_arrays); eval(['loc_tile.' loc_arrays{iF} '=mytiles.' loc_arrays{iF} '(ik);']); end; %5) output result varargout={loc_tile}; gcmfaces/gcmfaces_calc/regrid_dblres.m0000644000435400001440000000163612030163460017725 0ustar gforgetusersfunction [P]=regrid_dblres(P,pType,nDblRes); %object : double the resolution (only along 3rd dimension for now) % for a variable P (extensive or intensive) a number of times. %input : P is the variable of interest % pType is 'extensive' or 'intensive' % nDblRes is the number of resolution doublings. %output : P is the input variable but with 2^nDblRes resolution gcmfaces_global; for ii=1:nDblRes; %start with repmat tmp1=repmat(P,[1 1 2]); nn=size(P{1},3); tmp1(:,:,1:2:2*nn)=P; tmp1(:,:,2:2:2*nn)=P; %interpolate (in grid point space) tmp2=NaN*tmp1; tmp2(:,:,2:2:2*nn-2)=3/4*P(:,:,1:nn-1)+1/4*P(:,:,2:nn); tmp2(:,:,3:2:2*nn-1)=1/4*P(:,:,1:nn-1)+3/4*P(:,:,2:nn); tmp1(~isnan(tmp2))=tmp2(~isnan(tmp2)); %if extensive then we want to conserve the sum over grid points if strcmp(pType,'extensive'); tmp1=tmp1/2; end; %overwite P P=tmp1; end; gcmfaces/gcmfaces_calc/calc_overturn.m0000644000435400001440000000431612274331426017773 0ustar gforgetusersfunction [FLD]=calc_overturn(fldU,fldV,doFlip,list_factors); %object: compute meridional overturning streamfunction %inputs: fldU and fldV are the fields of grid point transport %optional: doFlip (default is 1). If 1 then flip the vertical % axis back and forth, hence intergrating from the % 'bottom'. If 0 then dont. % list_factors (default is {'dh','dz'}) %output: FLD is the streamfunction % %notes: mygrid.LATS_MASKS is the set of quasi longitudinal lines along which % transports will integrated, as computed in gcmfaces_lines_zonal % the result is converted to Sv, and sign is changed. global mygrid; if nargin<3; doFlip=1; end; if nargin<4; list_factors={'dh','dz'}; end; %initialize output: n3=max(size(fldU.f1,3),1); n4=max(size(fldV.f1,4),1); FLD=NaN*squeeze(zeros(length(mygrid.LATS_MASKS),n3+1,n4)); %prepare fldU/fldV: fldU(isnan(fldU))=0; fldV(isnan(fldV))=0; dxg=mk3D(mygrid.DXG,fldU); dyg=mk3D(mygrid.DYG,fldU); if size(fldU.f1,3)==length(mygrid.DRF); drf=mk3D(mygrid.DRF,fldU); else; drf=fldU; drf(:)=1; end; facW=drf; facW(:)=1; facS=facW; for ii=1:length(list_factors); tmp1=list_factors{ii}; if strcmp(tmp1,'dh'); facW=facW.*dyg; facS=facS.*dxg; elseif strcmp(tmp1,'dz'); facW=facW.*drf; facS=facS.*drf; elseif strcmp(tmp1,'hfac'); facW=facW.*mygrid.hFacW; facS=facS.*mygrid.hFacS; elseif isempty(tmp1); 1; else; fprintf('error in calc_overturn : non supported factor\n'); return; end; end; for k4=1:n4; fldU(:,:,:,k4)=fldU(:,:,:,k4).*facW; fldV(:,:,:,k4)=fldV(:,:,:,k4).*facS; end; %use array format to speed up computation below: fldU=convert2array(fldU); fldV=convert2array(fldV); for iy=1:length(mygrid.LATS_MASKS); %get list ofpoints that form a zonal band: mskW=mygrid.LATS_MASKS(iy).mskWedge; vecW=gcmfaces_subset(mskW,fldU); mskS=mygrid.LATS_MASKS(iy).mskSedge; vecS=gcmfaces_subset(mskS,fldV); trsp=nansum(vecW,1)+nansum(vecS,1); %store: if doFlip; FLD(iy,1:n3,:)=flipdim(cumsum(flipdim(trsp,2),2),2); else; FLD(iy,2:n3+1,:)=cumsum(trsp,2); end; %convert to Sv and change sign: FLD(iy,:,:)=-1e-6*FLD(iy,:,:); end; if doFlip; FLD(:,end,:)=0; else; FLD(:,1,:)=0; end; gcmfaces/gcmfaces_calc/calc_bolus.m0000644000435400001440000000222112023427435017222 0ustar gforgetusersfunction [bolusU,bolusV,bolusW]=calc_bolus(GM_PsiX,GM_PsiY); %object: compute bolus velocty field (bolusU,bolusV,bolusW) % from gm streamfunction (GM_PsiX,GM_PsiY). %input: GM_PsiX,GM_PsiY %output: bolusU,bolusV,bolusW gcmfaces_global; nr=length(mygrid.RC); %compute bolus velocity: GM_PsiX(:,:,nr+1)=0*GM_PsiX(:,:,end); GM_PsiY(:,:,nr+1)=0*GM_PsiY(:,:,end); bolusU=0*mygrid.hFacW; bolusV=0*mygrid.hFacS; for k=1:nr; bolusU(:,:,k)=(GM_PsiX(:,:,k+1)-GM_PsiX(:,:,k))/mygrid.DRF(k); bolusV(:,:,k)=(GM_PsiY(:,:,k+1)-GM_PsiY(:,:,k))/mygrid.DRF(k); end; bolusU=bolusU.*(~isnan(mygrid.mskW)); bolusV=bolusV.*(~isnan(mygrid.mskS)); %and its vertical part % (seems correct, leading to 0 divergence) tmp_x=GM_PsiX(:,:,1:nr).*repmat(mygrid.DYG,[1 1 nr]); tmp_y=GM_PsiY(:,:,1:nr).*repmat(mygrid.DXG,[1 1 nr]); [tmp_x,tmp_y]=exch_UV(tmp_x,tmp_y); tmp_a=repmat(mygrid.RAC,[1 1 nr]); tmp_w=0*tmp_x; for iFace=1:mygrid.nFaces; tmp_w{iFace}=( tmp_x{iFace}(2:end,:,:)-tmp_x{iFace}(1:end-1,:,:) )+... ( tmp_y{iFace}(:,2:end,:)-tmp_y{iFace}(:,1:end-1,:) ); tmp_w{iFace}=tmp_w{iFace}./tmp_a{iFace}; end; bolusW=tmp_w.*(~isnan(mygrid.mskC)); gcmfaces/gcmfaces_calc/gcmfaces_subset.m0000644000435400001440000000213611626741400020255 0ustar gforgetusersfunction [vec]=gcmfaces_subset(msk,fld,applyMsk); %object: extract the subset of points from fld(.*msk) such that msk~=0 %inputs: msk is the gcmfaces subdomain mask (one vertical level) % fld is the complete field (gcmfaces or array version) %optional: applyMsk is a flag that stated whether to multiply with % msk (applyMsk==1; default) or not (applyMsk==0); %output: vec is the subset field % %note: - if fld is an array, then it must be a result of convert2array % - for velocity subsets, msk may be -1 or +1, depending on % directionality, e.g. when msk delineates a transport section. if isempty(whos('applyMsk')); applyMsk=1; end; if isa(fld,'gcmfaces'); fld=convert2array(fld); end; nn=size(fld); nn=[nn ones(1,4-length(nn))]; fld=reshape(fld,nn(1)*nn(2),nn(3)*nn(4)); msk=convert2vector(msk); ii=find(msk~=0&~isnan(msk)); mm=length(ii); if mm==0; vec=zeros(1,nn(3),nn(4)); else; if applyMsk; vec=fld(ii,:).*(msk(ii)*ones(1,nn(3)*nn(4))); else; vec=fld(ii,:); end; vec=reshape(vec,[mm nn(3) nn(4)]); end; gcmfaces/gcmfaces_calc/gcmfaces_lines_zonal.m0000644000435400001440000000164712057277271021304 0ustar gforgetusersfunction []=gcmfaces_lines_zonal(varargin); %object: define the set of quasi longitudinal lines % along which transports will integrated; % LATS_MASKS that will be added to mygrid. %optional input: % LATS_VAL is the latitudes vector ([-89:89]' by default) % MSKS_NAM is the list of fields to store in mygrid global mygrid; if nargin>0; LATS_VAL=varargin{1}; else; LATS_VAL=[-89:89]'; end; if nargin>1; MSKS_NAM=varargin{2}; else; MSKS_NAM={'mskCint','mskCedge','mskWedge','mskSedge'}; end; for iy=1:length(LATS_VAL); mskCint=1*(mygrid.YC>=LATS_VAL(iy)); [mskCedge,mskWedge,mskSedge]=gcmfaces_edge_mask(mskCint); for im=1:length(MSKS_NAM); eval(['tmp1.' MSKS_NAM{im} '=' MSKS_NAM{im} ';']); end; tmp1.lat=LATS_VAL(iy); %store: if iy==1; LATS_MASKS=tmp1; else; LATS_MASKS(iy)=tmp1; end; end; mygrid.LATS_MASKS=LATS_MASKS; gcmfaces/gcmfaces_calc/regrid_sum.m0000644000435400001440000000131412030163460017247 0ustar gforgetusersfunction [trP]=regrid_sum(P,tracer,trGrid); %object : add 3rd dimension elements of extensive variable P, % according to values of a tracer field collocated with P, % to the tracer grid defined by trGrid (1D vector) %input : P is the extensive variable of interest % tracer is the associated tracer field % trGrid is the vector of tracer values at % bins center of the tracer grid bins. %output : trP is the counterpart to P on the tracer grid trP=NaN*repmat(P(:,:,1),[1 1 length(trGrid)-1]); trBounds=[-Inf (trGrid(1:end-1)+trGrid(2:end))/2 Inf]; for kk=1:length(trGrid); tmp1=P.*(tracer>=trBounds(kk)).*(tracer3; doNearFill=varargin{1}; else; doNearFill=1; end; %switch longitude range to -180+180 or 0-360 according to grid if max(mygrid.XC)<0; lon(find(lon>180))=lon(find(lon>180))-360; end; if max(mygrid.XC)>180; lon(find(lon<0))=lon(find(lon<0))+360; end; %do the actual interpolation if ~myenv.useDelaunayTri;%(code from old griddata.m) % Find the nearest triangle (t) x=convert2array(mygrid.XC); x=x(mytri.kk); y=convert2array(mygrid.YC); y=y(mytri.kk); VEC=convert2array(fld); VEC=VEC(mytri.kk); t = tsearch(x,y,mytri.TRI,lon',lat')';%the order of dims matters!! % Only keep the relevant triangles. out = find(isnan(t)); if ~isempty(out), t(out) = ones(size(out)); end tri = mytri.TRI(t(:),:); % Compute Barycentric coordinates (w). P. 78 in Watson. del = (x(tri(:,2))-x(tri(:,1))) .* (y(tri(:,3))-y(tri(:,1))) - ... (x(tri(:,3))-x(tri(:,1))) .* (y(tri(:,2))-y(tri(:,1))); w(:,3) = ((x(tri(:,1))-lon(:)).*(y(tri(:,2))-lat(:)) - ... (x(tri(:,2))-lon(:)).*(y(tri(:,1))-lat(:))) ./ del; w(:,2) = ((x(tri(:,3))-lon(:)).*(y(tri(:,1))-lat(:)) - ... (x(tri(:,1))-lon(:)).*(y(tri(:,3))-lat(:))) ./ del; w(:,1) = ((x(tri(:,2))-lon(:)).*(y(tri(:,3))-lat(:)) - ... (x(tri(:,3))-lon(:)).*(y(tri(:,2))-lat(:))) ./ del; val = sum(VEC(tri) .* w,2); val(out)=NaN; val=reshape(val,size(lon)); else;%(use TriScatteredInterp) %get interpolant VEC=convert2array(fld); VEC=VEC(mytri.kk); F = TriScatteredInterp(mytri.TRI, VEC); %do interpolation val=F(lon,lat); end; if doNearFill;%use the nearest neighbor to complement linear interp kk=gcmfaces_bindata(lon(:),lat(:)); ARR=convert2array(fld); val2=ARR(kk); val(isnan(val))=val2(isnan(val)); end; gcmfaces/gcmfaces_calc/calc_T_grad.m0000644000435400001440000000324411600767236017312 0ustar gforgetusersfunction [varargout]=calc_T_grad(fld,putGradOnTpoints); %object: compute horizontal gradients %inputs: fld is the 'tracer' field of interest % putGradOnTpoints states wherther to return the gradients % at velocity points (0) or on tracer points (1) %output: [dFLDdx,dFLDdy] are the gradient fields %optional: [...,dFLDdxdx,dFLDdydy] are the second order % derivatives at tracer points. global mygrid; msk=fld; msk(~isnan(fld))=1; FLD=exch_T_N(fld); dFLDdx=fld; dFLDdy=fld; for iF=1:FLD.nFaces; tmpA=FLD{iF}(2:end-1,2:end-1); tmpB=FLD{iF}(1:end-2,2:end-1); dFLDdx{iF}=(tmpA-tmpB)./mygrid.DXC{iF}; tmpA=FLD{iF}(2:end-1,2:end-1); tmpB=FLD{iF}(2:end-1,1:end-2); dFLDdy{iF}=(tmpA-tmpB)./mygrid.DYC{iF}; end; if nargout>2; %compute second order derivatives [DX,DY]=exch_UV(dFLDdx,dFLDdy); dFLDdxdx=fld; dFLDdydy=fld; dFLDdxdy=fld; dFLDdydx=fld; for iF=1:FLD.nFaces; tmpA=DX{iF}(2:end,:); tmpB=DX{iF}(1:end-1,:); dFLDdxdx{iF}=(tmpA-tmpB)./mygrid.DXF{iF}; tmpA=DY{iF}(:,2:end); tmpB=DY{iF}(:,1:end-1); dFLDdydy{iF}=(tmpA-tmpB)./mygrid.DYF{iF}; end; end; if putGradOnTpoints; dFLDdx(isnan(dFLDdx))=0; dFLDdy(isnan(dFLDdy))=0; dFLDdx0=dFLDdx; dFLDdy0=dFLDdy; [dFLDdx,dFLDdy]=exch_UV(dFLDdx,dFLDdy); for iF=1:FLD.nFaces; dFLDdx{iF}=0.5*(dFLDdx{iF}(1:end-1,:)+dFLDdx{iF}(2:end,:)); dFLDdy{iF}=0.5*(dFLDdy{iF}(:,1:end-1)+dFLDdy{iF}(:,2:end)); end; dFLDdx=dFLDdx.*msk; dFLDdy=dFLDdy.*msk; %remakr: dFLDdxdx and dFLDdydy are on T points already end; varargout{1}=dFLDdx; varargout{2}=dFLDdy; if nargout>2; varargout{3}=dFLDdxdx; varargout{4}=dFLDdydy; end; gcmfaces/gcmfaces_calc/gcmfaces_remap_3d.m0000644000435400001440000000615112061752135020444 0ustar gforgetusersfunction [fldOut]=gcmfaces_remap_3d(lon,lat,depIn,fldIn,nDblRes); %object: use bin average to remap a lat-lon-depth field to mygrid.mskC %input: lon,lat,dep,fld are the gridded product arrays (2D,2D,1D,3D) %assumption:fld should show NaN for missing values gcmfaces_global; %initiate triangulation: gcmfaces_bindata; %vertical levels: nrIn=length(depIn); depOut=-mygrid.RC; nrOut=length(depOut); if isempty(whos('nDblRes')); nDblRes=3; end; %corresponding model mask: chosen to avoid vertical extrapolation later % 1) from model just above mskC=repmat(0*mygrid.XC,[1 1 nrIn]); KK2=zeros(1,nrIn); for kk=1:nrIn; kk2=max(find(depOut<=depIn(kk)));%model level just above if isempty(kk2); kk2=1; end;%pathological case KK2(kk)=kk2; mskC(:,:,kk)=mygrid.mskC(:,:,kk2); end; % 2) shift to above atlas level mask for kk=nrIn:-1:2; mskC(:,:,kk)=mskC(:,:,kk-1);%atlas level just above end; %test vertical interpolation to mygrid.RC of the mask: % => the printed result should be 0 if 0; mskCout=atlas_interp_vert(mskC,depIn,depOut); aa=convert2gcmfaces(isnan(mskCout)&~isnan(mygrid.mskC)); nansum(aa(:)) end; %horizontal mapping to mygrid.XC, mygrid.YC, mskC: fld1=mskC; tocs=[]; for kk=1:nrIn; tic; fld1(:,:,kk)=gcmfaces_remap_2d(lon,lat,fldIn(:,:,kk),nDblRes,mskC(:,:,kk)); tocs=[tocs;toc]; [kk nrIn mean(tocs)] end; %vertical interpolation to mygrid.RC fld2=atlas_interp_vert(fld1,depIn,depOut); %final mask handling: %1) remask with mygrid.mskC (mskC was wider by design) msk1=mygrid.mskC; tmp1=msk1.*fld2; %2) extrapolate vertically (some deep canions may still miss data) fldOut=atlas_extrap_vert(tmp1,msk1,depOut); function [fldOut]=atlas_interp_vert(fldIn,depthIn,depthOut); %vertical interpolation gcmfaces_global; nrIn=length(depthIn); nrOut=length(depthOut); %map depthIn to depthOut: coeff=interp1(depthIn,[1:nrIn],depthOut); tmp1=find(isnan(coeff)); coeff(tmp1)=nrIn-0.01; %quick fix %vertical interpolation to mygrid.RC: fldOut=repmat(0*mygrid.XC,[1 1 nrOut]); for kk=1:nrOut; tmp1=coeff(kk); tmp2=floor(tmp1); tmp1=tmp1-tmp2; if tmp2==nrIn; tmp3=fldIn(:,:,tmp2); else; tmp3=(1-tmp1)*fldIn(:,:,tmp2)+tmp1*fldIn(:,:,tmp2+1); end; fldOut(:,:,kk)=tmp3; end; function [fldOut]=atlas_extrap_vert(fldIn,mskOut,depthIn); %vertical extrapolation when needed fldOut=convert2array(fldIn); mskOut=convert2array(mskOut); nrIn=length(depthIn); for kk=2:nrIn; tmp_kk=fldOut(:,:,kk); msk_kk=mskOut(:,:,kk); [II,JJ]=find(isnan(tmp_kk)&~isnan(msk_kk)); if ~isempty(II)&kk==2; tmp_kkM1=fldOut(:,:,kk-1); tmp1=find(isnan(tmp_kk)&~isnan(msk_kk)&~isnan(tmp_kkM1)); tmp_kk(tmp1)=tmp_kkM1(tmp1); fldOut(:,:,kk)=tmp_kk; elseif ~isempty(II); tmp_kkM1=fldOut(:,:,kk-1); tmp_kkM2=fldOut(:,:,kk-2); coeff=(depthIn(kk)-depthIn(kk-1))/(depthIn(kk-1)-depthIn(kk-2)); tmp_kk_x=tmp_kkM1+coeff*(tmp_kkM1-tmp_kkM2); tmp1=find(isnan(tmp_kk)&~isnan(msk_kk)&~isnan(tmp_kk_x)); tmp_kk(tmp1)=tmp_kk_x(tmp1); fldOut(:,:,kk)=tmp_kk; end; end; fldOut=convert2array(fldOut); gcmfaces/gcmfaces_calc/calc_MeridionalTransport.m0000644000435400001440000000314711626741400022105 0ustar gforgetusersfunction [FLD]=calc_MeridionalTransport(fldU,fldV,varargin); %object: compute net meridional transports of e.g. heat or fresh water %inputs: fldU and fldV are the fields of grid point transport %optional: doScaleWithArea, if 1 then multiply fldU by % dyg.*drf and accordingly for fldV. % If 0 (default) then it is assumed that those factors % have already been included (e.g. by pkg/diagnostics). %output: FLD is the integrated transport vector (one point per latitude). % %notes: mygrid.LATS_MASKS is the set of quasi longitudinal lines along which % transports will integrated, as computed in gcmfaces_lines_zonal global mygrid; if nargin==3; doScaleWithArea=varargin{1}; else; doScaleWithArea=0; end; %initialize output: n3=max(size(fldU.f1,3),1); n4=max(size(fldV.f1,4),1); FLD=NaN*squeeze(zeros(length(mygrid.LATS_MASKS),n4)); %prepare fldU/fldV: fldU(isnan(fldU))=0; fldV(isnan(fldV))=0; if doScaleWithArea; dxg=mk3D(mygrid.DXG,fldU); dyg=mk3D(mygrid.DYG,fldU); drf=mk3D(mygrid.DRF,fldU); for k4=1:n4; fldU(:,:,:,k4)=fldU(:,:,:,k4).*dyg.*drf; fldV(:,:,:,k4)=fldV(:,:,:,k4).*dxg.*drf; end; end; %use array format to speed up computation below: fldU=convert2array(fldU); fldV=convert2array(fldV); for iy=1:length(mygrid.LATS_MASKS); %get list ofpoints that form a zonal band: mskW=mygrid.LATS_MASKS(iy).mskWedge; vecW=gcmfaces_subset(mskW,fldU); mskS=mygrid.LATS_MASKS(iy).mskSedge; vecS=gcmfaces_subset(mskS,fldV); %store vertically integrated transport: FLD(iy,:)=nansum(nansum(vecW,1)+nansum(vecS,1),2); end; gcmfaces/gcmfaces_calc/gcmfaces_close_basin.m0000644000435400001440000001365312076314746021250 0ustar gforgetusersfunction [msk]=gcmfaces_close_basin(basinEdge,landMsk,doLargerBasin); %object : compute closed basin mask from a specificed edge and a "land" mask % By design basinEdge is required to split the global ocean into two and % only two basins. Successive calls allow for numerous basin definitions. % %input : - basinEdge is an index (standard cases; defined by great circle arcs % between pairs of locations; see below) or a 2D map (interactive case) % - test cases : basinEdge = 0 to -3 (included hereafter) % - user cases : basinEdge > 0 (for user to add hereafter) % - interactive case : basinEdge is a 2D map of 1s and NaNs % where NaNs delineate the "wet" egde of the basin. % - landMsk is the "land" mask (1s & NaNs; mygrid.mskC(:,:,1) default) % basinEdge values where landMsk is NaN are of no consequence. % - doLargerBasin is 0 (default) or 1. If set to 1 then output % larger basin mask, otherwise output smaller basin mask. The ocean % edge points are always counted as part of the output basin mask. % %output : msk is the closed basin mask, with 1s over the basin of interest, % 0s over the rest of the ocean, and NaNs consistent with landMsk. % %notes : - unless used in interactive mode the ocean basin edge is based on % great circle arcs. That is usually perfectly adequate. The most % notable exception is when one wants to delimit a basin by latitude lines, % but those are easy to do in interactive mode. The NOT implemented general % approach would use small circle arcs rather than great circle arcs. % - the test cases below demonstrate the algorithm using great circles (0), % the algorithm error cases (-1, -2) and the limitation of great circles (-3) gcmfaces_global; if isempty(whos('basinEdge')); basinEdge=0; end; if isempty(whos('landMsk')); landMsk=mygrid.mskC(:,:,1); end; if isempty(whos('doLargerBasin')); doLargerBasin=0; end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%BEGINING OF EDGE DEFINITION%%%%%%%%%%%%%%%%%%%%%%%%%%% if isnumeric(basinEdge)&length(basinEdge(:))==1; %standard cases: to be extended by user if basinEdge==0; lonPairs=[[ 10 19];[ 19 60];[ 60 100];[ 100 110]]; latPairs=[[ 60 80];[ 80 81];[ 81 80];[ 80 60]]; %a case that matches v4_basin_one elseif basinEdge==-1; lonPairs=[[ -70 20];[ 20 110];[ 110 200];[ 200 -70]]; latPairs=[[ -30 -30];[ -30 -30];[ -30 -30];[ -30 -30]]; %a case that fails because it delimits three basins elseif basinEdge==-2; lonPairs=[[ -70 20];[ 20 145]]; latPairs=[[ -35 -35];[ -35 -35]]; %a case that fails because it does not close basins elseif basinEdge==-3; lonPairs=[[ -70 20];[ 20 145];[ 145 -70]]; latPairs=[[ -35 -35];[ -35 -35];[ -35 -35]]; %a case that does not fail, but illustrates that long great %circle arcs are not always the most appopriate basin edges %(a line of constant latitude would be better in this case) else; error('unknown basin'); end; %close basin: msk=landMsk; msk0=msk; for iy=1:size(lonPairs,1); %define great circle line by end points: lonPair=lonPairs(iy,:); latPair=latPairs(iy,:); %get line: line_cur=gcmfaces_lines_transp(lonPair,latPair,{'tmp'}); %close line: msk(line_cur.mskCedge==1)=NaN; end; else; %interactive cases: based on field provided by user msk=landMsk; msk0=msk; msk(isnan(basinEdge))=NaN; end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%END OF EDGE DEFINITION%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %compute the closed basin labels for each grid face: msk1=msk; msk=1*~isnan(msk); for iF=1:msk.nFaces; msk{iF}=bwlabel(msk{iF},4); end; %remove potential aliases / account for domain periodicity: msk2=msk; test0=1;%do at least one faces sweep while test0; test0=0;%unless something changes in the upcoming sweep we will stop tmpmsk=exch_T_N(msk); %list aliases list0=[]; for iF=1:msk.nFaces; for iS=1:4; tmp1=msk{iF}; if iS==1; tmp2=tmpmsk{iF}(1:end-2,2:end-1); elseif iS==2; tmp2=tmpmsk{iF}(3:end,2:end-1); elseif iS==3; tmp2=tmpmsk{iF}(2:end-1,1:end-2); elseif iS==4; tmp2=tmpmsk{iF}(2:end-1,3:end); end; tmp3=find( (tmp1~=tmp2)&(tmp1>0)&(tmp2~=0)); %note : tmp1~=tmp2 is an alias if the two other conditions apply %note : "land" (label 0) is not an alias (tmp1>0&tmp2~=0 test) %note : basins cannot be relabeld multiple times (tmp1>0 test) but % relabeld basins can be tested against (tmp2~=0 rather than tmp2>0) list0=[list0;[tmp1(tmp3) tmp2(tmp3) iF+0*tmp3]]; end; end; %not needed : list0=unique(list0,'rows'); if ~isempty(list0); %start with previously relabeld basin if any (needed to avoid conflicts) ii=find(list0(:,2)==min(list0(:,2))); ii=ii(1); iF=list0(ii,3); list1=list0(ii,1:2); tmp1=msk{iF}; %since we will have relabeld at least one basin in this %faces sweep, then another faces sweep will be needed : test0=1; %apply unique negative label if list1(2)<0; %carry over unique label from previously relabeld basin tmp4=list1(2); else; %define new unique negative label tmp4=min(min(msk)-1,-1); end; tmp1(tmp1==list1(1))=tmp4; msk{iF}=tmp1; end; end; %final list should have 2 elements (1 per basin) list2=convert2array(msk); list2=unique(list2(:)); list2=list2(find(~isnan(list2)&list2~=0)); if length(list2)<2; msk=msk1; fprintf('failure : basin was not closed properly\n'); return; end; if length(list2)>2; fprintf('failure : more than two basins\n'); return; end; %attribute edge and prepare output: tmp1=sum(mygrid.RAC.*(msk==list2(1))); tmp2=sum(mygrid.RAC.*(msk==list2(2))); if doLargerBasin&tmp1>=tmp2; excl=list2(2); elseif doLargerBasin ; excl=list2(1); elseif tmp1<=tmp2; excl=list2(2); else ; excl=list2(1); end; msk3=msk; msk=(msk~=excl).*mygrid.mskC(:,:,1); gcmfaces/gcmfaces_calc/calc_budget_mean_zonal.m0000644000435400001440000000351712072655011021561 0ustar gforgetusersfunction [budg,area]=calc_budget_mean_zonal(cont,zconv,hconv); %object : compute budget of cont=zconv+hconv, on average over latitute bands %input : cont is the time derivative of the content (e.g. d/dt[T*drf]; per m2) % zconv is the convergence of vertical fluxes (e.g. TFLUX; per m2) % hconv is the convergence of advective and diffusive fluxes (per grid cell) %output : budg is the vector of the 3 terms mean, over each latitude band % area is the vector of each latitude band %note : for a closed budget you expect 0~(contTot-hconvTot-zconvTot)/contTot gcmfaces_global; warning('off','MATLAB:divideByZero'); nl=length(mygrid.LATS); budg=zeros(3,nl); area=zeros(1,nl); for il=1:nl; if il>1&il=tmpMin&mygrid.YC0; budg(:,il)=[tmpcont;tmphconv;tmpzconv]; area(1,il)=tmparea; else; budg(:,il)=[0;0;0]; area(1,il)=0; end; %to check the results: if 0; (contTot-hconvTot-zconvTot)/contTot; end; end; budg(isnan(budg))=0; warning('on','MATLAB:divideByZero'); gcmfaces/gcmfaces_calc/gcmfaces_section.m0000644000435400001440000000407412367515675020437 0ustar gforgetusersfunction [LO,LA,FLD,X,Y]=gcmfaces_section(lons,lats,fld,varargin); %purpose: extract a great circle section (defined by two points) from a field % or a latitude circle (defined by one latitude) % %inputs: lons/lats are the longitude/latitude vector % fld is the gcmfaces field (can incl. depth/time dimensions) %optional: sortByLon to sort point by longitude (default = 0 -> sort by latgitude) %outputs: LO/LA is the vector of grid points longitude/latitude % FLD is the vector/matrix of grid point values (from fld) if nargin>3; sortByLon=varargin{1}; else; sortByLon=0; end; global mygrid; if length(lats)==2; line_cur=gcmfaces_lines_transp(lons,lats,{'tmp'}); elseif length(lats)==1; tmp1=abs(mygrid.LATS-lats); tmp2=find(tmp1==min(tmp1)); tmp2=tmp2(1); line_cur=mygrid.LATS_MASKS(tmp2); else; error('wrong specification of lons,lats'); end; secP=find(line_cur.mskCedge==1); secN=length(secP); %lon/lat vectors: LO=zeros(secN,1); LA=zeros(secN,1); %sections: n3=max(size(fld{1},3),1); n4=max(size(fld{1},4),1); FLD=zeros(secN,n3,n4); %counter: ii0=0; for ff=1:secP.nFaces; tmp0=secP{ff}; [tmpI,tmpJ]=ind2sub(size(mygrid.XC{ff}),tmp0); tmp1=mygrid.XC{ff}; for ii=1:length(tmpI); LO(ii+ii0)=tmp1(tmpI(ii),tmpJ(ii)); end; tmp1=mygrid.YC{ff}; for ii=1:length(tmpI); LA(ii+ii0)=tmp1(tmpI(ii),tmpJ(ii)); end; tmp1=fld{ff}; for ii=1:length(tmpI); FLD(ii+ii0,:,:)=squeeze(tmp1(tmpI(ii),tmpJ(ii),:,:)); end; ii0=ii0+length(tmpI); end; %sort according to increasing latitude or longitude: if sortByLon; [tmp1,ii]=sort(LO); %sort according to increasing longitude else; [tmp1,ii]=sort(LA); %sort according to increasing latitude end; LO=LO(ii); LA=LA(ii); FLD=FLD(ii,:,:); %output axes for ploting with pcolor nr=length(mygrid.RC); nx=length(LO); X=[]; Y=[]; if size(FLD,2)==nr&sortByLon; X=LO'*ones(1,nr); Y=ones(nx,1)*mygrid.RC'; elseif size(FLD,2)==nr&~sortByLon; X=LA'*ones(1,nr); Y=ones(nx,1)*mygrid.RC'; elseif size(FLD,1)==nr&sortByLon; X=LO'; Y=ones(nx,1); elseif size(FLD,2)==1&~sortByLon; X=LA'; Y=ones(nx,1); end; gcmfaces/gcmfaces_calc/calc_UEVNfromUXVY.m0000644000435400001440000000155711600767236020314 0ustar gforgetusersfunction [fldUe,fldVn]=calc_UEVNfromUXVY(fldU,fldV); %object: compute Eastward/Northward vectors form X/Y vectors %inputs: fldU/fldV are the X/Y vector fields at velocity points %outputs: fldUe/fldVn are the Eastward/Northward vectors at tracer points global mygrid; %fldU(mygrid.hFacW==0)=NaN; fldV(mygrid.hFacS==0)=NaN; nr=size(fldU.f1,3); fldU(mygrid.hFacW(:,:,1:nr)==0)=NaN; fldV(mygrid.hFacS(:,:,1:nr)==0)=NaN; [FLDU,FLDV]=exch_UV(fldU,fldV); fldUe=fldU; fldVn=fldV; for iF=1:fldU.nFaces; tmp1=FLDU{iF}(1:end-1,:,:); tmp2=FLDU{iF}(2:end,:,:); fldUe{iF}=reshape(nanmean([tmp1(:) tmp2(:)],2),size(tmp1)); tmp1=FLDV{iF}(:,1:end-1,:); tmp2=FLDV{iF}(:,2:end,:); fldVn{iF}=reshape(nanmean([tmp1(:) tmp2(:)],2),size(tmp1)); end; FLDU=fldUe; FLDV=fldVn; cs=mk3D(mygrid.AngleCS,FLDU); sn=mk3D(mygrid.AngleSN,FLDU); fldUe=+FLDU.*cs-FLDV.*sn; fldVn=FLDU.*sn+FLDV.*cs; gcmfaces/gcmfaces_calc/calc_UV_conv.m0000644000435400001440000000377612274331426017477 0ustar gforgetusersfunction [fldDIV]=calc_UV_conv(fldU,fldV,varargin); %object: compute flow field convergent part (i.e. minus the divergence) %inputs: fldU and fldV are transport or velocity fields %optional: list_factors is the list of factors that need to % be applied to fldU,fldV. By default it is empty (i.e. {}). % The most complete list would be {'dh','dz','hfac'}. %output: fldDIV is the convergence (integrated, not averaged, over grid cell area) % %notes: fldU,fldV that may be % either [A] a 3D vector field % or [B] a 2D vector field % % in case [A], layer thicknesses = mygrid.DRF; in case [B] layer thickness = 1 % in any case, the global variable mygrid is supposed to be available global mygrid; %initialize output: n3=max(size(fldU.f1,3),1); n4=max(size(fldV.f1,4),1); %prepare fldU/fldV: fldU(isnan(fldU))=0; fldV(isnan(fldV))=0; %if nargin==3; list_factors=varargin; else; list_factors={'dh','dz','hfac'}; end; if nargin==3; list_factors=varargin{1}; else; list_factors={}; end; dxg=mk3D(mygrid.DXG,fldU); dyg=mk3D(mygrid.DYG,fldU); if size(fldU.f1,3)==length(mygrid.DRF); drf=mk3D(mygrid.DRF,fldU); elseif size(fldU.f1,3)==1; drf=fldU; drf(:)=1; else; error('error in calc_UV_conv: non supported field size\n'); end; facW=drf; facW(:)=1; facS=facW; for ii=1:length(list_factors); tmp1=list_factors{ii}; if strcmp(tmp1,'dh'); facW=facW.*dyg; facS=facS.*dxg; elseif strcmp(tmp1,'dz'); facW=facW.*drf; facS=facS.*drf; elseif strcmp(tmp1,'hfac'); facW=facW.*mygrid.hFacW; facS=facS.*mygrid.hFacS; elseif isempty(tmp1); 1; else; fprintf('error in calc_UV_conv: non supported factor\n'); return; end; end; for k4=1:n4; fldU(:,:,:,k4)=fldU(:,:,:,k4).*facW; fldV(:,:,:,k4)=fldV(:,:,:,k4).*facS; end; [FLDU,FLDV]=exch_UV(fldU,fldV); FLDU(isnan(FLDU))=0; FLDV(isnan(FLDV))=0; fldDIV=fldU; for iFace=1:fldDIV.nFaces; fldDIV{iFace}=FLDU{iFace}(1:end-1,:,:,:)-FLDU{iFace}(2:end,:,:,:)+... FLDV{iFace}(:,1:end-1,:,:)-FLDV{iFace}(:,2:end,:,:); end; gcmfaces/gcmfaces_calc/calc_transports.m0000644000435400001440000000370612274331426020330 0ustar gforgetusersfunction [FLD]=calc_transports(fldU,fldV,SECTIONS_MASKS,list_factors); %object: compute transports through pre-defined sections %inputs: fldU and fldV are the fields of grid point transport % SECTIONS_MASKS is the set of sections along % which transports will integrated (SECTIONS_MASKS should % have been produced by line_greatC_TUV_mask.m) %optional: list_factors is the list of factors that need to % be applied to fldU,fldV. By default it is empty (i.e. {}). % The most complete list would be {'dh','dz','hfac'}. %output: FLD is the array of transport profiles global mygrid; %initialize output: n3=max(size(fldU.f1,3),1); n4=max(size(fldV.f1,4),1); FLD=NaN*squeeze(zeros(length(SECTIONS_MASKS),n3,n4)); %prepare fldU/fldV: fldU(isnan(fldU))=0; fldV(isnan(fldV))=0; if isempty(who('list_factors')); list_factors={}; end; if sum(strcmp(list_factors,'dh'))>0; dxg=mk3D(mygrid.DXG,fldU); dyg=mk3D(mygrid.DYG,fldU); else; dxg=1; dyg=1; end; if sum(strcmp(list_factors,'dz'))>0; drf=mk3D(mygrid.DRF,fldU); else; drf=1; end; facW=1; facS=1; for ii=1:length(list_factors); tmp1=list_factors{ii}; if strcmp(tmp1,'dh'); facW=facW.*dyg; facS=facS.*dxg; elseif strcmp(tmp1,'dz'); facW=facW.*drf; facS=facS.*drf; elseif strcmp(tmp1,'hfac'); facW=facW.*mygrid.hFacW; facS=facS.*mygrid.hFacS; elseif isempty(tmp1); 1; else; fprintf('error in calc_transports : non supported factor\n'); return; end; end; for k4=1:n4; fldU(:,:,:,k4)=fldU(:,:,:,k4).*facW; fldV(:,:,:,k4)=fldV(:,:,:,k4).*facS; end; %use array format to speed up computation below: fldU=convert2array(fldU); fldV=convert2array(fldV); for iy=1:length(SECTIONS_MASKS); %get list ofpoints that form a zonal band: mskW=SECTIONS_MASKS(iy).mskWedge; vecW=gcmfaces_subset(mskW,fldU); mskS=SECTIONS_MASKS(iy).mskSedge; vecS=gcmfaces_subset(mskS,fldV); %store: FLD(iy,:)=nansum(vecW,1)+nansum(vecS,1); end; gcmfaces/gcmfaces_calc/gcmfaces_edge_mask.m0000644000435400001440000000224211626741400020665 0ustar gforgetusersfunction [mskCedge,mskWedge,mskSedge]=gcmfaces_edge_mask(mskCint); %object: computes the edge mask corresponding with % an ocean basin interior mask %inputs: mskCint is the 0/1 mask defining an ocean basin interior %outputs: mskCedge is the tracer edge mask (1 point outside interior) % mskWedge/mskSedge is the U/V velocity mask (1 for entering % flow, -1 for exiting flow, and 0 otherwise) gcmfaces_global; %treat the case of blank tiles: mskCint(mygrid.RAC==0)=NaN; %add one point at edges: mskCplus=exch_T_N(mskCint); %edge tracer mask: mskCedge=mskCint; for iF=1:mskCint.nFaces; tmp1=mskCplus{iF}; tmp2=tmp1(2:end-1,1:end-2)+tmp1(2:end-1,3:end)... +tmp1(1:end-2,2:end-1)+tmp1(3:end,2:end-1); mskCedge{iF}=1*(tmp2>0&tmp1(2:end-1,2:end-1)==0); end; %edge velocity mask: mskWedge=mskCint; mskSedge=mskCint; for iF=1:mskCplus.nFaces; mskWedge{iF}=mskCplus{iF}(2:end-1,2:end-1) - mskCplus{iF}(1:end-2,2:end-1); mskSedge{iF}=mskCplus{iF}(2:end-1,2:end-1) - mskCplus{iF}(2:end-1,1:end-2); end; %treat the case of blank tiles: mskCedge(isnan(mskCedge))=0; mskWedge(isnan(mskWedge))=0; mskSedge(isnan(mskSedge))=0; gcmfaces/gcmfaces_calc/gcmfaces_lines_transp.m0000644000435400001440000001015312134046056021447 0ustar gforgetusersfunction [line_out]=gcmfaces_lines_transp(varargin); %object: compute geat circle transport lines, defined % by pair of coordinates, for use in calc_transports %inputs: lonPairs (e.g. [-68 -63] by default) is the pair of longitudes % latPairs (e.g. [-54 -66] by default) is the pair of latgitudes % names (e.g. {'Drake Passage'} by default) is the transport line name %output: (optional) line_out is a strcuture with the following fields % lonPair, latPair, name, mskCedge, mskWedge, mskSedge % If no output is specified then line_out is copied to % mygrid (global variable) as 'mygrid.LINES_MASKS' global mygrid; if nargin>0; lonPairs=varargin{1}; latPairs=varargin{2}; names=varargin{3}; else; lonPairs=[-68 -63]; latPairs=[-54 -66]; names={'Drake Passage'}; end; for iy=1:length(names); lonPair=lonPairs(iy,:); latPair=latPairs(iy,:); name=names{iy}; %get carthesian coordinates: %... of grid lon=mygrid.XC; lat=mygrid.YC; x=cos(lat*pi/180).*cos(lon*pi/180); y=cos(lat*pi/180).*sin(lon*pi/180); z=sin(lat*pi/180); %... and of end points x0=cos(latPair*pi/180).*cos(lonPair*pi/180); y0=cos(latPair*pi/180).*sin(lonPair*pi/180); z0=sin(latPair*pi/180); %get the rotation matrix: %1) rotate around x axis to put first point at z=0 theta=atan2(-z0(1),y0(1)); R1=[[1;0;0] [0;cos(theta);sin(theta)] [0;-sin(theta);cos(theta)]]; tmp0=[x0;y0;z0]; tmp1=R1*tmp0; x1=tmp1(1,:); y1=tmp1(2,:); z1=tmp1(3,:); x0=x1; y0=y1; z0=z1; %2) rotate around z axis to put first point at y=0 theta=atan2(x0(1),y0(1)); R2=[[cos(theta);sin(theta);0] [-sin(theta);cos(theta);0] [0;0;1]]; tmp0=[x0;y0;z0]; tmp1=R2*tmp0; x1=tmp1(1,:); y1=tmp1(2,:); z1=tmp1(3,:); x0=x1; y0=y1; z0=z1; %3) rotate around y axis to put second point at z=0 theta=atan2(-z0(2),-x0(2)); R3=[[cos(theta);0;-sin(theta)] [0;1;0] [sin(theta);0;cos(theta)]]; tmp0=[x0;y0;z0]; tmp1=R3*tmp0; x1=tmp1(1,:); y1=tmp1(2,:); z1=tmp1(3,:); x0=x1; y0=y1; z0=z1; %apply rotation to grid: tmpx=convert2array(x); tmpy=convert2array(y); tmpz=convert2array(z); tmp1=find(~isnan(tmpx)); tmpx2=tmpx(tmp1); tmpy2=tmpy(tmp1); tmpz2=tmpz(tmp1); tmp2=[tmpx2';tmpy2';tmpz2']; tmp3=R3*R2*R1*tmp2; tmpx2=tmp3(1,:); tmpy2=tmp3(2,:); tmpz2=tmp3(3,:); tmpx(tmp1)=tmpx2; tmpy(tmp1)=tmpy2; tmpz(tmp1)=tmpz2; x=convert2array(tmpx); y=convert2array(tmpy); z=convert2array(tmpz); %compute the great circle mask: mskCint=1*(z>0); [mskCedge,mskWedge,mskSedge]=gcmfaces_edge_mask(mskCint); %select the shorther segment: for kk=1:3; %select field to treat: switch kk; case 1; mm=mskCedge; case 2; mm=mskWedge; case 3; mm=mskSedge; end; %split in two segments: theta=[]; theta(1)=atan2(y0(1),x0(1)); theta(2)=atan2(y0(2),x0(2)); tmpx=convert2array(x); tmpy=convert2array(y); tmpz=convert2array(z); tmptheta=atan2(tmpy,tmpx); tmpm=convert2array(mm); if theta(2)<0; tmp00=find(tmptheta<=theta(2)); tmptheta(tmp00)=tmptheta(tmp00)+2*pi; theta(2)=theta(2)+2*pi; end; %select the shorther segment: if theta(2)-theta(1)<=pi; tmpm(find(tmptheta>theta(2)|tmptheta=theta(1)))=NaN; end; mm=convert2array(tmpm); %store result: switch kk; case 1; mskCedge=mm; case 2; mskWedge=mm; case 3; mskSedge=mm; end; end; %store so-defined line: line_cur=struct('lonPair',lonPair,'latPair',latPair,'name',name,... 'mskCedge',mskCedge,'mskWedge',mskWedge,'mskSedge',mskSedge); %add to lines: if iy==1; LINES_MASKS=line_cur; else; LINES_MASKS(iy)=line_cur; end; end; if nargout==0; %add to mygrid mygrid.LINES_MASKS=LINES_MASKS; else; %output to line_out line_out=line_cur; end; gcmfaces/gcmfaces_calc/calc_zonmean_T.m0000644000435400001440000000305012367515675020050 0ustar gforgetusersfunction [FLD,X,Y]=calc_zonmean_T(fld); %object: compute zonal mean %inputs: fld is the field of interest %output: FLD is the zonal mean field % %notes: mygrid.LATS_MASKS is the set of quasi longitudinal lines along which % means will computed, as computed in gcmfaces_lines_zonal global mygrid; %initialize output: n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); FLD=NaN*squeeze(zeros(length(mygrid.LATS_MASKS),n3,n4)); %use array format to speed up computation below: fld=convert2array(fld); n1=size(fld,1); n2=size(fld,2); fld=reshape(fld,n1*n2,n3*n4); rac=reshape(convert2array(mygrid.RAC),n1*n2,1)*ones(1,n3*n4); if n3==length(mygrid.RC); hFacC=reshape(convert2array(mygrid.hFacC),n1*n2,n3*n4); else; hFacC=reshape(convert2array(mygrid.mskC(:,:,1)),n1*n2,1)*ones(1,n3*n4); hFacC(isnan(hFacC))=0; end; %masked area only: rac(isnan(fld))=0; hFacC(isnan(fld))=0; fld(isnan(fld))=0; rac=rac.*hFacC; fld=fld.*rac; for iy=1:length(mygrid.LATS_MASKS); %get list ofpoints that form a zonal band: mm=convert2array(mygrid.LATS_MASKS(iy).mskCedge); mm=find(~isnan(mm)&mm~=0); %do the area weighed average along this band: tmp1=sum(fld(mm,:),1); tmp2=sum(rac(mm,:),1); tmp2(tmp2==0)=NaN; tmp1=tmp1./tmp2; %store: FLD(iy,:,:)=reshape(tmp1,n3,n4); end; X=[]; Y=[]; if size(FLD,2)==length(mygrid.RC); X=mygrid.LATS*ones(1,length(mygrid.RC)); Y=ones(length(mygrid.LATS),1)*(mygrid.RC'); elseif size(FLD,2)==1; X=mygrid.LATS; Y=ones(length(mygrid.LATS),1); end; gcmfaces/gcmfaces_calc/gcmfaces_remap_2d.m0000644000435400001440000001046011747566663020464 0ustar gforgetusersfunction [fld]=gcmfaces_remap_2d(lon,lat,fld,nDblRes,varargin); %object: use bin average to remap ONE lat-lon grid FIELD to a gcmfaces grid %input: lon,lat,fld are the gridded product arrays % nDblRes is the number of times the input field % resolution should be doubled before bin average. %optional: mskExtrap is the mask to which to extrapolate after bin average % If it is not specified we do no extrapolation %note: nDblRes>0 is useful if the starting resolution is coarse % enough that the bin average would leave many empty points. %assumption:fld should show NaN for missing values global mygrid; if nargin>4; mskExtrap=varargin{1}; else; mskExtrap=[]; end; %refine grid before bin average: for ii=1:nDblRes; [lon,lat,fld]=dbl_res(lon,lat,fld,ii); end; %put in vector form: tmp1=find(~isnan(fld)); lon=lon(tmp1); lat=lat(tmp1); fld=fld(tmp1); %switch longitude range to -180+180 lon(find(lon>180))=lon(find(lon>180))-360; %compute bin average: fld=gcmfaces_bindata(lon,lat,fld); %potential extrapolation: if ~isempty(mskExtrap); fld=diffsmooth2D_extrap_inv(fld,mskExtrap); end; %apply surface land mask: fld=fld.*mygrid.mskC(:,:,1); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function [lonOut,latOut,obsOut]=dbl_res(lon,lat,obs,extendNaN); %object: use neighbor average to double the fields resolution %inputs: lon,lat,fld are the gridded product arrays, with % NaN for missing values in fld. % extendNaN states whether between a real and a NaN % we add a NaN (extendNaN==1) or a real (extendNaN~=1) %outputs: lonOut,latOut,fldOut are the x2 resolution arrays % %assumptions: 0-360 longitudes and a consistent ordering of arrays %check longitude range: if ~isempty(find(lon(:)<0))|~isempty(find(lon(:)>360)); fprintf('problem in longitude specs\n'); return; end; %check simple ordering: tmp1=diff(lon(:,1)); if ~isempty(find(tmp1<=0)); fprintf('problem in longitude specs\n'); return; end; %make sure that we are >=0 and <360: if lon(1,1)>0&lon(end,1)==360; lon=[lon(end,:)-360;lon(1:end-1,:)]; lat=[lat(end,:);lat(1:end-1,:)]; obs=[obs(end,:);obs(1:end-1,:)]; end; %make sure that the last point is not duplicated: if lon(1,1)==0&lon(end,1)==360; lon=lon(1:end-1,:); lat=lat(1:end-1,:); obs=obs(1:end-1,:); end; %what do we do with last longitude points: if lon(1,1)>0&lon(end,1)<360; addOnePt=1; %add point at the beginning else; addOnePt=2; %add point at the end end; for ii=1:3; %0) get field if ii==1; tmpA=lon; elseif ii==2; tmpA=lat; elseif ii==3; tmpA=obs; end; %1) zonal direction: tmpB=nanmean2flds(tmpA(1:end-1,:),tmpA(2:end,:),extendNaN); tmpC=ones(size(tmpA,1)*2-1,size(tmpA,2)); tmpC(1:2:end,:)=tmpA; tmpC(2:2:end-1,:)=tmpB; %treat zonal edge of the domain if addOnePt==1; %add one point at the beginning if ii==1; offset=-360; else; offset=0; end; tmpB=nanmean2flds(tmpA(1,:),offset+tmpA(end,:),extendNaN); tmpC=[tmpB;tmpC]; end; if addOnePt==2; %add one point at the end if ii==1; offset=360; else; offset=0; end; tmpB=nanmean2flds(offset+tmpA(1,:),tmpA(end,:),extendNaN); tmpC=[tmpC;tmpB]; end; %check that we did not go too far (should not happen) if ii==1; tmp1=~isempty(find(lon(:)<0))|~isempty(find(lon(:)>360)); if tmp1; fprintf('problem in longitude interp\n'); return; end; end; %2) meridional direction: tmpB=nanmean2flds(tmpC(:,1:end-1),tmpC(:,2:end),extendNaN); tmpA=ones(size(tmpC,1),size(tmpC,2)*2-1); tmpA(:,1:2:end)=tmpC; tmpA(:,2:2:end-1)=tmpB; %3) store field: if ii==1; lonOut=tmpA; elseif ii==2; latOut=tmpA; elseif ii==3; obsOut=tmpA; end; end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function [fld]=nanmean2flds(fld1,fld2,extendNaN); %object: compute the average of two fields, accounting for NaNs %inputs: fld1 and fld2 are the two fields % if extendNaN==1 the result is NaN if either fld1 or fld2 is NaN. % Otherwise the result is real if either fld1 or fld2 is real. if extendNaN==1; fld=(fld1+fld2)/2; else; msk1=~isnan(fld1); fld1(isnan(fld1))=0; msk2=~isnan(fld2); fld2(isnan(fld2))=0; fld=fld1+fld2; msk=msk1+msk2; msk(msk==0)=NaN; fld=fld./msk; end; gcmfaces/gcmfaces_calc/calc_barostream.m0000644000435400001440000000657212274331426020254 0ustar gforgetusersfunction [fldBAR]=calc_barostream(fldU,fldV,noDiv,list_factors); %object: compute barotropic streamfunction %inputs: fldU and fldV are the fields of grid point transport %optional: noDiv (default is 1). If 1 then remove the divergent % part of the flow field first. If 0 then dont. % list_factors (default is {'dh','dz'}) %output: FLD is the streamfunction %notes: the result is converted to Sv global mygrid; if nargin<3; noDiv=1; end; if nargin<4; list_factors={'dh','dz'}; end; %0) prepare fldU/fldV (transport fields): n3=max(size(fldU.f1,3),1); n4=max(size(fldV.f1,4),1); fldU(isnan(fldU))=0; fldV(isnan(fldV))=0; dxg=mk3D(mygrid.DXG,fldU); dyg=mk3D(mygrid.DYG,fldU); if size(fldU.f1,3)==length(mygrid.DRF); drf=mk3D(mygrid.DRF,fldU); else; drf=fldU; drf(:)=1; end; facW=drf; facW(:)=1; facS=facW; for ii=1:length(list_factors); tmp1=list_factors{ii}; if strcmp(tmp1,'dh'); facW=facW.*dyg; facS=facS.*dxg; elseif strcmp(tmp1,'dz'); facW=facW.*drf; facS=facS.*drf; elseif strcmp(tmp1,'hfac'); facW=facW.*mygrid.hFacW; facS=facS.*mygrid.hFacS; elseif isempty(tmp1); 1; else; fprintf('error in calc_barostream : non supported factor\n'); return; end; end; for k4=1:n4; fldU(:,:,:,k4)=fldU(:,:,:,k4).*facW; fldV(:,:,:,k4)=fldV(:,:,:,k4).*facS; end; %apply mask: fldU=sum(fldU,3).*mygrid.mskW(:,:,1); fldV=sum(fldV,3).*mygrid.mskS(:,:,1); %take out thedivergent part of the flow: if noDiv; [fldUdiv,fldVdiv,fldDivPot]=diffsmooth2D_div_inv(fldU,fldV); fldU=fldU-fldUdiv; fldV=fldV-fldVdiv; end; %1) compute streamfunction face by face: [fldU,fldV]=exch_UV(fldU,fldV); fldU(isnan(fldU))=0; fldV(isnan(fldV))=0; tmp1=cumsum(fldV,1); for iF=1:fldU.nFaces; tmp2=tmp1{iF}; tmp1{iF}=[zeros(1,size(tmp2,2));tmp2]; end; tmp2=diff(tmp1,1,2)+fldU; tmp3=cumsum(mean(tmp2,1)); %to check divergence implied errors: %figure; for iF=1:fldU.nFaces; subplot(3,2,iF); plot(std(tmp2{iF},0,1)); end; for iF=1:fldU.nFaces; tmp2=tmp1{iF}; tmp1{iF}=tmp2-ones(size(tmp2,1),1)*[0 tmp3{iF}]; end; bf_step1=tmp1; if fldU.nFaces==1; bf_step2=bf_step1; else; %2) match edges: %... set face number field TMP1=tmp1; for iF=1:TMP1.nFaces; TMP1{iF}(:)=iF; end; TMP2=exch_T_N(TMP1);%!!! this is a trick, since TMP1 is (n+1 X n+1) and loc. at vorticity points tmp1=bf_step1; for iF=1:fldU.nFaces-1; tmp2=exch_T_N(tmp1);%!!! same trick tmp3=tmp2{iF+1}; tmp3(3:end-2,3:end-2)=NaN;%mask out interior points TMP3=TMP2{iF+1}; tmp3(find(TMP3>iF+1))=NaN;%mask out edges points coming from unadjusted faces tmp3(:,1)=tmp3(:,1)-tmp3(:,2); tmp3(:,end)=tmp3(:,end)-tmp3(:,end-1);%compare edge points tmp3(1,:)=tmp3(1,:)-tmp3(2,:); tmp3(end,:)=tmp3(end,:)-tmp3(end-1,:);%compare edge points tmp3(2:end-1,2:end-1)=NaN;%mask out remaining interior points tmp1{iF+1}=tmp1{iF+1}+nanmedian(tmp3(:));%adjust the face data end; bf_step2=tmp1; end; %3) put streamfunction at cell center tmp1=bf_step2; tmp2=tmp1; for iF=1:tmp1.nFaces; tmp3=tmp2{iF}; tmp3=(tmp3(:,1:end-1)+tmp3(:,2:end))/2; tmp3=(tmp3(1:end-1,:)+tmp3(2:end,:))/2; tmp2{iF}=tmp3; end; bf_step3=tmp2; %4) set 0 on land on average: tmp1=convert2array(bf_step3); tmp2=convert2array(mygrid.mskC(:,:,1)); tmp2=find(isnan(tmp2)&~isnan(tmp1)); tmp2=median(tmp1(tmp2)); if isnan(tmp2); tmp2=nanmedian(tmp1(:)); end; bf_step4=(bf_step3-tmp2).*mygrid.mskC(:,:,1); %5) return the result: fldBAR=bf_step4; %convert to Sv and change sign: fldBAR=1e-6*fldBAR; gcmfaces/gcmfaces_calc/calc_budget_mean_mask.m0000644000435400001440000000223512044532205021363 0ustar gforgetusersfunction [budg,area]=calc_budget_mean_mask(cont,zconv,hconv,mask); %object : compute budget of cont=zconv+hconv, on average over masked region %input : cont is the time derivative of the content (e.g. d/dt[T*drf]i; per m2) % zconv is the convergence of vertical fluxes (e.g. TFLUX; per m2) % hconv is the convergence of advective and diffusive fluxes (per grid cell) % mask is the region of interest mask (1 to include point; 0 or NaN to exclude it) %output : budg is the vector of the 3 terms mean, over the masked region % area is the vector of each latitude band %note : for a closed budget you expect 0~(contTot-hconvTot-zconvTot)/contTot gcmfaces_global; mask(mask==0)=NaN; areaMask=mygrid.RAC.*mask; %vertical integrals: cont=nansum(cont,3)./mask; zconv=nansum(zconv,3)./mask; hconv=nansum(hconv,3)./areaMask; %horizontal integrals: contTot=nansum(cont.*areaMask)/nansum(areaMask); hconvTot=nansum(hconv.*areaMask)/nansum(areaMask); zconvTot=nansum(zconv.*areaMask)/nansum(areaMask); %output result: budg=[contTot;hconvTot;zconvTot]; area=nansum(areaMask); %to check the results: if 0; (contTot-hconvTot-zconvTot)/contTot; end; gcmfaces/gcmfaces_calc/layers_remap.m0000644000435400001440000000453512030163460017602 0ustar gforgetusersfunction [varargout]=layers_remap(P,pType,tracer,trGrid,nDblRes); %object : remap variables (e.g. transports) from depth to tracer classes. %input : P is the variable of interest % pType is 'extensive' or 'intensive' % tracer is the tracer field (3D; at cell center in depth space). % trGrid is the tracer space grid (1D; centers of tracer bins). % nDblRes is the number of resolution doublings (in depth, not tracer space) %output : P is the remapped variable %notes : this was not fully tested for intensive quantities gcmfaces_global; doUV=iscell(P);%should depend on argument list if isempty(whos('nDblRes')); nDblRes=0; end;%default is no grid refinement tracer=tracer.*mygrid.mskC;%needed for trW/S, and regrid_dblres/intensive if ~doUV; listVar={'P'}; listTr={'tracer'}; listPos={'C'}; else; listVar={'U','V'}; listTr={'trW','trS'}; listPos={'W','S'}; % U=P{1}; V=P{2}; % FLD=exch_T_N(tracer); trW=NaN*tracer; trS=NaN*tracer; for iF=1:FLD.nFaces; tmpA=FLD{iF}(2:end-1,2:end-1,:); tmpB=FLD{iF}(1:end-2,2:end-1,:); trW{iF}=(tmpA+tmpB)/2; tmpA=FLD{iF}(2:end-1,2:end-1,:); tmpB=FLD{iF}(2:end-1,1:end-2,:); trS{iF}=(tmpA+tmpB)/2; end; end; for ii=1:length(listVar); %rename eval(['P=' listVar{ii} '; tracer=' listTr{ii} ';']); %set to extensive if strcmp(pType,'intensive'); if listPos{ii}=='C'; dxy=mk3D(mygrid.RAC,P).*mygrid.hFacC; elseif listPos{ii}=='W'; dxy=mk3D(mygrid.DYG,P); elseif listPos{ii}=='S'; dxy=mk3D(mygrid.DXG,P); else; error('unknown position'); %document the different weights about C vs U/V end; S=dxy.*mk3D(mygrid.DRF,P); P=P.*S; end; %apply mask eval(['P=P.*mygrid.msk' listPos{ii} ';']); %grid refinement (if nDblRes>0) tracer=regrid_dblres(tracer,'intensive',nDblRes); P=regrid_dblres(P,'extensive',nDblRes); %the very remaping P=regrid_sum(P,tracer,trGrid); %reset to intensive if strcmp(pType,'intensive'); eval(['S=S.*mygrid.msk' listPos{ii} ';']); S=regrid_dblres(S,'extensive',nDblRes); S=regrid_sum(S,tracer,trGrid); P=P./S; end; %rename eval([listVar{ii} '=P;']); end; %output result if ~doUV; varargout={P}; else; varargout={U,V}; end; gcmfaces/@gcmfaces/0000755000435400001440000000000012375431055014062 5ustar gforgetusersgcmfaces/@gcmfaces/m_ll2xy.m0000644000435400001440000000065111650105435015623 0ustar gforgetusersfunction [xx,yy] = m_ll2xy(x,y,varargin) %overloaded gcmfaces m_ll2xy function : % simply calls m_map's m_ll2xy function for each face data % if the first two arguments (lon and lat) are gcmfaces objects % passing over the other arguments xx=x; yy=y; for iFace=1:x.nFaces; iF=num2str(iFace); eval(['[tmpx,tmpy]=m_ll2xy(x.f' iF ',y.f' iF ',varargin{:});']); eval(['xx.f' iF '=tmpx; yy.f' iF '=tmpy;']); end; gcmfaces/@gcmfaces/log10.m0000644000435400001440000000033312266567104015165 0ustar gforgetusersfunction r = log10(p) %overloaded gcmfaces log10 function : % simply calls double log10 function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=log10(p.f' iF ');']); end; gcmfaces/@gcmfaces/log2.m0000644000435400001440000000032711650105435015100 0ustar gforgetusersfunction r = log2(p) %overloaded gcmfaces log2 function : % simply calls double log2 function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=log2(p.f' iF ');']); end; gcmfaces/@gcmfaces/diff.m0000644000435400001440000000047711650105435015153 0ustar gforgetusersfunction r = diff(p,varargin) %overloaded gcmfaces diff function : % simply calls double diff function for each face data % if the first arguments is a gcmfaces object % passing over the other arguments r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=diff(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/le.m0000644000435400001440000000112411650105435014631 0ustar gforgetusersfunction r = le(p,q) %overloaded gcmfaces le function : % simply calls double le function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '<=q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '<=q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p<=q.f' iF ';']); else; error('gcmfaces le: types are incompatible') end; end; gcmfaces/@gcmfaces/lt.m0000644000435400001440000000112111650105435014645 0ustar gforgetusersfunction r = lt(p,q) %overloaded gcmfaces lt function : % simply calls double lt function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '=q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '>=q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p>=q.f' iF ';']); else; error('gcmfaces ge: types are incompatible') end; end; gcmfaces/@gcmfaces/eq.m0000644000435400001440000000112411650105435014636 0ustar gforgetusersfunction r = eq(p,q) %overloaded gcmfaces eq function : % simply calls double eq function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '==q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '==q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p==q.f' iF ';']); else; error('gcmfaces eq: types are incompatible') end; end; gcmfaces/@gcmfaces/subsasgn.m0000644000435400001440000000266211650105436016067 0ustar gforgetusersfunction a = subsasgn(a,index,val) %overloaded gcmfaces subsasgn function : subscripted assignment according to % beta{n} will return the n^{th} face data (array). % beta(:,:,n) will return the n^{th} vertical level (gcmfaces). % beta.nFaces will return the nFaces attribute (double). switch index(1).type case '{}' if length(index)>1; aa=subsref(a,index(1)); val=subsasgn(aa,index(2:end),val); end; nFaces=get(a,'nFaces'); iFace=index(1).subs{:}; if iFace<=nFaces&iFace>0; eval(['a.f' num2str(iFace) '=val;']); else error('Index out of range') end case '.' if length(index)>1; aa=subsref(a,index(1)); val=subsasgn(aa,index(2:end),val); end; a=set(a,index(1).subs,val); case '()' if length(index)>1; error('indexing not supported by gcmfaces objects'); end; for iFace=1:a.nFaces; iF=num2str(iFace); if isa(index.subs{1},'gcmfaces'); if isa(val,'gcmfaces'); eval(['a.f' iF '(index.subs{1}.f' iF ')=val.f' iF ';']); else; eval(['a.f' iF '(index.subs{1}.f' iF ')=val;']); end; else; if isa(val,'gcmfaces'); eval(['a.f' iF '=subsasgn(a.f' iF ',index,val.f' iF ');']); else; eval(['a.f' iF '=subsasgn(a.f' iF ',index,val);']); end; end; end; otherwise error('indexing not supported by gcmfaces objects') end %if length(index)>1; b=subsref(b,index(2:end)); end; gcmfaces/@gcmfaces/repmat.m0000644000435400001440000000050711650105435015525 0ustar gforgetusersfunction r = repmat(p,varargin) %overloaded gcmfaces repmat function : % simply calls double repmat function for each face data % if the first arguments is a gcmfaces object % passing over the other arguments r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=repmat(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/display.m0000644000435400001440000000067411650105435015707 0ustar gforgetusersfunction display(a) %overloaded gcmfaces display function : % displays the gcmfaces object content and attributes stg = sprintf(' nFaces: %d\n',a.nFaces); for iFace=1:a.nFaces; eval(['tmp1=a.f' num2str(iFace) ';']); tmp1=size(tmp1); tmp2='['; for ii=1:length(tmp1); tmp2=[tmp2 num2str(tmp1(ii)) 'x']; end; tmp2=[tmp2(1:end-1) ' ' class(tmp1) ']']; stg=strvcat(stg,[' f' num2str(iFace) ': ' tmp2]); end; disp(stg) gcmfaces/@gcmfaces/nanmedian.m0000644000435400001440000000110611650105435016163 0ustar gforgetusersfunction r = nanmedian(p,varargin) %overloaded gcmfaces nanmedian function : % 1) if single gcmfaces argument, then returns the global nanmedian over all faces % 2) if more than one argument, then simply calls double nanmedian function for % each face data, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=nanmedian(tmp1); return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=nanmedian(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/sin.m0000644000435400001440000000032311650105436015023 0ustar gforgetusersfunction r = sin(p) %overloaded gcmfaces sin function : % simply calls double sin function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=sin(p.f' iF ');']); end; gcmfaces/@gcmfaces/isnan.m0000644000435400001440000000033311650105435015342 0ustar gforgetusersfunction r = isnan(p) %overloaded gcmfaces isnan function : % simply calls double isnan function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=isnan(p.f' iF ');']); end; gcmfaces/@gcmfaces/mrdivide.m0000644000435400001440000000114711650105435016041 0ustar gforgetusersfunction r = rdivide(p,q) %overloaded gcmfaces mrdivide function : % simply calls double mrdivide function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '/q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '/q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p/q.f' iF ';']); else; error('gcmfaces rdivide: types are incompatible') end; end; gcmfaces/@gcmfaces/or.m0000644000435400001440000000112111650105435014646 0ustar gforgetusersfunction r = or(p,q) %overloaded gcmfaces or function : % simply calls double or function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '|q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '|q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p|q.f' iF ';']); else; error('gcmfaces or: types are incompatible') end; end; gcmfaces/@gcmfaces/mk3D.m0000644000435400001440000000233611364665712015050 0ustar gforgetusersfunction a = mk3D(b,c) %function a = mk3D(b,c) % => makes a 3D field of the same format as c, based on b, which may be % either [A] a 2D field consistent with c(:,:,1) % or [B] a 1D vector concistent % % in case [A], if b has more that 2D, then the first 2D field is used % in case [B], if the length of b is n3=size(c.f1,3), then we map b(k) to % a(:,:,k). Otherwise we map b(1) to a(:,:,k) and issue a warning. a=c; n3=size(a.f1,3); if isa(b,'gcmfaces'); %go from 2D field to 3D field for iFace=1:a.nFaces; iF=num2str(iFace); eval(['tmp1=b.f' iF ';']); [n1,n2]=size(tmp1); tmp1=tmp1(:); tmp1=tmp1*ones(1,size(a.f1,3)); tmp1=reshape(tmp1,[n1 n2 n3]); eval(['a.f' iF '=tmp1;']); end; elseif isa(b,'double'); if length(b)~=1&length(b)~=n3; fprintf(' mk3D warning: b(1) is used \n'); end; if length(b)~=n3; b=b(1)*ones(1,n3); end; if size(b,1)~=1; b=b'; end; for iFace=1:a.nFaces; iF=num2str(iFace); eval(['tmp1=c.f' iF ';']); tmp2=size(tmp1); n1=tmp2(1); n2=tmp2(2); tmp1=reshape(ones(n1*n2,1)*b,[n1 n2 n3]);; eval(['a.f' iF '=tmp1;']); end; else error('indexing not supported by gcmfaces objects') end gcmfaces/@gcmfaces/power.m0000644000435400001440000000114011650105435015363 0ustar gforgetusersfunction r = power(p,q) %overloaded gcmfaces power function : % simply calls double power function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '.^q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '.^q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.^q.f' iF ';']); else; error('gcmfaces power: types are incompatible') end; end; gcmfaces/@gcmfaces/uplus.m0000644000435400001440000000032411650105436015403 0ustar gforgetusersfunction r = uplus(p) %overloaded gcmfaces uplus function : % simply calls double uplus function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=+p.f' iF ';']); end; gcmfaces/@gcmfaces/sum.m0000644000435400001440000000104411650105436015037 0ustar gforgetusersfunction r = sum(p,varargin) %overloaded gcmfaces sum function : % 1) if single gcmfaces argument, then returns the global sum over all faces % 2) if more than one argument, then simply calls double sum function for % each face data, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=sum(tmp1); return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=sum(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/minus.m0000644000435400001440000000113511650105435015366 0ustar gforgetusersfunction r = minus(p,q) %overloaded gcmfaces minus function : % simply calls double minus function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '-q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '-q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p-q.f' iF ';']); else; error('gcmfaces minus: types are incompatible') end; end; gcmfaces/@gcmfaces/cumsum.m0000644000435400001440000000050711650105435015546 0ustar gforgetusersfunction r = cumsum(p,varargin) %overloaded gcmfaces cumsum function : % simply calls double cumsum function for each face data % if the first arguments is a gcmfaces object % passing over the other arguments r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=cumsum(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/subsref.m0000644000435400001440000000203111650105436015701 0ustar gforgetusersfunction b = subsref(a,index) %overloaded gcmfaces subsref function : subscripted reference according to % beta{n} will return the n^{th} face data (array). % beta(:,:,n) will return the n^{th} vertical level (gcmfaces). % beta.nFaces will return the nFaces attribute (double). switch index(1).type case '{}' nFaces=get(a,'nFaces'); iFace=index(1).subs{:}; if iFace<=nFaces&iFace>0; eval(['b=a.f' num2str(iFace) ';']); else error('Index out of range') end if length(index)>1; b=subsref(b,index(2:end)); end; case '.' b = get(a,index(1).subs); if length(index)>1; b=subsref(b,index(2:end)); end; case '()' if length(index)>1; error('indexing not supported by gcmfaces objects'); end; b=a; for iFace=1:a.nFaces; iF=num2str(iFace); if isa(index.subs{1},'gcmfaces'); eval(['b.f' iF '=a.f' iF '(index.subs{1}.f' iF ');']); else; eval(['b.f' iF '=subsref(a.f' iF ',index);']); end; end; otherwise error('indexing not supported by gcmfaces objects') end gcmfaces/@gcmfaces/find.m0000644000435400001440000000047711650105435015163 0ustar gforgetusersfunction r = find(p,varargin) %overloaded gcmfaces find function : % simply calls double find function for each face data % if the first arguments is a gcmfaces object % passing over the other arguments r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=find(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/exch_UV_N.m0000644000435400001440000000074111650105435016053 0ustar gforgetusersfunction [aU,aV]=exch_UV_N(bU,bV,varargin); %special exchange routine for velocity points if strcmp(bU.gridType,'llc'); [aU,aV]=exch_UV_N_llc(bU,bV,varargin{:}); elseif strcmp(bU.gridType,'cube'); [aU,aV]=exch_UV_N_cube(bU,bV,varargin{:}); elseif strcmp(bU.gridType,'llpc'); [aU,aV]=exch_UV_N_llpc(bU,bV,varargin{:}); elseif strcmp(bU.gridType,'ll'); [aU,aV]=exch_UV_N_ll(bU,bV,varargin{:}); else; error(['exch_UV_N not implemented for ' bU.gridType '!?']); end; gcmfaces/@gcmfaces/nanmean.m0000644000435400001440000000107211650105435015650 0ustar gforgetusersfunction r = nanmean(p,varargin) %overloaded gcmfaces nanmean function : % 1) if single gcmfaces argument, then returns the global nanmean over all faces % 2) if more than one argument, then simply calls double nanmean function for % each face data, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=nanmean(tmp1); return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=nanmean(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/exp.m0000644000435400001440000000032311650105435015025 0ustar gforgetusersfunction r = exp(p) %overloaded gcmfaces exp function : % simply calls double exp function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=exp(p.f' iF ');']); end; gcmfaces/@gcmfaces/exch_Z.m0000644000435400001440000000054512024523424015455 0ustar gforgetusersfunction [FLD]=exch_Z(fld); %[FLD]=exch_Z(fld); %adds vorticity points (to north and east of center points) if strcmp(fld.gridType,'llc'); FLD=exch_Z_llc(fld); elseif strcmp(fld.gridType,'cube'); FLD=exch_Z_cube(fld); elseif strcmp(fld.gridType,'ll'); FLD=exch_Z_ll(fld); else; error(['exch_Z not implemented for ' fld.gridType '!?']); end; gcmfaces/@gcmfaces/median.m0000644000435400001440000000106411650105435015471 0ustar gforgetusersfunction r = median(p,varargin) %overloaded gcmfaces median function : % 1) if single gcmfaces argument, then returns the global median over all faces % 2) if more than one argument, then simply calls double median function for % each face data, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=median(tmp1); return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=median(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/mean.m0000644000435400001440000000105011650105435015147 0ustar gforgetusersfunction r = mean(p,varargin) %overloaded gcmfaces mean function : % 1) if single gcmfaces argument, then returns the global mean over all faces % 2) if more than one argument, then simply calls double mean function for % each face data, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=mean(tmp1); return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=mean(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/nanmax.m0000644000435400001440000000142212321540553015514 0ustar gforgetusersfunction r = nanmax(p,varargin) %overloaded gcmfaces nanmax function : % 1) if single gcmfaces argument, then returns the global nanmax over all faces % 2) if two gcmfaces arguments, then returns the nanmax of the two at each point % 3) otherwise calls double nanmax function for each face, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=nanmax(tmp1); return; end; if isa(varargin{1},'gcmfaces'); r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=nanmax(p.f' iF ',varargin{1}.f' iF ');']); end; return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=nanmax(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/min.m0000644000435400001440000000137112321540553015020 0ustar gforgetusersfunction r = min(p,varargin) %overloaded gcmfaces min function : % 1) if single gcmfaces argument, then returns the global min over all faces % 2) if two gcmfaces arguments, then returns the min of the two at each point % 3) otherwise calls double min function for each face, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=min(tmp1); return; end; if isa(varargin{1},'gcmfaces'); r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=min(p.f' iF ',varargin{1}.f' iF ');']); end; return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=min(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/exch_UV.m0000644000435400001440000000063411650105435015577 0ustar gforgetusersfunction [aU,aV]=exch_UV(bU,bV); %special exchange routine for velocity points if strcmp(bU.gridType,'llc'); [aU,aV]=exch_UV_llc(bU,bV); elseif strcmp(bU.gridType,'cube'); [aU,aV]=exch_UV_cube(bU,bV); elseif strcmp(bU.gridType,'llpc'); [aU,aV]=exch_UV_llpc(bU,bV); elseif strcmp(bU.gridType,'ll'); [aU,aV]=exch_UV_ll(bU,bV); else; error(['exch_UV not implemented for ' bU.gridType '!?']); end; gcmfaces/@gcmfaces/nansum.m0000644000435400001440000000107111650105435015533 0ustar gforgetusersfunction r = nannansum(p,varargin) %overloaded gcmfaces nansum function : % 1) if single gcmfaces argument, then returns the global nansum over all faces % 2) if more than one argument, then simply calls double nansum function for % each face data, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=nansum(tmp1); return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=nansum(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/tan.m0000644000435400001440000000032311650105436015014 0ustar gforgetusersfunction r = tan(p) %overloaded gcmfaces tan function : % simply calls double tan function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=tan(p.f' iF ');']); end; gcmfaces/@gcmfaces/cos.m0000644000435400001440000000032311650105435015015 0ustar gforgetusersfunction r = cos(p) %overloaded gcmfaces cos function : % simply calls double cos function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=cos(p.f' iF ');']); end; gcmfaces/@gcmfaces/max.m0000644000435400001440000000137212321540553015023 0ustar gforgetusersfunction r = max(p,varargin) %overloaded gcmfaces max function : % 1) if single gcmfaces argument, then returns the global max over all faces % 2) if two gcmfaces arguments, then returns the max of the two at each point % 3) otherwise calls double max function for each face, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=max(tmp1); return; end; if isa(varargin{1},'gcmfaces'); r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=max(p.f' iF ',varargin{1}.f' iF ');']); end; return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=max(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/angle.m0000644000435400001440000000033311650105435015320 0ustar gforgetusersfunction r = angle(p) %overloaded gcmfaces angle function : % simply calls double angle function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=angle(p.f' iF ');']); end; gcmfaces/@gcmfaces/uminus.m0000644000435400001440000000032711650105436015556 0ustar gforgetusersfunction r = uminus(p) %overloaded gcmfaces uminus function : % simply calls double uminus function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=-p.f' iF ';']); end; gcmfaces/@gcmfaces/prctile.m0000644000435400001440000000023512272061776015707 0ustar gforgetusersfunction r = prctile(p,varargin) %overloaded gcmfaces prctile function (operates on full domain) tmp1=convert2gcmfaces(p); r=prctile(tmp1(:),varargin{1}); gcmfaces/@gcmfaces/nanmin.m0000644000435400001440000000142112321540553015511 0ustar gforgetusersfunction r = nanmin(p,varargin) %overloaded gcmfaces nanmin function : % 1) if single gcmfaces argument, then returns the global nanmin over all faces % 2) if two gcmfaces arguments, then returns the nanmin of the two at each point % 3) otherwise calls double nanmin function for each face, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=nanmin(tmp1); return; end; if isa(varargin{1},'gcmfaces'); r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=nanmin(p.f' iF ',varargin{1}.f' iF ');']); end; return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=nanmin(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/mtimes.m0000644000435400001440000000113711650105435015533 0ustar gforgetusersfunction r = times(p,q) %overloaded gcmfaces mtimes function : % simply calls double mtimes function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '*q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '*q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p*q.f' iF ';']); else; error('gcmfaces times: types are incompatible') end; end; gcmfaces/@gcmfaces/std.m0000644000435400001440000000104211650105436015023 0ustar gforgetusersfunction r = std(p,varargin) %overloaded gcmfaces std function : % 1) if single gcmfaces argument, then returns the global std over all faces % 2) if more than one argument, then simply calls double std function for % each face data, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=std(tmp1); return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=std(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/squeeze.m0000644000435400001440000000034311650105436015715 0ustar gforgetusersfunction r = squeeze(p) %overloaded gcmfaces squeeze function : % simply calls double squeeze function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=squeeze(p.f' iF ');']); end; gcmfaces/@gcmfaces/imag.m0000644000435400001440000000032711650105435015152 0ustar gforgetusersfunction r = imag(p) %overloaded gcmfaces imag function : % simply calls double imag function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=imag(p.f' iF ');']); end; gcmfaces/@gcmfaces/isinf.m0000644000435400001440000000033312266567104015353 0ustar gforgetusersfunction r = isinf(p) %overloaded gcmfaces isinf function : % simply calls double isinf function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=isinf(p.f' iF ');']); end; gcmfaces/@gcmfaces/rdivide.m0000644000435400001440000000115011650105435015656 0ustar gforgetusersfunction r = rdivide(p,q) %overloaded gcmfaces rdivide function : % simply calls double rdivide function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF './q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF './q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p./q.f' iF ';']); else; error('gcmfaces rdivide: types are incompatible') end; end; gcmfaces/@gcmfaces/exch_T_N.m0000644000435400001440000000177211650105435015731 0ustar gforgetusersfunction [a]=exch_T_N(b,varargin); %object : add halo region data; exchange data between faces. %input: b is a gcmfaces object %optional: N (1 by default) is the halo region width %output: a is the augmented gcmfaces object % %notes: % - This routine adds N points at the edge of each face, which % are obtained from the neighboring faces edge points; those are necessary to % operations such as neighbor averaging, or computing gradients over a face. % - Applying this routine recursively will likely lead to errors. % - The connectivity between faces depends on the grid topology and needs % to be implemented by hand for any new grid topology (see gcmfaces_exch). if strcmp(b.gridType,'llc'); a=exch_T_N_llc(b,varargin{:}); elseif strcmp(b.gridType,'cube'); a=exch_T_N_cube(b,varargin{:}); elseif strcmp(b.gridType,'llpc'); a=exch_T_N_llpc(b,varargin{:}); elseif strcmp(b.gridType,'ll'); a=exch_T_N_ll(b,varargin{:}); else; error(['exch_T_N not implemented for ' b.gridType '!?']); end; gcmfaces/@gcmfaces/times.m0000644000435400001440000000114011650105436015351 0ustar gforgetusersfunction r = times(p,q) %overloaded gcmfaces times function : % simply calls double times function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '.*q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '.*q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.*q.f' iF ';']); else; error('gcmfaces times: types are incompatible') end; end; gcmfaces/@gcmfaces/zeros.m0000644000435400001440000000064511650105436015403 0ustar gforgetusersfunction r = zeros(p,varargin) %overloaded gcmfaces zeros function : % if the first arguments is a gcmfaces object % we call the double zeros function for each face data % using face dimensions for the first two arguments and % passing over the other arguments r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['[n1,n2]=size(p.f' iF '(:,:,1));']); eval(['r.f' iF '=zeros(n1,n2,varargin{:});']); end; gcmfaces/@gcmfaces/sqrt.m0000644000435400001440000000032711650105436015227 0ustar gforgetusersfunction r = sqrt(p) %overloaded gcmfaces sqrt function : % simply calls double sqrt function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=sqrt(p.f' iF ');']); end; gcmfaces/@gcmfaces/not.m0000644000435400001440000000031711650105435015034 0ustar gforgetusersfunction r = not(p) %overloaded gcmfaces not function : % simply calls double not function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=~p.f' iF ';']); end; gcmfaces/@gcmfaces/nanstd.m0000644000435400001440000000106411650105435015523 0ustar gforgetusersfunction r = nanstd(p,varargin) %overloaded gcmfaces nanstd function : % 1) if single gcmfaces argument, then returns the global nanstd over all faces % 2) if more than one argument, then simply calls double nanstd function for % each face data, passing over the other arguments if nargin==1; tmp1=[]; for iFace=1:p.nFaces; iF=num2str(iFace); eval(['tmp1=[tmp1;p.f' iF '(:)];']); end; r=nanstd(tmp1); return; end; r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=nanstd(p.f' iF ',varargin{:});']); end; gcmfaces/@gcmfaces/real.m0000644000435400001440000000032711650105435015160 0ustar gforgetusersfunction r = real(p) %overloaded gcmfaces real function : % simply calls double real function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=real(p.f' iF ');']); end; gcmfaces/@gcmfaces/and.m0000644000435400001440000000112511650105435014774 0ustar gforgetusersfunction r = and(p,q) %overloaded gcmfaces and function : % simply calls double and function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '&q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '&q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p&q.f' iF ';']); else; error('gcmfaces and: types are incompatible') end; end; gcmfaces/@gcmfaces/gcmfaces.m0000644000435400001440000000322012006026473016000 0ustar gforgetusersfunction s=gcmfaces(varargin); %object: create an empty gcmfaces object %input: fld cell array containing each face data % OR nFaces number of faces (empty faces in output) % OR (none; results in empty face data, with nFaces=mygrid.nFaces) %output: gcmfaces object %object: create an empty gcmfaces object %input: fld cell array containing each face data % OR nFaces,fld (to add consistency check) % OR nFaces number of faces (empty faces in output) % OR (none) (empty faces in output) %output: gcmfaces object formatted/filled accordingly global mygrid; if nargin==2; nFaces=varargin{1}; fld=varargin{2}; if ~iscell(fld)|length(fld)~=nFaces; error('inconsistent spec. of nFaces,fld'); end; elseif nargin==1; tmp1=varargin{1}; if iscell(tmp1); fld=tmp1; nFaces=length(fld); else; nFaces=varargin{1}; fld=[]; end; elseif isfield(mygrid,'nFaces'); nFaces=mygrid.nFaces; fld=[]; else; error('nFaces needs to be specified'); end; if nFaces==1; gridType='ll'; elseif nFaces==4; gridType='llpc'; elseif nFaces==5; gridType='llc'; elseif nFaces==6; gridType='cube'; else; error('wrong gcmfaces definition'); end; nFacesMax=6; if iscell(fld); s.nFaces=length(fld); s.gridType=gridType; for iF=1:s.nFaces; eval(['s.f' num2str(iF) '=fld{iF};']); end; for iF=s.nFaces+1:nFacesMax; eval(['s.f' num2str(iF) '=[];']); end; else; s.nFaces=nFaces; s.gridType=gridType; for iF=1:nFacesMax; eval(['s.f' num2str(iF) '=[];']); end; end; s = class(s,'gcmfaces'); gcmfaces/@gcmfaces/set.m0000644000435400001440000000062611650105435015032 0ustar gforgetusersfunction a = set(a,varargin) %overloaded gcmfaces set function : % V = SET(H,'PropertyName',PropertyValue) sets the value of the specified % attribute (e.g. nFaces and gridType) of a gcmfaces object H. propertyArgIn = varargin; while length(propertyArgIn) >= 2, propName = propertyArgIn{1}; val = propertyArgIn{2}; propertyArgIn = propertyArgIn(3:end); eval(['a.' propName '=val;']); end gcmfaces/@gcmfaces/get.m0000644000435400001440000000035111650105435015011 0ustar gforgetusersfunction val = get(a, propName) %overloaded gcmfaces get function : % V = GET(H,'PropertyName') returns the value of the specified % attribute (e.g. nFaces and gridType) of a gcmfaces object H. eval(['val = a.' propName ';']); gcmfaces/@gcmfaces/cat.m0000644000435400001440000000035111650105435015001 0ustar gforgetusersfunction r = cat(nDim,p,q) %overloaded gcmfaces cat function : % simply calls double cat function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=cat(nDim,p.f' iF ',q.f' iF ');']); end; gcmfaces/@gcmfaces/abs.m0000644000435400001440000000032311650105435014776 0ustar gforgetusersfunction r = abs(p) %overloaded gcmfaces abs function : % simply calls double abs function for each face data r=p; for iFace=1:r.nFaces; iF=num2str(iFace); eval(['r.f' iF '=abs(p.f' iF ');']); end; gcmfaces/@gcmfaces/gt.m0000644000435400001440000000112111650105435014640 0ustar gforgetusersfunction r = gt(p,q) %overloaded gcmfaces gt function : % simply calls double gt function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '>q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '>q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p>q.f' iF ';']); else; error('gcmfaces gt: types are incompatible') end; end; gcmfaces/@gcmfaces/plus.m0000644000435400001440000000113111650105435015212 0ustar gforgetusersfunction r = plus(p,q) %overloaded gcmfaces plus function : % simply calls double plus function for each face data % if any of the two arguments is a gcmfaces object if isa(p,'gcmfaces'); r=p; else; r=q; end; for iFace=1:r.nFaces; iF=num2str(iFace); if isa(p,'gcmfaces')&isa(q,'gcmfaces'); eval(['r.f' iF '=p.f' iF '+q.f' iF ';']); elseif isa(p,'gcmfaces')&isa(q,'double'); eval(['r.f' iF '=p.f' iF '+q;']); elseif isa(p,'double')&isa(q,'gcmfaces'); eval(['r.f' iF '=p+q.f' iF ';']); else; error('gcmfaces plus: types are incompatible') end; end; gcmfaces/gcmfaces_global.m0000644000435400001440000000763212365534161015471 0ustar gforgetusersfunction []=gcmfaces_global(varargin); %object: take care of path and global variables (mygrid and myenv), % and sends global variables to caller routine workspace %optional inputs: optional paramaters take the following form % {'name',param1,param2,...}. Are currently active: % {'resetGrid',resetGrid} states that mygrid will be cleared % and re-loaded interactively (1), or not (0;default). % {'listVars',varName1,varName2} is a list of variables % to check is in mygrid (empty by default). %notes: - in any call, if this has not yet been done, % this routine also adds gcmfaces subdirectories % to the matlab path, and it defines myenv. % - calls to this routine will eventually replace % both gcmfaces_path and 'global mygrid' calls. %set optional paramaters to default values resetGrid=0; listVars={}; %set more optional paramaters to user defined values for ii=1:nargin; if ~iscell(varargin{ii}); warning('inputCheck:gcmfaces_global_1',... ['As of june 2011, gcmfaces_global expects \n'... ' its optional parameters as cell arrays. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help gcmfaces_global'' for details.']); elseif ~ischar(varargin{ii}{1}); warning('inputCheck:gcmfaces_global_2',... ['As of june 2011, gcmfaces_global expects \n'... ' its optional parameters cell arrays \n'... ' to start with character string. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help gcmfaces_global'' for details.']); else; if strcmp(varargin{ii}{1},'listVars'); eval([varargin{ii}{1} '={varargin{ii}{2:end}};']); elseif strcmp(varargin{ii}{1},'resetGrid'); eval([varargin{ii}{1} '=varargin{ii}{2};']); else; warning('inputCheck:gcmfaces_global_3',... ['unknown option ''' varargin{ii}{1} ''' was ignored']); end; end; end; %get/define global variables: global myenv mygrid; %take care of path: test0=which('convert2gcmfaces.m'); if isempty(test0); test0=which('gcmfaces_global.m'); ii=strfind(test0,filesep); mydir=test0(1:ii(end)); % eval(['addpath ' mydir ';']); eval(['addpath ' mydir '/gcmfaces_IO/;']); eval(['addpath ' mydir 'gcmfaces_convert/;']); eval(['addpath ' mydir 'gcmfaces_exch/;']); eval(['addpath ' mydir 'gcmfaces_maps/;']); eval(['addpath ' mydir '/gcmfaces_misc/;']); eval(['addpath ' mydir '/gcmfaces_calc/;']); eval(['addpath ' mydir '/gcmfaces_smooth/;']); eval(['addpath ' mydir 'ecco_v4/;']); eval(['addpath ' mydir 'sample_analysis/;']); eval(['addpath ' mydir 'sample_processing/;']); eval(['addpath ' mydir 'gcmfaces_diags/;']); eval(['addpath ' mydir 'gcmfaces_devel/;']); end; %environment variables: if isempty(myenv); test0=which('gcmfaces_global.m'); ii=strfind(test0,filesep); myenv.gcmfaces_dir=test0(1:ii(end)); myenv.verbose=0; myenv.lessplot=0; myenv.lesstest=0; myenv.useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); %... check m_map and netcdf end; %load grid variables: if resetGrid==1; mygrid=[]; dirGrid=input('grid directory name?\n','s'); nFaces=input('number of grid faces?\n'); fileFormat=input('file format?\n[''native'',''straight'',''cube'' or ''compact'']\n','s'); if strcmp(fileFormat,'native'); grid_load_native(dirGrid,nFaces); else; grid_load(dirGrid,nFaces,fileFormat); end; end; %check available mygrid variables: for ii=1:length(listVars); if ~isfield(mygrid,listVars{ii}); error(['mygrid does not include ' listVars{ii}]); end; end; %send to workspace: evalin('caller','global mygrid myenv'); gcmfaces/gcmfaces_convert/0000755000435400001440000000000012375431055015522 5ustar gforgetusersgcmfaces/gcmfaces_convert/convert2array_cube.m0000644000435400001440000000345611600205337021477 0ustar gforgetusersfunction [FLD]=convert2array_cube(fld); %object: gcmfaces to array format conversion (if gcmfaces input) % or: array to gcmfaces format conversion (if array input) % %notes: if array input, the gcmfaces format will be the one of mygrid.XC, so % the array input must have originally been created according to convert2array global mygrid; if isa(fld,'gcmfaces'); do_gcmfaces2array=1; else; do_gcmfaces2array=0; end; if do_gcmfaces2array; n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); n1=size(fld.f1,1)*4; n2=size(fld.f1,2)+2*size(fld.f1,1); FLD=squeeze(zeros(n1,n2,n3,n4)); else; n3=max(size(fld,3),1); n4=max(size(fld,4),1); FLD=NaN*mygrid.XC; for k3=1:n3; for k4=1:n4; for iFace=1:FLD.nFaces; iF=num2str(iFace); eval(['FLD.f' iF '(:,:,k3,k4)=FLD.f' iF '(:,:,1,1);']); end; end; end; end; for k3=1:n3; for k4=1:n4; if do_gcmfaces2array; %ASSEMBLE SIDE FACES: %---------------------- FLD0=[fld.f1(:,:,k3,k4);fld.f2(:,:,k3,k4);sym_g(fld.f4(:,:,k3,k4),7,0);sym_g(fld.f5(:,:,k3,k4),7,0)]; %ADD NORTH FACE: %-------------- pp=fld.f3(:,:,k3,k4); FLDp=[sym_g(pp,5,0);pp.*NaN;sym_g(pp.*NaN,7,0);sym_g(pp.*NaN,6,0)]; FLD1=[FLD0 FLDp]; %ADD NORTH FACE: %-------------- pp=fld.f6(:,:,k3,k4); FLDp=[pp.*NaN;sym_g(pp*NaN,5,0);sym_g(pp.*NaN,6,0);sym_g(pp,7,0)]; FLD1=[FLDp FLD1]; %store: %------ FLD(:,:,k3,k4)=FLD1; else; n1=size(FLD.f1,1); n2=size(FLD.f1,2); FLD.f1(:,:,k3,k4)=fld(1:n1,n1+1:n1+n2,k3,k4); FLD.f2(:,:,k3,k4)=fld(n1+[1:n1],n1+1:n1+n2,k3,k4); FLD.f3(:,:,k3,k4)=sym_g(fld([1:n1],n1+n2+1:n1+n2+n1,k3,k4),7,0); FLD.f4(:,:,k3,k4)=sym_g(fld(n1*2+[1:n1],n1+1:n1+n2,k3,k4),5,0); FLD.f5(:,:,k3,k4)=sym_g(fld(n1*3+[1:n1],n1+1:n1+n2,k3,k4),5,0); FLD.f6(:,:,k3,k4)=sym_g(fld(n1*3+[1:n1],1:n1,k3,k4),5,0); end; end; end; gcmfaces/gcmfaces_convert/convert2pcol_ll.m0000644000435400001440000000233211600247732021004 0ustar gforgetusersfunction [X,Y,FLD]=convert2pcol_ll(x,y,fld,varargin); %object: gcmfaces to 'pcolor format' conversion %inputs: x is longitude (e.g. mygrid.XC) % y is latitude (e.g. mygrid.YC) % fld is the 2D field of interest (e.g. mygrid.hFacC(:,:,1)) %outputs: X,Y,FLD are array versions of x,y,fld % %note: this function is designed so that one may readily % plot the output in geographic coordinates % using e.g. 'figure; pcolor(X,Y,FLD);' k3=1; k4=1; global regularizeXC; if isempty(regularizeXC); fprintf('\n\nconvert2pcol_ll.m init: by default gcmfaces assumes\n'); fprintf(' that XC is longitude in the [-180 180] range, and \n'); fprintf(' if XC shows values outside this range, gcmfaces \n'); fprintf(' will to enforce this convention in graphs. If this is \n'); fprintf(' inadequate, you may try to set regularizeXC to 0 below \n\n'); regularizeXC=1; end; %ASSEMBLE "LATLON" FACES: %---------------------- X=x{1}; Y=y{1}; FLD=fld{1}(:,:,k3,k4); %FIX DATE CHANGE LINE IN LATLON PART: %-------------------------------------- if regularizeXC; ii=max(find(X(:,1)<=180)); X=circshift(X,[-ii 0]); X(X>180)=X(X>180)-360; Y=circshift(Y,[-ii 0]); FLD=circshift(FLD,[-ii 0]); end; gcmfaces/gcmfaces_convert/convert2arctic.m0000644000435400001440000000252411367365111020632 0ustar gforgetusersfunction [fld0]=convert2arctic(fld00,varargin); if fld00.nFaces==1; fld00=convert2cube(fld00); end; n1=size(fld00{1},1); n2=size(fld00{1},2); n3=size(fld00{1},3); n4=size(fld00{1},4); f1=flipdim(permute(fld00{1},[2 1 3 4]),2); f2=fld00{2}; f3=fld00{3}; f4=fld00{4}; f5=flipdim(permute(fld00{5},[2 1 3 4]),1); if isempty(fld00{3}); f3=NaN*zeros(n1,n1,n3,n4); end; fld0=NaN*zeros(n2*2+n1,n2*2+n1,n3,n4); fld0(1:n2,n2+1:n2+n1,:,:)=f1; fld0(n2+1:n2+n1,n2+1:n2+n1,:,:)=f3; fld0(n2+n1+1:end,n2+1:n2+n1,:,:)=f4; fld0(n2+1:n2+n1,1:n2,:,:)=f2; fld0(n2+1:n2+n1,n2+n1+1:end,:,:)=f5; nn=round(n2/2); nn2=n2-nn+1; nn1=n2*2+n1-nn2+1; fld0=fld0(nn2:nn1,nn2:nn1); if nargin==2; doFill=varargin{1}; else; doFill=1; end; if doFill; if n3>1; fprintf('not implemented yet\n'); return; end; %fill the corners of fld0: warning('off','MATLAB:interp1:NaNinY'); for pp=1:4; %do the interpolation in polar coordinates... ii=[0:nn]'*ones(1,nn+1); jj=ones(nn+1,1)*[0:nn]; aa=angle(ii+i*jj); bb=min(abs(ii+i*jj),nn); % v0=fld0(end-nn:end,end-nn:end); k1=find(aa==0); k2=find(aa>0&aa<=pi/4); v0(k2)=interp1(bb(k1),v0(k1),bb(k2)); k1=find(aa==pi/2); k2=find(aa>pi/4&aa<=pi/2); v0(k2)=interp1(bb(k1),v0(k1),bb(k2)); fld0(end-nn+1:end,end-nn+1:end)=v0(2:end,2:end); fld0=sym_g(fld0,5,0); % end; warning('on','MATLAB:interp1:NaNinY'); end;%if doFill; gcmfaces/gcmfaces_convert/convert2pcol_cube.m0000644000435400001440000000514212266566744021335 0ustar gforgetusersfunction [X,Y,FLD]=convert2pcol_cube(x,y,fld,varargin); %object: gcmfaces to 'pcolor format' conversion %inputs: x is longitude (e.g. mygrid.XC) % y is latitude (e.g. mygrid.YC) % fld is the 2D field of interest (e.g. mygrid.hFacC(:,:,1)) %outputs: X,Y,FLD are array versions of x,y,fld % %note: this function is designed so that one may readily % plot the output in geographic coordinates % using e.g. 'figure; pcolor(X,Y,FLD);' k3=1; k4=1; %ASSEMBLE SIDE FACES: %---------------------- X=[x{1};x{2};sym_g(x{4},7,0); sym_g(x{5},7,0)]; Y=[y{1};y{2};sym_g(y{4},7,0); sym_g(y{5},7,0)]; FLD=[fld{1}(:,:,k3,k4);fld{2}(:,:,k3,k4);sym_g(fld{4}(:,:,k3,k4),7,0);sym_g(fld{5}(:,:,k3,k4),7,0)]; %ADD NORTH FACE: %--------------- pp=x{3}; M1=pp; M1(M1>M1(1,1))=NaN; M1(M1M2(end,1))=NaN; M2(M2=0)=1; M3=pp; M3(M3M3(end,end))=NaN; M3(~isnan(M3))=1; %M4=pp; M4(M4>M4(1,end))=NaN; M4(M4=0)=NaN; M4(pp<0)=1; pp=x{3}; Xp=[sym_g(pp.*M1,5,0);pp.*M2;sym_g(pp.*M3,7,0);sym_g(pp.*M4,6,0)]; X=[X Xp]; pp=y{3}; Yp=[sym_g(pp.*M1,5,0);pp.*M2;sym_g(pp.*M3,7,0);sym_g(pp.*M4,6,0)]; Y=[Y Yp]; pp=fld{3}(:,:,k3,k4); FLDp=[sym_g(pp.*M1,5,0);pp.*M2;sym_g(pp.*M3,7,0);sym_g(pp.*M4,6,0)]; FLD=[FLD FLDp]; %ADD SOUTH FACE: %-------------- pp=x{6}; M1=pp; M1(M1>M1(end,end))=NaN; M1(M1M2(end,1))=NaN; M2(M2=0)=1; M3=pp; M3(M3M3(1,1))=NaN; M3(~isnan(M3))=1; %M4=pp; M4(M4>M4(1,end))=NaN; M4(M4=0)=NaN; M4(pp<0)=1; pp=x{6}; Xp=[pp.*M1;sym_g(pp.*M2,5,0);sym_g(pp.*M3,6,0);sym_g(pp.*M4,7,0)]; X=[Xp X]; pp=y{6}; Yp=[pp.*M1;sym_g(pp.*M2,5,0);sym_g(pp.*M3,6,0);sym_g(pp.*M4,7,0)]; Y=[Yp Y]; pp=fld{6}(:,:,k3,k4); FLDp=[pp.*M1;sym_g(pp.*M2,5,0);sym_g(pp.*M3,6,0);sym_g(pp.*M4,7,0)]; FLD=[FLDp FLD]; %FIX DATE CHANGE LINE IN LATLON PART: %-------------------------------------- %X=circshift(X,[-240 0]); Y=circshift(Y,[-240 0]); FLD=circshift(FLD,[-240 0]); if size(x{1},1)==32; X=circshift(X,[+48 0]); Y=circshift(Y,[+48 0]); FLD=circshift(FLD,[+48 0]); elseif size(x{1},1)==510; X=circshift(X,[+765 0]); Y=circshift(Y,[+765 0]); FLD=circshift(FLD,[+765 0]); else; nn=size(x{1},1)*1.5; X=circshift(X,[+nn 0]); Y=circshift(Y,[+nn 0]); FLD=circshift(FLD,[+nn 0]); warning('you may want to check that the -180 line is the first column\n'); end; X=[X-360;X;X+360]; Y=[Y;Y;Y]; FLD=[FLD;FLD;FLD]; gcmfaces/gcmfaces_convert/convert2pcol_llpc.m0000644000435400001440000000231011600247732021323 0ustar gforgetusersfunction [X,Y,FLD]=convert2pcol_llpc(x,y,fld,varargin); %object: gcmfaces to 'pcolor format' conversion %inputs: x is longitude (e.g. mygrid.XC) % y is latitude (e.g. mygrid.YC) % fld is the 2D field of interest (e.g. mygrid.hFacC(:,:,1)) %outputs: X,Y,FLD are array versions of x,y,fld % %note: this function is designed so that one may readily % plot the output in geographic coordinates % using e.g. 'figure; pcolor(X,Y,FLD);' k3=1; k4=1; %ASSEMBLE "LATLON" FACES: %---------------------- X=[x{1};x{2};sym_g(x{3},7,0); sym_g(x{4},7,0)]; Y=[y{1};y{2};sym_g(y{3},7,0); sym_g(y{4},7,0)]; FLD=[fld{1}(:,:,k3,k4);fld{2}(:,:,k3,k4);sym_g(fld{3}(:,:,k3,k4),7,0);sym_g(fld{4}(:,:,k3,k4),7,0)]; %FIX DATE CHANGE LINE IN LATLON PART: %-------------------------------------- X=circshift(X,[55 0]); Y=circshift(Y,[55 0]); FLD=circshift(FLD,[55 0]); %ADD POINTS TO FIX DATE CHANGE LINE ELSEWHERE: %--------------------------------------------- X=[X(353:end,:);X;X(1:32,:)]; Y=[Y(353:end,:);Y;Y(1:32,:)]; FLD=[FLD(353:end,:);FLD;FLD(1:32,:)]; tmp1=X(1:64,:); tmp1(tmp1>0)=tmp1(tmp1>0)-360; X(1:64,:)=tmp1; tmp1=X(353:end,:); tmp1(tmp1<0)=tmp1(tmp1<0)+360; X(353:end,:)=tmp1; gcmfaces/gcmfaces_convert/convert2pcol_llc.m0000644000435400001440000000366412266566744021200 0ustar gforgetusersfunction [X,Y,FLD]=convert2pcol_llc(x,y,fld,varargin); %object: gcmfaces to 'pcolor format' conversion %inputs: x is longitude (e.g. mygrid.XC) % y is latitude (e.g. mygrid.YC) % fld is the 2D field of interest (e.g. mygrid.hFacC(:,:,1)) %outputs: X,Y,FLD are array versions of x,y,fld % %note: this function is designed so that one may readily % plot the output in geographic coordinates % using e.g. 'figure; pcolor(X,Y,FLD);' k3=1; k4=1; %ASSEMBLE "LATLON" FACES: %---------------------- X=[x{1};x{2};sym_g(x{4},7,0); sym_g(x{5},7,0)]; Y=[y{1};y{2};sym_g(y{4},7,0); sym_g(y{5},7,0)]; FLD=[fld{1}(:,:,k3,k4);fld{2}(:,:,k3,k4);sym_g(fld{4}(:,:,k3,k4),7,0);sym_g(fld{5}(:,:,k3,k4),7,0)]; %ADD POLAR CAP: %-------------- pp=x{3}; M1=pp; M1(M1>M1(1,1))=NaN; M1(M1M2(end,1))=NaN; M2(~isnan(M2))=1; M2=pp; M2(pp<0)=NaN; M2(pp>=0)=1; M3=pp; M3(M3M3(end,end))=NaN; M3(~isnan(M3))=1; %M3=NaN*pp; %M4=pp; M4(M4M4(1,end))=NaN; M4(~isnan(M4))=1; M4=pp; M4(pp>=0)=NaN; M4(pp<0)=1; pp=x{3}; Xp=[sym_g(pp.*M1,5,0);pp.*M2;sym_g(pp.*M3,7,0);sym_g(pp.*M4,6,0)]; X=[X Xp]; pp=y{3}; Yp=[sym_g(pp.*M1,5,0);pp.*M2;sym_g(pp.*M3,7,0);sym_g(pp.*M4,6,0)]; Y=[Y Yp]; pp=fld{3}(:,:,k3,k4); FLDp=[sym_g(pp.*M1,5,0);pp.*M2;sym_g(pp.*M3,7,0);sym_g(pp.*M4,6,0)]; FLD=[FLD FLDp]; %FIX DATE CHANGE LINE IN LATLON PART: %-------------------------------------- s1=size(X); s1=round(s1(2)/2); s2=find(diff(X(:,s1))<-180); X=circshift(X,[-s2 0]); Y=circshift(Y,[-s2 0]); FLD=circshift(FLD,[-s2 0]); %ADD POINTS TO FIX DATE CHANGE LINE ELSEWHERE: %--------------------------------------------- s1=size(X); s1=round(s1(1)/12); tmp1=X(1:2*s1,:); tmp1(tmp1>0)=tmp1(tmp1>0)-360; X(1:2*s1,:)=tmp1; tmp1=X(end-2*s1+1:end,:); tmp1(tmp1<0)=tmp1(tmp1<0)+360; X(end-2*s1+1:end,:)=tmp1; X=[X-360;X;X+360]; Y=[Y;Y;Y]; FLD=[FLD;FLD;FLD]; gcmfaces/gcmfaces_convert/convert2southern.m0000644000435400001440000000131011367365111021224 0ustar gforgetusersfunction [fld0]=convert2southern(fld00,varargin); if fld00.nFaces==1; fld00=convert2cube(fld00); end; n1=size(fld00{1},1); n2=size(fld00{1},2); n3=size(fld00{1},3); n4=size(fld00{1},4); %rotate the cube to bring f6 to f3 position fld11=fld00; fld11.nFaces=6; fld11{1}=flipdim(permute(fld00{5},[2 1 3 4]),1); fld11{2}=flipdim(permute(fld00{4},[2 1 3 4]),1); if ~isempty(fld00.f6); fld11{3}=fld00{6}; else; fld11{3}=NaN*zeros(n1,n1,n3,n4); end; fld11{4}=flipdim(permute(fld00{2},[2 1 3 4]),2); fld11{5}=flipdim(permute(fld00{1},[2 1 3 4]),2); if ~isempty(fld00.f3); fld11{6}=fld00{3}; else; fld11{6}=NaN*zeros(n1,n1,n3,n4); end; %then call convert2arctic [fld0]=convert2arctic(fld11,varargin{:}); gcmfaces/gcmfaces_convert/convert2cube.m0000644000435400001440000000103011367365111020272 0ustar gforgetusersfunction [fld11]=convert2cube(fld00); %convert2cube takes a 1 face object and format it as a cube object if ~(fld00.nFaces==1&mod(size(fld00{1},1),4)==0); error('unsupported option'); end; fld11=gcmfaces(6); n1=size(fld00{1},1)/4; n2=size(fld00{1},2); fld11{1}=fld00{1}(1:n1,:,:,:); fld11{2}=fld00{1}(n1+1:2*n1,:,:,:); fld11{3}=NaN*fld00{1}(1:n1,1:n1,:,:); fld11{4}=flipdim(permute(fld00{1}(2*n1+1:3*n1,:,:,:),[2 1 3 4]),1); fld11{5}=flipdim(permute(fld00{1}(3*n1+1:4*n1,:,:,:),[2 1 3 4]),1); fld11{6}=NaN*fld00{1}(1:n1,1:n1,:,:); gcmfaces/gcmfaces_convert/convert2vector.m0000644000435400001440000000147011600247732020664 0ustar gforgetusersfunction [a]=convert2vector(b); %object: gcmfaces to vector format conversion (if gcmfaces input) % or: vector to gcmfaces format conversion (if array input) % %notes: - if vector input, the gcmfaces format will be the one of mygrid.XC, so % the vector input must have originally been created according to convert2vector % - global mygrid parameters (mygrid.XC.gridType) are used global mygrid; if isa(b,'gcmfaces'); do_gcmfaces2vector=1; else; do_gcmfaces2vector=0; end; if do_gcmfaces2vector; bb=convert2array(b); a=bb(:); else; bb=convert2array(mygrid.XC); if mod(length(b(:)),length(bb(:)))~=0; error('vector length is inconsistent with gcmfaces objects'); else; n3=length(b(:))/length(bb(:)); end; b=reshape(b,[size(bb) n3]); a=convert2array(b); end; gcmfaces/gcmfaces_convert/convert2pcol.m0000644000435400001440000000176012266566744020341 0ustar gforgetusersfunction [X,Y,FLD]=convert2pcol(varargin); %object: gcmfaces to 'pcolor format' conversion %inputs: x is longitude (e.g. mygrid.XC) % y is latitude (e.g. mygrid.YC) % fld is the 2D field of interest (e.g. mygrid.hFacC(:,:,1)) %outputs: X,Y,FLD are array versions of x,y,fld % %note: this function is designed so that one may readily % plot the output in geographic coordinates % using e.g. 'figure; pcolor(X,Y,FLD);' input_list_check('convert2pcol',nargin); gcmfaces_global; c=varargin{1}; if isfield(mygrid,'xtrct'); [X,Y,FLD]=convert2pcol_xtrct(varargin{:}); elseif strcmp(c.gridType,'llc'); [X,Y,FLD]=convert2pcol_llc(varargin{:}); elseif strcmp(c.gridType,'cube'); [X,Y,FLD]=convert2pcol_cube(varargin{:}); elseif strcmp(c.gridType,'llpc'); [X,Y,FLD]=convert2pcol_llpc(varargin{:}); elseif strcmp(c.gridType,'ll'); [X,Y,FLD]=convert2pcol_ll(varargin{:}); else; error(['convert2pcol not implemented for ' c.gridType '!?']); end; gcmfaces/gcmfaces_convert/convert2array.m0000644000435400001440000000160112266566744020514 0ustar gforgetusersfunction [a]=convert2array(b,varargin); %object: gcmfaces to array format conversion (if gcmfaces input) % or: array to gcmfaces format conversion (if array input) % %notes: - if array input, the gcmfaces format will be the one of mygrid.XC, so % the array input must have originally been created according to convert2array % - global mygrid parameters (mygrid.XC.gridType) are used input_list_check('convert2array',nargin); gcmfaces_global; if isfield(mygrid,'xtrct'); a=convert2array_xtrct(b); elseif strcmp(mygrid.XC.gridType,'llc'); a=convert2array_llc(b); elseif strcmp(mygrid.XC.gridType,'cube'); a=convert2array_cube(b); elseif strcmp(mygrid.XC.gridType,'llpc'); a=convert2array_llpc(b); elseif strcmp(mygrid.XC.gridType,'ll'); a=convert2array_ll(b); else; error(['convert2array not implemented for ' mygrid.XC.gridType '!?']); end; gcmfaces/gcmfaces_convert/convert2array_llc.m0000644000435400001440000000256012266566744021353 0ustar gforgetusersfunction [FLD]=convert2array_llc(fld); %object: gcmfaces to array format conversion (if gcmfaces input) % or: array to gcmfaces format conversion (if array input) % %notes: if array input, the gcmfaces format will be the one of mygrid.XC, so % the array input must have originally been created according to convert2array global mygrid; if isa(fld,'gcmfaces'); do_gcmfaces2array=1; else; do_gcmfaces2array=0; end; if do_gcmfaces2array; n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); n1=size(fld.f1,1)*4; n2=size(fld.f1,2)+size(fld.f1,1); FLD=squeeze(zeros(n1,n2,n3,n4)); else; n3=max(size(fld,3),1); n4=max(size(fld,4),1); FLD=repmat(NaN*mygrid.XC,[1 1 n3 n4]); end; if do_gcmfaces2array; %ASSEMBLE "LATLON" FACES: %---------------------- FLD0=[fld.f1(:,:,:,:);fld.f2(:,:,:,:);sym_g(fld.f4(:,:,:,:),7,0);sym_g(fld.f5(:,:,:,:),7,0)]; %ADD POLAR CAP: %-------------- pp=fld.f3(:,:,:,:); FLDp=[sym_g(pp,5,0);pp.*NaN;sym_g(pp.*NaN,7,0);sym_g(pp.*NaN,6,0)]; FLD1=[FLD0 FLDp]; %store: %------ FLD(:,:,:,:)=FLD1; else; n1=size(FLD.f1,1); n2=size(FLD.f1,2); FLD.f1(:,:,:,:)=fld(1:n1,1:n2,:,:); FLD.f2(:,:,:,:)=fld(n1+[1:n1],1:n2,:,:); FLD.f3(:,:,:,:)=sym_g(fld([1:n1],n2+1:n2+n1,:,:),7,0); FLD.f4(:,:,:,:)=sym_g(fld(n1*2+[1:n1],1:n2,:,:),5,0); FLD.f5(:,:,:,:)=sym_g(fld(n1*3+[1:n1],1:n2,:,:),5,0); end; gcmfaces/gcmfaces_convert/convert2array_ll.m0000644000435400001440000000101611600205337021156 0ustar gforgetusersfunction [FLD]=convert2array_ll(fld); %object: gcmfaces to array format conversion (if gcmfaces input) % or: array to gcmfaces format conversion (if array input) % %notes: if array input, the gcmfaces format will be the one of mygrid.XC, so % the array input must have originally been created according to convert2array global mygrid; if isa(fld,'gcmfaces'); do_gcmfaces2array=1; else; do_gcmfaces2array=0; end; if do_gcmfaces2array; FLD=fld.f1; else; FLD=NaN*mygrid.XC; FLD.f1=fld; end; gcmfaces/gcmfaces_convert/convert2array_llpc.m0000644000435400001440000000252211600205337021504 0ustar gforgetusersfunction [FLD]=convert2array_llpc(fld); %object: gcmfaces to array format conversion (if gcmfaces input) % or: array to gcmfaces format conversion (if array input) % %notes: if array input, the gcmfaces format will be the one of mygrid.XC, so % the array input must have originally been created according to convert2array global mygrid; if isa(fld,'gcmfaces'); do_gcmfaces2array=1; else; do_gcmfaces2array=0; end; if do_gcmfaces2array; n3=max(size(fld.f1,3),1); n4=max(size(fld.f1,4),1); n1=size(fld.f1,1)*4; n2=size(fld.f1,2); FLD=squeeze(zeros(n1,n2,n3,n4)); else; n3=max(size(fld,3),1); n4=max(size(fld,4),1); FLD=NaN*mygrid.XC; for k3=1:n3; for k4=1:n4; for iFace=1:FLD.nFaces; iF=num2str(iFace); eval(['FLD.f' iF '(:,:,k3,k4)=FLD.f' iF '(:,:,1,1);']); end; end; end; end; for k3=1:n3; for k4=1:n4; if do_gcmfaces2array; %ASSEMBLE SIDE FACES: %---------------------- FLD1=[fld.f1(:,:,k3,k4);fld.f2(:,:,k3,k4);sym_g(fld.f3(:,:,k3,k4),7,0);sym_g(fld.f4(:,:,k3,k4),7,0)]; %store: %------ FLD(:,:,k3,k4)=FLD1; else; n1=size(FLD.f1,1); n2=size(FLD.f1,2); FLD.f1(:,:,k3,k4)=fld(1:n1,1:n2,k3,k4); FLD.f2(:,:,k3,k4)=fld(n1+[1:n1],1:n2,k3,k4); FLD.f3(:,:,k3,k4)=sym_g(fld(n1*2+[1:n1],1:n2,k3,k4),5,0); FLD.f4(:,:,k3,k4)=sym_g(fld(n1*3+[1:n1],1:n2,k3,k4),5,0); end; end; end; gcmfaces/sample_analysis/0000755000435400001440000000000012375431055015376 5ustar gforgetusersgcmfaces/sample_analysis/basic_diags_display_transport.m0000644000435400001440000000301511650106026023634 0ustar gforgetusersfunction [myplot]=basic_diags_display_transport(alldiag,ii,txt,RF,listTimes,rr,varargin); %object: display transport time series and/or time mean %inputs: alldiag.fldTRANSPORTS contains the transports time series % ii is the transport index in alldiag.fldTRANSPORTS % txt is the transport name to be displayed % RF is the depth vector % listTimes is the time vector % rr is the y axis range for plotting %optional nmean is a running mean window length (0 by default) % %note: as an example of computation leading to correct inputs, see % basic_diags_compute_v3_or_v4 (calls calc_transports) % basic_diags_display_v3_or_v4 (compile time series) gcmfaces_global; if nargin==7; nmean=varargin{1}; else; nmean=0; end; tt=[1:length(listTimes)]; nt=length(tt); TT=listTimes(tt)*3600/86400; if 1; fld=0*zeros(nt,1); for ttt=1:nt; tmp1=alldiag(tt(ttt)).fldTRANSPORTS(ii,:); fld(ttt)=sum(tmp1(:)); end; fldmean=1e-2*round(mean(fld)*1e2); fprintf([' ' txt '-- mean: ' num2str(fldmean) 'Sv\n']); if nt>1; fld=runmean(fld,nmean,1); myplot=plot(TT,fld,'LineWidth',2); title(txt); set(gca,'FontSize',14); aa=[min(TT) max(TT) rr]; axis(aa); end; else; RC=squeeze(mygrid.RC); fld=0*RC; for ttt=1:nt; tmp1=flipdim(sum(alldiag(tt(ttt)).fldTRANSPORTS(ii,:)',2),1); fld=fld+flipdim(cumsum(tmp1)/nt,1); end; if nt>1; fld(find(fld==0))=NaN; kk=find(~isnan(fld)); myplot=plot(fld(kk),RC(kk),'LineWidth',2); title(txt); set(gca,'FontSize',14); grid on; aa=axis; tmp1=max(abs(aa(1:2))); aa(1:2)=tmp1*[-1 1]; axis(aa); end; end; gcmfaces/sample_analysis/plot_one_field.m0000644000435400001440000001213211650106026020525 0ustar gforgetusersfunction []=plot_one_field(choiceV3orV4,plotMethod); %object: illustrate several methods to plot fields within gcmfaces. %inputs: choiceV3orV4 ('v3' or 'v4') selects the sample GRID % plotMethod selects the plotting method % 0) all, one after the other % 1) plot a gcmfaces object face by face % 2) use convert2array then plot in array coordinates. % 3) use convert2pcol then plot in lat-lon coordinates. % 4) use the gcmfaces front end to m_map. input_list_check('plot_one_field',nargin); gcmfaces_global; if myenv.verbose>0; gcmfaces_msg('==============================================='); gcmfaces_msg(['*** entering plot_one_field that displays ' ... 'a gridded field of ocean depth, first ' ... 'in gcmfaces and array formats. Then in geographic coordinates ' ... 'using pcolor and in various projections using m_map (if avail. in path). '],''); end; %%%%%%%%%%%%%%%%% %load parameters: %%%%%%%%%%%%%%%%% dir0=[myenv.gcmfaces_dir '/sample_input/']; dirGrid=[dir0 '/GRID' choiceV3orV4 '/']; dirIn=[dir0 '/SAMPLE' choiceV3orV4 '/']; if strcmp(choiceV3orV4,'v4'); nF=5; fileFormat='compact'; else; nF=1; fileFormat='straight'; end; mygrid=[]; grid_load(dirGrid,nF,fileFormat); %%%%%%%%%%% %get field: %%%%%%%%%%% fld=mygrid.mskC(:,:,1).*mygrid.Depth; cc=[[0:0.05:0.5] [0.6 0.75 1 1.25]]*1e4; myCmap='gray'; %%%%%%%%%%%% %plot field: %%%%%%%%%%%% if plotMethod==0|plotMethod==1; if myenv.verbose>0; gcmfaces_msg('* gcmfaces format display -- face by face.'); end; if nF==1; figure; imagescnan(fld{1}','nancolor',[1 1 1]*0.8); axis xy; cb=gcmfaces_cmap_cbar(cc,{'myCmap',myCmap}); delete(cb); elseif nF==5; figure; subplot(3,3,7); imagescnan(fld{1}','nancolor',[1 1 1]*0.8); axis xy; cb=gcmfaces_cmap_cbar(cc,{'myCmap',myCmap}); delete(cb); tmp1=axis; tmp2=text(tmp1(2)/2,tmp1(4)/2,'1','FontSize',32,'Color','r','Rotation',0); subplot(3,3,8); imagescnan(fld{2}','nancolor',[1 1 1]*0.8); axis xy; cb=gcmfaces_cmap_cbar(cc,{'myCmap',myCmap}); delete(cb); tmp1=axis; tmp2=text(tmp1(2)/2,tmp1(4)/2,'2','FontSize',32,'Color','r','Rotation',0); subplot(3,3,5); imagescnan(fld{3}','nancolor',[1 1 1]*0.8); axis xy; cb=gcmfaces_cmap_cbar(cc,{'myCmap',myCmap}); delete(cb); tmp1=axis; tmp2=text(tmp1(2)/2,tmp1(4)/2,'3','FontSize',32,'Color','r','Rotation',0); subplot(3,3,6); imagescnan(fld{4}','nancolor',[1 1 1]*0.8); axis xy; cb=gcmfaces_cmap_cbar(cc,{'myCmap',myCmap}); delete(cb); tmp1=axis; tmp2=text(tmp1(2)/2,tmp1(4)/2,'4','FontSize',32,'Color','r','Rotation',0); subplot(3,3,3); imagescnan(fld{5}','nancolor',[1 1 1]*0.8); axis xy; cb=gcmfaces_cmap_cbar(cc,{'myCmap',myCmap}); delete(cb); tmp1=axis; tmp2=text(tmp1(2)/2,tmp1(4)/2,'5','FontSize',32,'Color','r','Rotation',0); elseif nF==6; error('face by face plot for cude : not yet implemented'); end; end; if plotMethod==0|plotMethod==2; if myenv.verbose>0; gcmfaces_msg('* array format display -- all faces concatenated somehow.'); end; figure; FLD=convert2array(fld); imagescnan(FLD','nancolor',[1 1 1]*0.8); axis xy; cb=gcmfaces_cmap_cbar(cc,{'myCmap',myCmap}); %delete(cb); for ff=1:mygrid.nFaces; tmp0=0*mygrid.XC; tmp1=round(size(tmp0{ff})/2); tmp0{ff}(tmp1(1),tmp1(2))=1; tmp0=convert2array(tmp0); [ii,jj]=find(tmp0==1); if ff==3; ang=90; elseif ff>3; ang=-90; else; ang=0; end; hold on; text(ii,jj,num2str(ff),'FontSize',32,'Color','r','Rotation',ang); end; end; if plotMethod==0|plotMethod==3; if myenv.verbose>0; gcmfaces_msg('* geographical display -- using pcolor.'); end; figure; [X,Y,FLD]=convert2pcol(mygrid.XC,mygrid.YC,fld); pcolor(X,Y,FLD); if ~isempty(find(X>359)); axis([0 360 -90 90]); else; axis([-180 180 -90 90]); end; shading flat; cb=gcmfaces_cmap_cbar(cc,{'myCmap',myCmap}); delete(cb); xlabel('longitude'); ylabel('latitude'); end; if plotMethod==0|plotMethod==4; if myenv.verbose>0; gcmfaces_msg('* geographical display -- using m_map.'); end; if ~isempty(which('m_proj')); figure; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'myCmap',myCmap}); elseif myenv.verbose; fprintf('if you want to use m_map_gcmfaces, you will need to have m_map in your path\n'); end; end; %test case for depthStretchPlot: if plotMethod==0|plotMethod==5; if myenv.verbose>0; gcmfaces_msg('* section display -- using strecthed vertical coord.'); end; x=ones(length(mygrid.RC),1)*[1:200]; z=mygrid.RC*ones(1,200); c=sin(z/2000*pi).*cos(x/50*pi); figure; subplot(1,2,1); pcolor(x,z,c); shading flat; title('standard depth display'); subplot(1,2,2); depthStretchPlot('pcolor',{x,z,c}); shading flat; title('stretched depth display'); % subplot(1,2,1); plot(c(:,1),z(:,1)); title('standard depth display'); % subplot(1,2,2); depthStretchPlot('plot',{c(:,1),z(:,1)}); title('stretched depth display'); end; if myenv.verbose>0; gcmfaces_msg('*** leaving plot_one_field'); gcmfaces_msg('==============================================='); end; gcmfaces/sample_analysis/line_greatC_TUV_MASKS_v4.m0000644000435400001440000000403212117454027022072 0ustar gforgetusersfunction [lonPairs,latPairs,names]=line_greatC_TUV_MASKS_v4(); gcmfaces_global; for iy=1:23; switch iy; case 1; lonPair=[-173 -164]; latPair=[65.5 65.5]; name='Bering Strait'; case 2; lonPair=[-5 -5]; latPair=[34 40]; name='Gibraltar'; case 3; lonPair=[-81 -77]; latPair=[28 26]; name='Florida Strait'; case 4; lonPair=[-81 -79]; latPair=[28 22]; name='Florida Strait W1'; case 5; lonPair=[-76 -76]; latPair=[21 8]; name='Florida Strait S1'; case 6; lonPair=[-77 -77]; latPair=[26 24]; name='Florida Strait E1'; case 7; lonPair=[-77 -77]; latPair=[24 22]; name='Florida Strait E2'; case 8; lonPair=[-65 -50]; latPair=[66 66]; name='Davis Strait'; case 9; lonPair=[-35 -20]; latPair=[67 65]; name='Denmark Strait'; case 10; lonPair=[-16 -7]; latPair=[65 62.5]; name='Iceland Faroe'; case 11; lonPair=[-6.5 -4]; latPair=[62.5 57]; name='Faroe Scotland'; case 12; lonPair=[-4 8]; latPair=[57 62]; name='Scotland Norway'; case 13; lonPair=[-68 -63]; latPair=[-54 -66]; name='Drake Passage'; case 14; lonPair=[103 103]; latPair=[4 -1]; name='Indonesia W1'; case 15; lonPair=[104 109]; latPair=[-3 -8]; name='Indonesia W2'; case 16; lonPair=[113 118]; latPair=[-8.5 -8.5]; name='Indonesia W3'; case 17; lonPair=[118 127 ]; latPair=[-8.5 -15]; name='Indonesia W4'; case 18; lonPair=[127 127]; latPair=[-25 -68]; name='Australia Antarctica'; case 19; lonPair=[38 46]; latPair=[-10 -22]; name='Madagascar Channel'; case 20; lonPair=[46 46]; latPair=[-22 -69]; name='Madagascar Antarctica'; case 21; lonPair=[20 20]; latPair=[-30 -69.5]; name='South Africa Antarctica'; case 22; lonPair=[-76 -72]; latPair=[21 18.5]; name='Florida Strait E3'; case 23; lonPair=[-72 -72]; latPair=[18.5 10]; name='Florida Strait E4'; end; if iy==1; lonPairs=lonPair; latPairs=latPair; names={name}; else; lonPairs(iy,:)=lonPair; latPairs(iy,:)=latPair; names{iy}=name; end; end; gcmfaces/sample_analysis/plot_std_field.m0000644000435400001440000000176511617064116020556 0ustar gforgetusersfunction []=plot_std_field(choiceV3orV4); %object: compute and display a standard deviation field %inputs: choiceV3orV4 ('v3' or 'v4') selects the sample GRID input_list_check('plot_std_field',nargin); %%%%%%%%%%%%%%%%% %load parameters: %%%%%%%%%%%%%%%%% gcmfaces_global; dir0=[myenv.gcmfaces_dir '/sample_input/']; dirGrid=[dir0 '/GRID' choiceV3orV4 '/']; dirIn=[dir0 '/SAMPLE' choiceV3orV4 '/']; if strcmp(choiceV3orV4,'v4'); nF=5; fileFormat='compact'; else; nF=1; fileFormat='straight'; end; mygrid=[]; grid_load(dirGrid,nF,fileFormat); %%%%%%%%%%% %get field: %%%%%%%%%%% nameFld='DDetan'; tt=[53:78]*336; cc=[0 0.10]; fld=rdmds2gcmfaces([dirIn nameFld],tt); fld=std(fld,[],3); msk=mygrid.hFacC(:,:,1); fld(find(msk==0))=NaN; %%%%%%%%%%%% %plot field: %%%%%%%%%%%% if ~myenv.lessplot; figure; set(gcf,'Units','Normalized','Position',[0.1 0.3 0.4 0.6]); [X,Y,FLD]=convert2pcol(mygrid.XC,mygrid.YC,fld); pcolor(X,Y,FLD); axis([-180 180 -90 90]); shading flat; caxis(cc); colorbar; end; gcmfaces/sample_analysis/line_greatC_TUV_MASKS_core2_arctic.m0000644000435400001440000000217312126623454024106 0ustar gforgetusersfunction [lonPairs,latPairs,names]=line_greatC_TUV_MASKS_core2_arctic(); gcmfaces_global; for iy=1:10; switch iy; case 1; lonPair=[-21. 17.]; latPair=[79 79]; name='Fram Strait'; case 2; lonPair=[17. 100.]; latPair=[79 79]; name='Barents/Kara Sea North'; case 3; lonPair=[-170. -167.]; latPair=[66 66]; name='Bering Strait (66N)'; case 4; lonPair=[-62. -53.]; latPair=[66 66]; name='Davis Strait (66N)'; case 5; lonPair=[-37. -23.]; latPair=[66 66]; name='Greenland-Iceland (66N)'; case 6; lonPair=[-16 13]; latPair=[66 66]; name='Iceland-Norway (66N)'; case 7; lonPair=[-64 -44]; latPair=[60 60]; name='Newfoundland-Greenland (60N)'; case 8; lonPair=[-44 5]; latPair=[60 60]; name='Greenland-Norway (60N)'; % case 9; lonPair=[17. 17.]; latPair=[68 79]; name='Barents Sea Opening'; case 10; lonPair=[56. 56.]; latPair=[68 79]; name='Kara Sea Opening'; end; if iy==1; lonPairs=lonPair; latPairs=latPair; names={name}; else; lonPairs(iy,:)=lonPair; latPairs(iy,:)=latPair; names{iy}=name; end; end; gcmfaces/sample_analysis/basic_diags_compute_v3_or_v4.m0000644000435400001440000001346412057277577023307 0ustar gforgetusersfunction []=basic_diags_compute_v3_or_v4(choiceV3orV4); %object: illustrates a series of standard computations % (streamfunctions, transports, zonal means, etc.) %inputs: choiceV3orV4 ('v3' or 'v4') selects the sample GRID input_list_check('basic_diags_compute_v3_or_v4',nargin); gcmfaces_global; if myenv.verbose>0; gcmfaces_msg('==============================================='); gcmfaces_msg(['*** entering basic_diags_compute_v3_or_v4 ' ... 'that will load a set of variables form file ' ... 'and compute a series of derived diagnostics '],''); % gcmfaces_msg('*** entering basic_diags_compute_v3_or_v4',''); % gcmfaces_msg('that will load a set of variables form file',' '); % gcmfaces_msg('and compute a series of derived diagnostics',' '); end; %%%%%%%%%%%%%%%%% %load parameters: %%%%%%%%%%%%%%%%% if myenv.verbose>0; gcmfaces_msg('* set grid files path and format, and number of faces for this grid'); end; dir0=[myenv.gcmfaces_dir '/sample_input/']; dirGrid=[dir0 '/GRID' choiceV3orV4 '/']; dirIn=[dir0 '/SAMPLE' choiceV3orV4 '/']; if strcmp(choiceV3orV4,'v4'); nF=5; fileFormat='compact'; else; nF=1; fileFormat='straight'; end; if myenv.verbose>0; gcmfaces_msg('* call grid_load : load grid to memory (mygrid) according to'); gcmfaces_msg(['dirGrid = ' dirGrid],' '); gcmfaces_msg(['nFaces = ' num2str(nF)],' '); gcmfaces_msg(['fileFormat = ' fileFormat],' '); % fprintf([' > dirGrid = ' dirGrid '\n']); end; grid_load(dirGrid,nF,fileFormat); if myenv.verbose>0; gcmfaces_msg('* call gcmfaces_lines_zonal : determine grid lines that closely follow'); gcmfaces_msg('parallel lines and will be used in zonal mean and overturning computations',' '); end; if strcmp(choiceV3orV4,'v4'); gcmfaces_lines_zonal; else; gcmfaces_lines_zonal([-75:75]'); end; if myenv.verbose>0; gcmfaces_msg('* call gcmfaces_lines_transp : determine grid lines that closely follow'); gcmfaces_msg('great circles and will be used to compute transsects transports',' '); end; eval(['[lonPairs,latPairs,names]=line_greatC_TUV_MASKS_' choiceV3orV4 ';']); gcmfaces_lines_transp(lonPairs,latPairs,names); RF=squeeze(mygrid.RF)'; if myenv.verbose>0; gcmfaces_msg('* create directory for storing results to file'); end; dirOut=[dirIn 'matlabDiags/']; if ~isdir(dirOut); eval(['mkdir ' dirOut ';']); end; %%%%%%%%%%%%%%%%% %do computations: %%%%%%%%%%%%%%%%% listFld=dir([dirIn 'DDtheta.00*data']); listTimes=[]; for tt=1:length(listFld); listTimes=[listTimes;str2num(listFld(tt).name(9:end-5))]; end; for setDiags=1:2 for ttt=1:length(listTimes); tt=listTimes(ttt); % tic; if setDiags==1; if myenv.verbose>0; gcmfaces_msg('* call rdmds2gcmfaces : load velocity fields');end; fileFld='DDuvel'; msk=mygrid.hFacC; fldU=rdmds2gcmfaces([dirIn fileFld],tt); fldU=mean(fldU,4); fldU(msk==0)=NaN; fileFld='DDvvel'; msk=mygrid.hFacC; fldV=rdmds2gcmfaces([dirIn fileFld],tt); fldV=mean(fldV,4); fldV(msk==0)=NaN; if myenv.verbose>0; gcmfaces_msg('* call calc_barostream : comp. barotropic stream function');end; [fldBAR]=calc_barostream(fldU,fldV); if myenv.verbose>0; gcmfaces_msg('* call calc_overturn : comp. overturning stream function');end; [fldOV]=calc_overturn(fldU,fldV); if myenv.verbose>0; gcmfaces_msg('* call calc_transports : comp. transects transports');end; [fldTRANSPORTS]=1e-6*calc_transports(fldU,fldV,mygrid.LINES_MASKS,{'dh','dz'}); listDiags='fldBAR fldOV fldTRANSPORTS'; elseif setDiags==2; if myenv.verbose>0; gcmfaces_msg('* load tracer and transports fields');end; fileFld='DDtheta'; msk=mygrid.hFacC; fldT=rdmds2gcmfaces([dirIn fileFld],tt); fldT=mean(fldT,4); fldT(msk==0)=NaN; fileFld='DDsalt'; msk=mygrid.hFacC; fldS=rdmds2gcmfaces([dirIn fileFld],tt); fldS=mean(fldS,4); fldS(msk==0)=NaN; fileFld='ADVx_TH'; msk=mygrid.hFacW; fldADVTX=rdmds2gcmfaces([dirIn fileFld],tt); fldADVTX=mean(fldADVTX,4); fldADVTX(msk==0)=NaN; fileFld='ADVy_TH'; msk=mygrid.hFacS; fldADVTY=rdmds2gcmfaces([dirIn fileFld],tt); fldADVTY=mean(fldADVTY,4); fldADVTY(msk==0)=NaN; fileFld='ADVx_SLT'; msk=mygrid.hFacW; fldADVSX=rdmds2gcmfaces([dirIn fileFld],tt); fldADVSX=mean(fldADVSX,4); fldADVSX(msk==0)=NaN; fileFld='ADVy_SLT'; msk=mygrid.hFacS; fldADVSY=rdmds2gcmfaces([dirIn fileFld],tt); fldADVSY=mean(fldADVSY,4); fldADVSY(msk==0)=NaN; if myenv.verbose>0; gcmfaces_msg('* call calc_zonmean_T : comp. zonal mean temperature');end; [fldTzonmean]=calc_zonmean_T(fldT); if myenv.verbose>0; gcmfaces_msg('* call calc_zonmean_T : comp. zonal mean salinity');end; [fldSzonmean]=calc_zonmean_T(fldS); if myenv.verbose>0; gcmfaces_msg('* call calc_MeridionalTransport : comp. meridional heat transport');end; [fldMT_H]=1e-15*4e6*calc_MeridionalTransport(fldADVTX,fldADVTY); if myenv.verbose>0; gcmfaces_msg('* infer meridional fresh water transport from meridional salt transport');end; [fldMT_FW]=1e-6/35*calc_MeridionalTransport(fldADVSX,fldADVSY);%needs revision listDiags='fldTzonmean fldSzonmean fldMT_H fldMT_FW'; end; fileOut=[dirOut 'set' num2str(setDiags) '_' num2str(tt) '.mat']; if myenv.verbose>0; gcmfaces_msg(['* save diagnostics to fileOut = ' fileOut]); end; eval(['save ' fileOut ' ' listDiags ';']); % fprintf([num2str(ttt) '/' num2str(length(listTimes)) ' done in ' num2str(toc) '\n']); end;%for ttt=1:length(listTimes); end;%for setDiags=1:2 if myenv.verbose>0; gcmfaces_msg('*** leaving basic_diags_compute_v3_or_v4'); gcmfaces_msg('===============================================',''); end; gcmfaces/sample_analysis/basic_diags_display_v3_or_v4.m0000644000435400001440000001473712272607634023272 0ustar gforgetusersfunction []=basic_diags_display_v3_or_v4(choiceV3orV4); %object: display the result of basic_diags_compute_v3_or_v4 %inputs: choiceV3orV4 ('v3' or 'v4') selects the sample GRID input_list_check('basic_diags_display_v3_or_v4',nargin); gcmfaces_global; if myenv.verbose>0; gcmfaces_msg('==============================================='); gcmfaces_msg(['*** entering basic_diags_display_v3_or_v4 ' ... 'that will display (as a figure or as text) the results of basic_diags_compute_v3_or_v4'],''); end; %%%%%%%%%%%%%%%%% %load parameters: %%%%%%%%%%%%%%%%% dir0=[myenv.gcmfaces_dir '/sample_input/']; dirGrid=[dir0 '/GRID' choiceV3orV4 '/']; dirIn=[dir0 '/SAMPLE' choiceV3orV4 '/']; if strcmp(choiceV3orV4,'v4'); nF=5; fileFormat='compact'; else; nF=1; fileFormat='straight'; end; grid_load(dirGrid,nF,fileFormat); if strcmp(choiceV3orV4,'v4'); LATS=[-89:89]'; else; LATS=[-75:75]'; end; gcmfaces_lines_zonal(LATS); eval(['[lonPairs,latPairs,names]=line_greatC_TUV_MASKS_' choiceV3orV4 ';']); gcmfaces_lines_transp(lonPairs,latPairs,names); RF=squeeze(mygrid.RF)'; dirOut=[dirIn 'matlabDiags/']; if ~isdir(dirOut); eval(['mkdir ' dirOut ';']); end; %%%$%%%%%%%% %do display: %%%%$%%%%%%% listFld=dir([dirIn 'DDtheta.00*data']); listTimes=[]; for tt=1:length(listFld); listTimes=[listTimes;str2num(listFld(tt).name(9:end-5))]; end; for setDiags=1:2 %%%%%%%%%%%%%%%%%%%%%%%%% %load pre-computed diags: %%%%%%%%%%%%%%%%%%%%%%%%% for ttt=1:length(listTimes); tt=listTimes(ttt); eval(['load ' dirOut 'set' num2str(setDiags) '_' num2str(tt) '.mat;']); if setDiags==1; listDiags={'fldBAR','fldOV','fldTRANSPORTS'}; elseif setDiags==2; listDiags={'fldTzonmean','fldSzonmean','fldMT_H','fldMT_FW'}; else; 0 end; clear tmpdiag; for ii=1:length(listDiags); eval(['tmpdiag.' listDiags{ii} '=' listDiags{ii} ';']); end; if ttt==1; alldiag=tmpdiag; else; alldiag(ttt)=tmpdiag; end; end; %%%%%%%%%%%%%%% %display diags: %%%%%%%%%%%%%%% if setDiags==1; tt=[1]; nt=length(tt); TT=listTimes(tt)*3600/86400; %barotropic streamfunction: fld=0*alldiag(1).fldBAR; for ttt=tt; fld=fld+alldiag(ttt).fldBAR/nt; end; fldBF=fld; [X,Y,FLD]=convert2pcol(mygrid.XC,mygrid.YC,fld); cc=[[-200:40:-40] [-30:10:80]]; figure; pcolor(X,Y,FLD); axis([-180 180 -90 90]); set(gcf,'Renderer','zbuffer'); shading interp; colormap(jet(16)); caxis([-50 50]); colorbar; title('Horizontal Stream Function'); %meridional streamfunction: fld=0*alldiag(1).fldOV; for ttt=tt; fld=fld+alldiag(ttt).fldOV/nt; end; fldOV=fld; X=LATS*ones(1,length(RF)); Y=ones(length(LATS),1)*RF; cc=[[-50:10:-30] [-24:3:24] [30:10:50]]; figure; pcolor(X,Y,fld); axis([-90 90 -6000 0]); set(gcf,'Renderer','zbuffer'); shading interp; colormap(jet(16)); caxis([-25 25]); colorbar; title('Meridional Stream Function'); tt=[1:length(alldiag)]; nt=length(tt); TT=listTimes(tt)*3600/86400; if myenv.verbose>0; gcmfaces_msg('* call basic_diags_display_transport : print and/or plot transports');end; %Bering Strait and Arctic/Atlantic exchanges: if nt>1; figure; orient tall; end; iiList=[1 8:12]; rrList=[[-1 3];[-3 1];[-6 2];[-3 9];[-9 3];[-0.5 0.5]]; for iii=1:length(iiList); ii=iiList(iii); if nt>1; subplot(3,2,iii); end; basic_diags_display_transport(alldiag,ii,[mygrid.LINES_MASKS(ii).name ' (>0 to Arctic)'],RF,listTimes,rrList(iii,:)); end; %Florida Strait: if nt>1; figure; orient tall; end; iiList=[3 4 6 7]; rrList=[[0 35];[0 35];[-10 10];[-10 10]]; for iii=1:length(iiList); ii=iiList(iii); if nt>1; subplot(2,2,iii); end; basic_diags_display_transport(alldiag,ii,[mygrid.LINES_MASKS(ii).name ' (>0 to Atlantic)'],RF,listTimes,rrList(iii,:)); end; %Drake, ACC etc: if nt>1; figure; orient tall; end; iiList=[13 NaN 20 19 18]; rrList=[[120 200];[NaN NaN];[120 200];[-40 10];[120 200]]; for iii=1:length(iiList); ii=iiList(iii); if ~isnan(ii); if nt>1; subplot(3,2,iii); end; basic_diags_display_transport(alldiag,ii,[mygrid.LINES_MASKS(ii).name ' (>0 to the West)'],RF,listTimes,rrList(iii,:)); end; end; %Indonesian Throughflow special case: if nt>1; subplot(3,2,6); end; basic_diags_display_transport(alldiag,[14:17],'Indonesian Throughflow (>0 to the West)',RF,listTimes,[-40 10]); elseif setDiags==2; tt=[1:length(alldiag)]; nt=length(tt); TT=listTimes(tt)*3600/86400; fld=0*zeros(nt,length(LATS)); kk=1; for ttt=1:nt; tmp1=alldiag(tt(ttt)).fldTzonmean(:,kk); fld(ttt,:)=tmp1'; end; x=TT*ones(1,length(LATS)); y=ones(nt,1)*LATS'; figure; set(gcf,'Renderer','zbuffer'); if nt>1; pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); colormap(jet(15)); caxis([-3 30]); colorbar; else; plot(y,fld); aa=axis; aa(1:2)=max(abs(aa(1:2)))*[-1 1]; axis(aa); grid on; end; set(gca,'FontSize',14); title(['zonal mean T -- in degC -- at ' num2str(mygrid.RC(kk)) 'm']); fld=0*zeros(nt,length(LATS)); kk=1; for ttt=1:nt; tmp1=alldiag(tt(ttt)).fldSzonmean(:,kk); fld(ttt,:)=tmp1'; end; x=TT*ones(1,length(LATS)); y=ones(nt,1)*LATS'; figure; set(gcf,'Renderer','zbuffer'); if nt>1; pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); colormap(jet(15)); caxis([32 36]); colorbar; else; plot(y,fld); aa=axis; aa(1:2)=max(abs(aa(1:2)))*[-1 1]; axis(aa); grid on; end; set(gca,'FontSize',14); title(['zonal mean S -- in psu -- at ' num2str(mygrid.RC(kk)) 'm']); fld=0*zeros(nt,length(alldiag(1).fldMT_H)); for ttt=1:nt; tmp1=alldiag(tt(ttt)).fldMT_H; fld(ttt,:)=tmp1'; end; x=TT*ones(1,length(alldiag(1).fldMT_H)); y=ones(nt,1)*LATS'; figure; set(gcf,'Renderer','zbuffer'); if nt>1; pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); colormap(jet(15)); caxis([-2 2]); colorbar; else; plot(y,fld); aa=axis; aa(1:2)=max(abs(aa(1:2)))*[-1 1]; aa(3:4)=max(abs(aa(3:4)))*[-1 1]; axis(aa); grid on; end; set(gca,'FontSize',14); title('Meridional Heat Transport (in PW)'); set(gca,'FontSize',14); fld=0*zeros(nt,length(alldiag(1).fldMT_FW)); for ttt=1:nt; tmp1=alldiag(tt(ttt)).fldMT_FW; fld(ttt,:)=tmp1'; end; x=TT*ones(1,length(alldiag(1).fldMT_FW)); y=ones(nt,1)*LATS'; figure; set(gcf,'Renderer','zbuffer'); if nt>1; pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); colormap(jet(15)); caxis([-1 1]); colorbar; else; plot(y,fld); aa=axis; aa(1:2)=max(abs(aa(1:2)))*[-1 1]; aa(3:4)=max(abs(aa(3:4)))*[-1 1]; axis(aa); grid on; end; set(gca,'FontSize',14); title('Meridional FW Transport (in ??)'); set(gca,'FontSize',14); end;%if setDiags==1; end;%for setDiags=1:2 if myenv.verbose>0; gcmfaces_msg('*** leaving basic_diags_display_v3_or_v4'); gcmfaces_msg('===============================================',''); end; gcmfaces/sample_analysis/line_greatC_TUV_MASKS_v3.m0000644000435400001440000000364711617064116022104 0ustar gforgetusersfunction [lonPairs,latPairs,names]=line_greatC_TUV_MASKS_v3(); gcmfaces_global; for iy=1:21; switch iy; case 1; lonPair=[-173 -164]; latPair=[65.5 65.5]; name='Bering Strait'; case 2; lonPair=[-5 -5]; latPair=[34 40]; name='Gibraltar'; case 3; lonPair=[-81 -75]; latPair=[28 26]; name='Florida Strait'; case 4; lonPair=[-81 -79]; latPair=[28 22]; name='Florida Strait W1'; case 5; lonPair=[-76 -76]; latPair=[21 8]; name='Florida Strait S1'; case 6; lonPair=[-75 -75]; latPair=[26 24]; name='Florida Strait E1'; case 7; lonPair=[-75 -75]; latPair=[24 21]; name='Florida Strait E2'; case 8; lonPair=[-65 -50]; latPair=[66 66]; name='Davis Strait'; case 9; lonPair=[-35 -20]; latPair=[67 65]; name='Denmark Strait'; case 10; lonPair=[-16 -7]; latPair=[65 62.5]; name='Iceland Feroe'; case 11; lonPair=[-6.5 -4]; latPair=[62.5 57]; name='Feroe England'; case 12; lonPair=[-4 8]; latPair=[57 62]; name='England Norway'; case 13; lonPair=[-68 -63]; latPair=[-54 -66]; name='Drake Passage'; case 14; lonPair=[103 103]; latPair=[4 -1]; name='Indonesia W1'; case 15; lonPair=[104 109]; latPair=[-3 -7]; name='Indonesia W2'; case 16; lonPair=[113 118]; latPair=[-7.5 -7.5]; name='Indonesia W3'; case 17; lonPair=[118 127 ]; latPair=[-7.5 -15]; name='Indonesia W4'; case 18; lonPair=[127 127]; latPair=[-25 -68]; name='Australia Antarctica'; case 19; lonPair=[38 46]; latPair=[-10 -22]; name='Madagascar Channel'; case 20; lonPair=[46 46]; latPair=[-22 -69]; name='Madagascar Antarctica'; case 21; lonPair=[20 20]; latPair=[-30 -72]; name='South Africa Antarctica'; end; lonPair(lonPair<0)=lonPair(lonPair<0)+360; if iy==1; lonPairs=lonPair; latPairs=latPair; names={name}; else; lonPairs(iy,:)=lonPair; latPairs(iy,:)=latPair; names{iy}=name; end; end; gcmfaces/sample_analysis/line_greatC_TUV_MASKS_core2_antarctic.m0000644000435400001440000000136512126623454024613 0ustar gforgetusersfunction [lonPairs,latPairs,names]=line_greatC_TUV_MASKS_core2_antarctic(); gcmfaces_global; for iy=1:5; switch iy; case 1; lonPair=[20. 20.]; latPair=[-80. -50.]; name='Weddell-Indian (20E)'; case 2; 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R /ID [<88048667300CB0C830284FF3001F3897><88048667300CB0C830284FF3001F3897>] >> startxref 1552492 %%EOF gcmfaces/gcmfaces_demo.m0000644000435400001440000000244412006027054015137 0ustar gforgetusers %choose grid for test fprintf('\n Please set the demo grid : \n'); fprintf(' ''llc'': lat-lon-cap grid (5 faces). \n'); fprintf(' ''ll'' : simple lat-lon grid (1 face). \n'); choiceGrid=input(' and type return. ''llc'' is the default.\n'); if isempty(choiceGrid); choiceGrid='llc'; end; if strcmp(choiceGrid,'llc'); choiceGrid='v4'; elseif strcmp(choiceGrid,'ll'); choiceGrid='v3'; else; error('wrong grid choice'); end; %choose verbise level fprintf('\n Please set the amount of explanatory text display :\n'); fprintf(' 0: none.\n'); fprintf(' 1: comments.\n'); fprintf(' 2: comments preceeded with calling sequence.\n'); fprintf(' 3: same as 2, but preceeded with pause.\n'); verbose=input(' and/or type return. 0 is the default. \n'); if isempty(verbose); verbose=0; end; %initialize environment variables and mygrid gcmfaces_global; myenv.verbose=verbose; if myenv.verbose>0; gcmfaces_msg('* set path and environment variables (myenv) by calling gcmfaces_global'); end; basic_diags_compute_v3_or_v4(choiceGrid); basic_diags_display_v3_or_v4(choiceGrid); example_bin_average(choiceGrid,1);%incl. call to example_smooth.m; example_griddata(choiceGrid); example_interp(choiceGrid); example_faces2latlon2faces(choiceGrid); plot_one_field(choiceGrid,0);%%incl. call to m_map_gcmfaces; gcmfaces/gcmfaces_init.m0000644000435400001440000000214111625272017015157 0ustar gforgetusers gcmfaces_global; test0=dir('sample_input'); if isempty(test0); fprintf('no sample input data found\n'); return; end; warning('off','MATLAB:HandleGraphics:noJVM'); if myenv.verbose; fprintf('\n\n\n***********message from gcmfaces_init.m************\n '); fprintf(' starting basic test : plot_std_field ... \n'); end; plot_std_field('v4'); if ~myenv.lessplot; if myenv.verbose; fprintf('\n\n\n***********message from gcmfaces_init.m************\n '); fprintf(' starting plot test: plot_one_field ... \n'); end; plot_one_field('v4',0); end; if ~myenv.lesstest; if myenv.verbose; fprintf('\n\n\n***********message from gcmfaces_init.m************\n '); fprintf(' starting computations test: basic_diags_compute_v3_or_v4 ... \n'); end; basic_diags_compute_v3_or_v4('v4'); if ~myenv.lessplot; basic_diags_display_v3_or_v4('v4'); end; end; if myenv.verbose; fprintf('\n\n\n***********message from gcmfaces_init.m************\n'); fprintf(' --- initialization of gcmfaces completed correctly \n'); fprintf(' --- you are all set and may now use the gcmfaces package. \n\n\n'); end; gcmfaces/gcmfaces_devel/0000755000435400001440000000000012375431055015141 5ustar gforgetusersgcmfaces/gcmfaces_devel/README0000644000435400001440000000017411511447225016020 0ustar gforgetusers This directory is meant for routines that are in early stage development -- until they find a place in another directory. gcmfaces/gcmfaces_diags/0000755000435400001440000000000012375431055015131 5ustar gforgetusersgcmfaces/gcmfaces_diags/diags_set_E.m0000644000435400001440000003627712276601102017524 0ustar gforgetusers %select kBudget: if ~isempty(setDiagsParams); kBudget=setDiagsParams{1}; else; kBudget=1; end; %override default file name: %--------------------------- tmp1=setDiags; if kBudget>1; tmp1=sprintf('E%02i',kBudget); end; fileMat=['diags_set_' tmp1]; if userStep==1;%diags to be computed listDiags=['zm_area zm_vol_ocn zm_vol_tot zm_vol_ice']; listDiags=[listDiags ' zm_heat_ocn zm_heat_tot zm_heat_ice zm_heat_ocn_diff']; listDiags=[listDiags ' zm_salt_ocn zm_salt_tot zm_salt_ice zm_salt_ocn_diff']; elseif userStep==2;%input files and variables listFlds={ 'ETAN','SIheff','SIhsnow','THETA ','SALT ','PHIBOT'}; listFlds={listFlds{:},'SIatmFW ','oceFWflx','SItflux','TFLUX','SFLUX','oceSPflx','SRELAX'}; listFlds={listFlds{:},'oceQnet ','SIatmQnt','SIaaflux','SIsnPrcp','SIacSubl'}; listFlds={listFlds{:},'TRELAX','WTHMASS','WSLTMASS','oceSflux','oceQsw','oceSPtnd'}; if kBudget>1; listFlds={listFlds{:},'ADVr_TH','DFrE_TH','DFrI_TH','ADVr_SLT','DFrE_SLT','DFrI_SLT','WVELMASS'}; end; listFlds={listFlds{:},'UVELMASS','VVELMASS','AB_gT','AB_gS'}; listFlds={listFlds{:},'ADVx_TH ','ADVy_TH ','DFxE_TH ','DFyE_TH '}; listFlds={listFlds{:},'ADVx_SLT','ADVy_SLT','DFxE_SLT','DFyE_SLT'}; listFlds={listFlds{:},'ADVxHEFF','ADVyHEFF','DFxEHEFF','DFyEHEFF'}; listFlds={listFlds{:},'ADVxSNOW','ADVySNOW','DFxESNOW','DFyESNOW'}; listFldsNames=deblank(listFlds); % listFiles={'rate_budg2d_snap_set1','budg2d_hflux_set1','budg2d_zflux_set1','budg2d_zflux_set2'}; if kBudget==1; listFiles={listFiles{:},'rate_budg2d_snap_set2','budg2d_hflux_set2'}; else; tmp1=sprintf('rate_budg2d_snap_set3_%02i',kBudget); tmp2=sprintf('budg2d_zflux_set3_%02i',kBudget); tmp3=sprintf('budg2d_hflux_set3_%02i',kBudget); listFiles={listFiles{:},tmp1,tmp2,tmp3}; end; listSubdirs={[dirMat 'BUDG/' ],[dirMat '../BUDG/' ],[dirModel 'diags/BUDG/']}; elseif userStep==3;%computational part; %preliminary tests test1=isempty(dir([dirModel 'diags/BUDG/budg2d_snap_set1*'])); test2=isempty(dir([dirMat 'BUDG/rate_budg2d_snap_set1*']))&... isempty(dir([dirMat '../BUDG/rate_budg2d_snap_set1*'])); if (strcmp(setDiags,'E')&test1&test2); fprintf('\n abort : global and regional budgets, due to missing \n'); fprintf(['\n ' dirModel 'diags/BUDG/budg2d_snap_set1* \n']); return; end; if (strcmp(setDiags,'E')&test2); fprintf('\n abort : global and regional budgets, due to missing \n'); fprintf(['\n ' dirModel 'diags/BUDG/rate_budg2d_snap_set1* \n']); return; end; %override default file name: %--------------------------- tmp1=setDiags; if kBudget>1; tmp1=sprintf('E%02i',kBudget); end; fileMat=['diags_set_' tmp1 '_' num2str(tt) '.mat']; %fill in optional fields: %------------------------ if isempty(who('TRELAX')); TRELAX=0*mygrid.XC; end; if isempty(who('SRELAX')); SRELAX=0*mygrid.XC; end; if isempty(who('AB_gT')); AB_gT=0*mygrid.XC; end; if isempty(who('AB_gS')); AB_gS=0*mygrid.XC; end; if isempty(who('oceSPtnd')); oceSPtnd=0*mygrid.XC; end; if isempty(who('oceSPflx')); oceSPflx=0*mygrid.XC; end; if isempty(who('PHIBOT')); PHIBOT=0*mygrid.XC; end; %=======MASS========= %compute mapped budget: %---------------------- %mass = myparms.rhoconst * sea level contOCN=ETAN*myparms.rhoconst; contICE=(SIheff*myparms.rhoi+SIhsnow*myparms.rhosn); %for deep ocean layer : if kBudget>1&myparms.useNLFS<2; contOCN=0; elseif kBudget>1;%rstar case tmp1=mk3D(mygrid.DRF,mygrid.hFacC).*mygrid.hFacC; tmp2=sum(tmp1(:,:,kBudget:length(mygrid.RC)),3)./mygrid.Depth; contOCN=tmp2.*ETAN*myparms.rhoconst; end; % contTOT=contOCN+contICE; %vertical divergence (air-sea fluxes or vertical advection) zdivOCN=oceFWflx; zdivICE=SIatmFW-oceFWflx; %in virtual salt flux we omit : if ~myparms.useRFWF; zdivOCN=0*zdivOCN; end; %for deep ocean layer : if kBudget>1; zdivOCN=-WVELMASS*myparms.rhoconst; end; % zdivTOT=zdivOCN+zdivICE; %horizontal divergence (advection and ice diffusion) hdivOCN=myparms.rhoconst*calc_UV_conv(UVELMASS,VVELMASS,{'dh'}); %for 2D, already vertically integrated, fields tmpU=(myparms.rhoi*DFxEHEFF+myparms.rhosn*DFxESNOW+myparms.rhoi*ADVxHEFF+myparms.rhosn*ADVxSNOW); tmpV=(myparms.rhoi*DFyEHEFF+myparms.rhosn*DFyESNOW+myparms.rhoi*ADVyHEFF+myparms.rhosn*ADVySNOW); hdivICE=calc_UV_conv(tmpU,tmpV); %no dh needed here hdivTOT=hdivOCN+hdivICE; %bottom pressure for comparison: bp=myparms.rhoconst/9.81*PHIBOT; [zm_vol_tot,zm_area]=calc_budget_mean_zonal(contTOT,zdivTOT,hdivTOT); zm_vol_ocn=calc_budget_mean_zonal(contOCN,zdivOCN,hdivOCN); zm_vol_ice=calc_budget_mean_zonal(contICE,zdivICE,hdivICE); %=======HEAT======= contOCN=myparms.rcp*THETA-myparms.rcp*AB_gT; contICE=-myparms.flami*(SIheff*myparms.rhoi+SIhsnow*myparms.rhosn); contTOT=contOCN+contICE; %vertical divergence (air-sea fluxes or vertical adv/dif) zdivOCN=TFLUX; zdivICE=-(SItflux+TFLUX-TRELAX); %in linear surface we omit : if ~myparms.useNLFS; zdivOCN=zdivOCN-myparms.rcp*WTHMASS; end; %in virtual salt flux we omit : if ~myparms.useRFWF|~myparms.useNLFS; zdivICE=zdivICE+SIaaflux; end; %working approach for real fresh water (?) and virtual salt flux if 0; zdivICE=-oceQnet-SIatmQnt-myparms.flami*(SIsnPrcp-SIacSubl); end; %for deep ocean layer : if kBudget>1; zdivOCN=-(ADVr_TH+DFrE_TH+DFrI_TH)./mygrid.RAC*myparms.rcp; dd=mygrid.RF(kBudget); msk=mygrid.mskC(:,:,kBudget); swfrac=0.62*exp(dd/0.6)+(1-0.62)*exp(dd/20); if dd<-200; swfrac=0; end; zdivOCN=zdivOCN+swfrac*oceQsw;%.*msk; end; % zdivTOT=zdivOCN+zdivICE; %horizontal divergence (advection and diffusion) tmpU=myparms.rcp*(ADVx_TH+DFxE_TH); tmpV=myparms.rcp*(ADVy_TH+DFyE_TH); hdivOCN=calc_UV_conv(tmpU,tmpV); tmpU=-myparms.flami*(myparms.rhoi*DFxEHEFF+myparms.rhosn*DFxESNOW+myparms.rhoi*ADVxHEFF+myparms.rhosn*ADVxSNOW); tmpV=-myparms.flami*(myparms.rhoi*DFyEHEFF+myparms.rhosn*DFyESNOW+myparms.rhoi*ADVyHEFF+myparms.rhosn*ADVySNOW); hdivICE=calc_UV_conv(tmpU,tmpV); %no dh needed here hdivTOT=hdivOCN+hdivICE; zm_heat_tot=calc_budget_mean_zonal(contTOT,zdivTOT,hdivTOT); zm_heat_ocn=calc_budget_mean_zonal(contOCN,zdivOCN,hdivOCN); zm_heat_ice=calc_budget_mean_zonal(contICE,zdivICE,hdivICE); %ocean diffusion alone tmpU=myparms.rcp*(DFxE_TH); tmpV=myparms.rcp*(DFyE_TH); hdivOCN=calc_UV_conv(tmpU,tmpV); zm_heat_ocn_diff=calc_budget_mean_zonal(0*contOCN,0*zdivOCN,hdivOCN); %=======SALT======= contOCN=myparms.rhoconst*SALT-myparms.rhoconst*AB_gS; contICE=myparms.SIsal0*myparms.rhoi*SIheff; contTOT=contOCN+contICE; %vertical divergence (air-sea fluxes or vertical adv/dif) zdivOCN=SFLUX+oceSPflx; zdivICE=-zdivOCN+SRELAX; %in linear surface we omit : if ~myparms.useNLFS; zdivOCN=zdivOCN-myparms.rhoconst*WSLTMASS; end; %working approach for real fresh water (?) and virtual salt flux if ~myparms.useRFWF|~myparms.useNLFS; zdivICE=-oceSflux; end; %for deep ocean layer : if kBudget>1; zdivOCN=-(ADVr_SLT+DFrE_SLT+DFrI_SLT)./mygrid.RAC*myparms.rhoconst; zdivOCN=zdivOCN+oceSPtnd;%.*msk; end; zdivTOT=zdivOCN+zdivICE; %horizontal divergence (advection and diffusion) tmpU=myparms.rhoconst*(ADVx_SLT+DFxE_SLT); tmpV=myparms.rhoconst*(ADVy_SLT+DFyE_SLT); hdivOCN=calc_UV_conv(tmpU,tmpV); tmpU=myparms.SIsal0*(myparms.rhoi*DFxEHEFF+myparms.rhoi*ADVxHEFF); tmpV=myparms.SIsal0*(myparms.rhoi*DFyEHEFF+myparms.rhoi*ADVyHEFF); hdivICE=calc_UV_conv(tmpU,tmpV); %no dh needed here hdivTOT=hdivOCN+hdivICE; zm_salt_tot=calc_budget_mean_zonal(contTOT,zdivTOT,hdivTOT); zm_salt_ocn=calc_budget_mean_zonal(contOCN,zdivOCN,hdivOCN); zm_salt_ice=calc_budget_mean_zonal(contICE,zdivICE,hdivICE); %ocean diffusion alone tmpU=myparms.rhoconst*(DFxE_SLT); tmpV=myparms.rhoconst*(DFyE_SLT); hdivOCN=calc_UV_conv(tmpU,tmpV); zm_salt_ocn_diff=calc_budget_mean_zonal(0*contOCN,0*zdivOCN,hdivOCN); %===================== COMPUTATIONAL SEQUENCE ENDS =========================% %===================== PLOTTING SEQUENCE BEGINS =========================% elseif userStep==-1;%plotting if isempty(setDiagsParams); choicePlot={'all'}; elseif isnumeric(setDiagsParams{1})&length(setDiagsParams)==1; choicePlot={'all'}; elseif isnumeric(setDiagsParams{1}); choicePlot={setDiagsParams{2:end}}; else; choicePlot=setDiagsParams; end; tt=[1:length(alldiag.listTimes)]; TT=alldiag.listTimes(tt); nt=length(TT); if (kBudget==1)&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mass'))); %1.1) ocean+seaice mass budgets %------------------------------ figureL; %volume budget: subplot(2,1,1); disp_budget_mean_zonal(mygrid.LATS,alldiag.zm_vol_tot,'kg/m2','Mass (incl. ice)'); %cumulative integral: tmp1=repmat(alldiag.zm_area,[3 1 1]); tmp1=tmp1.*alldiag.zm_vol_tot; cumbudg=cumsum(tmp1,2); subplot(2,1,2); disp_budget_mean_zonal(mygrid.LATS,cumbudg,'kg','Mass (incl. ice)'); %add to tex file myCaption={myYmeanTxt,'mass budget (ocean+ice) at each latitude in kg/m2 (upper) and integrated from South (lower).'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; %1.2) ice mass budgets %--------------------- figureL; %volume budget: subplot(2,1,1); disp_budget_mean_zonal(mygrid.LATS,alldiag.zm_vol_ice,'kg/m2','Mass (only ice)'); %cumulative integral: tmp1=repmat(alldiag.zm_area,[3 1 1]); tmp1=tmp1.*alldiag.zm_vol_ice; cumbudg=cumsum(tmp1,2); subplot(2,1,2); disp_budget_mean_zonal(mygrid.LATS,cumbudg,'kg','Mass (only ice)'); %add to tex file myCaption={myYmeanTxt,'mass budget (only ice) at each latitude in kg/m2 (upper) and integrated from South (lower).'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mass'))); %1.3) ocean mass budgets %----------------------- figureL; %volume budget: subplot(2,1,1); disp_budget_mean_zonal(mygrid.LATS,alldiag.zm_vol_ocn,'kg/m2','Mass (ocean only)'); %cumulative integral: tmp1=repmat(alldiag.zm_area,[3 1 1]); tmp1=tmp1.*alldiag.zm_vol_ocn; cumbudg=cumsum(tmp1,2); subplot(2,1,2); disp_budget_mean_zonal(mygrid.LATS,cumbudg,'kg','Mass (ocean only)'); %add to tex file myCaption={myYmeanTxt,'mass budget (ocean only) at each latitude in kg/m2 (upper) and integrated from South (lower).'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; end; if (kBudget==1)&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'heat'))); %1.1) ocean+seaice heat budgets %------------------------------ figureL; %heat budget: subplot(2,1,1); disp_budget_mean_zonal(mygrid.LATS,alldiag.zm_heat_tot,'J/m2','Heat (incl. ice)'); %cumulative integral: tmp1=repmat(alldiag.zm_area,[3 1 1]); tmp1=tmp1.*alldiag.zm_heat_tot; cumbudg=cumsum(tmp1,2); subplot(2,1,2); disp_budget_mean_zonal(mygrid.LATS,cumbudg,'J','Heat (incl. ice)'); %add to tex file myCaption={myYmeanTxt,'heat budget (ocean+ice) at each latitude in J/m2 (upper) and integrated from South (lower).'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; %1.2) ice heat budgets %--------------------- figureL; %heat budget: subplot(2,1,1); disp_budget_mean_zonal(mygrid.LATS,alldiag.zm_heat_ice,'J/m2','Heat (only ice)'); %cumulative integral: tmp1=repmat(alldiag.zm_area,[3 1 1]); tmp1=tmp1.*alldiag.zm_heat_ice; cumbudg=cumsum(tmp1,2); subplot(2,1,2); disp_budget_mean_zonal(mygrid.LATS,cumbudg,'J','Heat (only ice)'); %add to tex file myCaption={myYmeanTxt,'heat budget (only ice) at each latitude in J/m2 (upper) and integrated from South (lower).'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'heat'))); %1.3) ocean heat budgets %----------------------- figureL; %heat budget: subplot(2,1,1); disp_budget_mean_zonal(mygrid.LATS,alldiag.zm_heat_ocn,'J/m2','Heat (ocean only)'); %cumulative integral: tmp1=repmat(alldiag.zm_area,[3 1 1]); tmp1=tmp1.*alldiag.zm_heat_ocn; cumbudg=cumsum(tmp1,2); subplot(2,1,2); disp_budget_mean_zonal(mygrid.LATS,cumbudg,'J','Heat (ocean only)'); %add to tex file myCaption={myYmeanTxt,'heat budget (ocean only) at each latitude in J/m2 (upper) and integrated from South (lower).'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; end; if (kBudget==1)&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'salt'))); %1.1) ocean+seaice salt budgets %------------------------------ figureL; %salt budget: subplot(2,1,1); disp_budget_mean_zonal(mygrid.LATS,alldiag.zm_salt_tot,'g/m2','Salt (incl. ice)'); %cumulative integral: tmp1=repmat(alldiag.zm_area,[3 1 1]); tmp1=tmp1.*alldiag.zm_salt_tot; cumbudg=cumsum(tmp1,2); subplot(2,1,2); disp_budget_mean_zonal(mygrid.LATS,cumbudg,'g','Salt (incl. ice)'); %add to tex file myCaption={myYmeanTxt,'salt budget (ocean+ice) at each latitude in g/m2 (upper) and integrated from South (lower).'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; %1.2) ice salt budgets %--------------------- figureL; %salt budget: subplot(2,1,1); disp_budget_mean_zonal(mygrid.LATS,alldiag.zm_salt_ice,'g/m2','Salt (only ice)'); %cumulative integral: tmp1=repmat(alldiag.zm_area,[3 1 1]); tmp1=tmp1.*alldiag.zm_salt_ice; cumbudg=cumsum(tmp1,2); subplot(2,1,2); disp_budget_mean_zonal(mygrid.LATS,cumbudg,'g','Salt (only ice)'); %add to tex file myCaption={myYmeanTxt,'salt budget (only ice) at each latitude in g/m2 (upper) and integrated from South (lower).'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'salt'))); %1.3) ocean salt budgets %----------------------- figureL; %salt budget: subplot(2,1,1); disp_budget_mean_zonal(mygrid.LATS,alldiag.zm_salt_ocn,'g/m2','Salt (ocean only)'); %cumulative integral: tmp1=repmat(alldiag.zm_area,[3 1 1]); tmp1=tmp1.*alldiag.zm_salt_ocn; cumbudg=cumsum(tmp1,2); subplot(2,1,2); disp_budget_mean_zonal(mygrid.LATS,cumbudg,'g','Salt (ocean only)'); %add to tex file myCaption={myYmeanTxt,'salt budget (ocean only) at each latitude in g/m2 (upper) and integrated from South (lower).'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; end; end; gcmfaces/gcmfaces_diags/diags_read_from_mat.m0000644000435400001440000000515412273015651021257 0ustar gforgetusersfunction [alldiag]=diags_read_from_mat(dirMat,nameMat,varargin); %object: load single record files off basic_diags_ecco, and assemble time records %inputs: dirMat is the model run sub-directory where the matlab files are (e.g. 'mat/') % nameMat is the mat files name (e.g. 'basic_diags_ecco_A_*.mat') %optional: nameDiag is the name of the diagnostic of interest % subListTimes is a vector to reduce listTimes to listTimes(subListTimes) if nargin>2; nameDiag=varargin{1}; else; nameDiag=''; end; if nargin>3; subListTimes=varargin{2}; else; subListTimes=[]; end; %model run paramters (from basic_diags_ecco_mygrid.mat) global myparms; %get list of files listFiles=dir([dirMat '/' nameMat]); %get time steps and sort listFiles listSteps=[]; for tt=1:length(listFiles); nn=listFiles(tt).name; ii=strfind(nn,'_'); ii=ii(end); listSteps=[listSteps;str2num(nn(ii+1:end-4))]; end; [listSteps,ii]=sort(listSteps); listFiles=listFiles(ii); %compute approximate times (in years -- using 365.25 as year length) listTimes=myparms.yearFirst(1)+listSteps*myparms.timeStep/86400/365.25; %initialize alldiag alldiag=open([dirMat listFiles(1).name]); listDiags=fieldnames(alldiag); %restrict list of diags to load if ~isempty(nameDiag); if iscell(nameDiag); listDiags=nameDiag; else; listDiags={nameDiag}; end; end; %restrict list of times if ~isempty(subListTimes); listSteps=listSteps(subListTimes); listTimes=listTimes(subListTimes); listFiles=listFiles(subListTimes); alldiag=open([dirMat listFiles(1).name]); end; %loop and concatenate for tt=2:length(listSteps); tmpdiag=open([dirMat listFiles(tt).name]); for ii=1:length(listDiags); %get data: eval(['tmp1=tmpdiag.' listDiags{ii} '; tmp2=alldiag.' listDiags{ii} ';']); %determine the time dimension: if strcmp(class(tmp1),'gcmfaces'); nDim=size(tmp1{1}); else; nDim=size(tmp1); end; if ~isempty(find(nDim==0)); nDim=0; elseif nDim(end)==1; nDim=length(nDim)-1; else; nDim=length(nDim); end; %concatenate along the time dimension: if nDim>0; tmp2=cat(nDim+1,tmp2,tmp1); eval(['alldiag.' listDiags{ii} '=tmp2;']); end; end; end; %clean empty diags up for ii=1:length(listDiags); eval(['tmp1=isempty(alldiag.' listDiags{ii} ');']); if tmp1; alldiag=rmfield(alldiag,listDiags{ii}); end; end; %remove diags that were not selected (and therefore not concatenated) tmpDiags=fieldnames(alldiag); for ii=1:length(tmpDiags); if ~sum(sum(strcmp(tmpDiags{ii},listDiags))); alldiag=rmfield(alldiag,tmpDiags{ii}); end; end; %complement alldiag alldiag.listSteps=listSteps; alldiag.listTimes=listTimes; alldiag.listDiags=listDiags; gcmfaces/gcmfaces_diags/diags_diff_snapshots.m0000644000435400001440000000330512365532631021472 0ustar gforgetusersfunction []=diags_diff_snapshots(dirModel,dirMat,fileStart); %object: compute time derivatives between snapshots that % will be compared with time mean flux terms in budgets %input: dirModel is the model directory % fileStart is the root of file names (e.g. budg2d_snap_set1) %result: create e.g. rate_budg2d_snap_set1 files fileList=dir([dirModel 'diags/BUDG/' fileStart '.*.data']); for ii=1:length(fileList)-1; %1) get the time of fld0 & fld1, & the data precision fileMeta=[dirModel 'diags/BUDG/' fileList(ii).name(1:end-5) '.meta']; time0={}; time1={}; fileMeta=[dirModel 'diags/BUDG/' fileList(ii).name(1:end-5) '.meta']; fid0=fopen(fileMeta); fileMeta=[dirModel 'diags/BUDG/' fileList(ii+1).name(1:end-5) '.meta']; fid1=fopen(fileMeta); while 1; tline = fgetl(fid0); if ~ischar(tline), break, end if isempty(time0); time0=tline; else; time0=[time0 ' ' tline]; end; tline = fgetl(fid1); if isempty(time1); time1=tline; else; time1=[time1 ' ' tline]; end; end fclose(fid0); fclose(fid1); eval(time0); time0=timeInterval; clear timeInterval; eval(time1); time1=timeInterval; clear timeInterval; dataprec=str2num(dataprec(end-1:end)); %2) get the binary data: fld0=read2memory([dirModel 'diags/BUDG/' fileList(ii).name],[],dataprec); fld1=read2memory([dirModel 'diags/BUDG/' fileList(ii+1).name],[],dataprec); %3) compute the tendency term: fld2=(fld1-fld0)/(time1-time0); %4) write to file: fileMetaOld=[dirModel 'diags/BUDG/' fileList(ii+1).name(1:end-5) '.meta']; fileMetaNew=[dirMat 'BUDG/rate_' fileList(ii+1).name(1:end-5) '.meta']; copyfile(fileMetaOld , fileMetaNew); fileDataNew=[dirMat 'BUDG/rate_' fileList(ii+1).name(1:end-5) '.data']; write2file(fileDataNew,fld2,dataprec); end; gcmfaces/gcmfaces_diags/diags_set_F.m0000644000435400001440000005032112365532631017520 0ustar gforgetusers %select kBudget: if ~isempty(setDiagsParams); kBudget=setDiagsParams{1}; else; kBudget=1; end; %override default file name: %--------------------------- tmp1=setDiags; if kBudget>1; tmp1=sprintf('F%02i',kBudget); end; fileMat=['diags_set_' tmp1]; if userStep==1;%diags to be computed listDiags=['glo_vol_ocn glo_vol_tot glo_vol_ice glo_bp']; listDiags=[listDiags ' glo_heat_ocn glo_heat_tot glo_heat_ice']; listDiags=[listDiags ' glo_salt_ocn glo_salt_tot glo_salt_ice']; if sum([90 1170]~=mygrid.ioSize)==0; listDiags=[listDiags ' gsbox_vol_ocn gsbox_vol_tot gsbox_vol_ice gsbox_bp']; listDiags=[listDiags ' arctic_vol_ocn arctic_vol_tot arctic_vol_ice arctic_bp']; listDiags=[listDiags ' gsbox_heat_ocn gsbox_heat_tot gsbox_heat_ice']; listDiags=[listDiags ' arctic_heat_ocn arctic_heat_tot arctic_heat_ice']; listDiags=[listDiags ' gsbox_salt_ocn gsbox_salt_tot gsbox_salt_ice']; listDiags=[listDiags ' arctic_salt_ocn arctic_salt_tot arctic_salt_ice']; end; elseif userStep==2;%input files and variables listFlds={ 'ETAN','SIheff','SIhsnow','THETA ','SALT ','PHIBOT'}; listFlds={listFlds{:},'SIatmFW ','oceFWflx','SItflux','TFLUX','SFLUX','oceSPflx','SRELAX'}; listFlds={listFlds{:},'oceQnet ','SIatmQnt','SIaaflux','SIsnPrcp','SIacSubl'}; listFlds={listFlds{:},'TRELAX','WTHMASS','WSLTMASS','oceSflux','oceQsw','oceSPtnd'}; if kBudget>1; listFlds={listFlds{:},'ADVr_TH','DFrE_TH','DFrI_TH','ADVr_SLT','DFrE_SLT','DFrI_SLT','WVELMASS'}; end; listFlds={listFlds{:},'SDIAG1','SDIAG2','SDIAG3'}; listFlds={listFlds{:},'UVELMASS','VVELMASS','AB_gT','AB_gS'}; listFlds={listFlds{:},'ADVx_TH ','ADVy_TH ','DFxE_TH ','DFyE_TH '}; listFlds={listFlds{:},'ADVx_SLT','ADVy_SLT','DFxE_SLT','DFyE_SLT'}; listFlds={listFlds{:},'ADVxHEFF','ADVyHEFF','DFxEHEFF','DFyEHEFF'}; listFlds={listFlds{:},'ADVxSNOW','ADVySNOW','DFxESNOW','DFyESNOW'}; listFldsNames=deblank(listFlds); % listFiles={'rate_budg2d_snap_set1','budg2d_hflux_set1','budg2d_zflux_set1','budg2d_zflux_set2'}; if kBudget==1; listFiles={listFiles{:},'rate_budg2d_snap_set2','budg2d_hflux_set2'}; else; tmp1=sprintf('rate_budg2d_snap_set3_%02i',kBudget); tmp2=sprintf('budg2d_zflux_set3_%02i',kBudget); tmp3=sprintf('budg2d_hflux_set3_%02i',kBudget); listFiles={listFiles{:},tmp1,tmp2,tmp3}; end; listSubdirs={[dirMat 'BUDG/' ],[dirMat '../BUDG/' ],[dirModel 'diags/BUDG/']}; elseif userStep==3;%computational part; %preliminary tests test1=isempty(dir([dirModel 'diags/BUDG/budg2d_snap_set1*'])); test2=isempty(dir([dirMat 'BUDG/rate_budg2d_snap_set1*']))&... isempty(dir([dirMat '../BUDG/rate_budg2d_snap_set1*'])); if (strcmp(setDiags,'F')&test1&test2); fprintf('\n abort : global and regional budgets, due to missing \n'); fprintf(['\n ' dirModel 'diags/BUDG/budg2d_snap_set1* \n']); return; end; if (strcmp(setDiags,'F')&test2); fprintf('\n abort : global and regional budgets, due to missing \n'); fprintf(['\n ' dirModel 'diags/BUDG/rate_budg2d_snap_set1* \n']); return; end; %override default file name: %--------------------------- tmp1=setDiags; if kBudget>1; tmp1=sprintf('F%02i',kBudget); end; fileMat=['diags_set_' tmp1 '_' num2str(tt) '.mat']; %fill in optional fields: %------------------------ if isempty(who('TRELAX')); TRELAX=0*mygrid.XC; end; if isempty(who('SRELAX')); SRELAX=0*mygrid.XC; end; if isempty(who('AB_gT')); AB_gT=0*mygrid.XC; end; if isempty(who('AB_gS')); AB_gS=0*mygrid.XC; end; if isempty(who('oceSPtnd')); oceSPtnd=0*mygrid.XC; end; if isempty(who('oceSPflx')); oceSPflx=0*mygrid.XC; end; if isempty(who('PHIBOT')); PHIBOT=0*mygrid.XC; end; %aliases from development phase (applies to 2012 core runs) %--------------------------------------------------------- if ~isempty(who('SDIAG1')); SRELAX=SDIAG1; end; if ~isempty(who('SDIAG2')); SIatmFW=SDIAG2; end; if ~isempty(who('SDIAG3')); SItflux=SDIAG3; end; %=======MASS========= %compute mapped budget: %---------------------- %mass = myparms.rhoconst * sea level contOCN=ETAN*myparms.rhoconst; contICE=(SIheff*myparms.rhoi+SIhsnow*myparms.rhosn); %for deep ocean layer : if kBudget>1&myparms.useNLFS<2; contOCN=0; elseif kBudget>1;%rstar case tmp1=mk3D(mygrid.DRF,mygrid.hFacC).*mygrid.hFacC; tmp2=sum(tmp1(:,:,kBudget:length(mygrid.RC)),3)./mygrid.Depth; contOCN=tmp2.*ETAN*myparms.rhoconst; end; % contTOT=contOCN+contICE; %vertical divergence (air-sea fluxes or vertical advection) zdivOCN=oceFWflx; zdivICE=SIatmFW-oceFWflx; %in virtual salt flux we omit : if ~myparms.useRFWF; zdivOCN=0*zdivOCN; end; %for deep ocean layer : if kBudget>1; zdivOCN=-WVELMASS*myparms.rhoconst; end; % zdivTOT=zdivOCN+zdivICE; %horizontal divergence (advection and ice diffusion) hdivOCN=myparms.rhoconst*calc_UV_conv(UVELMASS,VVELMASS,{'dh'}); %for 2D, already vertically integrated, fields tmpU=(myparms.rhoi*DFxEHEFF+myparms.rhosn*DFxESNOW+myparms.rhoi*ADVxHEFF+myparms.rhosn*ADVxSNOW); tmpV=(myparms.rhoi*DFyEHEFF+myparms.rhosn*DFyESNOW+myparms.rhoi*ADVyHEFF+myparms.rhosn*ADVySNOW); hdivICE=calc_UV_conv(tmpU,tmpV); %no dh needed here hdivTOT=hdivOCN+hdivICE; %bottom pressure for comparison: bp=myparms.rhoconst/9.81*PHIBOT; %compute global integrals: %------------------------- msk=mygrid.mskC(:,:,kBudget); glo_vol_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); glo_vol_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); glo_vol_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); glo_bp=nansum(bp.*msk.*mygrid.RAC)/nansum(msk.*mygrid.RAC); if sum([90 1170]~=mygrid.ioSize)==0; %compute gsboxern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*v4_basin('atl').*(mygrid.YC>=35&mygrid.YC<=42&mygrid.XC<=-40); gsbox_vol_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); gsbox_vol_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); gsbox_vol_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); gsbox_bp=nansum(bp.*msk.*mygrid.RAC)/nansum(msk.*mygrid.RAC); %and arcticern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*v4_basin('arct'); arctic_vol_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); arctic_vol_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); arctic_vol_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); arctic_bp=nansum(bp.*msk.*mygrid.RAC)/nansum(msk.*mygrid.RAC); end; %=======HEAT======= contOCN=myparms.rcp*THETA-myparms.rcp*AB_gT; contICE=-myparms.flami*(SIheff*myparms.rhoi+SIhsnow*myparms.rhosn); contTOT=contOCN+contICE; %vertical divergence (air-sea fluxes or vertical adv/dif) zdivOCN=TFLUX; zdivICE=-(SItflux+TFLUX-TRELAX); %in linear surface we omit : if ~myparms.useNLFS; zdivOCN=zdivOCN-myparms.rcp*WTHMASS; end; %in virtual salt flux we omit : if ~myparms.useRFWF|~myparms.useNLFS; zdivICE=zdivICE+SIaaflux; end; %working approach for real fresh water (?) and virtual salt flux if 0; zdivICE=-oceQnet-SIatmQnt-myparms.flami*(SIsnPrcp-SIacSubl); end; %for deep ocean layer : if kBudget>1; zdivOCN=-(ADVr_TH+DFrE_TH+DFrI_TH)./mygrid.RAC*myparms.rcp; dd=mygrid.RF(kBudget); msk=mygrid.mskC(:,:,kBudget); swfrac=0.62*exp(dd/0.6)+(1-0.62)*exp(dd/20); if dd<-200; swfrac=0; end; zdivOCN=zdivOCN+swfrac*oceQsw;%.*msk; end; % zdivTOT=zdivOCN+zdivICE; %horizontal divergence (advection and diffusion) tmpU=myparms.rcp*(ADVx_TH+DFxE_TH); tmpV=myparms.rcp*(ADVy_TH+DFyE_TH); hdivOCN=calc_UV_conv(tmpU,tmpV); tmpU=-myparms.flami*(myparms.rhoi*DFxEHEFF+myparms.rhosn*DFxESNOW+myparms.rhoi*ADVxHEFF+myparms.rhosn*ADVxSNOW); tmpV=-myparms.flami*(myparms.rhoi*DFyEHEFF+myparms.rhosn*DFyESNOW+myparms.rhoi*ADVyHEFF+myparms.rhosn*ADVySNOW); hdivICE=calc_UV_conv(tmpU,tmpV); %no dh needed here hdivTOT=hdivOCN+hdivICE; %compute global integrals: %------------------------- msk=mygrid.mskC(:,:,kBudget); glo_heat_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); glo_heat_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); glo_heat_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); if sum([90 1170]~=mygrid.ioSize)==0; %compute gsboxern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*v4_basin('atl').*(mygrid.YC>=35&mygrid.YC<=42&mygrid.XC<=-40); gsbox_heat_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); gsbox_heat_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); gsbox_heat_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); %and arcticern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*v4_basin('arct'); arctic_heat_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); arctic_heat_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); arctic_heat_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); end; %=======SALT======= contOCN=myparms.rhoconst*SALT-myparms.rhoconst*AB_gS; contICE=myparms.SIsal0*myparms.rhoi*SIheff; contTOT=contOCN+contICE; %vertical divergence (air-sea fluxes or vertical adv/dif) zdivOCN=SFLUX+oceSPflx; zdivICE=-zdivOCN+SRELAX; %in linear surface we omit : if ~myparms.useNLFS; zdivOCN=zdivOCN-myparms.rhoconst*WSLTMASS; end; %working approach for real fresh water (?) and virtual salt flux if ~myparms.useRFWF|~myparms.useNLFS; zdivICE=-oceSflux; end; %for deep ocean layer : if kBudget>1; zdivOCN=-(ADVr_SLT+DFrE_SLT+DFrI_SLT)./mygrid.RAC*myparms.rhoconst; zdivOCN=zdivOCN+oceSPtnd;%.*msk; end; zdivTOT=zdivOCN+zdivICE; %horizontal divergence (advection and diffusion) tmpU=myparms.rhoconst*(ADVx_SLT+DFxE_SLT); tmpV=myparms.rhoconst*(ADVy_SLT+DFyE_SLT); hdivOCN=calc_UV_conv(tmpU,tmpV); tmpU=myparms.SIsal0*(myparms.rhoi*DFxEHEFF+myparms.rhoi*ADVxHEFF); tmpV=myparms.SIsal0*(myparms.rhoi*DFyEHEFF+myparms.rhoi*ADVyHEFF); hdivICE=calc_UV_conv(tmpU,tmpV); %no dh needed here hdivTOT=hdivOCN+hdivICE; %compute global integrals: %------------------------- msk=mygrid.mskC(:,:,kBudget); glo_salt_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); glo_salt_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); glo_salt_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); if sum([90 1170]~=mygrid.ioSize)==0; %compute gsboxern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*v4_basin('atl').*(mygrid.YC>=35&mygrid.YC<=42&mygrid.XC<=-40); gsbox_salt_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); gsbox_salt_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); gsbox_salt_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); %and arcticern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*v4_basin('arct'); arctic_salt_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); arctic_salt_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); arctic_salt_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); end; %===================== COMPUTATIONAL SEQUENCE ENDS =========================% %===================== PLOTTING SEQUENCE BEGINS =========================% elseif userStep==-1&multiBasins==1;%plotting if isempty(setDiagsParams); choicePlot={'all'}; elseif isnumeric(setDiagsParams{1})&length(setDiagsParams)==1; choicePlot={'all'}; elseif isnumeric(setDiagsParams{1}); choicePlot={setDiagsParams{2:end}}; else; choicePlot=setDiagsParams; end; tt=[1:length(alldiag.listTimes)]; TT=alldiag.listTimes(tt); nt=length(TT); if (kBudget==1)&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mass'))); %1.1) ocean+seaice mass budgets %------------------------------ figureL; %global volume budget: subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_vol_tot,'kg/m2','Global Mean Mass (incl. ice)'); %add bp: dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.glo_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %gsboxern hemisphere budget: subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.gsbox_vol_tot,'kg/m2','Gulf Stream Box Mass (incl. ice)'); %add bp: dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.gsbox_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %arcticern hemisphere budget: subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.arctic_vol_tot,'kg/m2','Arctic Mass (incl. ice)'); %add bp: dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.arctic_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %add to tex file myCaption={myYmeanTxt,' global (upper) gsbox (mid) and arctic (lower), '}; myCaption={myCaption{:},'mass budget (ocean+ice) in kg/m2.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; %1.2) ice mass budgets %--------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_vol_ice,'kg/m2','Global Mean Mass (only ice)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.glo_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.gsbox_vol_ice,'kg/m2','Gulf Stream Box Mass (only ice)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.gsbox_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.arctic_vol_ice,'kg/m2','Arctic Mass (only ice)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.arctic_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %add to tex file myCaption={myYmeanTxt,' global (upper) gsbox (mid) and arctic (lower), '}; myCaption={myCaption{:},'mass budget (ice only) in kg/m2.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mass'))); %1.3) ocean mass budgets %----------------------- figureL; %global volume budget: subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_vol_ocn,'kg/m2','Global Mean Mass (only ocean)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.glo_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.gsbox_vol_ocn,'kg/m2','Gulf Stream Box Mass (only ocean)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.gsbox_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.arctic_vol_ocn,'kg/m2','Arctic Mass (only ocean)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.arctic_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %add to tex file myCaption={myYmeanTxt,' global (upper) gsbox (mid) and arctic (lower), '}; myCaption={myCaption{:},'mass budget (ocean only) in kg/m2.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (kBudget==1)&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'heat'))); %2.1) ocean+seaice heat budgets %------------------------------ figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_heat_tot,'J/m2','Global Mean Ocean Heat (incl. ice)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.gsbox_heat_tot,'J/m2','Gulf Stream Box Ocean Heat (incl. ice)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.arctic_heat_tot,'J/m2','Arctic Ocean Heat (incl. ice)'); %add to tex file myCaption={myYmeanTxt,' global (upper) gsbox (mid) and arctic (lower), '}; myCaption={myCaption{:},'heat budget (ocean+ice) in J/m2.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; %2.2) ice heat budgets %--------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_heat_ice,'J/m2','Global Mean Ocean Heat (only ice)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.gsbox_heat_ice,'J/m2','Gulf Stream Box Ocean Heat (only ice)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.arctic_heat_ice,'J/m2','Arctic Ocean Heat (only ice)'); %add to tex file myCaption={myYmeanTxt,' global (upper) gsbox (mid) and arctic (lower), '}; myCaption={myCaption{:},'heat budget (ice only) in J/m2.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'heat'))); %2.3) ocean heat budgets %----------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_heat_ocn,'J/m2','Global Mean Ocean Heat (only ocean)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.gsbox_heat_ocn,'J/m2','Gulf Stream Box Ocean Heat (only ocean)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.arctic_heat_ocn,'J/m2','Arctic Ocean Heat (only ocean)'); %add to tex file myCaption={myYmeanTxt,' global (upper) gsbox (mid) and arctic (lower), '}; myCaption={myCaption{:},'heat budget (ocean only) in J/m2.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (kBudget==1)&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'salt'))); %3.1) ocean+seaice salt budgets %------------------------------ figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_salt_tot,'g/m2','Global Mean Ocean Salt (incl. ice)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.gsbox_salt_tot,'g/m2','Gulf Stream Box Ocean Salt (incl. ice)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.arctic_salt_tot,'g/m2','Arctic Ocean Salt (incl. ice)'); %add to tex file myCaption={myYmeanTxt,' global (upper) gsbox (mid) and arctic (lower), '}; myCaption={myCaption{:},'salt budget (ocean+ice) in g/m2.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; %2.2) ice salt budgets %--------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_salt_ice,'g/m2','Global Mean Ocean Salt (only ice)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.gsbox_salt_ice,'g/m2','Gulf Stream Box Ocean Salt (only ice)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.arctic_salt_ice,'g/m2','Arctic Ocean Salt (only ice)'); %add to tex file myCaption={myYmeanTxt,' global (upper) gsbox (mid) and arctic (lower), '}; myCaption={myCaption{:},'salt budget (ice only) in g/m2.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'salt'))); %3.3) ocean salt budgets %----------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_salt_ocn,'g/m2','Global Mean Ocean Salt (only ocean)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.gsbox_salt_ocn,'g/m2','Gulf Stream Box Ocean Salt (only ocean)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.arctic_salt_ocn,'g/m2','Arctic Ocean Salt (only ocean)'); %add to tex file myCaption={myYmeanTxt,' global (upper) gsbox (mid) and arctic (lower), '}; myCaption={myCaption{:},'salt budget (ocean only) in g/m2.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; end; gcmfaces/gcmfaces_diags/diags_set_MLD.m0000644000435400001440000000647012276601102017744 0ustar gforgetusers if userStep==1;%diags to be computed listDiags='fldMldBoyer fldMldSuga fldMldKara'; elseif userStep==2;%input files and variables listFlds={ 'THETA','SALT'}; listFldsNames=deblank(listFlds); listFiles={'monthly_2d_set1','monthly_3d_set1','state_2d_set1','other_2d_set1','state_3d_set1'}; elseif userStep==3;%computational part; fldT=THETA.*mygrid.mskC; fldS=SALT.*mygrid.mskC; % %prepare to compute potential density: fldP=0*mygrid.mskC; for kk=1:length(mygrid.RC); fldP(:,:,kk)=-mygrid.RC(kk); end; T=convert2vector(fldT); S=convert2vector(fldS); msk=convert2vector(mygrid.mskC); P=convert2vector(fldP); %compute potential density: RHO=0*msk; alpha=0*msk; tmp1=find(~isnan(msk)); RHO(tmp1) = density(T(tmp1),S(tmp1),P(tmp1)); fldRhoPot=convert2vector(RHO); alpha(tmp1) = density(T(tmp1)+1e-4,S(tmp1),P(tmp1)); fldAlpha=(convert2vector(alpha)-fldRhoPot)/1e-4; clear T S P msk RHO RHOis tmp1; %compute mld: tmp1=NaN*mygrid.mskC(:,:,1); for kk=1:50; tmp2=fldRhoPot(:,:,kk)-fldRhoPot(:,:,1); %if we pass RHO(1)+0.03 for the first time (or we reach the bottom) %then mld is the velocity point above RC(kk), which is RF(kk) jj=find((tmp2>0.03|isnan(tmp2))&isnan(tmp1)); tmp1(jj)=-mygrid.RF(kk); end; fldMldBoyer=tmp1; %compute mld: tmp1=NaN*mygrid.mskC(:,:,1); for kk=1:50; tmp2=fldRhoPot(:,:,kk)-fldRhoPot(:,:,1); %if we pass RHO(1)+0.125 for the first time (or we reach the bottom) %then mld is the velocity point above RC(kk), which is RF(kk) jj=find((tmp2>0.125|isnan(tmp2))&isnan(tmp1)); tmp1(jj)=-mygrid.RF(kk); end; fldMldSuga=tmp1; %compute mld: tmp1=NaN*mygrid.mskC(:,:,1); fldRhoPotMax=fldRhoPot(:,:,1)-0.8*fldAlpha(:,:,1); for kk=1:50; tmp2=fldRhoPot(:,:,kk)-fldRhoPotMax; %if we pass RHO(1)+0.8*alpha(1) for the first time (or we reach the bottom) %then mld is the velocity point above RC(kk), which is RF(kk) jj=find((tmp2>0|isnan(tmp2))&isnan(tmp1)); tmp1(jj)=-mygrid.RF(kk); end; fldMldKara=tmp1; elseif userStep==-1;%plotting; list_var={'fldMldKara','fldMldSuga','fldMldBoyer'}; list_tit={' mixed layer depth per Kara formula (m)',... ' mixed layer depth per Suga formula (m)',... ' mixed layer depth per Boyer M. formula (m)'}; if myparms.diagsAreMonthly==1; for seas=1:2; for vv=1:length(list_var); eval(['fld=alldiag.' list_var{vv} ';']); %compute mean march and september fields if seas==1; fld_seas=nanmedian(fld(:,:,3:12:nt),3); mon='March'; else; fld_seas=nanmedian(fld(:,:,9:12:nt),3); mon='September'; end; fld_seas(fld_seas==0)=NaN; %plot cc=[[0:20:100] [150:50:300] 400 [500:200:1100] [1500:500:2000]]; if doAnomalies; cc=scaleAnom*[-5:0.5:5]; end; figureL; set(gcf,'Renderer','zbuffer'); m_map_gcmfaces(fld_seas,0,{'myCaxis',cc}); myCaption={myYmeanTxt,mon,' mean -- ',list_tit{vv}}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end;%for vv=1:length(list_var); end;%for seas=1:2; end;%if myparms.diagsAreMonthly==1 end; gcmfaces/gcmfaces_diags/diags_pre_process.m0000644000435400001440000001665312366217533021020 0ustar gforgetusersfunction [myswitch]=diags_pre_process(dirModel,dirMat,doInteractive); %object : pre-processing for grid, model parameters, budgets, % profiles, cost and control, etc if required %input : dirModel is the directory containing 'diags/' or 'nctiles/' % dirMat is the directory where diagnostics results will be saved % if isempty(dirMat) then [dirModel 'mat/'] is used by default %(optional) doInteractive=1 allows users to specify parameters interactively % doInteractive = 0 (default) uses ECCO v4 parameters % and omits budgets and model-data misfits analyses %output : myswitch is the set of switches (doBudget, doProfiles, doCost, doCtrl) % that are set here depending on the model output available gcmfaces_global; global myparms; dirModel=[dirModel '/']; if isempty(dirMat); dirMat=[dirModel 'mat/']; else; dirMat=[dirMat '/']; end; if isempty(who('doInteractive')); doInteractive=0; end; %detect which types of files are avaiable test0=isdir([dirModel 'diags']); test1=isdir([dirModel 'nctiles']); if test0&test1&doInteractive; myenv.nctiles=input('select to use binaries (0) or nctiles (1) files\n'); elseif test1; myenv.nctiles=1; elseif test0; myenv.nctiles=0; else; error('no files (diags/ or nctiles/) were found\n'); end if doInteractive; doBudget=~isempty(dir([dirModel 'diags/BUDG/'])) doBudget=doBudget&~myenv.nctiles; doCost=~isempty(dir([dirModel 'barfiles/'])) doCtrl=~isempty(dir([dirModel 'ADXXfiles/'])) else; doBudget=0; doCost=0; doCtrl=0; end; doProfiles=~isempty(dir([dirModel 'MITprof/'])); preprocessProfiles=0; myenv.profiles=[pwd '/' dirModel 'MITprof/']; if ~doProfiles; doProfiles=~isempty(dir([dirModel 'profiles/'])); preprocessProfiles=1; myenv.profiles=[pwd '/' dirMat 'profiles/output/']; end; %output switches myswitch.doBudget=doBudget; myswitch.doProfiles=doProfiles; myswitch.doCost=doCost; myswitch.doCtrl=doCtrl; %set the list of diags directories and files if myenv.nctiles; listSubdirs={[pwd '/' dirModel 'nctiles/']}; listFiles=dir(listSubdirs{1}); listFiles={listFiles(:).name}; %remove irrelevant files/dirs test1=ones(size(listFiles)); for kk=1:length(listFiles); tmp1=[listSubdirs{1} listFiles{kk} '/' listFiles{kk} '*.nc']; test1(kk)=~isempty(dir(tmp1)); end; listFiles={listFiles{find(test1)}}; %store in myparms for later use myenv.nctilesdir=listSubdirs{1}; myenv.nctileslist=listFiles; end; %0) create dirMat if needed: if isempty(dir(dirMat)); mkdir(dirMat); end; %1) pre-processing diags_grid_parms.mat test0=isempty(dir([dirMat 'diags_grid_parms.mat'])); test1=isempty(dir([dirMat 'lock_mygrid'])); if test0&test1;%this process will do the pre-processing fprintf(['pre-processing : started for mygrid, myparms \n']); write2file([dirMat 'lock_mygrid'],1); %set the list of diags times listSubdirs={[dirMat 'BUDG/' ],[dirModel 'diags/BUDG/' ],[dirModel 'diags/OTHER/' ],... [dirModel 'diags/STATE/' ],[dirModel 'diags/TRSP/'],[dirModel 'diags/' ]}; listFiles={'state_2d_set1','diags_2d_set1','monthly_2d_set1'}; [listTimes]=diags_list_times(listSubdirs,listFiles); %set grid and model parameters: diags_grid_parms(listTimes,doInteractive); %save to disk: if doInteractive; eval(['save ' dirMat 'diags_grid_parms.mat mygrid myparms;']); end; delete([dirMat 'lock_mygrid']); test1=1; fprintf(['pre-processing : completed for mygrid, myparms \n\n']); end; %here I should test that files are indeed found (may have been moved) while ~test1;%this process will wait for pre-processing to complete fprintf(['waiting 30s for removal of ' dirMat 'lock_mygrid \n']); fprintf(['- That should happen automatically after pre-processing is complete \n']); fprintf(['- But if a previous session was interupted, you may need to stop this one, \n ']); fprintf([' remove ' dirMat 'lock_grid manually, and start over. \n\n']); test1=isempty(dir([dirMat 'lock_mygrid'])); pause(30); end; %here we always reload the grid from dirMat to make sure the same one is used throughout if doInteractive; eval(['load ' dirMat 'diags_grid_parms.mat;']); end; %2) pre-processing profiles test0=isempty(dir([dirMat 'profiles/'])); test1=isempty(dir([dirMat 'lock_profiles'])); if test0&test1&doProfiles&preprocessProfiles;%this process will do the pre-processing fprintf(['pre-processing : started for profiles \n']); write2file([dirMat 'lock_profiles'],1); mkdir([dirMat 'profiles/']); % NOTE: if on DOS system change ln to mklink system(['ln -s /net/nares/raid11/ecco-shared/ecco-version-4/input/input_insitu ' dirMat 'profiles/input']); mkdir([dirMat 'profiles/output/']); if dirModel(1)~='/'; dirModelFull=[pwd '/' dirModel]; else; dirModelFull=dirModel; end; % NOTE: if on DOS system change ln to mklink system(['ln -s ' dirModelFull 'profiles/*equi.data ' dirMat 'profiles/.']); listModel={'argo_feb2013_1992_to_2007*','argo_feb2013_2008_to_2010*',... 'argo_feb2013_2011_to_2012*','ctd_feb2013*','itp_feb2013*',... 'seals_feb2013*','xbt_feb2013*','climode_feb2013*'}; MITprof_gcm2nc([dirMat 'profiles/'],listModel); delete([dirMat 'lock_profiles']); test1=1; fprintf(['pre-processing : completed for profiles \n\n']); end; while ~test1&doProfiles;%this process will wait for pre-processing to complete fprintf(['waiting 30s for removal of ' dirMat 'lock_profiles \n']); fprintf(['- That should happen automatically after pre-processing is complete \n']); fprintf(['- But if a previous session was interupted, you may need to stop this one, \n ']); fprintf([' remove ' dirMat 'lock_profiles manually, and start over. \n\n']); test1=isempty(dir([dirMat 'lock_profiles'])); pause(30); end; %3) budget pre-processing test0=isempty(dir([dirMat 'BUDG/'])); test1=isempty(dir([dirMat 'lock_budg']));%this aims at having only one process do the if (test0&test1&doBudget); fprintf(['pre-processing : started for budget \n']); write2file([dirMat 'lock_budg'],1); mkdir([dirMat 'BUDG/']); %compute time derivatives between snwpshots that will be %compared in budgets with the time mean flux terms diags_diff_snapshots(dirModel,dirMat,'budg2d_snap_set1'); diags_diff_snapshots(dirModel,dirMat,'budg2d_snap_set2'); diags_diff_snapshots(dirModel,dirMat,'budg2d_snap_set3'); %diags_diff_snapshots(dirModel,dirMat,'budg3d_snap_set1'); budget_list=1; for kk=1:length(mygrid.RC); tmp1=sprintf('%s/diags/BUDG/budg2d_snap_set3_%02i*',dirModel,kk); tmp2=~isempty(dir(tmp1)); if tmp2; budget_list=[budget_list kk]; tmp1=sprintf('budg2d_snap_set3_%02i',kk); diags_diff_snapshots(dirModel,dirMat,tmp1); end; end; eval(['save ' dirMat 'diags_select_budget_list.mat budget_list;']); delete([dirMat 'lock_budg']); test1=1; fprintf(['pre-processing : completed for budget \n\n']); end; while ~test1&doBudget;%this process will wait for pre-processing to complete fprintf(['waiting 30s more for removal of ' dirMat 'lock_budg \n']); fprintf(['- That should happen automatically after pre-processing is complete \n']); fprintf(['- But if a previous session was interupted, you may need to stop this one, \n ']); fprintf([' remove ' dirMat 'lock_budg manually, and start over. \n\n']); test1=isempty(dir([dirMat 'lock_budg'])); pause(30); end; gcmfaces/gcmfaces_diags/diags_display.m0000644000435400001440000001766012366240551020134 0ustar gforgetusersfunction []=diags_display(dirMat,setDiags,dirTex,nameTex); %object: display a set of diagnostics %input: dirMat is the directory where diagnozed .mat files are. % dirMat is usually specified as a chararcter string, but % user can also specify dirMat as {dirMat,dirMatRef} % in order to plot the dirMat-dirMatRef anlomalies. % setDiags is the choice of diagnostics set % 'A') trasnports % 'B') air-sea fluxes % 'C') state variables % 'D') global and regional budgets %optional: dirTex is the directory where tex and figures files are created % (if not specified then display all results to screen instead) % nameTex is the tex file name (default : 'myPlots') %note: specifying dirTex / nameTex requires that the tex file has been % initialized (see e.g. diags_driver_tex.m). Each figure will then % be save as an eps file, added to the tex file, and closed. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %determine input/output params: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %directory names: if iscell(dirMat); dirMatRef=dirMat{2}; dirMat=dirMat{1}; end; dirMat=[dirMat '/']; if isempty(who('dirMatRef')); dirMatRef=''; elseif ~isempty(dirMatRef); dirMatRef=[dirMatRef '/']; end; if isempty(who('dirTex')); dirTex=''; else; dirTex=[dirTex '/']; end; if isempty(who('nameTex')); nameTex='myPlots'; end; %determine if and where to create tex and figures files if ~ischar(dirTex); error('mis-specified dirTex'); end; if isempty(dirTex); addToTex=0; else; addToTex=1; fileTex=[dirTex nameTex '.tex']; end; %determined where to display anomalies between runs doAnomalies=~isempty(dirMatRef); %more params setDiagsParams=[]; if iscell(setDiags); setDiagsParams={setDiags{2:end}}; setDiags=setDiags{1}; end; %%%%%%%%%%%%%%%%%%%%%% %load grid and params: %%%%%%%%%%%%%%%%%%%%%% gcmfaces_global; global myparms; test1=~isempty(dir([dirMat 'basic_diags_ecco_mygrid.mat'])); test2=~isempty(dir([dirMat 'diags_grid_parms.mat'])); if ~test1&~test2; error('missing diags_grid_parms.mat') elseif test2; nameGrid='diags_grid_parms.mat'; suffDiag='diags_set_'; budgetList='diags_select_budget_list.mat'; else; nameGrid='basic_diags_ecco_mygrid.mat'; suffDiag='basic_diags_ecco_'; budgetList='basic_diags_ecco_budget_list.mat'; end; %here we always reload the grid from dirMat to make sure the same one is used throughout eval(['load ' dirMat nameGrid ';']); %backward compatibility: if ~isfield(mygrid,'memoryLimit'); mygrid.memoryLimit=0; end; if ~isfield(mygrid,'ioSize'); mygrid.ioSize=0; end; %in case mygrid.memoryLimit=1, load the stuff that was not saved to diags_grid_parms.mat if mygrid.memoryLimit==1; list0={'hFacS','hFacW'}; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds2gcmfaces([mygrid.dirGrid ''' list0{iFld} '*'']);']); end; % mygrid.hFacCsurf=mygrid.hFacC; for ff=1:mygrid.hFacC.nFaces; mygrid.hFacCsurf{ff}=mygrid.hFacC{ff}(:,:,1); end; % mskC=mygrid.hFacC; mskC(mskC==0)=NaN; mskC(mskC>0)=1; mygrid.mskC=mskC; mskW=mygrid.hFacW; mskW(mskW==0)=NaN; mskW(mskW>0)=1; mygrid.mskW=mskW; mskS=mygrid.hFacS; mskS(mskS==0)=NaN; mskS(mskS>0)=1; mygrid.mskS=mskS; % gcmfaces_lines_zonal; mygrid.LATS=[mygrid.LATS_MASKS.lat]'; [lonPairs,latPairs,names]=line_greatC_TUV_MASKS_v4; gcmfaces_lines_transp(lonPairs,latPairs,names); end; %%%%%%%%%%%%%% %define diags: %%%%%%%%%%%%%% %test for results organization if isdir([dirMat 'diags_set_' setDiags]); dirMat=[dirMat 'diags_set_' setDiags '/']; end; if isdir([dirMatRef 'diags_set_' setDiags]); dirMatRef=[dirMatRef 'diags_set_' setDiags '/']; end; if strcmp(nameGrid,'diags_grid_parms.mat'); %load listDiags and get fileMat (if applies) userStep=1; if ~isempty(which(['diags_set_' setDiags])); eval(['diags_set_' setDiags]); else; diags_set_user; end; %reformat listDiags to cell array: jj=strfind(listDiags,' '); jj=[0 jj length(listDiags)+1]; for ii=1:length(jj)-1; tmp1=listDiags(jj(ii)+1:jj(ii+1)-1); if ii==1; listDiags2={tmp1}; else; listDiags2{ii}=tmp1; end; end; listDiags=listDiags2; clear listDiags2; end; %set fileMat to default name if needed if isempty(who('fileMat')); fileMat=[suffDiag setDiags]; end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %are there results to display? %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% test1=isempty(dir([dirMat '/' fileMat '_*.mat'])); tmp1=[dirMat '/' fileMat '_*.mat']; tmp2=strfind(tmp1,'_'); tmp1(tmp2)=' '; if test1&addToTex; eval(['load ' dirTex nameTex '.mat;']); write2tex(fileTex,3,{'[ ',mySection,' ]'},1); write2tex(fileTex,3,{'abort : did not find any'},1); write2tex(fileTex,3,{tmp1},1); write2tex(fileTex,3,{'results files to display'},1); return; elseif test1; fprintf(['\n abort : did not find any \n ' tmp1 '\n results files to display\n\n']); return; end; %%%%%%%%%%%%%%%%%%%%%%%%% %load pre-computed diags: %%%%%%%%%%%%%%%%%%%%%%%%% tic; diagsWereLoaded=0; %specific load sequence (if any, diagsWereLoaded will be set to 1) if strcmp(nameGrid,'diags_grid_parms.mat'); userStep=0; if ~isempty(which(['diags_set_' setDiags])); eval(['diags_set_' setDiags]); else; diags_set_user; end; end; %generic load (if no specific one, or ) if ~diagsWereLoaded; alldiag=diags_read_from_mat(dirMat,[fileMat '_*.mat']); end; toc; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %load ref and compute anomalies: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if doAnomalies; % scaleAnom=10; scaleAnom=1; %store: dirMatBak=dirMat; dirMat=dirMatRef; alldiagBak=alldiag; %load reference solution: diagsWereLoaded=0; %specific load sequence (if any, diagsWereLoaded will be set to 1) if strcmp(nameGrid,'diags_grid_parms.mat'); userStep=0; if ~isempty(which(['diags_set_' setDiags])); eval(['diags_set_' setDiags]); else; diags_set_user; end; end; %generic load (if no specific one, or ) if ~diagsWereLoaded; alldiag=diags_read_from_mat(dirMat,[fileMat '_*.mat']); end; %restore: dirMat=dirMatBak; alldiagRef=alldiag; alldiag=alldiagBak; %compute anomalies: for ii=1:length(alldiag.listDiags); tmp0=alldiag.listDiags{ii}; if ~strcmp(tmp0,'listTimes')&~strcmp(tmp0,'listSteps') if isfield(alldiagRef,tmp0);%compute difference tmp1=getfield(alldiag,tmp0)-getfield(alldiagRef,tmp0); alldiag=setfield(alldiag,tmp0,tmp1); else;%cannot compute diff -> set to NaN tmp1=NaN*getfield(alldiag,tmp0); alldiag=setfield(alldiag,tmp0,tmp1); end; end; end; end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %determine time parameters for plots %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %number of months for runmean if myparms.diagsAreMonthly&myparms.diagsNbRec>12; myNmean=6; %half window myNmeanTxt=[' -- ' num2str(myNmean*2) ' months low pass filtered']; else; myNmean=0; myNmeanTxt=''; end; %first and last year of time average myYmean=myparms.yearInAve; if myYmean(1)==myYmean(2); myYmeanTxt=[num2str(myYmean(1)) ' ']; else; myYmeanTxt=[num2str(myYmean(1)) '-' num2str(myYmean(2)) ' ']; end; %to compute time mean/std on the fly if length(alldiag.listTimes)>diff(myparms.recInAve)+1; tt=[myparms.recInAve(1):min(myparms.recInAve(2),length(alldiag.listTimes))]; TT=alldiag.listTimes(tt); else; tt=[1:length(alldiag.listTimes)]; TT=alldiag.listTimes; end; nt=length(TT); %if only one record, swicth off time series and variance plots multiTimes=1*(myparms.recInAve(2)>myparms.recInAve(1)); %if llc90 we can plot overturn etc per basin multiBasins=(sum([90 1170]~=mygrid.ioSize)==0); %%%%%%%%%%%%%%% %display diags: %%%%%%%%%%%%%%% userStep=-1; if ~isempty(which(['diags_set_' setDiags])); eval(['diags_set_' setDiags]); else; diags_set_user; end; gcmfaces/gcmfaces_diags/diags_set_B.m0000644000435400001440000003737512366240551017530 0ustar gforgetusers doOmit3Dfields=0; if mygrid.memoryLimit~=0; doOmit3Dfields=1; end; if userStep==1;%diags to be computed %here _s stands for cumulative sum and _2s for cumulative sum of squares %the _s should be stated first listDiags=['SIatmQnt_s SIatmQnt_2s SIatmFW_s SIatmFW_2s oceQnet_s oceQnet_2s ' ... 'oceFWflx_s oceFWflx_2s fldTZ_s fldTZ_2s fldTM_s fldTM_2s ' ... 'curlTau_s curlTau_2s fldETAN_s fldETAN_2s ' ... 'fldSSH_s fldSSH_2s fldMLD_s fldMLD_2s']; if ~doOmit3Dfields; listDiags=[listDiags ' THETA_s THETA_2s SALT_s SALT_2s WVELMASS_s WVELMASS_2s']; end; elseif userStep==2;%input files and variables listFlds={ 'SIatmQnt','SIatmFW ','oceQnet ','oceFWflx','oceTAUX','oceTAUY','ETAN','sIceLoad','MXLDEPTH'}; if ~doOmit3Dfields; listFlds={listFlds{:} ,'THETA','SALT','WVELMASS'}; end; listFldsNames=deblank(listFlds); listFiles={'state_3d_set1','trsp_3d_set1','state_2d_set1','other_2d_set1'}; listSubdirs={[dirModel 'diags/OTHER/' ],[dirModel 'diags/STATE/' ],[dirModel 'diags/TRSP/' ]}; elseif userStep==3;%computation %mask fields: SIatmQnt=SIatmQnt.*mygrid.mskC(:,:,1); SIatmFW=SIatmFW.*mygrid.mskC(:,:,1); oceQnet=oceQnet.*mygrid.mskC(:,:,1); oceFWflx=oceFWflx.*mygrid.mskC(:,:,1); fldTX=oceTAUX.*mygrid.mskW(:,:,1); fldTY=oceTAUY.*mygrid.mskS(:,:,1); %compute Eastward/Northward wind stresses: [fldTZ,fldTM]=calc_UEVNfromUXVY(fldTX,fldTY); %compute wind stress curl: %curlTau=calc_UV_curl(fldTX, fldTY,1 );%the doMask argument should not matter as msk was already applied curlTau=NaN*fldTZ; %mask and re-arrange fields: fldETAN=ETAN.*mygrid.mskC(:,:,1); fldSSH=(ETAN+sIceLoad/myparms.rhoconst).*mygrid.mskC(:,:,1); fldMLD=MXLDEPTH.*mygrid.mskC(:,:,1); % if ~doOmit3Dfields; THETA=THETA.*mygrid.mskC; SALT=SALT.*mygrid.mskC; WVELMASS=WVELMASS.*mygrid.mskC; end; % if ii>myparms.recInAve(1); fileMatPrev=['diags_set_' tmp1 '_' num2str(listTimes(ii-1)) '.mat']; listTimesBak=listTimes; load([dirMat fileMatPrev]); listTimes=listTimesBak; end; for jj=1:length(listDiags)/2; myDiag=listDiags{1+2*(jj-1)}(1:end-2); if ii==myparms.recInAve(1); eval([myDiag '_s=0*' myDiag ';']); eval([myDiag '_2s=0*' myDiag '.^2;']); end; eval([myDiag '_s=' myDiag '_s+' myDiag ';']); eval([myDiag '_2s=' myDiag '_2s+' myDiag '.^2;']); end; %===================== COMPUTATIONAL SEQUENCE ENDS =========================% %===================== PLOTTING SEQUENCE BEGINS =========================% elseif userStep==0;%loading / post-processing of mat files nfiles=length(dir(fullfile(dirMat,[fileMat '_*.mat']))); if nfiles>=myparms.recInAve(2); ifile1=myparms.recInAve(2); ifile0=myparms.recInAve(1)-1; else; ifile1=nfiles; ifile0=0; end; %load last cumsum alldiag=diags_read_from_mat(dirMat,[fileMat '_*.mat'],'',ifile1); %load first cumsum if needed if ifile0>0; tmpdiag=diags_read_from_mat(dirMat,[fileMat '_*.mat'],'',ifile0); for ii=1:length(alldiag.listDiags); tmp0=alldiag.listDiags{ii}; if ~strcmp(tmp0,'listTimes')&~strcmp(tmp0,'listSteps'); tmp1=getfield(alldiag,alldiag.listDiags{ii}); tmp2=getfield(tmpdiag,alldiag.listDiags{ii}); alldiag=setfield(alldiag,tmp0,tmp1-tmp2); end; end; end; %ensure backward compatibility if ~doOmit3Dfields; if ~isfield(alldiag,'WVELMASS_s'); alldiag.WVELMASS_s=NaN*alldiag.THETA_s; end; if ~isfield(alldiag,'WVELMASS_2s'); alldiag.WVELMASS_2s=NaN*alldiag.THETA_2s; end; end; if ~isfield(alldiag,'fldSSH_s'); alldiag.fldSSH_s=alldiag.fldETANLEADS_s; end; if ~isfield(alldiag,'fldSSH_2s'); alldiag.fldSSH_2s=alldiag.fldETANLEADS_2s; end; jj=find(strcmp(alldiag.listDiags,'fldETANLEADS_s')); if ~isempty(jj); alldiag.listDiags{jj}='fldSSH_s'; end; jj=find(strcmp(alldiag.listDiags,'fldETANLEADS_2s')); if ~isempty(jj); alldiag.listDiags{jj}='fldSSH_2s'; end; % n=diff(myparms.recInAve)+1; for jj=1:length(alldiag.listDiags)/2; tmp0=alldiag.listDiags{1+2*(jj-1)}; if ~strcmp(tmp0,'listTimes')&~strcmp(tmp0,'listSteps'); tmp1=1/n*getfield(alldiag,tmp0); tmp2=1/n*getfield(alldiag,[tmp0(1:end-1) '2s']); tmp2=(tmp2-tmp1.^2); tmp2=n/(n-1)*tmp2; %tmp2(tmp2<0)=0; tmp2=sqrt(tmp2); alldiag=setfield(alldiag,[tmp0(1:end-2) '_mean'],tmp1); alldiag=setfield(alldiag,[tmp0(1:end-2) '_std'],tmp2); end; end; diagsWereLoaded=1 elseif userStep==-1;%plotting if isempty(setDiagsParams); choicePlot={'all'}; else; choicePlot=setDiagsParams; end; %===== start with state variables if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'surface')); if addToTex; write2tex(fileTex,1,'sea surface height',2); end; %ETAN: fld=alldiag.fldETAN_mean; cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]/100; title0='sea surface height (EXCLUDING ice)'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.05; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- sea surface height (EXCLUDING ice, in m)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %ETANLEADS: fld=alldiag.fldSSH_mean; cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]/100; title0='sea surface height (INCLUDING ice)'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.05; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- sea surface height (INCLUDING ice, in m)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; if multiTimes; %ETAN: fld=alldiag.fldETAN_std; cc=[0:25:500]/2500; title0='std(ETAN)'; if doAnomalies; cc=scaleAnom*[0:0.1:1]*0.02; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- sea surface height (EXCLUDING ice, in m)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %ETANLEADS: fld=alldiag.fldSSH_std; cc=[0:25:500]/2500; title0='std(ETANLEADS)'; if doAnomalies; cc=scaleAnom*[0:0.1:1]*0.02; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- sea surface height (INCLUDING ice, in m)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if ( sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'subsrfc')) )&(~doOmit3Dfields); if addToTex; write2tex(fileTex,1,'3D state variables',2); end; cc_mean=1/100*[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]; cc_std=1/250*[0:25:500]; kkList=[1 11 20 28 37 44]; vvList={'THETA','SALT','WVELMASS'}; for vv=1:length(vvList); vvtxt=vvList{vv}; eval(['fld_mean=alldiag.' vvtxt '_mean;']); eval(['fld_std=alldiag.' vvtxt '_std;']); if strcmp(vvtxt,'WVELMASS');%convert into mm/day fld_mean=fld_mean*86400*365/1e3; fld_std=fld_std*86400*365/1e3; end; for kk=kkList; if strcmp(vvtxt,'WVELMASS')&kk==1; kk=2; end; if mygrid.RC(kk)>=-50; facD=0.5; elseif mygrid.RC(kk)>=-150; facD=1; elseif mygrid.RC(kk)>=-500; facD=2.5; elseif mygrid.RC(kk)>=-2000; facD=10; else; facD=20; end; % if strcmp(vvtxt,'THETA'); nm='temperature (in degC)'; facV=1; elseif strcmp(vvtxt,'SALT'); nm='salinity (in psu)'; facV=10; elseif strcmp(vvtxt,'WVELMASS'); nm='vertical velocity (in mm/year)'; facV=10; else; error('not yet implemented'); end; % title0=sprintf('%s at %4dm',nm,round(-mygrid.RC(kk))); %time mean map: fld=fld_mean(:,:,kk).*mygrid.mskC(:,:,kk); if doAnomalies; cc=scaleAnom/facV/facD*cc_mean; elseif strcmp(vvtxt,'WVELMASS'); cc=1/facV*cc_mean; else; cc=prctile(facV*fld,[2.5 97.5]); cc=[floor(cc(1)):ceil(cc(end))]/facV; %ensure at least 10 color levels fac0=1; while length(cc)<15; fac0=fac0*2; cc=prctile(fac0*facV*fld,[2.5 97.5]); cc=[floor(cc(1)):ceil(cc(end))]/facV/fac0; end; %ensure at most 10 color levels fac0=1; while length(cc)>30; fac0=fac0/2; cc=prctile(fac0*facV*fld,[2.5 97.5]); cc=[floor(cc(1)):ceil(cc(end))]/facV/fac0; end; end; % figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- ',title0}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; if multiTimes; fld=fld_std(:,:,kk).*mygrid.mskC(:,:,kk); cc=1/facV/facD*cc_std; if strcmp(vvtxt,'WVELMASS'); cc=1/facV*cc_std; end; if doAnomalies; cc=scaleAnom*cc; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- ',title0}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end;%for kk=... end;%for vv=... end;%if ( sum(strcmp(... %now do surface fluxes and forcing fields if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'qnet')); if addToTex; write2tex(fileTex,1,'air-sea heat flux',2); end; %qnet from ocean+ice: fld=-alldiag.SIatmQnt_mean; cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]; title0='QNET to ocean+ice'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*10; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- QNET to ocean+ice (W/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %qnet to ocean: fld=alldiag.oceQnet_mean; cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]; title0='QNET to ocean'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*10; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- QNET to ocean (W/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; if multiTimes; %qnet from ocean+ice: fld=alldiag.SIatmQnt_std; cc=[[0:5:25] 35 [50:25:200] [250 300]]; title0='std(QNET to ocean+ice)'; if doAnomalies; cc=scaleAnom*[0:0.1:1]*5; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- QNET to ocean+ice (W/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %qnet from ocean: fld=alldiag.oceQnet_std; cc=[[0:5:25] 35 [50:25:200] [250 300]]; title0='std(QNET to ocean)'; if doAnomalies; cc=scaleAnom*[0:0.1:1]*5; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- QNET to ocean (W/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'fwf')); if addToTex; write2tex(fileTex,1,'air-sea freshwater flux',2); end; %FW flux from ocean+ice: fld=-alldiag.SIatmFW_mean/1000;%conversion to m/s fld=fld*86400*1000;%conversion to mm/day cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]*0.06; title0='E-P-R to ocean+ice'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.5; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- E-P-R from ocean+ice (mm/day)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %FW flux from ocean: fld=-alldiag.oceFWflx_mean/1000;%conversion to m/s fld=fld*86400*1000;%conversion to mm/day cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]*0.06; title0='E-P-R to ocean'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.5; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- E-P-R from ocean (mm/day)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; if multiTimes; %empmr from ocean+ice: fld=alldiag.SIatmFW_std*86400;%conversion to mm/day cc=[[0:5:25] 35 [50:25:200] [250 300]]*0.04; title0='std(E-P-R to ocean+ice)'; if doAnomalies; cc=scaleAnom*[0:0.1:1]*0.5; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- E-P-R to ocean+ice (W/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %empmr from ocean: fld=alldiag.oceFWflx_std*86400;%conversion to mm/day cc=[[0:5:25] 35 [50:25:200] [250 300]]*0.04; title0='std(E-P-R to ocean)'; if doAnomalies; cc=scaleAnom*[0:0.1:1]*0.5; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- E-P-R to ocean (W/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'tau')); if addToTex; write2tex(fileTex,1,'surface wind stress',2); end; %zonal wind stress: fld=alldiag.fldTZ_mean; cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]/500; title0='zonal wind stress'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.01; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- zonal wind stress (N/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %meridional wind stress: fld=alldiag.fldTM_mean; cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]/500; title0='meridional wind stress'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.01; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- meridional wind stress (N/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %fld=alldiag.curlTau_mean; %cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]/5e8; title0='wind stress curl'; %if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.01; end; %figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); %myCaption={myYmeanTxt,'mean -- wind stress curl (N/m$^3$)'}; %if addToTex; write2tex(fileTex,2,myCaption,gcf); end; if multiTimes; %zonal wind stress: fld=alldiag.fldTZ_std; cc=[[0:5:25] 35 [50:25:200] [250 300]]/2000; title0='std(tauZ)'; if doAnomalies; cc=scaleAnom*[0:0.1:1]*0.005; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- tauZ (W/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %meridional wind stress: fld=alldiag.fldTM_std; cc=[[0:5:25] 35 [50:25:200] [250 300]]/2000; title0='std(tauM)'; if doAnomalies; cc=scaleAnom*[0:0.1:1]*0.005; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- tauM (W/m$^2$)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %fld=alldiag.curlTau_std; %cc=[[0:5:25] 35 [50:25:200] [250 300]]/1e9; title0='wind stress curl'; %if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.01; end; %figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); %myCaption={myYmeanTxt,'standard deviation -- tauCurl (N/m$^3$)'}; %if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; end; gcmfaces/gcmfaces_diags/diags_driver.m0000644000435400001440000000644012367511015017751 0ustar gforgetusersfunction []=diags_driver(dirModel,dirMat,years,setDiags,doInteractive); %object: compute the various cost and physics % diagnosits from model output %input: dirModel is the directory containing 'diags/' or 'nctiles/' % dirMat is the directory where diagnostics results will be saved % if isempty(dirMat) then [dirModel 'mat/'] is used by default % years (vector) that states years (or sets of 12 records) to compute % if years=[1:4] then the first 4 years are computed %(optional) setDiags further specifies physical diags to be computed % if setDiags='A' then one set of diags ('A') is computed % By default three sets of diags ('A','B','C') are computed. %(optional) doInteractive=1 allows users to specify parameters interactively % doInteractive = 0 (default) uses ECCO v4 parameters % and omits budgets and model-data misfits analyses % %notes : eventually should also use dirMat, dirTex interactively for years=[]; gcmfaces_global; global myparms; %%%%%%%%%%%%%%% %pre-processing %%%%%%%%%%%%%%% if isempty(who('doInteractive')); doInteractive=0; end; myswitch=diags_pre_process(dirModel,dirMat,doInteractive); dirModel=[dirModel '/']; if isempty(dirMat); dirMat=[dirModel 'mat/']; else; dirMat=[dirMat '/']; end; if ~doInteractive; myparms.yearInAve=[years(1) years(end)]; myparms.recInAve=[1 12]+12*([years(1) years(end)]-1992); years=years-1992+1; eval(['save ' dirMat 'diags_grid_parms.mat myparms;']); end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %now do the selected computation chunk: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if ~isempty(who('setDiags')); lChunk=12; %physical diagnostics for myYear=years; diags_select(dirModel,dirMat,setDiags,lChunk,myYear); end; else; for myYear=years; %standard physical diagnostics : diags_select(dirModel,dirMat,'A',12,myYear); if ~doInteractive; diags_select(dirModel,dirMat,'B',12,myYear); elseif myYear==years(1); recInAve=[myparms.recInAve(1):myparms.recInAve(2)]; diags_select(dirModel,dirMat,'B',1,recInAve); end; diags_select(dirModel,dirMat,'C',12,myYear); %budgets : if myswitch.doBudget; budget_list=1; if ~isempty(dir([dirMat 'diags_select_budget_list.mat'])); eval(['load ' dirMat 'diags_select_budget_list.mat;']); end; for kk=budget_list; diags_select(dirModel,dirMat,{'D',kk},12,myYear); end; end; %model-data misfits : % in situ profiles fit if myswitch.doProfiles&myYear==years(1); insitu_diags(dirMat,1); end; % altimeter fit if myswitch.doCost&myYear==years(1); cost_altimeter(dirModel,dirMat); end; % other cost terms if myswitch.doCost&myYear==years(1); cost_sst(dirModel,dirMat,1); end; if myswitch.doCost&myYear==years(1); cost_bp(dirModel,dirMat,1); end; if myswitch.doCost&myYear==years(1); cost_seaicearea(dirModel,dirMat,1); end; % controls if myswitch.doCtrl&myYear==years(1); cost_xx(dirModel,dirMat,1); end; end; end; gcmfaces/gcmfaces_diags/diags_list_times.m0000644000435400001440000000263712274263207020642 0ustar gforgetusersfunction [listTimes]=diags_list_times(listSubdirs,listFiles); %object : get the list of diags times by scanning pkg/diagnostics files %inputs : listSubdirs is the cell array of directories to scan, in order % listFiles is the list of files to scan for, in order %example: listSubdirs={[dirMat 'BUDG/' ],[dirModel 'diags/BUDG/' ],[dirModel 'diags/OTHER/' ],... % [dirModel 'diags/STATE/' ],[dirModel 'diags/TRSP/'],[dirModel 'diags/' ]}; % listFiles={'state_2d_set1.','diags_2d_set1.','monthly_2d_set1.'}; gcmfaces_global; global myparms; if isfield(myenv,'nctiles'); use_nctiles=myenv.nctiles; else; use_nctiles=0; end; %get time list from binary directory scan if ~use_nctiles; listTimes=[]; for kk=1:length(listFiles); if isempty(listTimes); for jj=1:length(listSubdirs); tmp1=dir([listSubdirs{jj} '/' listFiles{kk} '.*meta']); if ~isempty(tmp1); for tt=1:length(tmp1); listTimes=[listTimes;str2num(tmp1(tt).name(end-14:end-5))]; end; end; end; end; end; end; %get time list from one netcdf file if use_nctiles; timeStep=[]; di=myenv.nctilesdir; %nm=myenv.nctileslist{1}; nm='ETAN'; fileIn=sprintf('%s/%s/%s.%04d.nc',di,nm,nm,1); nc=netcdf.open(fileIn,0); vv = netcdf.inqVarID(nc,'step'); listTimes=netcdf.getVar(nc,vv); netcdf.close(nc); end; %if no files were found then stop if isempty(listTimes); error('no files were found'); end; gcmfaces/gcmfaces_diags/diags_set_LAYERS.m0000644000435400001440000002056712075643535020347 0ustar gforgetusers layersOffline=0; layersEulerian=0; integrateFromBottom=1; if isempty(whos('setDiagsParams')); setDiagsParams={}; end; if length(setDiagsParams)==2; layersName=setDiagsParams{1}; layersLims=setDiagsParams{2}; layersOffline=1; layersEulerian=1;%hacked : should be 0 elseif length(setDiagsParams)==1; layersName=setDiagsParams{1}; else; layersName='1SLT'; end; layersFileSuff=['LAYERS_' layersName]; if layersOffline; layersFileSuff=['LAYERS_offline_' layersName]; end; %override default file name: %--------------------------- fileMat=['diags_set_' layersFileSuff]; if userStep==1;%diags to be computed listDiags=['layersParams gloOV gloThick gloDelThick gloBAR']; if sum([90 1170]~=mygrid.ioSize)==0; listDiags=[listDiags ' atlOV atlThick atlDelThick atlBAR']; listDiags=[listDiags ' pacindOV pacindThick pacindDelThick pacindBAR']; end; elseif userStep==2&~layersOffline;%input files and variables listFlds={ ['LaUH' layersName],['LaVH' layersName],... ['LaHw' layersName],['LaHs' layersName]}; listFldsNames=deblank(listFlds); listFiles={'layersDiags'}; listSubdirs={[dirModel 'diags/LAYERS/' ]}; %load layersLims consistent with online MITgcmpkg/layers layersLims=squeeze(rdmds([dirModel 'diags/LAYERS/layers' layersName])); elseif userStep==2&layersOffline;%input files and variables listFlds={'THETA','SALT','UVELMASS','VVELMASS','GM_PsiX','GM_PsiY'}; listFldsNames=deblank(listFlds); listFiles={'state_3d_set1','trsp_3d_set1','trsp_3d_set2'}; elseif userStep==3; %override default file name: %--------------------------- fileMat=['diags_set_' layersFileSuff '_' num2str(tt) '.mat']; if ~layersOffline; eval(['fldU=LaUH' layersName '; fldV=LaVH' layersName ';']); if ~isempty(whos(['LaHw' layersName])); eval(['fldHw=LaHw' layersName '; fldHs=LaHs' layersName ';']); else; fldHw=[]; fldHs=[]; end; layersGrid=(layersLims(1:end-1)+layersLims(2:end))'/2; else; if ~layersEulerian; [fldUbolus,fldVbolus,fldWbolus]=calc_bolus(GM_PsiX,GM_PsiY); fldUbolus=fldUbolus.*mygrid.mskW; fldVbolus=fldVbolus.*mygrid.mskS; UVELMASS=UVELMASS+fldUbolus; VVELMASS=VVELMASS+fldVbolus; end; U=UVELMASS.*mk3D(mygrid.DRF,UVELMASS); V=VVELMASS.*mk3D(mygrid.DRF,VVELMASS); if strcmp(layersName,'2TH'); tracer=THETA; if isempty(whos('layersLims')); layersLims=[-2:35]; end; elseif strcmp(layersName,'1SLT'); tracer=SALT; if isempty(whos('layersLims')); layersLims=[33:0.1:38]; end; elseif strcmp(layersName,'3RHO'); P=mk3D(-mygrid.RC,THETA); t=convert2vector(THETA); s=convert2vector(SALT); p=convert2vector(P); pref=2000+0*p;%could be made an extra param [rhop,rhpis,rhor] = density(t,s,p,pref); tracer=convert2vector(rhor); if isempty(whos('layersLims')); layersLims=1000+[30:0.1:38]'; end; end layersGrid=(layersLims(1:end-1)+layersLims(2:end))'/2; tic; [fldU,fldV]=layers_remap({U,V},'extensive',tracer,layersGrid,1); toc;%hacked: should be 2 fldHw=[]; fldHs=[]; end;%if ~layersOffline; if sum([90 1170]~=mygrid.ioSize)==0; listBasins=[1:3]; else; listBasins=1; end; for bb=listBasins; %mask : global, atlantic or Pac+Ind if bb==1; mskC=mygrid.mskC(:,:,1); mskW=mygrid.mskW(:,:,1); mskS=mygrid.mskS(:,:,1); elseif bb==2; [mskC,mskW,mskS]=v4_basin({'atlExt'}); elseif bb==3; [mskC,mskW,mskS]=v4_basin({'pacExt','indExt'}); end; mskC3d=1*(mskC>0); mskW3d=1*(mskW>0); mskS3d=1*(mskS>0); mskC3d=mk3D(mskC3d,fldU); mskW3d=mk3D(mskW3d,fldU); mskS3d=mk3D(mskS3d,fldU); %the overturning streamfunction computation itself layersOV=calc_overturn(fldU.*mskW3d,fldV.*mskS3d,1,{'dh'}); %the associated barotropic streamfunction (for checking) layersBAR=calc_barostream(fldU.*mskW3d,fldV.*mskS3d,1,{'dh'}); %the associated thickness if isempty(fldHw); layersThick=[]; layersDelThick=[]; else; %interpolate to tracer points fldH=0*fldHw; [fldHwp,fldHsp]=exch_UV(LaHw1SLT.*mskW3d,LaHs1SLT.*mskS3d); for iF=1:fldH.nFaces; tmpA=fldHwp{iF}(2:end,:,:); tmpB=fldHwp{iF}(1:end-1,:,:); tmpC=fldHsp{iF}(:,2:end,:); tmpD=fldHsp{iF}(:,1:end-1,:); tmpTot=tmpA+tmpB+tmpC+tmpD; tmpNb=1*(tmpA~=0)+1*(tmpB~=0)+1*(tmpC~=0)+1*(tmpD~=0); jj=find(tmpNb>0); tmpTot(jj)=tmpTot(jj)./tmpNb(jj); jj=find(isnan(tmpTot)); tmpTot(jj)=0; fldH{iF}=tmpTot; end; %compute zonal mean fldH=calc_zonmean_T(fldH.*mskC3d); %integrate to overturning points if integrateFromBottom; layersThick=[flipdim(cumsum(flipdim(fldH,2),2),2) zeros(size(fldH,1),1)]; else; layersThick=[zeros(size(fldH,1),1) cumsum(fldH,2)]; end; %compute dH/dLayer layersDelThick=[zeros(size(fldH,1),1) fldH./( ones(size(fldH,1),1)*diff(layersLims') )]; end; %store to global, atlantic or Pac+Ind arrays: if bb==1; gloOV=layersOV; gloThick=layersThick; gloDelThick=layersDelThick; gloBAR=layersBAR; elseif bb==2; kk=find(mygrid.LATS<-35|mygrid.LATS>70); layersOV(kk,:)=NaN; if ~isempty(layersThick); layersThick(kk,:)=NaN; layersDelThick(kk,:)=NaN; end; atlOV=layersOV; atlThick=layersThick; atlDelThick=layersDelThick; atlBAR=layersBAR; elseif bb==3; kk=find(mygrid.LATS<-35|mygrid.LATS>65); layersOV(kk,:)=NaN; if ~isempty(layersThick); layersThick(kk,:)=NaN; layersDelThick(kk,:)=NaN; end; pacindOV=layersOV; pacindThick=layersThick; pacindDelThick=layersDelThick; pacindBAR=layersBAR; end; end; layersParams.name=layersName; layersParams.LC=layersGrid; layersParams.LF=layersLims; layersParams.isOffline=layersOffline; layersParams.suffix=layersFileSuff; layersParams.isEulerian=layersEulerian; %===================== COMPUTATIONAL SEQUENCE ENDS =========================% %===================== PLOTTING SEQUENCE BEGINS =========================% elseif userStep==-1;%plotting %meridional streamfunction (Eulerian) : fld=mean(alldiag.gloOV(:,:,tt),3); fld(fld==0)=NaN; X=mygrid.LATS*ones(1,length(alldiag.layersParams.LF)); Y=ones(length(mygrid.LATS),1)*(alldiag.layersParams.LF'); cc=[[-50:10:-30] [-24:3:24] [30:10:50]]; title0='Meridional Stream Function'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]; end; figureL; set(gcf,'Renderer','zbuffer'); %set(gcf,'Units','Normalized','Position',[0.05 0.1 0.4 0.8]); pcolor(X,Y,fld); shading interp; cbar=gcmfaces_cmap_cbar(cc); title(title0); myCaption={myYmeanTxt,'mean -- overturning streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; if multiBasins; %meridional streamfunction (Eulerian): fld=mean(alldiag.atlOV(:,:,tt),3); fld(fld==0)=NaN; X=mygrid.LATS*ones(1,length(alldiag.layersParams.LF)); Y=ones(length(mygrid.LATS),1)*(alldiag.layersParams.LF'); cc=[[-50:10:-30] [-24:3:24] [30:10:50]]; title0='Atlantic Meridional Stream Function'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]; end; figureL; set(gcf,'Renderer','zbuffer'); %set(gcf,'Units','Normalized','Position',[0.05 0.1 0.4 0.8]); pcolor(X,Y,fld); shading interp; cbar=gcmfaces_cmap_cbar(cc); title(title0); myCaption={myYmeanTxt,'mean -- Atlantic overturning streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %meridional streamfunction (residual): fld=mean(alldiag.pacindOV(:,:,tt),3); fld(fld==0)=NaN; X=mygrid.LATS*ones(1,length(alldiag.layersParams.LF)); Y=ones(length(mygrid.LATS),1)*(alldiag.layersParams.LF'); cc=[[-50:10:-30] [-24:3:24] [30:10:50]]; title0='Pac+Ind Meridional Stream Function'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]; end; figureL; set(gcf,'Renderer','zbuffer'); %set(gcf,'Units','Normalized','Position',[0.05 0.1 0.4 0.8]); pcolor(X,Y,fld); shading interp; cbar=gcmfaces_cmap_cbar(cc); title(title0); myCaption={myYmeanTxt,'mean -- Pac+Ind overturning streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; gcmfaces/gcmfaces_diags/diags_set_A.m0000644000435400001440000005450212367511325017517 0ustar gforgetusers if userStep==1;%diags to be computed listDiags='fldBAR fldTRANSPORTS gloOV gloOVbolus gloOVres gloMT_H gloMT_FW gloMT_SLT'; if sum([90 1170]~=mygrid.ioSize)==0; listDiags=[listDiags ' atlOV atlOVbolus atlOVres atlMT_H atlMT_FW atlMT_SLT']; listDiags=[listDiags ' pacindOV pacindOVbolus pacindOVres pacindMT_H pacindMT_FW pacindMT_SLT']; end; elseif userStep==2;%input files and variables listFlds={'UVELMASS','VVELMASS','GM_PsiX','GM_PsiY'}; listFlds={listFlds{:},'ADVx_TH ','ADVy_TH ','DFxE_TH ','DFyE_TH '}; listFlds={listFlds{:},'ADVx_SLT','ADVy_SLT','DFxE_SLT','DFyE_SLT'}; listFldsNames=deblank(listFlds); listFiles={'trsp_3d_set1','trsp_2d_set1','trsp_3d_set2'}; listSubdirs={[dirModel 'diags/TRSP/']}; elseif userStep==3;%computational part; %mask fields: fldU=UVELMASS.*mygrid.mskW; fldV=VVELMASS.*mygrid.mskS; if ~isempty(whos('ADVx_TH'));%for backward compatibility if size(ADVx_TH{1},3)>1; %assume full 3D fields mskW=mygrid.mskW; mskS=mygrid.mskS; else; %assume vertically integrated (2D fields) mskW=mygrid.mskW(:,:,1); mskS=mygrid.mskS(:,:,1); end; ADVx_TH=ADVx_TH.*mskW; ADVy_TH=ADVy_TH.*mskS; ADVx_SLT=ADVx_SLT.*mskW; ADVy_SLT=ADVy_SLT.*mskS; DFxE_TH=DFxE_TH.*mskW; DFyE_TH=DFyE_TH.*mskS; DFxE_SLT=DFxE_SLT.*mskW; DFyE_SLT=DFyE_SLT.*mskS; end; if ~isempty(whos('GM_PsiX'));%for backward compatibility [fldUbolus,fldVbolus,fldWbolus]=calc_bolus(GM_PsiX,GM_PsiY); fldUbolus=fldUbolus.*mygrid.mskW; fldVbolus=fldVbolus.*mygrid.mskS; fldUres=fldU+fldUbolus; fldVres=fldV+fldVbolus; end; %compute barotropic stream function: [fldBAR]=calc_barostream(fldU,fldV); %compute transports along transects: [fldTRANSPORTS]=1e-6*calc_transports(fldU,fldV,mygrid.LINES_MASKS,{'dh','dz'}); %compute overturning stream functions: if sum([90 1170]~=mygrid.ioSize)==0; listBasins=[1:3]; else; listBasins=1; end; for bb=listBasins; %mask : global, atlantic or Pac+Ind if bb==1; mskC=mygrid.mskC; mskC(:)=1; elseif bb==2; mskC=v4_basin({'atlExt'}); mskC=mk3D(mskC,fldU); elseif bb==3; mskC=v4_basin({'pacExt','indExt'}); mskC=mk3D(mskC,fldU); end; %note: while mskC is a basin mask for tracer points, it can be applied to U/V below %compute overturning: eulerian contribution [fldOV]=calc_overturn(fldU.*mskC,fldV.*mskC); if ~isempty(whos('GM_PsiX'));%for backward compatibility %compute overturning: eddy contribution [fldOVbolus]=calc_overturn(fldUbolus.*mskC,fldVbolus.*mskC); %compute overturning: residual overturn [fldOVres]=calc_overturn(fldUres.*mskC,fldVres.*mskC); else; fldOVbolus=NaN*fldOV; fldOVres=NaN*fldOV; end; if ~isempty(whos('ADVx_TH'));%for backward compatibility %compute meridional heat transports: tmpU=(ADVx_TH+DFxE_TH).*mskC(:,:,1:size(ADVx_TH{1},3)); tmpV=(ADVy_TH+DFyE_TH).*mskC(:,:,1:size(ADVx_TH{1},3)); [fldMT_H]=1e-15*4e6*calc_MeridionalTransport(tmpU,tmpV,0); %compute meridional fresh water transports: %... using the virtual salt flux formula: %[fldMT_FW]=1e-6/35*calc_MeridionalTransport(ADVx_SLT+DFxE_SLT,ADVy_SLT+DFyE_SLT,0); %[fldMT_FW]=1e-6/35*calc_MeridionalTransport(ADVx_SLT,ADVy_SLT,0); %... using the real freshwater flux formula: [fldMT_FW]=1e-6*calc_MeridionalTransport(fldU.*mskC,fldV.*mskC,1); %compute meridional salt transports: tmpU=(ADVx_SLT+DFxE_SLT).*mskC(:,:,1:size(ADVx_TH{1},3)); tmpV=(ADVy_SLT+DFyE_SLT).*mskC(:,:,1:size(ADVx_TH{1},3)); [fldMT_SLT]=1e-6*calc_MeridionalTransport(tmpU,tmpV,0); else; fldMT_H=NaN*mygrid.LATS; fldMT_FW=NaN*mygrid.LATS; fldMT_SLT=NaN*mygrid.LATS; end; %store to global, atlantic or Pac+Ind arrays: if bb==1; gloMT_H=fldMT_H; gloMT_FW=fldMT_FW; gloMT_SLT=fldMT_SLT; gloOV=fldOV; gloOVbolus=fldOVbolus; gloOVres=fldOVres; elseif bb==2; kk=find(mygrid.LATS<-35|mygrid.LATS>70); fldMT_H(kk,:)=NaN; fldMT_FW(kk,:)=NaN; fldMT_SLT(kk,:)=NaN; fldOV(kk,:)=NaN; fldOVbolus(kk,:)=NaN; fldOVres(kk,:)=NaN; atlMT_H=fldMT_H; atlMT_FW=fldMT_FW; atlMT_SLT=fldMT_SLT; atlOV=fldOV; atlOVbolus=fldOVbolus; atlOVres=fldOVres; elseif bb==3; kk=find(mygrid.LATS<-35|mygrid.LATS>65); fldMT_H(kk,:)=NaN; fldMT_FW(kk,:)=NaN; fldMT_SLT(kk,:)=NaN; fldOV(kk,:)=NaN; fldOVbolus(kk,:)=NaN; fldOVres(kk,:)=NaN; pacindMT_H=fldMT_H; pacindMT_FW=fldMT_FW; pacindMT_SLT=fldMT_SLT; pacindOV=fldOV; pacindOVbolus=fldOVbolus; pacindOVres=fldOVres; end; end; %===================== COMPUTATIONAL SEQUENCE ENDS =========================% %===================== PLOTTING SEQUENCE BEGINS =========================% elseif userStep==-1;%plotting if isempty(setDiagsParams); choicePlot={'all'}; else; choicePlot=setDiagsParams; end; if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'bf')); if addToTex; write2tex(fileTex,1,'barotropic streamfunction',2); end; %barotropic streamfunction: fld=mean(alldiag.fldBAR(:,:,tt),3); cc=[[-80:20:-40] [-25 -15:5:15 25] [40:40:200]]; title0='Horizontal Stream Function'; if doAnomalies; cc=scaleAnom*[-5:0.5:5]; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,'mean -- barotropic streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %and the corresponding standard deviation: if multiTimes; fld=std(alldiag.fldBAR(:,:,tt),[],3); cc=[0:0.5:3 4 5 7 10 15:5:25 35 50]; title0='Horizontal Stream Function'; if doAnomalies; cc=scaleAnom*[0:0.25:2]; end; figureL; m_map_gcmfaces(fld,0,{'myCaxis',cc},{'do_m_coast',1},{'myTitle',title0}); myCaption={myYmeanTxt,' standard deviation -- barotropic streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'ov')); if addToTex; write2tex(fileTex,1,'meridional streamfunction',2); end; %meridional streamfunction (Eulerian) : fld=mean(alldiag.gloOV(:,:,tt),3); fld(fld==0)=NaN; X=mygrid.LATS*ones(1,length(mygrid.RF)); Y=ones(length(mygrid.LATS),1)*(mygrid.RF'); cc=[[-50:10:-30] [-24:3:24] [30:10:50]]; title0='Meridional Stream Function'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]; end; figureL; set(gcf,'Renderer','zbuffer'); %set(gcf,'Units','Normalized','Position',[0.05 0.1 0.4 0.8]); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc); title(title0); myCaption={myYmeanTxt,'mean -- overturning streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %meridional streamfunction (residual) : fld=mean(alldiag.gloOVres(:,:,tt),3); fld(fld==0)=NaN; X=mygrid.LATS*ones(1,length(mygrid.RF)); Y=ones(length(mygrid.LATS),1)*(mygrid.RF'); cc=[[-50:10:-30] [-24:3:24] [30:10:50]]; title0='Meridional Stream Function (incl. GM)'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]; end; figureL; set(gcf,'Renderer','zbuffer'); %set(gcf,'Units','Normalized','Position',[0.05 0.1 0.4 0.8]); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc); title(title0); myCaption={myYmeanTxt,'mean -- overturning streamfunction incl. GM (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; if multiBasins; %meridional streamfunction (Eulerian): fld=mean(alldiag.atlOV(:,:,tt),3); fld(fld==0)=NaN; X=mygrid.LATS*ones(1,length(mygrid.RF)); Y=ones(length(mygrid.LATS),1)*(mygrid.RF'); cc=[[-50:10:-30] [-24:3:24] [30:10:50]]; title0='Atlantic Meridional Stream Function'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]; end; figureL; set(gcf,'Renderer','zbuffer'); %set(gcf,'Units','Normalized','Position',[0.05 0.1 0.4 0.8]); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc); title(title0); myCaption={myYmeanTxt,'mean -- Atlantic overturning streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %meridional streamfunction (residual): fld=mean(alldiag.pacindOV(:,:,tt),3); fld(fld==0)=NaN; X=mygrid.LATS*ones(1,length(mygrid.RF)); Y=ones(length(mygrid.LATS),1)*(mygrid.RF'); cc=[[-50:10:-30] [-24:3:24] [30:10:50]]; title0='Pac+Ind Meridional Stream Function'; if doAnomalies; cc=scaleAnom*[-1:0.1:1]; end; figureL; set(gcf,'Renderer','zbuffer'); %set(gcf,'Units','Normalized','Position',[0.05 0.1 0.4 0.8]); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc); title(title0); myCaption={myYmeanTxt,'mean -- Pac+Ind overturning streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; if multiTimes; %and the corresponding standard deviation: fld=std(alldiag.gloOV(:,:,tt),[],3); fld(fld==0)=NaN; X=mygrid.LATS*ones(1,length(mygrid.RF)); Y=ones(length(mygrid.LATS),1)*(mygrid.RF'); cc=[0:0.5:3 4 5 7 10 15:5:25 35 50]; title0='Meridional Stream Function'; if doAnomalies; cc=scaleAnom*[0:0.1:1]; end; figureL; set(gcf,'Renderer','zbuffer'); %set(gcf,'Units','Normalized','Position',[0.05 0.1 0.4 0.8]); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc); title(title0); myCaption={myYmeanTxt,' standard deviation -- overturning streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; if multiTimes&multiBasins; %and the corresponding standard deviation: fld=std(alldiag.atlOV(:,:,tt),[],3); fld(fld==0)=NaN; X=mygrid.LATS*ones(1,length(mygrid.RF)); Y=ones(length(mygrid.LATS),1)*(mygrid.RF'); cc=[0:0.5:3 4 5 7 10 15:5:25 35 50]; title0='Atlantic Meridional Stream Function'; if doAnomalies; cc=scaleAnom*[0:0.1:1]; end; figureL; set(gcf,'Renderer','zbuffer'); %set(gcf,'Units','Normalized','Position',[0.05 0.1 0.4 0.8]); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc); title(title0); myCaption={myYmeanTxt,' standard deviation -- Atlantic overturning streamfunction (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'ovtime')); if addToTex; write2tex(fileTex,1,'meridional streamfunction (time series)',2); end; %time series if multiTimes; figureL; tmp1=abs(-mygrid.RC-1000); kk=find(tmp1==min(tmp1)); kk=kk(1); gloOV1000=squeeze(alldiag.gloOV(:,kk,:)); gloOV1000=runmean(gloOV1000,myNmean,2); plot(TT,gloOV1000(90+25,:),'LineWidth',2); hold on; plot(TT,gloOV1000(90+35,:),'k','LineWidth',2); plot(TT,gloOV1000(90+45,:),'r','LineWidth',2); plot(TT,gloOV1000(90+55,:),'g','LineWidth',2); title0='annual global overturning at \approx 1000m depth (Sv)'; aa=axis; aa() legend('25N','35N','45N','55N'); title(title0); aa(3:4)=[0 20]; axis(aa); grid on; if doAnomalies; aa(3:4)=scaleAnom*[-1 1]; axis(aa); end; myCaption={'annual global overturning at select latitudes at $\\approx$ 1000m depth'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; if multiTimes&multiBasins; figureL; tmp1=abs(-mygrid.RC-1000); kk=find(tmp1==min(tmp1)); kk=kk(1); atlOV1000=squeeze(alldiag.atlOV(:,kk,:)); atlOV1000=runmean(atlOV1000,myNmean,2); plot(TT,atlOV1000(90+25,:),'LineWidth',2); hold on; plot(TT,atlOV1000(90+35,:),'k','LineWidth',2); plot(TT,atlOV1000(90+45,:),'r','LineWidth',2); plot(TT,atlOV1000(90+55,:),'g','LineWidth',2); title0='annual atlantic overturning at \approx 1000m depth'; legend('25N','35N','45N','55N'); title(title0); aa(3:4)=[0 20]; axis(aa); grid on; if doAnomalies; aa(3:4)=scaleAnom*[-1 1]*2; axis(aa); end; myCaption={'annual Atlantic overturning at select latitudes at $\\approx$ 1000m depth (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mht')); if addToTex; write2tex(fileTex,1,'meridional heat transport',2); end; %meridional heat transport figureL; fld=mean(alldiag.gloMT_H(:,tt),2); plot(mygrid.LATS,fld,'LineWidth',2); if multiBasins; atl=mean(alldiag.atlMT_H(:,tt),2); pacind=mean(alldiag.pacindMT_H(:,tt),2); hold on; plot(mygrid.LATS,atl,'r','LineWidth',2); plot(mygrid.LATS,pacind,'g','LineWidth',2); legend('global','Atlantic','Pacific+Indian','Location','SouthEast'); end; set(gca,'FontSize',14); grid on; axis([-90 90 -2 2]); if doAnomalies; aa=axis; aa(3:4)=scaleAnom*[-1 1]*0.05; axis(aa); end; title('Meridional Heat Transport (in PW)'); myCaption={myYmeanTxt,'mean -- meridional heat transport (PW)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %and the corresponding standard deviation: if multiTimes; figureL; fld=std(alldiag.gloMT_H(:,tt),[],2); plot(mygrid.LATS,fld,'LineWidth',2); if multiBasins; atl=std(alldiag.atlMT_H(:,tt),[],2); pacind=std(alldiag.pacindMT_H(:,tt),[],2); hold on; plot(mygrid.LATS,atl,'r','LineWidth',2); plot(mygrid.LATS,pacind,'g','LineWidth',2); legend('global','Atlantic','Pacific+Indian'); end; set(gca,'FontSize',14); grid on; axis([-90 90 0 4]); if doAnomalies; aa=axis; aa(3:4)=scaleAnom*[0 1]*0.1; axis(aa); end; title('Meridional Heat Transport (in PW)'); myCaption={myYmeanTxt,' standard deviation -- meridional heat transport (PW)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mfwt')); if addToTex; write2tex(fileTex,1,'meridional freshwater transport',2); end; %meridional freshwater transport figureL; fld=mean(alldiag.gloMT_FW(:,tt),2); plot(mygrid.LATS,fld,'LineWidth',2); if multiBasins; atl=mean(alldiag.atlMT_FW(:,tt),2); pacind=mean(alldiag.pacindMT_FW(:,tt),2); hold on; plot(mygrid.LATS,atl,'r','LineWidth',2); plot(mygrid.LATS,pacind,'g','LineWidth',2); legend('global','Atlantic','Pacific+Indian'); end; set(gca,'FontSize',14); grid on; axis([-90 90 -1.5 2.0]); if doAnomalies; aa=axis; aa(3:4)=scaleAnom*[-1 1]*0.1; axis(aa); end; title('Meridional Freshwater Transport (in Sv)'); myCaption={myYmeanTxt,'mean -- meridional freshwater transport (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %and the corresponding standard deviation: if multiTimes; figureL; fld=std(alldiag.gloMT_FW(:,tt),[],2); plot(mygrid.LATS,fld,'LineWidth',2); if multiBasins; atl=std(alldiag.atlMT_FW(:,tt),[],2); pacind=std(alldiag.pacindMT_FW(:,tt),[],2); hold on; plot(mygrid.LATS,atl,'r','LineWidth',2); plot(mygrid.LATS,pacind,'g','LineWidth',2); legend('global','Atlantic','Pacific+Indian'); end; set(gca,'FontSize',14); grid on; axis([-90 90 0 2]); if doAnomalies; aa=axis; aa(3:4)=scaleAnom*[0 1]*0.2; axis(aa); end; title('Meridional Freshwater Transport (in Sv)'); myCaption={myYmeanTxt,' standard deviation -- meridional freshwater transport (Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mslt')); if addToTex; write2tex(fileTex,1,'meridional salt transport',2); end; %meridional salt transport figureL; fld=mean(alldiag.gloMT_SLT(:,tt),2); plot(mygrid.LATS,fld,'LineWidth',2); if sum([90 1170]~=mygrid.ioSize)==0; atl=mean(alldiag.atlMT_SLT(:,tt),2); pacind=mean(alldiag.pacindMT_SLT(:,tt),2); hold on; plot(mygrid.LATS,atl,'r','LineWidth',2); plot(mygrid.LATS,pacind,'g','LineWidth',2); legend('global','Atlantic','Pacific+Indian'); end; set(gca,'FontSize',14); grid on; axis([-90 90 -50 50]); if doAnomalies; aa=axis; aa(3:4)=scaleAnom*[-1 1]*2; axis(aa); end; title('Meridional Salt Transport (in psu.Sv)'); myCaption={myYmeanTxt,'mean -- meridional salt transport (psu.Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %and the corresponding standard deviation: if multiTimes; figureL; fld=std(alldiag.gloMT_SLT(:,tt),[],2); plot(mygrid.LATS,fld,'LineWidth',2); if sum([90 1170]~=mygrid.ioSize)==0; atl=std(alldiag.atlMT_SLT(:,tt),[],2); pacind=std(alldiag.pacindMT_SLT(:,tt),[],2); hold on; plot(mygrid.LATS,atl,'r','LineWidth',2); plot(mygrid.LATS,pacind,'g','LineWidth',2); legend('global','Atlantic','Pacific+Indian'); end; set(gca,'FontSize',14); grid on; axis([-90 90 0 60]); if doAnomalies; aa=axis; aa(3:4)=scaleAnom*[0 1]*2; axis(aa); end; title('Meridional Salt Transport (in psu.Sv)'); myCaption={myYmeanTxt,' standard deviation -- meridional salt transport (psu.Sv)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if multiTimes&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mttime'))); if addToTex; write2tex(fileTex,1,'meridional transports (time series)',2); end; %meridional heat transport fld=squeeze(alldiag.gloMT_H(:,tt))'; x=TT*ones(1,length(mygrid.LATS)); y=ones(nt,1)*mygrid.LATS'; fld=runmean(fld,myNmean,1); cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]/50; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.05; end; figureL; pcolor(x,y,fld); shading flat; axis([TT(1) TT(end) -90 90]); gcmfaces_cmap_cbar(cc); title('Meridional Heat Transport (in PW)'); myCaption={'meridional heat transport (PW, annual mean)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %meridional freshwater transport fld=squeeze(alldiag.gloMT_FW(:,tt))'; x=TT*ones(1,length(mygrid.LATS)); y=ones(nt,1)*mygrid.LATS'; fld=runmean(fld,myNmean,1); cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]/100; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*0.05; end; figureL; pcolor(x,y,fld); shading flat; axis([TT(1) TT(end) -90 90]); gcmfaces_cmap_cbar(cc); title('Meridional Freshwater Transport (in Sv)'); myCaption={'meridional freshwater transport (Sv, annual mean)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %meridional salt transport fld=squeeze(alldiag.gloMT_SLT(:,tt))'; x=TT*ones(1,length(mygrid.LATS)); y=ones(nt,1)*mygrid.LATS'; fld=runmean(fld,myNmean,1); cc=[[-250:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:250]]/10; if doAnomalies; cc=scaleAnom*[-1:0.1:1]*1; end; figureL; pcolor(x,y,fld); shading flat; axis([TT(1) TT(end) -90 90]); gcmfaces_cmap_cbar(cc); title('Meridional Salt Transport (in psu.Sv)'); myCaption={'meridional salt transport (psu.Sv, annual mean)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'sectime'))); if addToTex; write2tex(fileTex,1,'transects transport',2); end; %Bering Strait and Arctic/Atlantic exchanges: if multiTimes; figureL; end; iiList=[1 8:12]; rrList=[[-1 3];[-3 1];[-7 -2];[0 9];[-4 4];[-0.5 0.5]]; for iii=1:length(iiList); ii=iiList(iii); if multiTimes; subplot(3,2,iii); end; trsp=squeeze(alldiag.fldTRANSPORTS(ii,:,:)); txt=[mygrid.LINES_MASKS(ii).name ' (>0 to Arctic)']; ylim=rrList(iii,:); if doAnomalies; ylim=scaleAnom*[-1 1]*0.4; end; disp_transport(trsp,TT,txt,{'ylim',ylim},{'nmean',myNmean}); end; myCaption={'volume transports entering the Arctic (Sv, annual mean)'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; %Florida Strait: if multiTimes; figureL; end; iiList=[3 4 6 7]; rrList=[[20 40];[20 40];[-1 3];[-6 2]]; for iii=1:length(iiList); ii=iiList(iii); if multiTimes; subplot(2,2,iii); end; trsp=squeeze(alldiag.fldTRANSPORTS(ii,:,:)); txt=[mygrid.LINES_MASKS(ii).name ' (>0 to Atlantic)']; ylim=rrList(iii,:); if doAnomalies; ylim=scaleAnom*[-1 1]*2; end; disp_transport(trsp,TT,txt,{'ylim',ylim},{'nmean',myNmean}); end; myCaption={'volume transports entering the Atlantic (Sv, annual mean)'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; %Gibraltar special case: if multiTimes; figureL; end; trsp=squeeze(alldiag.fldTRANSPORTS(2,:,:)); txt='Gibraltar Overturn (upper ocean transport towards Med.)'; ylim=[0.4 1.2]; if doAnomalies; ylim=scaleAnom*[-1 1]*0.05; end; disp_transport(trsp,TT,txt,{'ylim',ylim},{'nmean',myNmean},{'choicePlot',2}); myCaption={'Gibraltar Overturn (Sv, annual mean)'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; %Drake, ACC etc: if multiTimes; figureL; end; iiList=[13 20 19 18]; rrList=[[120 180];[140 200];[-40 -10];[140 200]]; for iii=1:length(iiList); ii=iiList(iii); if multiTimes; subplot(2,2,iii); end; trsp=squeeze(alldiag.fldTRANSPORTS(ii,:,:)); txt=[mygrid.LINES_MASKS(ii).name ' (>0 westward)']; ylim=rrList(iii,:); if doAnomalies; ylim=scaleAnom*[-1 1]*5; end; disp_transport(trsp,TT,txt,{'ylim',ylim},{'nmean',myNmean}); end; myCaption={'ACC volume transports (Sv, annual mean)'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; %Indonesian Throughflow special case: if multiTimes; figureL; end; %trsp=-squeeze(nansum(alldiag.fldTRANSPORTS([15:17],:,:),1)); trsp=-squeeze(nansum(alldiag.fldTRANSPORTS([14:17],:,:),1));%needed to fix sign for the (small) No.14 transport txt='Indonesian Throughflow (>0 toward Indian Ocean)'; ylim=[5 25]; if doAnomalies; ylim=scaleAnom*[-1 1]*0.5; end; disp_transport(trsp,TT,txt,{'ylim',ylim},{'nmean',myNmean}); myCaption={'Indonesian Throughflow (Sv, annual mean)'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); end; end; end; gcmfaces/gcmfaces_diags/diags_grid_parms.m0000644000435400001440000001741712366217533020622 0ustar gforgetusersfunction []=diags_grid_parms(listTimes,doInteractive); %object : load grid, set params, and save both to dirMat %input : listTimes is the time list obtained from diags_list_times %(optional) doInteractive=1 allows users to specify parameters interactively % doInteractive = 0 (default) uses ECCO v4 parameters % and omits budgets and model-data misfits analyses %global variables gcmfaces_global; global myparms; %load grid if isempty(dir('GRID')); dirGrid=input('grid directory?\n'); else; dirGrid='GRID/'; end; if doInteractive; nF=input('number of faces? (1, 4, 5or 6)\n'); frmt=input('file format ? (''straight'', ''cube'' or ''compact'')\n'); memoryLimit=input('memoryLimit ? (0=load full grid, 1=load less, 2=load even less)\n'); else; nF=5; frmt='compact'; memoryLimit=0; end; grid_load(dirGrid,nF,frmt,memoryLimit); %set default for model run parameters if doInteractive; choiceParams=input(['choice of default parameters? (1=ecco v4, ' ... '2=core, 3=ecco2 adjoint, 4=ecco v3, 5=core-Jeff)\n']); else; choiceParams=1; end; myparms=default_parms(choiceParams); %allow user to change model params if necessary myparms=review_parms(myparms,listTimes,doInteractive); function [parms]=default_parms(choiceParams); %set model parameters to default (ecco_v4) if choiceParams==1|choiceParams==2|choiceParams==4|choiceParams==5; parms.yearFirst=1992; %first year covered by model integration parms.yearLast =2011; %last year covered by model integration parms.yearInAve=[parms.yearFirst parms.yearLast]; %period for time averages and variance computations parms.timeStep =3600; %model time step for tracers parms.iceModel =1;%0=use freezing point 1=use pkg/seaice 2=use pkg/thsice parms.useRFWF =1;%1=real fresh water flux 0=virtual salt flux parms.useNLFS =2;%2=rstar 1=nlfs 0=linear free surface parms.rhoconst =1029; %sea water density parms.rcp =3994*parms.rhoconst; % sea water rho X heat capacity parms.rhoi = 910; %sea ice density parms.rhosn = 330; %snow density parms.flami = 3.34e05; % latent heat of fusion of ice/snow (J/kg) parms.flamb = 2.50e06; % latent heat of evaporation (J/kg) parms.SIsal0 =4; if choiceParams==2; parms.yearFirst=1948; %first year covered by model integration parms.yearLast =2007; %last year covered by model integration parms.yearInAve = [1948 2007]; end; if choiceParams==4; parms.useRFWF =0;%1=real fresh water flux 0=virtual salt flux parms.useNLFS =0;%2=rstar 1=nlfs 0=linear free surface end; if choiceParams==5; parms.yearFirst=2006; %first year covered by model integration parms.yearLast =2305; %last year covered by model integration parms.yearInAve = [2006 2305]; end; end; if choiceParams==3; parms.yearFirst=2004; %first year covered by model integration parms.yearLast =2005; %last year covered by model integration parms.yearInAve=[parms.yearFirst parms.yearLast]; %period for time averages and variance computations parms.timeStep =1200; %model time step for tracers parms.iceModel =1;%0=use freezing point 1=use pkg/seaice 2=use pkg/thsice parms.useRFWF =0;%1=real fresh water flux 0=virtual salt flux parms.useNLFS =0;%2=rstar 1=nlfs 0=linear free surface parms.rhoconst =1027.5; %sea water density parms.rcp =3994*parms.rhoconst; % sea water rho X heat capacity parms.rhoi = 910; %sea ice density parms.rhosn = 330; %snow density parms.flami = 3.34e05; % latent heat of fusion of ice/snow (J/kg) parms.flamb = 2.50e06; % latent heat of evaporation (J/kg) parms.SIsal0 = 0; end; function [parms]=review_parms(parms,listTimes,doInteractive); %review model parameters, correct them if needed, and check a couple more things test1=1;%so that we print params at least once while test1; fprintf('\n\n'); gcmfaces_msg('model parameters summary','==== '); tmp1=sprintf('parms.yearFirst = %i (first year covered by model integration)',parms.yearFirst); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.yearLast = %i (first year covered by model integration)',parms.yearLast); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.yearInAve = [%i %i] (time mean and variance years)',parms.yearInAve); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.timeStep = %i (model time step for tracers)',parms.timeStep); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.iceModel = %i (0=freezing point 1=pkg/seaice 2=pkg/thsice)',parms.iceModel); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.useRFWF = %i (1=real fresh water flux 0=virtual salt flux)',parms.useRFWF); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.useNLFS = %i; (2=rstar 1=nlfs 0=linear free surface)',parms.useNLFS); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.rhoconst = %0.6g (sea water density)',parms.rhoconst); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.rcp = %0.6g (sea water density X heat capacity)',parms.rcp); gcmfaces_msg(tmp1,'== '); if parms.iceModel==1; tmp1=sprintf('parms.rhoi = %0.6g (sea ice density)',parms.rhoi); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.rhosn = %0.6g (snow density)',parms.rhosn); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.flami = %0.6g (latent heat of fusion of ice/snow in J/kg)',parms.flami); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.flamb = %0.6g (latent heat of evaporation in J/kg)',parms.flamb); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.SIsal0 = %0.6g (sea ice constant salinity)',parms.SIsal0); gcmfaces_msg(tmp1,'== '); %tmp1=sprintf('',); gcmfaces_msg(tmp1,'== '); else; error('only parms.iceModel=1 is currently treated\n'); end; if doInteractive; gcmfaces_msg('to change a param type e.g. ''parms.yearFirst=1;'' or hit return if all params are ok. Change a param?','==== '); tmp1=input(''); test1=~isempty(tmp1); %so that we change param and iterate process if test1; eval(tmp1); end; else; test1=[]; end; end; %determine a few more things about the diagnostic time axis fprintf('\n\n'); parms.diagsNbRec=length(listTimes); test1=median(diff(listTimes)*parms.timeStep/86400); if abs(test1-30.5)<1; parms.diagsAreMonthly=1; else; parms.diagsAreMonthly=0; end; if abs(test1-365.25)<1; parms.diagsAreAnnual=1; else; parms.diagsAreAnnual=0; end; if doInteractive; tmp1=sprintf('parms.diagsNbRec = %i (number of records, based on model output files)',parms.diagsNbRec); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.diagsAreMonthly = %i (0/1 = false/true; based on output frequency)',parms.diagsAreMonthly); gcmfaces_msg(tmp1,'== '); tmp1=sprintf('parms.diagsAreAnnual = %i (0/1 = false/true; based on output frequency)',parms.diagsAreAnnual); gcmfaces_msg(tmp1,'== '); gcmfaces_msg('hit return if this seems correct otherwise stop here','== '); test0=input(''); if ~isempty(test0); error('likely dir problem'); end; end; listTimes2=parms.yearFirst+listTimes*parms.timeStep/86400/365.25;%this approximation of course makes things simpler tmp1=-0.5*diff(listTimes,1,1)*parms.timeStep/86400/365.25; tmp1=[median(tmp1);tmp1]; listTimes2=listTimes2+tmp1;%this converts the enddate to the middate of pkg/diags ii=find(listTimes2>=parms.yearInAve(1)&listTimes2<=parms.yearInAve(2)+1); if parms.diagsAreMonthly;%then restrict to full years ni=floor(length(ii)/12)*12; if ni>0; parms.recInAve=[ii(1) ii(floor(ni))]; else; parms.recInAve=[ii(1) ii(end)]; end; elseif ~isempty(ii); parms.recInAve=[ii(1) ii(end)]; else; parms.recInAve=[1 1]; end; if doInteractive; tmp1=sprintf('parms.recInAve = [%i %i] (time mean and variance records)',parms.recInAve); gcmfaces_msg(tmp1,'== '); end; fprintf('\n\n'); gcmfaces/gcmfaces_diags/diags_store_to_mat.m0000644000435400001440000000124512044544145021155 0ustar gforgetusersfunction []=diags_store_to_mat(dirMat,fileMat,onediag); %object : store results to memory as [dirMat fileMat] %inputs: dirMat is the matlab output directory name % fileMat is the matlab output file name. It is to be specified % by the diags_set routine, incl. the relevant time stamp. % onediag is a structure containting all fields to output listDiags=fieldnames(onediag); for jj=1:length(listDiags); eval([listDiags{jj} '=getfield(onediag,''' listDiags{jj} ''');']); if jj==1; eval(['save ' dirMat fileMat ' ' listDiags{jj} ';']); else; eval(['save ' dirMat fileMat ' -append ' listDiags{jj} ';']); end; end; gcmfaces/gcmfaces_diags/diags_set_C.m0000644000435400001440000004142212273204646017517 0ustar gforgetusers if userStep==1;%diags to be computed listDiags='fldTzonmean fldSzonmean fldETANzonmean fldSSHzonmean fldSIzonmean fldMLDzonmean'; listDiags=[listDiags ' IceAreaNorth IceAreaSouth IceVolNorth IceVolSouth SnowVolNorth SnowVolSouth']; listDiags=[listDiags ' Ueq Teq SSHglo Tglo Sglo TgloProf SgloProf']; elseif userStep==2;%input files and variables listFlds={ 'THETA','SALT','ETAN','SIarea','SIheff','SIhsnow','sIceLoad','MXLDEPTH','UVELMASS','VVELMASS'}; listFldsNames=deblank(listFlds); listFiles={'state_2d_set1','other_2d_set1','state_3d_set1','trsp_3d_set1'}; listSubdirs={[dirModel 'diags/OTHER/' ],[dirModel 'diags/STATE/' ],[dirModel 'diags/TRSP/']}; elseif userStep==3;%computational part; %mask and re-arrange fields: fldT=THETA.*mygrid.mskC; fldS=SALT.*mygrid.mskC; fldETAN=ETAN.*mygrid.mskC(:,:,1); fldSSH=(ETAN+sIceLoad/myparms.rhoconst).*mygrid.mskC(:,:,1); fldSI=SIarea.*mygrid.mskC(:,:,1); fldMLD=MXLDEPTH.*mygrid.mskC(:,:,1); ux=UVELMASS.*mygrid.mskW; vy=VVELMASS.*mygrid.mskS; [ue,un]=calc_UEVNfromUXVY(ux,vy); %compute zonal means: [fldTzonmean]=calc_zonmean_T(fldT); [fldSzonmean]=calc_zonmean_T(fldS); [fldETANzonmean]=calc_zonmean_T(fldETAN); [fldSSHzonmean]=calc_zonmean_T(fldSSH); [fldSIzonmean]=calc_zonmean_T(fldSI); [fldMLDzonmean]=calc_zonmean_T(fldMLD); %compute hemispheric ice sums: fld=SIarea.*mygrid.RAC.*(mygrid.YC>0); IceAreaNorth=sum(fld); fld=SIarea.*mygrid.RAC.*(mygrid.YC<0); IceAreaSouth=sum(fld); fld=SIheff.*mygrid.RAC.*(mygrid.YC>0); IceVolNorth=sum(fld); fld=SIheff.*mygrid.RAC.*(mygrid.YC<0); IceVolSouth=sum(fld); fld=SIhsnow.*mygrid.RAC.*(mygrid.YC>0); SnowVolNorth=sum(fld); fld=SIhsnow.*mygrid.RAC.*(mygrid.YC<0); SnowVolSouth=sum(fld); %equatorial sections of T and U: [secX,secY,Teq]=gcmfaces_section([],0,fldT,1); [secX,secY,Ueq]=gcmfaces_section([],0,ue,1); %global means and profiles: msk=mygrid.RAC.*mygrid.mskC(:,:,1); SSHglo=nansum(fldSSH.*msk)./nansum(msk); % msk=mygrid.mskC.*mygrid.hFacC; msk=msk.*mk3D(mygrid.RAC,msk).*mk3D(mygrid.DRF,msk); Tglo=nansum(fldT.*msk)./nansum(msk); Sglo=nansum(fldS.*msk)./nansum(msk); nr=length(mygrid.RC); TgloProf=zeros(nr,1); SgloProf=zeros(nr,1); for kk=1:nr; rac=mygrid.RAC.*mygrid.mskC(:,:,kk); TgloProf(kk)=nansum(rac.*fldT(:,:,kk))/nansum(rac); SgloProf(kk)=nansum(rac.*fldS(:,:,kk))/nansum(rac); end; %===================== COMPUTATIONAL SEQUENCE ENDS =========================% %===================== PLOTTING SEQUENCE BEGINS =========================% elseif userStep==-1;%plotting if isempty(setDiagsParams); choicePlot={'all'}; else; choicePlot=setDiagsParams; end; %ensure backward compatibility if ~isfield(alldiag,'fldSSHzonmean'); alldiag.fldSSHzonmean=alldiag.fldETANLEADSzonmean; end; if ~isfield(alldiag,'SSHglo'); alldiag.SSHglo=NaN*alldiag.Tglo; end; if multiTimes&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'zmtend'))); if addToTex; write2tex(fileTex,1,'zonal mean tendencies',2); end; figureL; set(gcf,'Renderer','zbuffer'); %cc=[-2:0.25:2]; cc=1/100*[[-200:50:-100] [-75 -50] [-35:10:35] [50 75] [100:50:200]] if doAnomalies; cc=scaleAnom/10*cc; end; X=mygrid.LATS*ones(1,length(mygrid.RC)); Y=ones(length(mygrid.LATS),1)*(mygrid.RC'); %T subplot(2,1,1); fld=annualmean(alldiag.listTimes,alldiag.fldTzonmean,'last')-annualmean(alldiag.listTimes,alldiag.fldTzonmean,'first'); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc); title('zonal mean T anomaly'); %S subplot(2,1,2); fld=annualmean(alldiag.listTimes,alldiag.fldSzonmean,'last')-annualmean(alldiag.listTimes,alldiag.fldSzonmean,'first'); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc/4); title('zonal mean S anomaly'); % myCaption={myYmeanTxt,', last year minus first year -- zonal mean temperature (degC; top) and salinity (psu; bottom)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; if sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'eq')); if addToTex; write2tex(fileTex,1,'equatorial sections',2); end; %time mean equator sections : figureL; set(gcf,'Renderer','zbuffer'); cc0=[-2:0.25:2]; [secX,secY,LONeq]=gcmfaces_section([],0,mygrid.XC,1); X=LONeq*ones(1,length(mygrid.RC)); Y=ones(length(LONeq),1)*mygrid.RC'; X=circshift(X,[-180 0]); X(X<0)=X(X<0)+360; %T subplot(2,1,1); fld=annualmean(alldiag.listTimes,alldiag.Teq,'all'); fld=circshift(fld,[-180 0]); depthStretchPlot('pcolor',{X,Y,fld},[0:50:350],[0 350 350]); shading interp; if ~doAnomalies; cc=18+6*cc0; else; cc=scaleAnom/10*cc0*2; end; cbar=gcmfaces_cmap_cbar(cc); title('equator T (degC)'); %U subplot(2,1,2); fld=annualmean(alldiag.listTimes,alldiag.Ueq,'all'); fld=circshift(fld,[-180 0]); depthStretchPlot('pcolor',{X,Y,fld},[0:50:350],[0 350 350]); shading interp; if ~doAnomalies; cc=cc0/5*2; else; cc=scaleAnom/10*cc0/5; end; cbar=gcmfaces_cmap_cbar(cc); title('equator zonal velocity (m/s)'); % myCaption={myYmeanTxt,' mean -- equator temperature (degC;top) and zonal velocity (m/s;bottom)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; if multiTimes&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'gmtime'))); if addToTex; write2tex(fileTex,1,'global mean properties',2); end; %global mean T/S: figureL; subplot(3,1,1); vec=alldiag.SSHglo; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); aa=axis; axis([min(TT) max(TT) aa(3:4)]); grid on; legend('monthly','annual mean'); title('Global Mean Sea level (m, uncorrected free surface)'); subplot(3,1,2); vec=alldiag.Tglo; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); aa=axis; axis([min(TT) max(TT) aa(3:4)]); grid on; legend('monthly','annual mean'); title('Global Mean Temperature (degC)'); subplot(3,1,3); vec=alldiag.Sglo; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); aa=axis; axis([min(TT) max(TT) aa(3:4)]); grid on; legend('monthly','annual mean'); title('Global Mean Salinity (psu)'); myCaption={'global mean T (degC; top) and S (psu; bottom)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %global mean T/S profiles: figureL; set(gcf,'Renderer','zbuffer'); cc0=[-2:0.25:2]; X=TT*ones(1,length(mygrid.RC)); Y=ones(length(TT),1)*(mygrid.RC'); X=X'; Y=Y'; %T subplot(2,1,1); [tmp1,fld]=annualmean(alldiag.listTimes,squeeze(alldiag.TgloProf),'first'); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; if ~doAnomalies; cc=cc0/5; else; cc=scaleAnom/10*cc0/10; end; cbar=gcmfaces_cmap_cbar(cc); title('global mean T minus first year (K)'); %S subplot(2,1,2); [tmp1,fld]=annualmean(alldiag.listTimes,squeeze(alldiag.SgloProf),'first'); depthStretchPlot('pcolor',{X,Y,fld}); shading interp; if ~doAnomalies; cc=cc0/50; else; cc=scaleAnom/10*cc0/50; end; cbar=gcmfaces_cmap_cbar(cc); title('global mean S minus first year (psu)'); % myCaption={'global mean temperature (K; top) and salinity (psu; bottom) minus first year'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; if multiTimes&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'lzmtime'))); if addToTex; write2tex(fileTex,1,'zonal mean properties',2); end; listLatPlot=[-75 -65 -45 -25 0 25 45 65 75] %zonal mean temperature profile at selected latitude: for iLatPlot=1:length(listLatPlot); tmp1=abs(mygrid.LATS-listLatPlot(iLatPlot)); iLat=find(tmp1==min(tmp1)); iLat=iLat(1); figureL; set(gcf,'Renderer','zbuffer'); cc=[-2:0.25:2]; if doAnomalies; cc=scaleAnom/10*cc; end; %T subplot(2,1,1); [tmp1,fld]=annualmean(alldiag.listTimes,squeeze(alldiag.fldTzonmean(iLat,:,:)),'first'); X=TT*ones(1,length(mygrid.RC)); Y=ones(length(TT),1)*(mygrid.RC'); X=X'; Y=Y'; title0=['mean T minus first year (K) at lat ~ ' num2str(listLatPlot(iLatPlot))]; depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc/5); title(title0); %S subplot(2,1,2); [tmp1,fld]=annualmean(alldiag.listTimes,squeeze(alldiag.fldSzonmean(iLat,:,:)),'first'); X=TT*ones(1,length(mygrid.RC)); Y=ones(length(TT),1)*(mygrid.RC'); X=X'; Y=Y'; title0=['mean S minus first year (psu) at lat ~ ' num2str(listLatPlot(iLatPlot))]; depthStretchPlot('pcolor',{X,Y,fld}); shading interp; cbar=gcmfaces_cmap_cbar(cc/25); title(title0); myCaption={'mean temperature (top; K) and salinity (bottom; psu) minus first year ',... ['at lat $\\approx$ ' num2str(listLatPlot(iLatPlot))]}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; if multiTimes&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'szmtime'))); if addToTex; write2tex(fileTex,1,'zonal mean properties (surface)',2); end; %zonal mean SST/SSS: figureL; set(gcf,'Renderer','zbuffer'); cc0=[-2:0.25:2]; kk=1; x=TT*ones(1,length(mygrid.LATS)); y=ones(nt,1)*mygrid.LATS'; x=x'; y=y'; %T subplot(2,1,1); fld=squeeze(alldiag.fldTzonmean(:,kk,:)); [tmp1,fld]=annualmean(alldiag.listTimes,fld,'first'); if ~doAnomalies; cc=cc0*3; else; cc=scaleAnom/10*cc0; end; pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); cbar=gcmfaces_cmap_cbar(cc); title('zonal mean SST minus first year (degC)'); %S subplot(2,1,2); fld=squeeze(alldiag.fldSzonmean(:,kk,:)); [tmp1,fld]=annualmean(alldiag.listTimes,fld,'first'); if ~doAnomalies; cc=cc0*2/5; else; cc=scaleAnom/10*cc0/2; end; pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); cbar=gcmfaces_cmap_cbar(cc); title('zonal mean SSS minus first year (psu)'); % myCaption={'zonal mean temperature (degC; top) and salinity ',... '(psu; bottom) minus first year (psu)',[' at ' num2str(-mygrid.RC(kk)) 'm depth']}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figureL; set(gcf,'Renderer','zbuffer'); cc=[-2:0.25:2]; kk=1; if doAnomalies; cc=scaleAnom/10*cc/2; end; x=TT*ones(1,length(mygrid.LATS)); y=ones(nt,1)*mygrid.LATS'; x=x'; y=y'; %SSH subplot(2,1,1); [tmp1,fld]=annualmean(alldiag.listTimes,alldiag.fldSSHzonmean,'first'); pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); cbar=gcmfaces_cmap_cbar(2*cc/25); title(['zonal mean SSH minus first year (INCLUDING ice, in m)']); %ETAN subplot(2,1,2); [tmp1,fld]=annualmean(alldiag.listTimes,alldiag.fldETANzonmean,'first'); pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); cbar=gcmfaces_cmap_cbar(4*cc/5); title(['zonal mean SSH minus first year (EXCLUDING ice, in m)']); % myCaption={'zonal mean SSH (m, uncorrected free surface) minus first year, including ice (top) and below ice (bottom) '}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figureL; set(gcf,'Renderer','zbuffer'); cc=[-2:0.25:2]; kk=1; if doAnomalies; cc=scaleAnom/10*cc; end; x=TT*ones(1,length(mygrid.LATS)); y=ones(nt,1)*mygrid.LATS'; x=x'; y=y'; %SSH subplot(2,1,1); fld=squeeze(alldiag.fldSIzonmean(:,tt)); pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); if doAnomalies; cc2=scaleAnom/50*cc; else; cc2=0.5+cc/4; end; cbar=gcmfaces_cmap_cbar(cc2); title(['zonal mean Ice conc. -- in m ']); %MLD subplot(2,1,2); fld=squeeze(alldiag.fldMLDzonmean(:,tt)); pcolor(x,y,fld); shading interp; axis([TT(1) TT(end) -90 90]); if doAnomalies; cc2=scaleAnom*40*cc; else; cc2=200+500*cc/5; end; cbar=gcmfaces_cmap_cbar(cc2); title(['zonal mean MLD -- in m ']); % myCaption={'zonal mean ice concentration (no units) and mixed layer depth (m)'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; if multiTimes&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'icetime'))); if addToTex; write2tex(fileTex,1,'seaice time series',2); end; %sea ice area figureL; subplot(2,1,1); vec=alldiag.IceAreaNorth/1e12; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 20]); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]; axis(aa); end; grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Northern Hemisphere ice cover (in 10^{12}m^2)'); subplot(2,1,2); vec=alldiag.IceAreaSouth/1e12; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 25]); grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Southern Hemisphere ice cover (in 10^{12}m^2)'); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]; axis(aa); end; myCaption={'sea ice cover (in $10^{12}m^2$) in northern (top) and southern (bottom) hemisphere'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %sea ice volume figureL; subplot(2,1,1); vec=alldiag.IceVolNorth/1e12; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 50]); grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Northern Hemisphere ice volume (in 10^{12m}^3)'); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]*2; axis(aa); end; subplot(2,1,2); vec=alldiag.IceVolSouth/1e12; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 15]); grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Southern Hemisphere ice volume (in 10^{12}m^3)'); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]*2; axis(aa); end; myCaption={'sea ice volume (in $10^{12}m^3$) in northern (top) and southern (bottom) hemisphere'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %snow volume figureL; subplot(2,1,1); vec=alldiag.SnowVolNorth/1e12; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 5]); grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Northern Hemisphere snow volume (in 10^{12}m^3)'); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]; axis(aa); end; subplot(2,1,2); vec=alldiag.SnowVolSouth/1e12; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 4]); grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Southern Hemisphere snow volume (in 10^{12}m^3)'); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]; axis(aa); end; myCaption={'snow volume (in $10^{12}m^3$) in northern (top) and southern (bottom) hemisphere'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; if ~doAnomalies; %does not work for anomalies -> need to compute ratio in basic_diags_ecco %sea ice thickness figureL; subplot(2,1,1); vec=alldiag.IceVolNorth./alldiag.IceAreaNorth; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 5]); grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Northern Hemisphere ice thickness (in m)'); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]; axis(aa); end; subplot(2,1,2); vec=alldiag.IceVolSouth./alldiag.IceAreaSouth; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 2]); grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Southern Hemisphere ice thickness (in m)'); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]; axis(aa); end; myCaption={'sea ice thickness (in m) in northern (top) and southern (bottom) hemisphere'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; %sea ice thickness figureL; subplot(2,1,1); vec=alldiag.SnowVolNorth./alldiag.IceAreaNorth; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 0.4]); grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Northern Hemisphere snow thickness (in m)'); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]; axis(aa); end; subplot(2,1,2); vec=alldiag.SnowVolSouth./alldiag.IceAreaSouth; plot(TT,vec,'LineWidth',2); hold on; plot(TT,runmean(vec,myNmean,2),'r','LineWidth',2); axis([min(TT) max(TT) 0 0.25]); grid on; if myNmean>0; legend('monthly','annual mean'); end; title('Southern Hemisphere snow thickness (in m)'); if doAnomalies; aa(3:4)=scaleAnom*[-1 1]; axis(aa); end; myCaption={'snow thickness (in m) in northern (top) and southern (bottom) hemisphere'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; end; end; gcmfaces/gcmfaces_diags/diags_select.m0000644000435400001440000001645412365532631017750 0ustar gforgetusersfunction []=diags_select(dirModel,dirMat,setDiags,lChunk,listChunk); %object: compute a set of basic diagnostics %input: dirModel is the model run directory % dirMat is the directory where diagnozed .mat files will be saved % -> set it to '' to use the default [dirModel 'mat/'] % setDiags is the choice of diagnostics % 'A') trasnports (see diags_set_A.m) % 'B') air-sea fluxes % 'C') state variables % 'D') global and regional budgets % 'LAYERS') T/S/RHO coordinate overturns % 'user') is a placeholder for user diags additions % lChunk states how many records are computed at once % listChunk states which parts of the records should be % computed (i0+1:i0+lChunk where i0~lTot/lChunk) gcmfaces_global; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %create dirModel/mat if needed: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if lChunk==0; return; end; dirModel=[dirModel '/']; if isempty(dirMat); dirMat=[dirModel 'mat/']; end; if isempty(dir(dirMat)); mkdir(dirMat); end; %list of subdirectories where to scan for output listSubdirs={[dirMat 'BUDG/' ],[dirModel 'diags/BUDG/' ],[dirModel 'diags/OTHER/' ],... [dirModel 'diags/STATE/' ],[dirModel 'diags/TRSP/'],[dirModel 'diags/' ]}; if isfield(myenv,'nctiles'); use_nctiles=myenv.nctiles; else; use_nctiles=0; end; setDiagsParams=[]; if iscell(setDiags); setDiagsParams={setDiags{2:end}}; setDiags=setDiags{1}; end; %%%%%%%%%%%%%%%%%%%%%% %load grid and params: %%%%%%%%%%%%%%%%%%%%%% gcmfaces_global; global myparms; test0=~isempty(dir([dirMat 'diags_grid_parms.mat'])); test1=~isempty(dir([dirMat 'basic_diags_ecco_mygrid.mat'])); if test0;%load mygrid and myparms from file eval(['load ' dirMat 'diags_grid_parms.mat;']); elseif test1;%for backward compatibility eval(['load ' dirMat 'basic_diags_ecco_mygrid.mat;']); else; error('could not find diags_grid_parms.mat'); end; %in case mygrid.memoryLimit=1, load the stuff that was not saved to diags_grid_parms.mat if mygrid.memoryLimit==1; list0={'hFacS','hFacW'}; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds2gcmfaces([mygrid.dirGrid ''' list0{iFld} '*'']);']); end; % mygrid.hFacCsurf=mygrid.hFacC; for ff=1:mygrid.hFacC.nFaces; mygrid.hFacCsurf{ff}=mygrid.hFacC{ff}(:,:,1); end; % mskC=mygrid.hFacC; mskC(mskC==0)=NaN; mskC(mskC>0)=1; mygrid.mskC=mskC; mskW=mygrid.hFacW; mskW(mskW==0)=NaN; mskW(mskW>0)=1; mygrid.mskW=mskW; mskS=mygrid.hFacS; mskS(mskS==0)=NaN; mskS(mskS>0)=1; mygrid.mskS=mskS; % gcmfaces_lines_zonal; mygrid.LATS=[mygrid.LATS_MASKS.lat]'; [lonPairs,latPairs,names]=line_greatC_TUV_MASKS_v4; gcmfaces_lines_transp(lonPairs,latPairs,names); end; %%%%%%%%%%%%%% %define diags: %%%%%%%%%%%%%% userStep=1; if ~isempty(which(['diags_set_' setDiags])); eval(['diags_set_' setDiags]); else; diags_set_user; end; %reformat listDiags to cell array: jj=strfind(listDiags,' '); jj=[0 jj length(listDiags)+1]; for ii=1:length(jj)-1; tmp1=listDiags(jj(ii)+1:jj(ii+1)-1); if ii==1; listDiags2={tmp1}; else; listDiags2{ii}=tmp1; end; end; listDiags=listDiags2; clear listDiags2; %%%%%%%%%%%%%% %detect files: %%%%%%%%%%%%%% userStep=2; if ~isempty(which(['diags_set_' setDiags])); eval(['diags_set_' setDiags]); else; diags_set_user; end; %remove blanks in pkg/diagnostics flds name listFlds=deblank(listFlds); listFldsNames=deblank(listFldsNames); %set the list of diags times [listTimes]=diags_list_times(listSubdirs,listFiles); %then scan directories (listSubdirs) for files (listFiles) if ~use_nctiles; for ii=1:length(listFiles); tmp0=''; for jj=1:length(listSubdirs); tmp1=listFiles{ii}; tmp2=listSubdirs{jj}; if ~isempty(dir([tmp2 '/' tmp1 '*meta'])); tmp0=[tmp2 '/' tmp1]; listFiles{ii}=tmp0; end; end; if isempty(tmp0); fprintf([' not found: ' tmp1 '\n']); listFiles{ii}=''; end; end; end; if use_nctiles; for ii=1:length(listFlds); tmp0=sum(strcmp(myenv.nctileslist,listFlds{ii})); if tmp0==0; error([' not found: ' tmp1 '\n']); end; if tmp0<1; error([' found several : ' tmp1 '\n']); end; end; end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %loop over chunks %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if isdir([dirMat 'diags_set_' setDiags]); dirMat=[dirMat 'diags_set_' setDiags '/']; end; for iChunk=listChunk; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %load records for computation: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% lTot=length(listTimes); i0=min(lChunk*(iChunk-1),lTot); i1=min(i0+lChunk,lTot); tic; if ~use_nctiles; tt=listTimes([i0+1:i1])'; for iFile=1:length(listFiles); fileFld=listFiles{iFile}; if ~isempty(fileFld); rdmds2workspace_list(fileFld,tt,listFlds); for ii=1:length(meta.fldList); tmp1=deblank(meta.fldList{ii}); jj=find(strcmp(tmp1,listFlds)); if ~isempty(jj); eval(['all_' listFldsNames{jj} '=' tmp1 ';']); end; eval(['clear ' tmp1]); end; end; end; end; if use_nctiles; tt=[i0+1:i1]'; di=myenv.nctilesdir; for iFld=1:length(listFlds); nm=listFlds{iFld}; fileIn=sprintf('%s/%s/%s',di,nm,nm); fld=read_nctiles(fileIn,nm,tt); eval(['all_' nm '=fld;']); end; end; fprintf([num2str(i1-i0) ' records loaded in ' num2str(toc) '\n']); %check that all fields were found, and otherwise reduce listFlds listFldsIsPresent=zeros(1,length(listFldsNames)); for iFld=1:length(listFldsNames); fldName=['all_' listFldsNames{iFld}]; if isempty(who(fldName)); fprintf([fldName ' is missing \n']); else; listFldsIsPresent(iFld)=1; % fprintf([fldName ' was found \n']); end; end; listFldsNames={listFldsNames{find(listFldsIsPresent)}}; listFlds={listFlds{find(listFldsIsPresent)}}; %%%%%%%%%%%%%%%%%%%% %do the computation: %%%%%%%%%%%%%%%%%%%% for ii=i0+1:i1; tic; tt=listTimes(ii); %get data from buffer for jj=1:length(listFldsNames); if lChunk==1|length(listTimes)==1; eval([listFldsNames{jj} '=all_' listFldsNames{jj} ';']); else; eval(['tmp1=size(all_' listFldsNames{jj} '{1});']); if length(tmp1)==4; eval([listFldsNames{jj} '=all_' listFldsNames{jj} '(:,:,:,ii-i0);']); else; eval([listFldsNames{jj} '=all_' listFldsNames{jj} '(:,:,ii-i0);']); end; end; end; fprintf([num2str(ii-i0) '/' num2str(i1-i0) ' started \n']); %generic output file name (that will potentially be overriden) tmp1=setDiags; fileMat=['diags_set_' tmp1 '_' num2str(tt) '.mat']; %the actual computations userStep=3; if ~isempty(which(['diags_set_' setDiags])); eval(['diags_set_' setDiags]); else; diags_set_user; end; fprintf([num2str(ii) '/' num2str(length(listTimes)) ' done in ' num2str(toc) '\n']); %package results onediag=[]; onediag.listTimes=myparms.yearFirst(1)+tt*myparms.timeStep/86400/365.25; onediag.listSteps=tt; for jj=1:length(listDiags); eval(['onediag.' listDiags{jj} '=' listDiags{jj} ';']); end; %write to disk diags_store_to_mat(dirMat,fileMat,onediag); end;%for ii=i0+1:i1; end;%for iChunk=listChunk; gcmfaces/gcmfaces_diags/diags_set_user.m0000644000435400001440000000462212147222223020303 0ustar gforgetusers%userStep is set in basic_diags_ecco in 'user' blocs %this routine is by choice not a function, in %order to have access to entire workspace) if ~strcmp(setDiags,'user') error(['unknown setDiags ' setDiags]); end; %%%%%%%%%%%%%%%%%%TEMPLATE%%%%%%%%%%%%%%%%%%% if strcmp(setDiags,'user')&userStep==1;%diags to be computed fprintf('this is a place-holder for an extra set of diags : to be defined by you if you please\n') fprintf('how to proceed : 1) define listDiags HERE 2) define listFlds etc. below \n'); fprintf('how to proceed : 3) add the computation code below 4) add the display code below\n'); fprintf('how to proceed : 5) once done, remove this print the ''return'' call below\n'); return; end; if strcmp(setDiags,'user')&userStep==2;%input files and variables fprintf('this is a place-holder for an extra set of diags : to be defined by you if you please\n') fprintf('how to proceed : 1) define listDiags above 2) define listFlds etc. HERE \n'); fprintf('how to proceed : 3) add the computation code below 4) add the display code below\n'); fprintf('how to proceed : 5) once done, remove this print the ''return'' call below\n'); listSubdirs={[dirMat 'BUDG/' ],[dirModel 'diags/BUDG/' ],[dirModel 'diags/OTHER/' ],... [dirModel 'diags/STATE/' ],[dirModel 'diags/TRSP/'],[dirModel 'diags/' ]}; listFiles={listFiles{:},'diags_2d_set1','diags_ice_set1','diags_3d_set1','diags_3d_set2','diags_3d_set3'};%for backward compatibility return; end; if strcmp(setDiags,'user')&userStep==3;%computational part; fprintf('this is a place-holder for an extra set of diags : to be defined by you if you please\n') fprintf('how to proceed : 1) define listDiags above 2) define listFlds etc. above \n'); fprintf('how to proceed : 3) add the computation code HERE 4) add the display code below\n'); fprintf('how to proceed : 5) once done, remove this print the ''return'' call below\n'); return; end; if strcmp(setDiags,'user')&userStep==-1;%computational part; fprintf('this is a place-holder for an extra set of diags : to be defined by you if you please\n') fprintf('how to proceed : 1) define listDiags above 2) define listFlds etc. above \n'); fprintf('how to proceed : 3) add the computation code above 4) add the display code below\n'); fprintf('how to proceed : 5) once done, remove this print the ''return'' call below\n'); return; end; gcmfaces/gcmfaces_diags/diags_set_D.m0000644000435400001440000004763112365532631017530 0ustar gforgetusers %select kBudget: if ~isempty(setDiagsParams); kBudget=setDiagsParams{1}; else; kBudget=1; end; %override default file name: %--------------------------- tmp1=setDiags; if kBudget>1; tmp1=sprintf('D%02i',kBudget); end; fileMat=['diags_set_' tmp1]; if userStep==1;%diags to be computed listDiags=['glo_vol_ocn glo_vol_tot glo_vol_ice glo_bp']; listDiags=[listDiags ' north_vol_ocn north_vol_tot north_vol_ice north_bp']; listDiags=[listDiags ' south_vol_ocn south_vol_tot south_vol_ice south_bp']; listDiags=[listDiags ' glo_heat_ocn glo_heat_tot glo_heat_ice']; listDiags=[listDiags ' north_heat_ocn north_heat_tot north_heat_ice']; listDiags=[listDiags ' south_heat_ocn south_heat_tot south_heat_ice']; listDiags=[listDiags ' glo_salt_ocn glo_salt_tot glo_salt_ice']; listDiags=[listDiags ' north_salt_ocn north_salt_tot north_salt_ice']; listDiags=[listDiags ' south_salt_ocn south_salt_tot south_salt_ice']; elseif userStep==2;%input files and variables listFlds={ 'ETAN','SIheff','SIhsnow','THETA ','SALT ','PHIBOT'}; listFlds={listFlds{:},'SIatmFW ','oceFWflx','SItflux','TFLUX','SFLUX','oceSPflx','SRELAX'}; listFlds={listFlds{:},'oceQnet ','SIatmQnt','SIaaflux','SIsnPrcp','SIacSubl'}; listFlds={listFlds{:},'TRELAX','WTHMASS','WSLTMASS','oceSflux','oceQsw','oceSPtnd'}; if kBudget>1; listFlds={listFlds{:},'ADVr_TH','DFrE_TH','DFrI_TH','ADVr_SLT','DFrE_SLT','DFrI_SLT','WVELMASS'}; end; listFlds={listFlds{:},'SDIAG1','SDIAG2','SDIAG3'}; listFlds={listFlds{:},'UVELMASS','VVELMASS','AB_gT','AB_gS'}; listFlds={listFlds{:},'ADVx_TH ','ADVy_TH ','DFxE_TH ','DFyE_TH '}; listFlds={listFlds{:},'ADVx_SLT','ADVy_SLT','DFxE_SLT','DFyE_SLT'}; listFlds={listFlds{:},'ADVxHEFF','ADVyHEFF','DFxEHEFF','DFyEHEFF'}; listFlds={listFlds{:},'ADVxSNOW','ADVySNOW','DFxESNOW','DFyESNOW'}; listFldsNames=deblank(listFlds); % listFiles={'rate_budg2d_snap_set1','budg2d_hflux_set1','budg2d_zflux_set1','budg2d_zflux_set2'}; if kBudget==1; listFiles={listFiles{:},'rate_budg2d_snap_set2','budg2d_hflux_set2'}; else; tmp1=sprintf('rate_budg2d_snap_set3_%02i',kBudget); tmp2=sprintf('budg2d_zflux_set3_%02i',kBudget); tmp3=sprintf('budg2d_hflux_set3_%02i',kBudget); listFiles={listFiles{:},tmp1,tmp2,tmp3}; end; listSubdirs={[dirMat 'BUDG/' ],[dirMat '../BUDG/' ],[dirModel 'diags/BUDG/']}; elseif userStep==3;%computational part; %preliminary tests test1=isempty(dir([dirModel 'diags/BUDG/budg2d_snap_set1*'])); test2=isempty(dir([dirMat 'BUDG/rate_budg2d_snap_set1*']))&... isempty(dir([dirMat '../BUDG/rate_budg2d_snap_set1*'])); if (strcmp(setDiags,'D')&test1&test2); fprintf('\n abort : global and regional budgets, due to missing \n'); fprintf(['\n ' dirModel 'diags/BUDG/budg2d_snap_set1* \n']); return; end; if (strcmp(setDiags,'D')&test2); fprintf('\n abort : global and regional budgets, due to missing \n'); fprintf(['\n ' dirModel 'diags/BUDG/rate_budg2d_snap_set1* \n']); return; end; %override default file name: %--------------------------- tmp1=setDiags; if kBudget>1; tmp1=sprintf('D%02i',kBudget); end; fileMat=['diags_set_' tmp1 '_' num2str(tt) '.mat']; %fill in optional fields: %------------------------ if isempty(who('TRELAX')); TRELAX=0*mygrid.XC; end; if isempty(who('SRELAX')); SRELAX=0*mygrid.XC; end; if isempty(who('AB_gT')); AB_gT=0*mygrid.XC; end; if isempty(who('AB_gS')); AB_gS=0*mygrid.XC; end; if isempty(who('oceSPtnd')); oceSPtnd=0*mygrid.XC; end; if isempty(who('oceSPflx')); oceSPflx=0*mygrid.XC; end; if isempty(who('PHIBOT')); PHIBOT=0*mygrid.XC; end; %aliases from development phase (applies to 2012 core runs) %--------------------------------------------------------- if ~isempty(who('SDIAG1')); SRELAX=SDIAG1; end; if ~isempty(who('SDIAG2')); SIatmFW=SDIAG2; end; if ~isempty(who('SDIAG3')); SItflux=SDIAG3; end; %=======MASS========= %compute mapped budget: %---------------------- %mass = myparms.rhoconst * sea level contOCN=ETAN*myparms.rhoconst; contICE=(SIheff*myparms.rhoi+SIhsnow*myparms.rhosn); %for deep ocean layer : if kBudget>1&myparms.useNLFS<2; contOCN=0; elseif kBudget>1;%rstar case tmp1=mk3D(mygrid.DRF,mygrid.hFacC).*mygrid.hFacC; tmp2=sum(tmp1(:,:,kBudget:length(mygrid.RC)),3)./mygrid.Depth; contOCN=tmp2.*ETAN*myparms.rhoconst; end; % contTOT=contOCN+contICE; %vertical divergence (air-sea fluxes or vertical advection) zdivOCN=oceFWflx; zdivICE=SIatmFW-oceFWflx; %in virtual salt flux we omit : if ~myparms.useRFWF; zdivOCN=0*zdivOCN; end; %for deep ocean layer : if kBudget>1; zdivOCN=-WVELMASS*myparms.rhoconst; end; % zdivTOT=zdivOCN+zdivICE; %horizontal divergence (advection and ice diffusion) hdivOCN=myparms.rhoconst*calc_UV_conv(UVELMASS,VVELMASS,{'dh'}); %for 2D, already vertically integrated, fields tmpU=(myparms.rhoi*DFxEHEFF+myparms.rhosn*DFxESNOW+myparms.rhoi*ADVxHEFF+myparms.rhosn*ADVxSNOW); tmpV=(myparms.rhoi*DFyEHEFF+myparms.rhosn*DFyESNOW+myparms.rhoi*ADVyHEFF+myparms.rhosn*ADVySNOW); hdivICE=calc_UV_conv(tmpU,tmpV); %no dh needed here hdivTOT=hdivOCN+hdivICE; %bottom pressure for comparison: bp=myparms.rhoconst/9.81*PHIBOT; %compute global integrals: %------------------------- msk=mygrid.mskC(:,:,kBudget); glo_vol_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); glo_vol_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); glo_vol_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); glo_bp=nansum(bp.*msk.*mygrid.RAC)/nansum(msk.*mygrid.RAC); %compute northern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*(mygrid.YC>0); north_vol_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); north_vol_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); north_vol_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); north_bp=nansum(bp.*msk.*mygrid.RAC)/nansum(msk.*mygrid.RAC); %and southern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*(mygrid.YC<=0); south_vol_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); south_vol_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); south_vol_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); south_bp=nansum(bp.*msk.*mygrid.RAC)/nansum(msk.*mygrid.RAC); %=======HEAT======= contOCN=myparms.rcp*THETA-myparms.rcp*AB_gT; contICE=-myparms.flami*(SIheff*myparms.rhoi+SIhsnow*myparms.rhosn); contTOT=contOCN+contICE; %vertical divergence (air-sea fluxes or vertical adv/dif) zdivOCN=TFLUX; zdivICE=-(SItflux+TFLUX-TRELAX); %in linear surface we omit : if ~myparms.useNLFS; zdivOCN=zdivOCN-myparms.rcp*WTHMASS; end; %in virtual salt flux we omit : if ~myparms.useRFWF|~myparms.useNLFS; zdivICE=zdivICE+SIaaflux; end; %working approach for real fresh water (?) and virtual salt flux if 0; zdivICE=-oceQnet-SIatmQnt-myparms.flami*(SIsnPrcp-SIacSubl); end; %for deep ocean layer : if kBudget>1; zdivOCN=-(ADVr_TH+DFrE_TH+DFrI_TH)./mygrid.RAC*myparms.rcp; dd=mygrid.RF(kBudget); msk=mygrid.mskC(:,:,kBudget); swfrac=0.62*exp(dd/0.6)+(1-0.62)*exp(dd/20); if dd<-200; swfrac=0; end; zdivOCN=zdivOCN+swfrac*oceQsw;%.*msk; end; % zdivTOT=zdivOCN+zdivICE; %horizontal divergence (advection and diffusion) tmpU=myparms.rcp*(ADVx_TH+DFxE_TH); tmpV=myparms.rcp*(ADVy_TH+DFyE_TH); hdivOCN=calc_UV_conv(tmpU,tmpV); tmpU=-myparms.flami*(myparms.rhoi*DFxEHEFF+myparms.rhosn*DFxESNOW+myparms.rhoi*ADVxHEFF+myparms.rhosn*ADVxSNOW); tmpV=-myparms.flami*(myparms.rhoi*DFyEHEFF+myparms.rhosn*DFyESNOW+myparms.rhoi*ADVyHEFF+myparms.rhosn*ADVySNOW); hdivICE=calc_UV_conv(tmpU,tmpV); %no dh needed here hdivTOT=hdivOCN+hdivICE; %compute global integrals: %------------------------- msk=mygrid.mskC(:,:,kBudget); glo_heat_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); glo_heat_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); glo_heat_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); %compute northern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*(mygrid.YC>0); north_heat_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); north_heat_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); north_heat_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); %and southern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*(mygrid.YC<=0); south_heat_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); south_heat_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); south_heat_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); %=======SALT======= contOCN=myparms.rhoconst*SALT-myparms.rhoconst*AB_gS; contICE=myparms.SIsal0*myparms.rhoi*SIheff; contTOT=contOCN+contICE; %vertical divergence (air-sea fluxes or vertical adv/dif) zdivOCN=SFLUX+oceSPflx; zdivICE=-zdivOCN+SRELAX; %in linear surface we omit : if ~myparms.useNLFS; zdivOCN=zdivOCN-myparms.rhoconst*WSLTMASS; end; %working approach for real fresh water (?) and virtual salt flux if ~myparms.useRFWF|~myparms.useNLFS; zdivICE=-oceSflux; end; %for deep ocean layer : if kBudget>1; zdivOCN=-(ADVr_SLT+DFrE_SLT+DFrI_SLT)./mygrid.RAC*myparms.rhoconst; zdivOCN=zdivOCN+oceSPtnd;%.*msk; end; zdivTOT=zdivOCN+zdivICE; %horizontal divergence (advection and diffusion) tmpU=myparms.rhoconst*(ADVx_SLT+DFxE_SLT); tmpV=myparms.rhoconst*(ADVy_SLT+DFyE_SLT); hdivOCN=calc_UV_conv(tmpU,tmpV); tmpU=myparms.SIsal0*(myparms.rhoi*DFxEHEFF+myparms.rhoi*ADVxHEFF); tmpV=myparms.SIsal0*(myparms.rhoi*DFyEHEFF+myparms.rhoi*ADVyHEFF); hdivICE=calc_UV_conv(tmpU,tmpV); %no dh needed here hdivTOT=hdivOCN+hdivICE; %compute global integrals: %------------------------- msk=mygrid.mskC(:,:,kBudget); glo_salt_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); glo_salt_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); glo_salt_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); %compute northern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*(mygrid.YC>0); north_salt_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); north_salt_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); north_salt_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); %and southern hemisphere integrals: msk=mygrid.mskC(:,:,kBudget).*(mygrid.YC<=0); south_salt_tot=calc_budget_mean_mask(contTOT,zdivTOT,hdivTOT,msk); south_salt_ocn=calc_budget_mean_mask(contOCN,zdivOCN,hdivOCN,msk); south_salt_ice=calc_budget_mean_mask(contICE,zdivICE,hdivICE,msk); %===================== COMPUTATIONAL SEQUENCE ENDS =========================% %===================== PLOTTING SEQUENCE BEGINS =========================% elseif userStep==-1;%plotting if isempty(setDiagsParams); choicePlot={'all'}; elseif isnumeric(setDiagsParams{1})&length(setDiagsParams)==1; choicePlot={'all'}; elseif isnumeric(setDiagsParams{1}); choicePlot={setDiagsParams{2:end}}; else; choicePlot=setDiagsParams; end; tt=[1:length(alldiag.listTimes)]; TT=alldiag.listTimes(tt); nt=length(TT); if (kBudget==1)&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mass'))); %1.1) ocean+seaice mass budgets %------------------------------ figureL; %global volume budget: subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_vol_tot,'kg/m^2','Global Mean Mass (incl. ice)'); %add bp: dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.glo_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %northern hemisphere budget: subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.north_vol_tot,'kg/m^2','Northern Mean Mass (incl. ice)'); %add bp: dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.north_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %southern hemisphere budget: subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.south_vol_tot,'kg/m^2','Southern Mean Mass (incl. ice)'); %add bp: dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.south_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %add to tex file myCaption={myYmeanTxt,' global (upper) north (mid) and south (lower), '}; myCaption={myCaption{:},'mass budget (ocean+ice) in kg/m$^2$.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; %1.2) ice mass budgets %--------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_vol_ice,'kg/m^2','Global Mean Mass (only ice)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.glo_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.north_vol_ice,'kg/m^2','Northern Mean Mass (only ice)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.north_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.south_vol_ice,'kg/m^2','Southern Mean Mass (only ice)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.south_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %add to tex file myCaption={myYmeanTxt,' global (upper) north (mid) and south (lower), '}; myCaption={myCaption{:},'mass budget (ice only) in kg/m$^2$.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'mass'))); %1.3) ocean mass budgets %----------------------- figureL; %global volume budget: subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_vol_ocn,'kg/m^2','Global Mean Mass (only ocean)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.glo_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.north_vol_ocn,'kg/m^2','Northern Mean Mass (only ocean)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.north_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.south_vol_ocn,'kg/m^2','Southern Mean Mass (only ocean)'); dt=median(diff(TT))*86400; bp=dt*cumsum(alldiag.south_bp); plot(TT,bp,'k'); aa=legend; bb=get(aa,'String'); bb={bb{:},'bp'}; legend(bb,'Orientation','horizontal'); %add to tex file myCaption={myYmeanTxt,' global (upper) north (mid) and south (lower), '}; myCaption={myCaption{:},'mass budget (ocean only) in kg/m$^2$.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (kBudget==1)&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'heat'))); %2.1) ocean+seaice heat budgets %------------------------------ figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_heat_tot,'J/m^2','Global Mean Ocean Heat (incl. ice)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.north_heat_tot,'J/m^2','Northern Mean Ocean Heat (incl. ice)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.south_heat_tot,'J/m^2','Southern Mean Ocean Heat (incl. ice)'); %add to tex file myCaption={myYmeanTxt,' global (upper) north (mid) and south (lower), '}; myCaption={myCaption{:},'heat budget (ocean+ice) in J/m$^2$.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; %2.2) ice heat budgets %--------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_heat_ice,'J/m^2','Global Mean Ocean Heat (only ice)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.north_heat_ice,'J/m^2','Northern Mean Ocean Heat (only ice)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.south_heat_ice,'J/m^2','Southern Mean Ocean Heat (only ice)'); %add to tex file myCaption={myYmeanTxt,' global (upper) north (mid) and south (lower), '}; myCaption={myCaption{:},'heat budget (ice only) in J/m$^2$.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'heat'))); %2.3) ocean heat budgets %----------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_heat_ocn,'J/m^2','Global Mean Ocean Heat (only ocean)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.north_heat_ocn,'J/m^2','Northern Mean Ocean Heat (only ocean)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.south_heat_ocn,'J/m^2','Southern Mean Ocean Heat (only ocean)'); %add to tex file myCaption={myYmeanTxt,' global (upper) north (mid) and south (lower), '}; myCaption={myCaption{:},'heat budget (ocean only) in J/m$^2$.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (kBudget==1)&(sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'salt'))); %3.1) ocean+seaice salt budgets %------------------------------ figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_salt_tot,'g/m^2','Global Mean Ocean Salt (incl. ice)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.north_salt_tot,'g/m^2','Northern Mean Ocean Salt (incl. ice)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.south_salt_tot,'g/m^2','Southern Mean Ocean Salt (incl. ice)'); %add to tex file myCaption={myYmeanTxt,' global (upper) north (mid) and south (lower), '}; myCaption={myCaption{:},'salt budget (ocean+ice) in g/m$^2$.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; %2.2) ice salt budgets %--------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_salt_ice,'g/m^2','Global Mean Ocean Salt (only ice)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.north_salt_ice,'g/m^2','Northern Mean Ocean Salt (only ice)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.south_salt_ice,'g/m^2','Southern Mean Ocean Salt (only ice)'); %add to tex file myCaption={myYmeanTxt,' global (upper) north (mid) and south (lower), '}; myCaption={myCaption{:},'salt budget (ice only) in g/m$^2$.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; if (sum(strcmp(choicePlot,'all'))|sum(strcmp(choicePlot,'salt'))); %3.3) ocean salt budgets %----------------------- figureL; subplot(3,1,1); disp_budget_mean_mask(TT,alldiag.glo_salt_ocn,'g/m^2','Global Mean Ocean Salt (only ocean)'); subplot(3,1,2); disp_budget_mean_mask(TT,alldiag.north_salt_ocn,'g/m^2','Northern Mean Ocean Salt (only ocean)'); subplot(3,1,3); disp_budget_mean_mask(TT,alldiag.south_salt_ocn,'g/m^2','Southern Mean Ocean Salt (only ocean)'); %add to tex file myCaption={myYmeanTxt,' global (upper) north (mid) and south (lower), '}; myCaption={myCaption{:},'salt budget (ocean only) in g/m$^2$.'}; if addToTex&multiTimes; write2tex(fileTex,2,myCaption,gcf); elseif ~multiTimes; close; end; end; end; gcmfaces/gcmfaces_diags/diags_set_SEAICE.m0000644000435400001440000001504612276601102020260 0ustar gforgetusers if userStep==1;%diags to be computed listDiags='seaIceConc seaIceThick seaSnowThick seaIceStrFun seaIceDiv'; listDiags=[listDiags ' iceThickNorth iceThickSouth']; listDiags=[listDiags ' iceAreaNorth iceAreaSouth']; listDiags=[listDiags ' snowThickNorth snowThickSouth']; listDiags=[listDiags ' snowAreaNorth snowAreaSouth']; end; if userStep==2;%input files and variables listFlds={'SIarea ','SIheff ','SIhsnow ',... 'ADVxHEFF','ADVyHEFF','ADVxSNOW','ADVySNOW',... 'DFxEHEFF','DFyEHEFF','DFxESNOW','DFyESNOW'}; listFldsNames=deblank(listFlds); listFiles={'state_2d_set1'}; listSubdirs={[dirModel 'diags/STATE/' ]}; end; if userStep==3;%computational part; %ice masks mskC=mygrid.mskC(:,:,1); mskC(SIheff==0)=NaN; mskW=mygrid.mskW(:,:,1); mskW(ADVxHEFF==0)=NaN; mskS=mygrid.mskS(:,:,1); mskS(ADVyHEFF==0)=NaN; %ice and snow thickness seaIceConc=mskC.*SIarea; seaIceThick=SIheff./seaIceConc; seaSnowThick=SIhsnow./seaIceConc; %transports in kg/s tmpU=(myparms.rhoi*DFxEHEFF+myparms.rhosn*DFxESNOW+... myparms.rhoi*ADVxHEFF+myparms.rhosn*ADVxSNOW); tmpV=(myparms.rhoi*DFyEHEFF+myparms.rhosn*DFyESNOW+... myparms.rhoi*ADVyHEFF+myparms.rhosn*ADVySNOW); %convergence in kiloton/s seaIceDiv=1e-6*mskC.*calc_UV_conv(tmpU,tmpV); %no dh needed here %streamfunction in kg/s %(factor 1e6 to compensare for calc_barostream internal conversion) seaIceStrFun=1e6*calc_barostream(tmpU.*mskW,tmpV.*mskS,1,{}); %convert to megaton/s seaIceStrFun=1e-9*mskC.*seaIceStrFun; %thickness distributions per hemisphere xx=convert2vector(seaIceThick); yy=convert2vector(1+0*seaIceThick); zz=convert2vector(seaIceConc.*mygrid.RAC); mm=convert2vector(mygrid.YC>0); jj=find(mm.*zz>0); [x,y,z,n]=MITprof_stats(xx(jj),[0:0.05:10],yy(jj),[0 1 2],'sum',zz(jj)); iceThickNorth=x(:,2); iceAreaNorth=z(:,2); mm=convert2vector(mygrid.YC<0); jj=find(mm.*zz>0); [x,y,z,n]=MITprof_stats(xx(jj),[0:0.05:10],yy(jj),[0 1 2],'sum',zz(jj)); iceThickSouth=x(:,2); iceAreaSouth=z(:,2); xx=convert2vector(seaSnowThick); mm=convert2vector(mygrid.YC>0); jj=find(mm.*zz>0); [x,y,z,n]=MITprof_stats(xx(jj),[0:0.05:10],yy(jj),[0 1 2],'sum',zz(jj)); snowThickNorth=x(:,2); snowAreaNorth=z(:,2); mm=convert2vector(mygrid.YC<0); jj=find(mm.*zz>0); [x,y,z,n]=MITprof_stats(xx(jj),[0:0.05:10],yy(jj),[0 1 2],'sum',zz(jj)); snowThickSouth=x(:,2); snowAreaSouth=z(:,2); end; if userStep==-1&myparms.diagsAreMonthly==1;%plotting if ~doAnomalies; if addToTex; write2tex(fileTex,1,'Monthly Thickness Distribution',2); end; %compute seasonal cycle in thickness distributions y=alldiag.iceThickNorth(:,1:12); x=ones(size(y,1),1)*[1:12]; iceNorth=zeros(size(x)); iceSouth=zeros(size(x)); snowNorth=zeros(size(x)); snowSouth=zeros(size(x)); for mm=1:12; tmp1=alldiag.iceAreaNorth(:,mm:12:nt); tmp1(isnan(tmp1))=0; iceNorth(:,mm)=log10(mean(tmp1,2)); % tmp1=alldiag.iceAreaSouth(:,mm:12:nt); tmp1(isnan(tmp1))=0; iceSouth(:,mm)=log10(mean(tmp1,2)); % tmp1=alldiag.snowAreaNorth(:,mm:12:nt); tmp1(isnan(tmp1))=0; snowNorth(:,mm)=log10(mean(tmp1,2)); % tmp1=alldiag.snowAreaSouth(:,mm:12:nt); tmp1(isnan(tmp1))=0; snowSouth(:,mm)=log10(mean(tmp1,2)); end; iceNorth(~isfinite(iceNorth))=NaN; iceSouth(~isfinite(iceSouth))=NaN; snowNorth(~isfinite(snowNorth))=NaN; snowSouth(~isfinite(snowSouth))=NaN; %now display seasonal cycle x=[x x+12]-0.5; y=[y y]; z=[iceNorth iceNorth]; figureL; set(gcf,'Renderer','zbuffer'); subplot(2,1,1); z=[iceNorth iceNorth]; pcolor(x,y,z); shading interp; axis([1 13 0 6]); grid on; caxis([9.5 12]); colormap(jet(25)); colorbar; xlabel('month of year'); ylabel('log(thickness)'); title('log(ice area) -- North. Hemi.'); subplot(2,1,2); z=[snowNorth snowNorth]; pcolor(x,y,z); shading interp; axis([1 13 0 1.2]); grid on; caxis([9.5 12]+0.5); colormap(jet(25)); colorbar; xlabel('month of year'); ylabel('log(thickness)'); title('log(snow area) -- North. Hemi.'); myCaption={myYmeanTxt,'Northern Hemisphere :',... 'monthly mean ice (top) and snow (bottom)',... ' thickness distribution (in log(m$^2$))'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; figureL; set(gcf,'Renderer','zbuffer'); subplot(2,1,1); z=[iceSouth iceSouth]; pcolor(x,y,z); shading interp; axis([1 13 0 4]); grid on; caxis([9.5 12]); colormap(jet(25)); colorbar; xlabel('month of year'); ylabel('log(thickness)'); title('log(ice area) -- South. Hemi.'); subplot(2,1,2); z=[snowSouth snowSouth]; pcolor(x,y,z); shading interp; axis([1 13 0 1.2]); grid on; caxis([9.5 12]+0.5); colormap(jet(30)); colorbar; xlabel('month of year'); ylabel('log(thickness)'); title('log(snow area) -- South. Hemi.'); myCaption={myYmeanTxt,'Southern Hemisphere :',... 'monthly mean ice (top) and snow (bottom)',... ' thickness distribution (in log(m$^2$))'}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end; %maps of mean march and september ice fields list_var={'seaIceConc',... 'seaIceThick',... 'seaSnowThick',... 'seaIceStrFun',... 'seaIceDiv'}; list_cc={[0:0.1:1],... [0:0.1:0.5 0.75 1:0.5:2.5 3:5],... [0:0.1:0.5 0.75 1:0.5:2.5 3:5]/5,... 1/50*[-5:-3 -2.5:0.5:-1 -0.5:0.2:0.5 1:0.5:2.5 3:5],... 1/5*[-5:-3 -2.5:0.5:-1 -0.5:0.2:0.5 1:0.5:2.5 3:5]}; list_ccAno={2*[-0.2:0.04:0.2],... 4*[-0.2:0.04:0.2],... [-0.2:0.04:0.2],... 0.25*[-0.2:0.04:0.2],... [-0.2:0.04:0.2]}; list_tit={' ice concentration (unitless)',... ' ice thickness (m)',... ' snow thickness (m)',... ' ice+snow streamfunction (megaton/s)',... ' ice+snow convergence (kiloton/s)'}; for hemi=1:2; for seas=1:2; %select month if seas==1; mon='March'; else; mon='September'; end; %select projection if hemi==1; pp=2; txt='Northern '; else; pp=3; txt='Southern '; end; if addToTex; write2tex(fileTex,1,[txt 'Hem. in ' mon],2); end; for vv=1:length(list_var); eval(['fld=alldiag.' list_var{vv} ';']); %mask out negligible amounts (e.g. due to monthly averaging) msk=1+0*alldiag.seaIceConc; msk(alldiag.seaIceConc<1e-2)=NaN; msk(alldiag.seaIceThick<1e-2)=NaN; fld=fld.*msk; %compute mean march and september fields if seas==1; tmp1=fld(:,:,3:12:nt); tmp1(isnan(tmp1))=0; fld_seas=mean(tmp1,3); else; tmp1=fld(:,:,9:12:nt); tmp1(isnan(tmp1))=0; fld_seas=mean(tmp1,3); end; fld_seas(fld_seas==0)=NaN; %ice concentration figureL; set(gcf,'Renderer','zbuffer'); cc=list_cc{vv}; if doAnomalies; cc=list_ccAno{vv}; end; caxi={'myCaxis',cc}; docb={'doCbar',1}; m_map_gcmfaces(fld_seas,pp,caxi,docb); myCaption={myYmeanTxt,mon,' mean -- ',list_tit{vv}}; if addToTex; write2tex(fileTex,2,myCaption,gcf); end; end;%for vv=1:length(list_var); end;%for seas=1:2; end;%for hemi=1:2; end; gcmfaces/gcmfaces_diags/diags_driver_tex.m0000644000435400001440000002165112365532631020637 0ustar gforgetusersfunction []=diags_driver_tex(dirMat,setDiags,dirTex,nameTex); %object: build tex file from a set of diagnostics %input: dirMat is the directory where diagnozed .mat files are. % dirMat is usually specified as a chararcter string, but % user can also specify dirMat as {dirMat,dirMatRef} % in order to plot the dirMat-dirMatRef anlomalies. % setDiags is the choice of diagnostics set. The default % is {'profiles','cost','A','B','C','D','MLD'} where % 'profiles') model to insitu data comparison % 'cost') ssh etc. cost functions % 'A') trasnports % 'B') air-sea fluxes % 'C') state variables % 'D') global and regional budgets % 'MLD') mixed layer depth fields % 'SEAICE') seaice fields % 'controls') control vector adjustments % dirTex is the directory where tex and figures files are created % nameTex is the tex file name (default : 'myPlots') %note: e.g. to plot just the budgets setDiags={'D'}, and % to plot just the subsurface budgets setDiags={{'D',11}} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %determine input/output params: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %directory names: if iscell(dirMat); dirMatRef=dirMat{2}; dirMat=dirMat{1}; end; dirMat=[dirMat '/']; if isempty(who('dirMatRef')); dirMatRef=''; elseif ~isempty(dirMatRef); dirMatRef=[dirMatRef '/']; end; if isempty(who('dirTex')); dirTex=''; else; dirTex=[dirTex '/']; end; if isempty(who('nameTex')); nameTex='myPlots'; end; %set default setDiags and myTitle if isempty(setDiags); setDiags={'profiles','cost','A','B','C','D','MLD'}; if strcmp(nameTex,'myPlots'); nameTex='standardAnalysis'; end; % tmp1=dirMat; tmp2=strfind(tmp1,'_'); tmp1(tmp2)=' '; myTitle={'gcmfaces','standard analysis of the solution in',tmp1}; else; tmp1=dirMat; tmp2=strfind(tmp1,'_'); tmp1(tmp2)=' '; myTitle={'gcmfaces analysis of the solution in',tmp1}; end; %set fileTex and create dirTex if needed if isempty(dirTex); error('dirTex must be specified'); end; fileTex=[dirTex nameTex '.tex']; if isempty(dir(dirTex)); mkdir(dirTex); end; %%%%%%%%%%%%%%%%%%%%%% %load grid and params: %%%%%%%%%%%%%%%%%%%%%% gcmfaces_global; global myparms; test1=~isempty(dir([dirMat 'basic_diags_ecco_mygrid.mat'])); test2=~isempty(dir([dirMat 'diags_grid_parms.mat'])); if ~test1&~test2; error('missing diags_grid_parms.mat') elseif test2; nameGrid='diags_grid_parms.mat'; suffDiag='diags_set_'; budgetList='diags_select_budget_list.mat'; else; nameGrid='basic_diags_ecco_mygrid.mat'; suffDiag='basic_diags_ecco_'; budgetList='basic_diags_ecco_budget_list.mat'; end; %here we always reload the grid from dirMat to make sure the same one is used throughout eval(['load ' dirMat nameGrid ';']); %in case mygrid.memoryLimit=1, load the stuff that was not saved to diags_grid_parms.mat if mygrid.memoryLimit==1; list0={'hFacS','hFacW'}; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds2gcmfaces([mygrid.dirGrid ''' list0{iFld} '*'']);']); end; % mygrid.hFacCsurf=mygrid.hFacC; for ff=1:mygrid.hFacC.nFaces; mygrid.hFacCsurf{ff}=mygrid.hFacC{ff}(:,:,1); end; % mskC=mygrid.hFacC; mskC(mskC==0)=NaN; mskC(mskC>0)=1; mygrid.mskC=mskC; mskW=mygrid.hFacW; mskW(mskW==0)=NaN; mskW(mskW>0)=1; mygrid.mskW=mskW; mskS=mygrid.hFacS; mskS(mskS==0)=NaN; mskS(mskS>0)=1; mygrid.mskS=mskS; % gcmfaces_lines_zonal; mygrid.LATS=[mygrid.LATS_MASKS.lat]'; [lonPairs,latPairs,names]=line_greatC_TUV_MASKS_v4; gcmfaces_lines_transp(lonPairs,latPairs,names); end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %finalize listDiags %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %determined where to display anomalies between runs doAnomalies=~isempty(dirMatRef); %check if result is here to plot doBudget=~isempty(dir([dirMat suffDiag 'D_*'])); doBudget=~isempty(dir([dirMat suffDiag 'D_*']))|... ~isempty(dir([dirMat 'diags_set_D/' suffDiag 'D_*'])); doProfiles=~isempty(dir([dirMat 'insitu_cost_all.mat']))|... ~isempty(dir([dirMat 'cost/insitu_cost_all.mat'])); doCost=~isempty(dir([dirMat 'cost_altimeter_obs.mat']))|... ~isempty(dir([dirMat 'cost/cost_altimeter_obs.mat'])); doCtrl=~isempty(dir([dirMat 'cost_xx_aqh.mat']))|... ~isempty(dir([dirMat 'cost/cost_xx_aqh.mat'])); %the following have no code for diff between runs if doAnomalies; doProfiles=0; doCost=0; doCtrl=0; end; %reduce setDiags if needed: doDiags=ones(1,length(setDiags)); % for ii=1:length(setDiags); if iscell(setDiags{ii}); if ~doBudget&strcmp(setDiags{ii}{1},'D'); doDiags(ii)=0; end; elseif ~doBudget&strcmp(setDiags{ii},'D'); doDiags(ii)=0; elseif ~doProfiles&strcmp(setDiags{ii},'profiles'); doDiags(ii)=0; elseif ~doCost&strcmp(setDiags{ii},'cost'); doDiags(ii)=0; elseif ~doCtrl&strcmp(setDiags{ii},'controls'); doDiags(ii)=0; end; end; % setDiags={setDiags{find(doDiags)}}; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %initialize tex file %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if ~isempty(dirMatRef); tmp1=dirMat; tmp2=strfind(tmp1,'_'); tmp1(tmp2)=' '; myTitle={'gcmfaces analysis of the solution in',tmp1}; tmp1=dirMatRef; tmp2=strfind(tmp1,'_'); tmp1(tmp2)=' '; myTitle={myTitle{:},' minus ',tmp1}; end; if isempty(dirMatRef)&~isempty(dir([dirMat '../README'])); [rdm]=read_readme([dirMat '../README']); else; rdm=[]; end; write2tex(fileTex,0,myTitle,rdm); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %augment tex file %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% for ii=1:length(setDiags); if iscell(setDiags{ii}); ttl=input('specify tex file section title:\n'); write2tex(fileTex,1,ttl,1); diags_display({dirMat,dirMatRef},setDiags{ii},dirTex,nameTex); elseif strcmp(setDiags{ii},'profiles'); %in situ profiles fit write2tex(fileTex,1,'fit to data',1); write2tex(fileTex,1,'fit to in situ data',2); insitu_diags(dirMat,0,dirTex,nameTex); elseif strcmp(setDiags{ii},'cost'); %altimeter fit if isempty(find(strcmp(setDiags,'profiles'))); write2tex(fileTex,1,'fit to data',1); end; write2tex(fileTex,1,'fit to altimeter data (RADS)',2); cost_altimeter_disp(dirMat,2,'modMobs',dirTex,nameTex); cost_altimeter_disp(dirMat,1,'modMobs',dirTex,nameTex); cost_altimeter_disp(dirMat,3,'modMobs',dirTex,nameTex); cost_altimeter_disp(dirMat,1,'obs',dirTex,nameTex); cost_altimeter_disp(dirMat,1,'mod',dirTex,nameTex); %other cost terms write2tex(fileTex,1,'fit to sst data',2); cost_sst('',dirMat,0,dirTex,nameTex); write2tex(fileTex,1,'fit to grace r4 data',2); cost_bp('',dirMat,0,dirTex,nameTex); write2tex(fileTex,1,'fit to seaice data',2); cost_seaicearea('',dirMat,0,dirTex,nameTex); elseif strcmp(setDiags{ii},'A'); write2tex(fileTex,1,'volume, heat and salt transports',1); diags_display({dirMat,dirMatRef},'A',dirTex,nameTex); elseif strcmp(setDiags{ii},'B'); write2tex(fileTex,1,'mean and variance maps',1); diags_display({dirMat,dirMatRef},'B',dirTex,nameTex); elseif strcmp(setDiags{ii},'C'); write2tex(fileTex,1,'global, zonal, regional averages',1); diags_display({dirMat,dirMatRef},'C',dirTex,nameTex); elseif strcmp(setDiags{ii},'D'); budget_list=1; if ~isempty(dir([dirMat budgetList])); eval(['load ' dirMat budgetList ';']); end; for kk=budget_list; if kk==1; tmp1='(top to bottom)'; else; tmp1=sprintf('(%im to bottom)',round(-mygrid.RF(kk))); end; write2tex(fileTex,1,['budgets : volume, heat and salt ' tmp1],1); diags_display({dirMat,dirMatRef},{'D',kk},dirTex,nameTex); end; elseif strcmp(setDiags{ii},'MLD'); write2tex(fileTex,1,'mixed layer depth fields',1); diags_display({dirMat,dirMatRef},'MLD',dirTex,nameTex); elseif strcmp(setDiags{ii},'SEAICE'); write2tex(fileTex,1,'seaice and snow fields',1); diags_display({dirMat,dirMatRef},'SEAICE',dirTex,nameTex); elseif strcmp(setDiags{ii},'controls'); %controls write2tex(fileTex,1,'controls',1); cost_xx('',dirMat,0,dirTex,nameTex); else; ttl=input('specify tex file section title:\n'); write2tex(fileTex,1,ttl,1); diags_display({dirMat,dirMatRef},setDiags{ii},dirTex,nameTex); end;%if iscell(setDiags{ii}); end;%for ii=1:length(setDiags); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %finalize tex file %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% write2tex(fileTex,4); write2tex(fileTex,5); %%%%% get README text information function [rdm]=read_readme(filReadme); gcmfaces_global; rdm=[]; fid=fopen(filReadme,'rt'); while ~feof(fid); nn=length(rdm); rdm{nn+1} = fgetl(fid); end; fclose(fid); gcmfaces/gcmfaces_IO/0000755000435400001440000000000012375431055014351 5ustar gforgetusersgcmfaces/gcmfaces_IO/rdmds2workspace.m0000644000435400001440000000241212365534163017643 0ustar gforgetusersfunction []=rdmds2workspace(varargin); %object: read with rmds2gcmfaces then pass variables to workspace %input: varargin are the options to pass to rdmds (type help rdmds) %output: no output needs to be specified % data=rdmds2gcmfaces(varargin{:}); tmp1=dir([varargin{1} '*.meta']); tmp1=tmp1(1).name; tmp2=strfind(varargin{1},filesep); if ~isempty(tmp2); tmp2=tmp2(end); else; tmp2=0; end; tmp1=[varargin{1}(1:tmp2) tmp1]; fid=fopen(tmp1); while 1; tline = fgetl(fid); if ~ischar(tline), break, end if isempty(whos('tmp3')); tmp3=tline; else; tmp3=[tmp3 ' ' tline]; end; end fclose(fid); tmp1=who;%list current workspace variables eval(tmp3);%add meta variables to workspace tmp3=who;%also list meta variables for ii=1:length(tmp3);%store in structure (meta) if sum(strcmp(tmp1,tmp3(ii)))==0; eval(['meta.' tmp3{ii} '=' tmp3{ii} ';']); end; end; %export the various fields to caller workspace: assignin('caller','meta',meta); %export the various fields to caller workspace: for ii=1:meta.nFlds; if meta.nDims==3; assignin('caller',deblank(meta.fldList{ii}),squeeze(data(:,:,:,ii,:))); else; assignin('caller',deblank(meta.fldList{ii}),squeeze(data(:,:,ii,:))); end; % fprintf([deblank(meta.fldList{ii}) ' loaded into workspace \n']); end; gcmfaces/gcmfaces_IO/rdmds2workspace_list.m0000644000435400001440000000736512365534163020712 0ustar gforgetusersfunction []=rdmds2workspace_list(fileName,timeListToRead,fldListToRead); %object: read with rmds2gcmfaces then pass variables to workspace %input: fileName is the file name root (e.g. 'diags_3d_set2*') % timeListToRead is time steps Nos list (e.g. [98088 98089], or % NaN to load all files) % fldListToRead is the list of fields to be read (e.g. % 'THETA' or {'THETA','SALT'} or '*' to load all fields) %output: no output needs to be specified % global mygrid; %read meta file tmp1=dir([fileName '*.meta']); tmp1=tmp1(1).name; tmp2=strfind(fileName,filesep); if ~isempty(tmp2); tmp2=tmp2(end); else; tmp2=0; end; tmp1=[fileName(1:tmp2) tmp1]; fid=fopen(tmp1); while 1; tline = fgetl(fid); if ~ischar(tline), break, end if isempty(whos('tmp3')); tmp3=tline; else; tmp3=[tmp3 ' ' tline]; end; end fclose(fid); %add meta variables to workspace eval(tmp3); %reformat to meta structure meta.dataprec=dataprec; meta.nDims=nDims; meta.nFlds=nFlds; meta.nrecords=nrecords; meta.fldList=fldList; meta.dimList=dimList; if ~isempty(who('timeInterval')); meta.timeInterval=timeInterval; end; if ~isempty(who('timeStepNumber')); meta.timeStepNumber=timeStepNumber; end; %fldListToRead special cases (1 field, if ischar(fldListToRead); if strcmp(fldListToRead,'*'); fldListToRead=meta.fldList; else; fldListToRead={fldListToRead}; end; end; %list fields that will actually be loaded recListToRead=zeros(meta.nFlds,1); for ii=1:meta.nFlds; test0=sum(strcmp(fldListToRead,strtrim(meta.fldList(ii)))); if test0; recListToRead(ii)=1; end; end; recListToRead=find(recListToRead); %update fldListToRead accordingly fldListToRead={meta.fldList{recListToRead}}; %timeListToRead special case if isnan(timeListToRead(1)); tmp1=dir([fileName '*.data']); timeListToRead=[]; for tt=1:length(tmp1); i0=strfind(tmp1(tt).name,'.00')+1; i1=strfind(tmp1(tt).name,'.data')-1; timeListToRead=[timeListToRead ; str2num(tmp1(tt).name(i0:i1))]; end; end; if 1;%use rdmds2gcmfaces if size(timeListToRead,1)>1; timeListToRead=timeListToRead'; end; for ii=1:length(recListToRead); data=rdmds2gcmfaces(fileName,timeListToRead,'rec',recListToRead(ii)); eval([deblank(fldListToRead{ii}) '=data;']); end; else;%use fread instead %initialize arrays nt=length(timeListToRead); siz=size(convert2gcmfaces(mygrid.XC)); txt='(:,:'; if meta.nDims==3; siz=[siz length(mygrid.RC)]; txt=[txt ',:']; end; for ii=1:length(recListToRead); eval([fldListToRead{ii} '=zeros([siz nt]);']); end; recl=prod(siz); %load the data for tt=1:nt; tmp1=dir([fileName sprintf('*.%010i',timeListToRead(tt)) '.data']); fname=tmp1.name; tmp2=strfind(fileName,filesep); if isempty(tmp2); dname='./'; else; dname=fileName(1:tmp2(end)); end; fid=fopen([dname fname],'r','b'); for ii=1:length(recListToRead); tmp1=recl*4*(recListToRead(ii)-1); status=fseek(fid,tmp1,'bof'); tmp1=reshape(fread(fid,recl,'float32'),siz); eval([fldListToRead{ii} txt ',tt)=tmp1' txt ');']); end; end; %convert2gcmfaces for ii=1:length(recListToRead); eval([fldListToRead{ii} '=convert2gcmfaces(' fldListToRead{ii} ');']); end; end; %export the various fields to caller workspace: assignin('caller','meta',meta); %export the various fields to caller workspace: for ii=1:length(fldListToRead); eval(['data=' deblank(fldListToRead{ii}) ';']); if meta.nDims==3; assignin('caller',deblank(fldListToRead{ii}),data); else; assignin('caller',deblank(fldListToRead{ii}),data); end; % fprintf([deblank(fldListToRead{ii}) ' loaded into workspace \n']); end; gcmfaces/gcmfaces_IO/read2memory.m0000644000435400001440000000141611504247210016746 0ustar gforgetusersfunction [fldOut]=read2memory(fileIn,varargin); %purpose: load binary file to memory % %inputs: fileIn is the file name %(optional) sizeOut is the output array size (or [] if not known) % prec is the file precision (32, by default, or 64) % %output: fldOut is the binary vector (default) or array (if sizeOut is spec.) if nargin>1; sizeOut=varargin{1}; else; sizeOut=[]; end; if nargin>2; prec=varargin{2}; else; prec=32; end; if ~strcmp(fileIn(end-2:end),'txt'); nn=dir(fileIn); nn=nn.bytes/(prec/8); fid=fopen(fileIn,'r','b'); fldOut=fread(fid,nn,['float' num2str(prec)]); fclose(fid); else; error('text read is not implemented\n'); % fid=fopen(fileIn,'rt'); fread(fid,fldOut); fclose(fid); end; if ~isempty(sizeOut); fldOut=reshape(fldOut,sizeOut); end; gcmfaces/gcmfaces_IO/grid_load.m0000644000435400001440000001604312357056757016473 0ustar gforgetusersfunction []=grid_load(dirGrid,nFaces,fileFormat,memoryLimit,omitNativeGrid); %object: load grid information, convert it to gcmfaces format % and encapsulate it in the global mygrid structure. %inputs: dirGrid is the directory where the grid files (gcm output) can be found. % nFaces is the number of faces in this gcm set-up of current interest. % fileFormat is the file format ('straight','cube','compact') %optional: memoryLimit is a flag that allows the user to omit secondary % grid fields in case memory/storage become an issue. It % takes 3 values : (0; the default) includes everything % (1) omits all 3D fields but hFacC (2) only loads XC & YC. % omitNativeGrid is a flag (0 by default) to bypass (when flag 1) % grid_load_native and grid_load_native_RAZ calls (that can % complement mygrid based upon e.g. tile*.mitgrid files) if isempty(whos('memoryLimit')); memoryLimit=0; end; if isempty(whos('omitNativeGrid')); omitNativeGrid=0; end; gcmfaces_global; mygrid=[]; mygrid.dirGrid=dirGrid; mygrid.nFaces=nFaces; mygrid.fileFormat=fileFormat; mygrid.gcm2facesFast=false; mygrid.memoryLimit=memoryLimit; if mygrid.memoryLimit>0; gcmfaces_msg(['* Warning from grid_load : memoryLimit>0 ' ... 'may precludes advanced gmcfaces functions.'],''); end; if mygrid.memoryLimit>1; gcmfaces_msg(['* Warning from grid_load : memoryLimit>1 ' ... 'may only allow for basic fields displays.'],''); end; if ~isempty(dir([dirGrid 'grid.specs.mat'])); specs=open([dirGrid 'grid.specs.mat']); mygrid.ioSize=specs.ioSize; mygrid.facesSize=specs.facesSize; mygrid.facesExpand=specs.facesExpand; %example for creating grid.specs.mat, to put in dirGrid : %ioSize=[364500 1]; %facesSize=[[270 450];[0 0];[270 270];[180 270];[450 270]]; %facesExpand=[270 450]; %save grid.specs.mat ioSize facesSize facesExpand; elseif strcmp(fileFormat,'compact'); v0=rdmds([dirGrid 'XC']); mygrid.ioSize=size(v0); nn=size(v0,1); pp=size(v0,2)/nn; mm=(pp+4-mygrid.nFaces)/4*nn; mygrid.facesSize=[[nn mm];[nn mm];[nn nn];[mm nn];[mm nn];[nn nn]]; mygrid.facesExpand=[]; elseif strcmp(fileFormat,'cube'); v0=rdmds([dirGrid 'XC']); mygrid.ioSize=size(v0); nn=size(v0,2); mygrid.facesSize=[[nn nn];[nn nn];[nn nn];[nn nn];[nn nn];[nn nn]]; mygrid.facesExpand=[]; elseif strcmp(fileFormat,'straight'); v0=rdmds([dirGrid 'XC']); mygrid.ioSize=size(v0); mygrid.facesSize=mygrid.ioSize; mygrid.facesExpand=[]; end; mygrid.missVal=NaN;%will be set to 0 once the grid has been loaded. if ~(nFaces==1&strcmp(fileFormat,'straight'))&... ~(nFaces==6&strcmp(fileFormat,'cube'))&... ~(nFaces==6&strcmp(fileFormat,'compact'))&... ~(nFaces==5&strcmp(fileFormat,'compact')); % if myenv.verbose; % fprintf('\nconvert2gcmfaces.m init: there are several supported file conventions. \n'); % fprintf(' By default gcmfaces assumes MITgcm type binary formats as follows: \n') % fprintf(' (1 face) straight global format; (4 or 5 faces) compact global format\n'); % fprintf(' (6 faces) cube format with one face after the other. \n'); % fprintf(' If this is inadequate, you can change the format below.\n\n'); % end; error('non-tested topology/fileFormat'); end; %the various grid fields: if mygrid.memoryLimit==0; list0={'XC','XG','YC','YG','RAC','RAZ','DXC','DXG','DYC','DYG','hFacC','hFacS','hFacW','Depth'}; elseif mygrid.memoryLimit==1; list0={'XC','XG','YC','YG','RAC','RAZ','DXC','DXG','DYC','DYG','hFacC','Depth'}; elseif mygrid.memoryLimit==2; list0={'XC','YC'}; end; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds2gcmfaces([dirGrid ''' list0{iFld} '*'']);']); end; %the vertical grid list0={'RC','RF','DRC','DRF'}; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=squeeze(rdmds([dirGrid ''' list0{iFld} '*'']));']); end; %grid orientation if mygrid.memoryLimit<2; list0={'AngleCS','AngleSN'}; test0=~isempty(dir([dirGrid 'AngleCS*'])); if test0; for iFld=1:length(list0); eval(['mygrid.' list0{iFld} '=rdmds2gcmfaces([dirGrid ''' list0{iFld} '*'']);']); end; else; warning('\n AngleCS/AngleSN not found; set to 1/0 assuming lat/lon grid.\n'); mygrid.AngleCS=mygrid.XC; mygrid.AngleCS(:)=1; mygrid.AngleSN=mygrid.XC; mygrid.AngleSN(:)=0; end; end; %if grid is incomplete (blank tiles) then try to get %additional info from native grid, or apply missing value. test0=sum(isnan(mygrid.XC))>0; test1=prod(mygrid.ioSize)~=sum(isnan(NaN*mygrid.XC(:))); if (test0|test1)&~omitNativeGrid; %treat fields that are part of the native grid mygrid1=mygrid; mygrid=[]; grid_load_native(dirGrid,nFaces,0); mygrid1.XC=mygrid.XC; mygrid1.YC=mygrid.YC; mygrid1.XC=mygrid.XG; mygrid1.YG=mygrid.YG; mygrid1.RAC=mygrid.RAC; mygrid=mygrid1; %apply missing value for fields that aren't list0={'hFacC','hFacS','hFacW','Depth','AngleCS','AngleSN'}; for ii=1:length(list0); eval(['tmp1=mygrid.' list0{ii} ';']); tmp1(isnan(tmp1))=0; eval(['mygrid.' list0{ii} '=tmp1;']); end; %and fix angles if needed tmp1=mygrid.AngleCS.^2+mygrid.AngleSN.^2; tmp1=1*(tmp1>0.999&tmp1<1.001); mygrid.AngleCS(tmp1==0)=1; mygrid.AngleSN(tmp1==0)=0; end; %get full RAZ (incl. 'extra line and column') needed for e.g. rotational computations if mygrid.memoryLimit<2&~omitNativeGrid; grid_load_native_RAZ; end; %grid masks if mygrid.memoryLimit<1; mygrid.hFacCsurf=mygrid.hFacC; for ff=1:mygrid.hFacC.nFaces; mygrid.hFacCsurf{ff}=mygrid.hFacC{ff}(:,:,1); end; mskC=mygrid.hFacC; mskC(mskC==0)=NaN; mskC(mskC>0)=1; mygrid.mskC=mskC; mskW=mygrid.hFacW; mskW(mskW==0)=NaN; mskW(mskW>0)=1; mygrid.mskW=mskW; mskS=mygrid.hFacS; mskS(mskS==0)=NaN; mskS(mskS>0)=1; mygrid.mskS=mskS; end; %zonal mean and sections needed for transport computations if mygrid.memoryLimit<1; if ~isfield(mygrid,'mygrid.LATS_MASKS'); gcmfaces_lines_zonal; mygrid.LATS=[mygrid.LATS_MASKS.lat]'; end; if ~isfield(mygrid,'LINES_MASKS'); [lonPairs,latPairs,names]=line_greatC_TUV_MASKS_v4; gcmfaces_lines_transp(lonPairs,latPairs,names); end; end; %to allow convert2gcmfaces/doFast: if isempty(mygrid.facesExpand)&mygrid.memoryLimit<2; tmp1=convert2gcmfaces(mygrid.XC); tmp1(:)=[1:length(tmp1(:))]; nn=length(tmp1(:)); mygrid.gcm2faces=convert2gcmfaces(tmp1); mygrid.faces2gcmSize=size(tmp1); mygrid.faces2gcm=convert2gcmfaces(tmp1); for iFace=1:mygrid.nFaces; n=length(mygrid.gcm2faces{iFace}(:)); mygrid.faces2gcm{iFace}=mygrid.gcm2faces{iFace}(:); mygrid.gcm2faces{iFace}=sparse([1:n],mygrid.gcm2faces{iFace}(:),ones(1,n),n,nn); end; mygrid.gcm2facesFast=true; end; %reset missVal parameter to 0. %Note : this is only used by convert2widefaces, for runs with cropped grids. %Note : 0 should not be used as a fill for the grid itself (NaN was used). mygrid.missVal=0; gcmfaces/gcmfaces_IO/convert2gcmfaces.m0000644000435400001440000000555212023652607017767 0ustar gforgetusersfunction [v1]=convert2gcmfaces(v0,varargin); %object: converts model output to gcmfaces object % or vice versa %input: v0 model output array (resp. gcmfaces object) %output: v1 gcmfaces object (model output array) % %note: global mygrid parameters (nFaces, fileFormat) are used input_list_check('convert2gcmfaces',nargin); aa=whos('v0'); doGcm2Faces=strcmp(aa.class,'double'); global mygrid; if doGcm2Faces&mygrid.gcm2facesFast; [n1,n2,n3,n4,n5]=size(v0); v0=reshape(v0,[n1*n2 n3*n4*n5]); for iFace=1:mygrid.nFaces; v1{iFace}=reshape(mygrid.gcm2faces{iFace}*v0,[size(mygrid.XC{iFace}) n3 n4 n5]); end; v1=gcmfaces(v1); elseif ~doGcm2Faces&mygrid.gcm2facesFast; [n1,n2,n3,n4,n5]=size(v0{1}); v1=zeros(mygrid.faces2gcmSize(1)*mygrid.faces2gcmSize(2),n3*n4*n5); for iFace=1:mygrid.nFaces; nn=size(mygrid.XC{iFace}); v1(mygrid.faces2gcm{iFace},:)=reshape(v0{iFace},[nn(1)*nn(2) n3*n4*n5]); end; v1=reshape(v1,[mygrid.faces2gcmSize n3 n4 n5]); elseif doGcm2Faces; [n1,n2,n3,n4,n5]=size(v0); if strcmp(mygrid.fileFormat,'straight'); v1={v0}; elseif strcmp(mygrid.fileFormat,'cube'); for ii=1:6; v1{ii}=v0(n2*(ii-1)+[1:n2],:,:,:,:); end; elseif strcmp(mygrid.fileFormat,'compact'); v00=reshape(v0,[n1*n2 n3*n4*n5]); i0=0; i1=0; for iFace=1:mygrid.nFaces; i0=i1+1; nn=mygrid.facesSize(iFace,1); mm=mygrid.facesSize(iFace,2); i1=i1+nn*mm; v1{iFace}=reshape(v00(i0:i1,:),[nn mm n3 n4 n5]); end; end; v1=gcmfaces(v1); if ~isempty(mygrid.facesExpand); v1=convert2widefaces(v1); end; else; [n1,n2,n3,n4,n5]=size(v0{1}); if strcmp(mygrid.fileFormat,'straight'); v1=v0{1}; elseif strcmp(mygrid.fileFormat,'cube'); v1=zeros(n2*6,n2,n3,n4,n5); for ii=1:6; v1([1:n2]+(ii-1)*n2,:,:,:,:)=v0{ii}; end; elseif strcmp(mygrid.fileFormat,'compact'); % is there a reason for this? % v0_faces=v0; clear v0; % for iFace=1:mygrid.nFaces; eval(['v0{iFace}=get(v0_faces,''f' num2str(iFace) ''');']); end; if ~isempty(mygrid.facesExpand); v0=convert2widefaces(v0); end; aa=0;bb=0; for iFace=1:mygrid.nFaces; aa=aa+prod(mygrid.facesSize(iFace,:)); bb=bb+prod(size(v0{iFace})); end; bb=bb/aa; v11=NaN*zeros(aa,bb); i0=0; i1=0; for iFace=1:mygrid.nFaces; i0=i1+1; nn=mygrid.facesSize(iFace,1); mm=mygrid.facesSize(iFace,2); i1=i1+nn*mm; v11(i0:i1,:)=reshape(v0{iFace},[nn*mm bb]); end; nn=mygrid.ioSize(1); mm=mygrid.ioSize(2); v1=reshape(v11,[nn mm n3 n4 n5]); end; end; gcmfaces/gcmfaces_IO/grid_load_native_RAZ.m0000644000435400001440000000307512024523333020532 0ustar gforgetusersfunction []=grid_load_native_RAZ(); %object: load NATIVE FORMAT grid information for RAZ, which % includes the extra line & column of vorticity points; % or derive it as exch_Z(RAZ). %input/ouput: none; all happens in the mygrid global structure. gcmfaces_global; %try default file names first files=dir([mygrid.dirGrid 'tile*.mitgrid']); %then try specific names if isempty(files)&~strcmp(mygrid.XC.gridType,'ll'); names=input('grid files not found; please specify \n names (e.g. ''grid_cs32*bin'')\n'); files=dir([mygrid.dirGrid names]); end; if ~isempty(files)&~strcmp(mygrid.XC.gridType,'ll'); %load from files RAZfull=gcmfaces; for iFile=1:mygrid.nFaces; [ni,nj]=size(mygrid.XC{iFile}); tmp1=dir([mygrid.dirGrid files(iFile).name]); nf=tmp1.bytes/8/(ni+1)/(nj+1); fld=read2memory([mygrid.dirGrid files(iFile).name],[ni+1 nj+1 nf],64); RAZfull{iFile}=fld(:,:,10); end; mygrid.RAZfull=RAZfull; elseif ~strcmp(mygrid.XC.gridType,'ll'); fprintf('\n No native grid file was found, so we will fill\n'); fprintf('corners of RAZfull using a vorticity point exchange.\n'); global exch_Z_assume_sym; fprintf('Choose a method : 0) approximate by neighbor average ? \n'); exch_Z_assume_sym=input('Choose a method : 1) assume uncertain symetry ? \n'); mygrid.RAZfull=mygrid.RAZ; mygrid.RAZfull=exch_Z(mygrid.RAZ); exch_Z_assume_sym=0;%exch_Z_assume_sym should not be used except for RAZ else;%latlon grid mygrid.RAZfull=exch_Z(mygrid.RAZ); end; gcmfaces/gcmfaces_IO/write2nctiles.m0000644000435400001440000001522212273771146017334 0ustar gforgetusersfunction [dimOut]=write2nctiles(fileOut,fldIn,doCreate,varargin); %object : write gcmfaces object to netcdf files (tiled) %inputs : fileOut is the name of the file to be created % fldIn is the array to write to disk % doCreate is a 0/1 switch; 1 => create file ; 0 => append to file. %optional paramaters : % can be provided in the form {'name',value} % those that are currently active are % 'descr' is the file description (default ''). % 'rdm' is the extended estimate description (default ''). % 'fldName' is the nc variable name for fld (default : the outside name of fldIn). % 'longName' is the corresponding long name (default : ''). % 'units' is the unit of fld (default : '(unknown)'). % 'missval' is the missing value (default : NaN). % 'fillval' is the fill value (default : NaN). % 'tileNo' is a map of tile indices (default is face number) % 'coord' is auxilliary coordinates attribute (e.g. 'lon lat dep') %netcdf dimensions : array dimensions are simply set to 'i1,i2,...' gcmfaces_global; if ~(myenv.useNativeMatlabNetcdf); error('only native matlab nectdf is supported in write2nctiles'); end; doCheck=0;%set to one to print stuff to screen %set more optional paramaters to default values descr=''; rdm=''; fldName=inputname(2); longName=''; units='(unknown)'; missval=NaN; fillval=NaN; dimIn=[]; tileNo=mygrid.XC; for ff=1:mygrid.nFaces; tileNo{ff}(:)=ff; end; coord=''; %set more optional paramaters to user defined values for ii=1:nargin-3; if ~iscell(varargin{ii}); warning('inputCheck:write2nctiles_1',... ['write2nctiles expects \n'... ' its optional parameters as cell arrays. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help write2nctiles'' for details.']); elseif ~ischar(varargin{ii}{1}); warning('inputCheck:write2nctiles_2',... ['write2nctiles expects \n'... ' its optional parameters cell arrays \n'... ' to start with character string. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help write2nctiles'' for details.']); else; if strcmp(varargin{ii}{1},'descr')|... strcmp(varargin{ii}{1},'rdm')|... strcmp(varargin{ii}{1},'fldName')|... strcmp(varargin{ii}{1},'longName')|... strcmp(varargin{ii}{1},'units')|... strcmp(varargin{ii}{1},'missval')|... strcmp(varargin{ii}{1},'fillval')|... strcmp(varargin{ii}{1},'tileNo')|... strcmp(varargin{ii}{1},'coord')|... strcmp(varargin{ii}{1},'dimIn'); eval([varargin{ii}{1} '=varargin{ii}{2};']); else; warning('inputCheck:write2nctiles_3',... ['unknown option ''' varargin{ii}{1} ''' was ignored']); end; end; end; %split fldIn (if isa gcmfaces) into tiles tileList=unique(convert2vector(tileNo)); tileList=tileList(~isnan(tileList)); ntile=length(tileList); % if isa(fldIn,'gcmfaces'); for ff=1:ntile; tmp1=[]; for gg=1:mygrid.nFaces; [tmpi,tmpj]=find(tileNo{gg}==ff); if ~isempty(tmpi); tmpi=[min(tmpi(:)):max(tmpi(:))]; tmpj=[min(tmpj(:)):max(tmpj(:))]; tmp1=fldIn{gg}(tmpi,tmpj,:,:); end; end; fldTiles{ff}=tmp1; end; end; %start processing loop for ff=1:ntile; if isa(fldIn,'gcmfaces'); fldTile=fldTiles{ff}; %reverse order of dimensions nn=length(size(fldTile)); fldTile=permute(fldTile,[nn:-1:1]); else; fldTile=fldIn; end; fileTile=[fileOut sprintf('.%04d.nc',ff)]; %select dimensions of relevance: nDim=length(size(fldTile)); dimsize=size(fldTile); for iDim=1:nDim; if size(fldTile,iDim)~=1; dimlist{iDim}=['i' num2str(iDim)]; dimName{iDim}=['array index ' num2str(iDim)]; eval(['dimvec.i' num2str(iDim) '=[1:size(fldTile,iDim)];']); end; end; %omit singleton dimensions: ii=find(dimsize~=1); dimsize=dimsize(ii); dimlist={dimlist{ii}}; dimName={dimName{ii}}; %check : if doCheck; whos fldTile descr fldName longName units missval fillval dimlist dimName dimsize dimvec keyboard; end; %output dimension information dimOut{ff}=dimlist; if doCreate; %create netcdf file: %------------------- % ncid=nccreate(fileTile,'NETCDF4');%to allow for big files ncid=nccreate(fileTile,'clobber'); if ~isempty(rdm); descr2=[descr ' -- ' rdm{1}]; else; descr2=descr; end; ncputAtt(ncid,'','description',descr2); for pp=2:length(rdm); tmp1=char(pp+63); netcdf.putAtt(ncid,nc_global,tmp1,rdm{pp}); end; %append readme pp=length(rdm)+1; netcdf.putAtt(ncid,nc_global,tmp1,'file created using gcmfaces_IO/write2nctiles.m'); ncputAtt(ncid,'','date',date); netcdf.putAtt(ncid,nc_global,'Conventions','CF-1.6') ncputAtt(ncid,'','_FillValue',fillval); ncputAtt(ncid,'','missing_value',missval); ncdefDim(ncid,'itxt',30); for dd=1:length(dimlist); ncdefDim(ncid,dimlist{dd},dimsize(dd)); end; for dd=1:length(dimlist); ncdefVar(ncid,dimlist{dd},'double',{dimlist{dd}}); ncputAtt(ncid,dimlist{dd},'long_name',dimName{dd}); ncputAtt(ncid,dimlist{dd},'units','1'); end; ncclose(ncid); %fill in the dimensions dimensions values vectors: %------------------------------------------------- ncid=ncopen(fileTile,'write'); for dd=1:length(dimlist); ncputvar(ncid,dimlist{dd},getfield(dimvec,dimlist{dd})); end; ncclose(ncid); end; %use dimentsion specified by user if ~isempty(dimIn); dimlist=dimIn{ff}; end; %define and fill field: %---------------------- ncid=ncopen(fileTile,'write'); % netcdf.reDef(ncid); ncdefVar(ncid,fldName,'double',flipdim(dimlist,2));%note the direction flip if ~isempty(longName); ncputAtt(ncid,fldName,'long_name',longName); end; if ~isempty(units); ncputAtt(ncid,fldName,'units',units); end; if ~isempty(coord); ncputAtt(ncid,fldName,'coordinates',coord); end; if strcmp(fldName,'lon'); ncputAtt(ncid,fldName,'standard_name','longitude'); end; if strcmp(fldName,'lat'); ncputAtt(ncid,fldName,'standard_name','latitude'); end; if strcmp(fldName,'dep'); ncputAtt(ncid,fldName,'standard_name','depth'); end; if strcmp(fldName,'tim'); ncputAtt(ncid,fldName,'standard_name','time'); end; if strcmp(fldName,'land'); ncputAtt(ncid,fldName,'standard_name','land_binary_mask'); end; if strcmp(fldName,'area'); ncputAtt(ncid,fldName,'standard_name','cell_area'); end; if strcmp(fldName,'thic'); ncputAtt(ncid,fldName,'standard_name','cell_thickness'); end; netcdf.endDef(ncid); % ncputvar(ncid,fldName,fldTile); ncclose(ncid); end;%for ff=1:ntile; gcmfaces/gcmfaces_IO/write2meta.m0000644000435400001440000000233611633477757016635 0ustar gforgetusersfunction []=write2meta(myFile,myDim,varargin); %purpose: write meta file to match binary file % %inputs: myFile is the file name (must finish with '.data') % myDim is the size of a field (2D or 3D integer vector) %(optional) myPrec is the file myPrecision (32, by default, or 64) %precision: if nargin>2; myPrec=varargin{1}; else; myPrec=32; end; %number of dimensions nDim=length(myDim); %number of records: tmp1=dir(myFile); nRec=tmp1.bytes/myDim(1)/myDim(2)/myPrec*8; if nDim>2; nRec=nRec/myDim(3); end; if nRec<1|floor(nRec)~=nRec; error('inconsistent dimensions'); end; %check that creating a meta file makes sense w\r\t rdmds if ~strcmp(myFile(end-4:end),'.data'); error('file name must finish in ''.data''\n'); else; myFile=[myFile(1:end-5) '.meta']; end; %create the meta file: fid=fopen(myFile,'wt'); %% fprintf(fid,'nDims = [ %i ];\n',min(nDim,3)); fprintf(fid,' dimList = [\n'); fprintf(fid,' %5i, %5i, %5i,\n',myDim(1),1,myDim(1)); fprintf(fid,' %5i, %5i, %5i,\n',myDim(2),1,myDim(2)); if nDim>2; fprintf(fid,' %5i, %5i, %5i,\n',myDim(3),1,myDim(3)); end; fprintf(fid,' ];\n'); fprintf(fid,' dataprec = [ ''float%2i'' ];\n',myPrec); fprintf(fid,' nrecords = [ %5i ];\n',nRec); %% fclose(fid); gcmfaces/gcmfaces_IO/read_bin.m0000644000435400001440000000227112273012731016265 0ustar gforgetusersfunction [fld]=read_bin(fileName,varargin); %usage: fld=read_bin(fileName); reads 3D field (N levels in 3rd dim) %usage: fld=read_bin(fileName,trec); reads 3D field, at trec (50 levels) %usage: fld=read_bin(fileName,trec,k); reads 2D field, at level k, at trec (50 levels) %usage: fld=read_bin(fileName,trec,0); reads 2D field, at trec (1 level) global mygrid; n1=mygrid.ioSize(1); n2=mygrid.ioSize(2); n3=length(mygrid.RC); nF=mygrid.nFaces; recl2D=n1*n2*4; recl3D=n1*n2*n3*4; myprec='float32'; %recl2D=n1*n2*8; recl3D=n1*n2*n3*8; myprec='float64'; if nargin==1; n3=dir(fileName); n3=n3.bytes/recl2D; recl3D=recl2D*n3; end; if nargin>1; tt=varargin{1}; else; tt=1; end; if nargin>2; kk=varargin{2}; else; kk=[]; end; fid=fopen(fileName,'r','b'); if ~isempty(kk); if kk==0;%meaning the field is only two dimensional status=fseek(fid,(tt-1)*recl2D,'bof'); fld=reshape(fread(fid,n1*n2,myprec),[n1 n2]); else; status=fseek(fid,(tt-1)*recl3D+(kk-1)*recl2D,'bof'); fld=reshape(fread(fid,n1*n2,myprec),[n1 n2]); end; else; status=fseek(fid,(tt-1)*recl3D,'bof'); fld=reshape(fread(fid,n1*n2*n3,myprec),[n1 n2 n3]); end; fclose(fid); fld=convert2gcmfaces(fld); gcmfaces/gcmfaces_IO/rdmds2gcmfaces.m0000644000435400001440000000126612367515723017426 0ustar gforgetusersfunction [fldOut]=rdmds2gcmfaces(varargin); %object: read with rmds then apply convert2gcmfaces %input: varargin are the options to pass to rdmds (type help rdmds) %output: fldOut is a gcmfaces object % %note: an earlier version was expecting nFaces to be passed % as the last argument; this is not the case anymore. gcmfaces_global; v0=rdmds(varargin{1:end}); nn=size(v0); test1=isfield(mygrid,'xtrct'); test1=test1&(prod(mygrid.ioSize)~=prod(nn(1:2))); if test1; if length(nn)==2; nn=[nn 1]; end; v0=reshape(v0,[nn(1)*nn(2) nn(3:end)]); v0=v0(mygrid.xtrct_inFull,:,:,:); v0=reshape(v0,[mygrid.ioSize nn(3:end)]); end; fldOut=convert2gcmfaces(v0); gcmfaces/gcmfaces_IO/read_nctiles.m0000644000435400001440000000546712365534210017173 0ustar gforgetusersfunction [fld]=read_nctiles(fileName,fldName,varargin); %usage: fld=read_nctiles(fileName); reads full field using fileName as field name %usage: fld=read_nctiles(fileName,fldName); reads full field (all depths, all times) %usage: fld=read_nctiles(fileName,fldName,tt); reads 3D or 2D field, at time index tt (all depths) %usage: fld=read_nctiles(fileName,fldName,tt,kk); reads 3D field, at depth index kk, at time index tt gcmfaces_global; if nargin==1; tmp1=['/' fileName]; tmp2=strfind(tmp1,filesep); fldName=tmp1(tmp2(end)+1:end); end; if nargin>2; tt=varargin{1}; else; tt=[]; end; if nargin>3; kk=varargin{2}; else; kk=[]; end; %A) determine map of tile indices (if not already done) global nctiles; test1=isempty(nctiles); test2=0; if ~test1; tmp1=dir([fileName '*']); test2=(length(tmp1)~=length(nctiles.no)); end; if test1|test2; %build map of tile indices if (length(dir([fileName '*']))==mygrid.nFaces); nctiles.map=NaN*mygrid.XC; for ff=1:mygrid.nFaces; nctiles.map{ff}(:)=ff; end; else; fileIn=sprintf('%s.%04d.nc',fileName,1); nc=netcdf.open(fileIn,0); vv = netcdf.inqVarID(nc,fldName); [varname,xtype,dimids,natts]=netcdf.inqVar(nc,vv); tileSize=zeros(1,2); [tmp,tileSize(1)] = netcdf.inqDim(nc,dimids(1)); [tmp,tileSize(2)] = netcdf.inqDim(nc,dimids(2)); netcdf.close(nc); nctiles.map=gcmfaces_loc_tile(tileSize(1),tileSize(2)); end; %determine tile list nctiles.no=unique(convert2vector(nctiles.map)); nctiles.no=nctiles.no(~isnan(nctiles.no)); %determine location of each tile for ff=1:length(nctiles.no); for gg=1:mygrid.nFaces; [tmpi,tmpj]=find(nctiles.map{gg}==ff); if ~isempty(tmpi); nctiles.f{ff}=gg; nctiles.i{ff}=[min(tmpi(:)):max(tmpi(:))]; nctiles.j{ff}=[min(tmpj(:)):max(tmpj(:))]; end; end; end; end; %B) the file read operation itself for ff=1:length(nctiles.no); %read one tile fileIn=sprintf('%s.%04d.nc',fileName,ff); nc=netcdf.open(fileIn,0); vv = netcdf.inqVarID(nc,fldName); [varname,xtype,dimids,natts]=netcdf.inqVar(nc,vv); [dimname,siz(1)] = netcdf.inqDim(nc,dimids(1)); [dimname,siz(2)] = netcdf.inqDim(nc,dimids(2)); siz=[siz length(mygrid.RC)]; if ~isempty(tt); t0=tt(1)-1; nt=tt(end)-tt(1)+1; if length(dimids)==3; start=[0 0 t0]; count=[siz(1) siz(2) nt]; elseif isempty(kk); start=[0 0 0 t0]; count=[siz(1) siz(2) siz(3) nt]; else; start=[0 0 kk-1 t0]; count=[siz(1) siz(2) 1 nt]; end; fldTile=netcdf.getVar(nc,vv,start,count); else; fldTile=netcdf.getVar(nc,vv); end; netcdf.close(nc); %initialize fld (full gcmfaces object) if ff==1; siz=[1 1 size(fldTile,3) size(fldTile,4)]; fld=NaN*repmat(mygrid.XC,siz); end; %place tile in fld fld{nctiles.f{ff}}(nctiles.i{ff},nctiles.j{ff},:,:)=fldTile; end;%for ff=1:mygrid.nFaces; gcmfaces/gcmfaces_IO/rdmds.m0000644000435400001440000003652511334543331015646 0ustar gforgetusersfunction [AA,itrs,MM] = rdmds(fnamearg,varargin) % RDMDS Read MITgcmUV meta/data files % % A = RDMDS(FNAME) % A = RDMDS(FNAME,ITER) % A = RDMDS(FNAME,[ITER1 ITER2 ...]) % A = RDMDS(FNAME,NaN) % A = RDMDS(FNAME,Inf) % [A,ITS,M] = RDMDS(FNAME,[...]) % A = RDMDS(FNAME,[...],'rec',RECNUM) % % A = RDMDS(FNAME) reads data described by meta/data file format. % FNAME is a string containing the "head" of the file names. % % eg. To load the meta-data files % T.0000002880.000.000.meta, T.0000002880.000.000.data % T.0000002880.001.000.meta, T.0000002880.001.000.data % T.0000002880.002.000.meta, T.0000002880.002.000.data % T.0000002880.003.000.meta, T.0000002880.003.000.data % use % >> A=rdmds('T.0000002880'); % >> size(A) % ans = % 64 32 5 % eg. To load a multiple record file % >> A=rdmds('pickup.0000002880'); % >> size(A) % ans = % 64 32 5 61 % % % A = RDMDS(FNAME,ITER) reads data described by meta/data file format. % FNAME is a string containing the "head" of the file name excluding the % 10-digit iterartion number. % ITER is a vector of positive integers that will expand to the 10-digit % number in the file name. % If ITER=NaN, all iterations will be read. % If ITER=Inf, the last (highest) iteration will be read. % % eg. To repeat above operation % >> A=rdmds('T',2880); % eg. To read multiple time steps % >> A=rdmds('T',[0 1440 2880]); % eg. To read all time steps % >> [A,ITS]=rdmds('T',NaN); % eg. To read the last time step % >> [A,IT]=rdmds('T',Inf); % Note: this form can not read files with no iteration count in file name. % % % A = RDMDS(FNAME,[...],'rec',RECNUM) reads individual records from % multiple record files. % % eg. To read a single record from a multi-record file % >> [A,IT]=rdmds('pickup.ckptA',11); % eg. To read several records from a multi-record file % >> [A,IT]=rdmds('pickup',Inf,'rec',[1:5 8 12]); % % % A = RDMDS(FNAME,ITER,MACHINEFORMAT) allows the machine format to be % A = RDMDS(FNAME,MACHINEFORMAT) % specified which MACHINEFORMAT is on of the following strings: % 'n' 'l' 'b' 'd' 'g' 'c' 'a' 's' - see FOPEN for more details % % $Header: /u/gcmpack/MITgcm_contrib/gael/matlab_class/gcmfaces_IO/rdmds.m,v 1.1 2010/02/10 14:46:49 gforget Exp $ % $Name: $ AA=[]; itrs=[]; MM=[]; % Default options ieee='b'; fname=fnamearg; userecords=0; recnum=[]; % Check optional arguments for ind=1:size(varargin,2); arg=varargin{ind}; if ischar(arg) if strcmp(arg,'n') | strcmp(arg,'native') ieee='n'; elseif strcmp(arg,'l') | strcmp(arg,'ieee-le') ieee='l'; elseif strcmp(arg,'b') | strcmp(arg,'ieee-be') ieee='b'; elseif strcmp(arg,'c') | strcmp(arg,'cray') ieee='c'; elseif strcmp(arg,'a') | strcmp(arg,'ieee-le.l64') ieee='a'; elseif strcmp(arg,'s') | strcmp(arg,'ieee-be.l64') ieee='s'; elseif strcmp(arg,'rec') userecords=1; else error(['Optional argument ' arg ' is unknown']) end else if userecords==1 recnum=arg; elseif isempty(itrs) if isnan(arg) itrs=scanforfiles(fname); disp([ sprintf('Reading %i time levels:',size(itrs,2)) sprintf(' %i',itrs) ]); elseif isinf(arg) itrs=scanforfiles(fname); if isempty(itrs) AA=[];itrs=[];return; end disp([ sprintf('Found %i time levels, reading %i',size(itrs,2),itrs(end)) ]); itrs=itrs(end); % elseif prod(double(arg>=0)) & prod(double(round(arg)==arg)) % elseif prod(arg>=0) & prod(round(arg)==arg) elseif min(arg)>=0 & isempty(find(round(arg)~=arg)) if arg>=9999999999 error(sprintf('Argument %i > 9999999999',arg)) end itrs=arg; else error(sprintf('Argument %i must be a positive integer',arg)) end else error('Multiple iterations should be specified as a vector') end end end if isempty(itrs) itrs=-1; end % Loop over each iteration for iter=1:size(itrs,2); if itrs(iter)>=0 fname=sprintf('%s.%10.10i',fnamearg,itrs(iter)); end % Figure out if there is a path in the filename NS=findstr('/',fname); if size(NS)>0 Dir=fname(1:NS(end)); else Dir='./'; end % Match name of all meta-files allfiles=dir( sprintf('%s*.meta',fname) ); if size(allfiles,1)==0 disp(sprintf('No files match the search: %s*.meta',fname)); %allow partial reads% error('No files found.') end % Loop through allfiles for j=1:size(allfiles,1); % Read meta- and data-file [A,N,M,mG] = localrdmds([Dir allfiles(j).name],ieee,recnum); %- Merge local Meta file content (M) to MM string: if j > 0, %- to comment out this block: "if j < 0" (since j is always > 0) ii=findstr(M,' timeStepNumber'); if isempty(ii), ii1=0; ii2=0; else ii1=ii; ii2=ii+min(findstr(M(1+ii:end),'];')); end ii=findstr(M,' timeInterval'); if isempty(ii), jj1=0; jj2=0; else jj1=ii; jj2=ii+min(findstr(M(1+ii:end),'];')); end if iter==1 & j==1, MM=M; ind1=0; ind2=0; is1=ii1; js1=jj1; M3=''; if ii1*jj1 > 0, %ind1=min(ii1,jj1); ind2=max(ii2,jj2); %if ii1 < jj1, ii3=ii2+1; jj3=jj1-1; %else ii3=jj2+1; jj3=ii1-1; end order=sort([ii1 ii2 jj1 jj2]); ind1=order(1); ii3=order(2)+1; jj3=order(3)-1; ind2=order(4); M2=M(ii1:ii2); M4=M(jj1:jj2); M3=M(ii3:jj3); elseif ii1 > 0, ind1=ii1; ind2=ii2; M2=M(ii1:ii2); M4=''; elseif jj1 > 0, ind1=jj1; ind2=jj2; M4=M(jj1:jj2); M2=''; end M5=M(1+ind2:end); %fprintf(' ii1,ii2 = %i %i ; jj1,jj2= %i %i ;', ii1,ii2, jj1,jj2); %fprintf(' ii3,jj3= %i %i ; ind1,ind2= %i %i\n',ii3,jj3,ind1,ind2); %fprintf('M(1:ind1)=%s<\n',M(1:ind1)); %fprintf(' M2=%s<\n',M2); %fprintf(' M3=%s<\n',M3); %fprintf(' M4=%s<\n',M4); %fprintf(' M5=%s<\n',M5); else if ii1*jj1 > 0, order=sort([ii1 ii2 jj1 jj2]); ind=order(1); ii3=order(2)+1; jj3=order(3)-1; ind2=order(4); else ind=max(ii1,jj1); ind2=ii2+jj2; end compar=(ind == ind1); ii=0; if compar & ind1 == 0, ii=1; compar=strcmp (MM,M); end if compar & ind1 > 0, ii=2; compar=strncmp(MM,M,ind1) ; end if compar & ind1 > 0, ii=3; compar=strcmp(M5,M(1+ind2:end)); end if compar & ii1*jj1 > 0, ii=4; compar=strcmp(M3,M(ii3:jj3)); end if ~compar, fprintf('WARNING: Meta file (%s) is different (%i) from 1rst one:\n', ... allfiles(j).name,ii); fprintf(' it=%i :MM:%s\n',itrs(1),MM); fprintf(' it=%i :M :%s\n\n',itrs(iter),M); elseif ind1 > 0, if ii1 > 0, Mj=M(ii1:ii2); ii=findstr(Mj,'['); Mj=Mj(1+ii:end); % add it-number from Mj to M2 (if different): if isempty(findstr(M2,Mj)), M2=[deblank(M2(1:end-1)),Mj]; end end if jj1 > 0, Mj=M(jj1:jj2); ii=findstr(Mj,'['); Mj=Mj(1+ii:end); % add time interval from Mj to M4 (if different): if isempty(findstr(M4,Mj)), M4=[deblank(M4(1:end-1)),' ;',Mj]; end end end end % save modifications: if ind1>0 & j==size(allfiles,1) & iter==size(itrs,2), if ii1 < jj1, MM=[MM(1:ind1-1),M2,M3,M4,M5]; else MM=[MM(1:ind1-1),M4,M3,M2,M5]; end end end %- put local data file content in global array AA: bdims=N(1,:); r0=N(2,:); rN=N(3,:); ndims=prod(size(bdims)); if j==1 & iter==1, AA=zeros([bdims size(itrs,2)]); end if mG(1)==0 & mG(2)==1, if (ndims == 1) AA(r0(1):rN(1),iter)=A; elseif (ndims == 2) AA(r0(1):rN(1),r0(2):rN(2),iter)=A; elseif (ndims == 3) AA(r0(1):rN(1),r0(2):rN(2),r0(3):rN(3),iter)=A; elseif (ndims == 4) AA(r0(1):rN(1),r0(2):rN(2),r0(3):rN(3),r0(4):rN(4),iter)=A; elseif (ndims == 5) AA(r0(1):rN(1),r0(2):rN(2),r0(3):rN(3),r0(4):rN(4),r0(5):rN(5),iter)=A; else error('Dimension of data set is larger than currently coded. Sorry!') end elseif (ndims == 1) AA(r0(1):rN(1),iter)=A; else %- to debug: do simple stransfert (with a loop on 2nd index); % will need to change this later, to improve efficiency: for i=0:rN(2)-r0(2), if (ndims == 2) AA(r0(1)+i*mG(1):rN(1)+i*mG(1),r0(2)+i*mG(2),iter)=A(:,1+i); elseif (ndims == 3) AA(r0(1)+i*mG(1):rN(1)+i*mG(1),r0(2)+i*mG(2), ... r0(3):rN(3),iter)=A(:,1+i,:); elseif (ndims == 4) AA(r0(1)+i*mG(1):rN(1)+i*mG(1),r0(2)+i*mG(2), ... r0(3):rN(3),r0(4):rN(4),iter)=A(:,1+i,:,:); elseif (ndims == 5) AA(r0(1)+i*mG(1):rN(1)+i*mG(1),r0(2)+i*mG(2), ... r0(3):rN(3),r0(4):rN(4),r0(5):rN(5),iter)=A(:,1+i,:,:,:); else error('Dimension of data set is larger than currently coded. Sorry!') end end end end % files end % iterations %------------------------------------------------------------------------------- function [A,N,M,map2glob] = localrdmds(fname,ieee,recnum) mname=strrep(fname,' ',''); dname=strrep(mname,'.meta','.data'); %- set default mapping from tile to global file: map2glob=[0 1]; % Read and interpret Meta file fid = fopen(mname,'r'); if (fid == -1) error(['File' mname ' could not be opened']) end % Scan each line of the Meta file allstr=' '; keepgoing = 1; while keepgoing > 0, line = fgetl(fid); if (line == -1) keepgoing=-1; else % Strip out "(PID.TID *.*)" by finding first ")" %old ind=findstr([line ')'],')'); line=line(ind(1)+1:end); ind=findstr(line,')'); if size(ind) ~= 0 line=line(ind(1)+1:end); end % Remove comments of form // line=[line,' //']; ind=findstr(line,'//'); line=line(1:ind(1)-1); % Add to total string (without starting & ending blanks) while line(1:1) == ' ', line=line(2:end); end if strncmp(line,'map2glob',8), eval(line); else allstr=[allstr,deblank(line),' ']; end end end % Close meta file fclose(fid); % Strip out comments of form /* ... */ ind1=findstr(allstr,'/*'); ind2=findstr(allstr,'*/'); if size(ind1) ~= size(ind2) error('The /* ... */ comments are not properly paired') end while size(ind1,2) > 0 allstr=[deblank(allstr(1:ind1(1)-1)) allstr(ind2(1)+2:end)]; %allstr=[allstr(1:ind1(1)-1) allstr(ind2(1)+3:end)]; ind1=findstr(allstr,'/*'); ind2=findstr(allstr,'*/'); end % This is a kludge to catch whether the meta-file is of the % old or new type. nrecords does not exist in the old type. nrecords = NaN; %- store the full string for output: M=strrep(allstr,'format','dataprec'); % Everything in lower case allstr=lower(allstr); % Fix the unfortunate choice of 'format' allstr=strrep(allstr,'format','dataprec'); % Evaluate meta information eval(allstr); N=reshape( dimlist , 3 , prod(size(dimlist))/3 ); rep=[' dimList = [ ',sprintf('%i ',N(1,:)),']']; if ~isnan(nrecords) & nrecords > 1 & isempty(recnum) N=[N,[nrecords 1 nrecords]']; elseif ~isempty(recnum) & recnum>nrecords error('Requested record number is higher than the number of available records') end %- make "dimList" shorter (& fit output array size) in output "M": pat=' dimList = \[(\s*\d+\,?)*\s*\]'; M=regexprep(M,pat,rep); % and remove double space within sq.brakets: ind1=findstr(M,'['); ind2=findstr(M,']'); if length(ind1) == length(ind2), for i=length(ind1):-1:1, if ind1(i) < ind2(i), M=[M(1:ind1(i)),regexprep(M(ind1(i)+1:ind2(i)-1),'(\s+)',' '),M(ind2(i):end)]; end; end else error('The [ ... ] brakets are not properly paired') end if isempty(recnum) recnum=1; end if isnan(nrecords) % This is the old 'meta' method that used sequential access A=allstr; % Open data file fid=fopen(dname,'r',ieee); % Read record size in bytes recsz=fread(fid,1,'uint32'); ldims=N(3,:)-N(2,:)+1; numels=prod(ldims); rat=recsz/numels; if rat == 4 A=fread(fid,numels,'real*4'); elseif rat == 8 A=fread(fid,numels,'real*8'); else sprintf(' Implied size in meta-file = %d', numels ) sprintf(' Record size in data-file = %d', recsz ) error('Ratio between record size and size in meta-file inconsistent') end erecsz=fread(fid,1,'uint32'); if erecsz ~= recsz sprintf('WARNING: Record sizes at beginning and end of file are inconsistent') end fclose(fid); A=reshape(A,ldims); else % This is the new MDS format that uses direct access ldims=N(3,:)-N(2,:)+1; for r=1:size(recnum(:),1); if dataprec == 'float32' A(:,r)=myrdda(dname,ldims,recnum(r),'real*4',ieee); elseif dataprec == 'float64' A(:,r)=myrdda(dname,ldims,recnum(r),'real*8',ieee); else error(['Unrecognized format in meta-file = ' format]); end end A=reshape(A,[ldims size(recnum(:),1)]); if size(recnum(:),1)>1 N(1,end+1)=size(recnum(:),1); N(2,end)=1; N(3,end)=size(recnum(:),1); end end %------------------------------------------------------------------------------- % result = RDDA( file, dim, irec [options] ) % % This routine reads the irec'th record of shape 'dim' from the % direct-access binary file (float or double precision) 'file'. % % Required arguments: % % file - string - name of file to read from % dim - vector - dimensions of the file records and the resulting array % irec - integer - record number in file in which to write data % % Optional arguments (must appear after the required arguments): % prec - string - precision of storage in file. Default = 'real*8'. % ieee - string - IEEE bit-wise representation in file. Default = 'b'. % % 'prec' may take the values: % 'real*4' - floating point, 32 bits. % 'real*8' - floating point, 64 bits - the efault. % % 'ieee' may take values: % 'ieee-be' or 'b' - IEEE floating point with big-endian % byte ordering - the default % 'ieee-le' or 'l' - IEEE floating point with little-endian % byte ordering % 'native' or 'n' - local machine format % 'cray' or 'c' - Cray floating point with big-endian % byte ordering % 'ieee-le.l64' or 'a' - IEEE floating point with little-endian % byte ordering and 64 bit long data type % 'ieee-be.l64' or 's' - IEEE floating point with big-endian byte % ordering and 64 bit long data type. % % eg. T=rdda('t.data',[64 64 32],1); % T=rdda('t.data',[256],4,'real*4'); % T=rdda('t.data',[128 64],2,'real*4','b'); function [arr] = myrdda(file,N,k,varargin) % Defaults WORDLENGTH=8; rtype='real*8'; ieee='b'; % Check optional arguments args=char(varargin); while (size(args,1) > 0) if deblank(args(1,:)) == 'real*4' WORDLENGTH=4; rtype='real*4'; elseif deblank(args(1,:)) == 'real*8' WORDLENGTH=8; rtype='real*8'; elseif deblank(args(1,:)) == 'n' | deblank(args(1,:)) == 'native' ieee='n'; elseif deblank(args(1,:)) == 'l' | deblank(args(1,:)) == 'ieee-le' ieee='l'; elseif deblank(args(1,:)) == 'b' | deblank(args(1,:)) == 'ieee-be' ieee='b'; elseif deblank(args(1,:)) == 'c' | deblank(args(1,:)) == 'cray' ieee='c'; elseif deblank(args(1,:)) == 'a' | deblank(args(1,:)) == 'ieee-le.l64' ieee='a'; elseif deblank(args(1,:)) == 's' | deblank(args(1,:)) == 'ieee-be.l64' ieee='s'; else error(['Optional argument ' args(1,:) ' is unknown']) end args=args(2:end,:); end nnn=prod(N); [fid mess]=fopen(file,'r',ieee); if fid == -1 error('Error while opening file:\n%s',mess) end st=fseek(fid,nnn*(k-1)*WORDLENGTH,'bof'); if st ~= 0 mess=ferror(fid); error('There was an error while positioning the file pointer:\n%s',mess) end [arr count]=fread(fid,nnn,rtype); if count ~= nnn error('Not enough data was available to be read: off EOF?') end st=fclose(fid); %arr=reshape(arr,N); % function [itrs] = scanforfiles(fname) itrs=[]; allfiles=dir([fname '.*.001.001.meta']); if isempty(allfiles) allfiles=dir([fname '.*.meta']); ioff=0; else ioff=8; end for k=1:size(allfiles,1); hh=allfiles(k).name; itrs(k)=str2num( hh(end-14-ioff:end-5-ioff) ); end itrs=sort(itrs); gcmfaces/gcmfaces_IO/grid_load_native.m0000644000435400001440000001055212160353224020015 0ustar gforgetusersfunction []=grid_load_native(dirGrid,nFaces,doWarn); %object: load NATIVE FORMAT grid information, convert it to gcmfaces format % and encapsulate it in the global mygrid structure. %inputs: dirGrid is the directory where the grid files (gcm output) can be found. % nFaces is the number of faces in this gcm set-up of current interest. % %note: - originally from /net/ross/raid2/gforget/mygrids/gael_code_v2/faces2mitgcm/mitgcmmygrid_read.m % - the hardcoded useChrisFormat allows to recover Chris' format used by the grid generation routines % %examples of dirGrid: %dirGrid='/net/weddell/raid3/gforget/mygrids/mygridCompleted/cube_FM/cube_96/'; %dirGrid='/net/weddell/raid3/gforget/mygrids/mygridCompleted/llcRegLatLon/llc_96/'; %dirGrid='/net/weddell/raid3/gforget/mygrids/mygridCompleted/llpcRegLatLon/llpc_96/'; %dirGrid='/net/weddell/raid3/gforget/mygrids/mygridCompleted/llcMoreTrop/eccollc_96/'; %dirGrid='/net/weddell/raid3/gforget/mygrids/mygridCompleted/llcRegLatLon/llc_540/'; %dirGrid='/net/weddell/raid3/gforget/mygrids/mygridCompleted/cube_FM/cube_32/'; %dirGrid='/net/weddell/raid3/gforget/mygrids/mygridCompleted/cs32_tutorial_held_suarez_cs/'; useChrisFormat=1; if useChrisFormat==1; global MM Nfaces; global dyG dxG dxF dyF dxC dyC dyU dxV rA rAw rAs rAz xC yC xG yG xS yS xW yW; end; if isempty(whos('doWarn')); doWarn=1; end; global mygrid; mygrid.dirGrid=dirGrid; mygrid.nFaces=nFaces; mygrid.fileFormat='native'; %search for native grid files files=dir([dirGrid '*bin']); while length(files)~=nFaces; fprintf('dirGrid does not contain the expected number of ''*.bin'' grid files\n'); nm=input('please specify file name pattern for the native grid such as ''llc*.bin''\n'); files=dir([dirGrid nm]); end; %discard intermediate step grid files: tmp1=[]; for ii=1:length(files); if isempty(strfind(files(ii).name,'FM')); tmp1=[tmp1;ii]; end; end; files=files(tmp1); %list fields of interest and their sizes list_fields2={'XC','YC','DXF','DYF','RAC','XG','YG','DXV','DYU','RAZ',... 'DXC','DYC','RAW','RAS','DXG','DYG'}; list_fields={'xC','yC','dxF','dyF','rA','xG','yG','dxV','dyU','rAz',... 'dxC','dyC','rAw','rAs','dxG','dyG'}; list_x={'xC','xC','xC','xC','xC','xG','xG','xG','xG','xG',... 'xW','xS','xW','xS','xS','xW'}; list_y={'yC','yC','yC','yC','yC','yG','yG','yG','yG','yG',... 'yW','yS','yW','yS','yS','yW'}; list_ni={'ni','ni','ni','ni','ni','ni+1','ni+1','ni+1','ni+1','ni+1',... 'ni+1','ni','ni+1','ni','ni','ni+1'}; list_nj={'nj','nj','nj','nj','nj','nj+1','nj+1','nj+1','nj+1','nj+1',... 'nj','nj+1','nj','nj+1','nj+1','nj'}; if nFaces~=length(files); error('wrong specification of nFaces'); else; Nfaces=length(files); end; for iFile=1:Nfaces; tmp1=files(iFile).name; %we need to know the face dimensions if ~isempty(strfind(dirGrid,'cs32_tutorial_held_suarez_cs'))|... ~isempty(strfind(dirGrid,'GRIDcube'));%cs32 ni=32; nj=32; else;%get the face dimensions form the file name tmp2=strfind(tmp1,'_'); ni=str2num(tmp1(tmp2(2)+1:tmp2(3)-1)); nj=str2num(tmp1(tmp2(3)+1:end-4)); end; if iFile==1; MM=ni; end; fid=fopen([dirGrid files(iFile).name],'r','b'); for iFld=1:length(list_fields); eval(['nni=' list_ni{iFld} ';']); eval(['nnj=' list_nj{iFld} ';']); tmp1=fread(fid,[ni+1 nj+1],'float64'); if useChrisFormat; eval([list_fields{iFld} '{' num2str(iFile) '}.vals=tmp1(1:nni,1:nnj);']); eval([list_fields{iFld} '{' num2str(iFile) '}.x=''' list_x{iFld} ''';']); end; if iFile==1; eval(['mygrid.' list_fields2{iFld} '=gcmfaces;']); end; eval(['mygrid.' list_fields2{iFld} '{iFile}=tmp1(1:ni,1:nj);']); end; fclose(fid); if useChrisFormat; xS{iFile}.vals=(xG{iFile}.vals(2:end,:)+xG{iFile}.vals(1:end-1,:))/2; yS{iFile}.vals=(yG{iFile}.vals(2:end,:)+yG{iFile}.vals(1:end-1,:))/2; xW{iFile}.vals=(xG{iFile}.vals(:,2:end)+xG{iFile}.vals(:,1:end-1))/2; yW{iFile}.vals=(yG{iFile}.vals(:,2:end)+yG{iFile}.vals(:,1:end-1))/2; end; end; if doWarn; list0={'hFacC','hFacS','hFacW','Depth','AngleCS','AngleSN'}; for ff=1:length(list0); warning(['native file miss ' list0{ff}]); end; fprintf('\n\n which will severely limit diagnostic computations.\n'); fprintf(' So you may want to get a full grid from an MITgcm run.\n'); end; gcmfaces/gcmfaces_IO/convert2widefaces.m0000644000435400001440000000333412160353224020140 0ustar gforgetusersfunction [v0]=convert2widefaces(v0); %object: when mygrid.facesSize is non standard (i.e. % some faces were troncated in the files) this % routine expands them back to dimensions that % allow e.g. the exchanges to work gcmfaces_global; if ~isempty(mygrid.facesExpand); nn=mygrid.facesExpand(1); mm=mygrid.facesExpand(2); widefacesSize=[[nn mm];[nn mm];[nn nn];[mm nn];[mm nn]]; v0facesSize=[size(v0{1});size(v0{2});size(v0{3});size(v0{4});size(v0{5})]; v0facesSize=v0facesSize(:,1:2); test0=02; prec=varargin{1}; else; prec=32; end; if ~ischar(fldIn); fid=fopen(fileOut,'w','b'); tmp1=fldIn; tmp1(isnan(tmp1))=0; fwrite(fid,tmp1,['float' num2str(prec)]); fclose(fid); else; fid=fopen(fileOut,'wt'); fwrite(fid,fldIn); fclose(fid); end; gcmfaces/gcmfaces_IO/process2nctiles.m0000644000435400001440000002214712367511146017660 0ustar gforgetusersfunction []=process2nctiles(dirModel,fileModel,fldModel,tileSize); %process2nctiles(dirModel); %object : convert MITgcm binary output to netcdf files (tiled) %inputs : dirModel is the MITgcm run directory % It is expected to contain binaries in % 'diags/STATE/', 'diags/TRSP/', etc. as well % as the 'available_diagnostics.log' text file. % fileModel the file name base e.g. 'state_2d_set1' % By default : all variables in e.g. 'state_2d_set1*' % files will be processed, and writen individually to % nctiles (tiled netcdf) that will be located in 'nctiles/' % fldModel (by default []) can be specified (as e.g. 'ETAN') % when fldModel is empty, all fields are processed % tileSize (optional) is e.g. [90 90] (by default tiles=faces) %output : (netcdf files) gcmfaces_global; %listFiles={'state_2d_set1','state_2d_set2','state_3d_set1','state_3d_set2'}; %listFiles={'trsp_3d_set1','trsp_3d_set2','trsp_3d_set3'}; %for ff=1:length(listFiles); process2nctiles('iter12/',listFiles{ff},[],[90 90]); end; %replace time series with monthly climatology? doClim=0; %directory names listDirs={'STATE/','TRSP/'}; filAvailDiag=[dirModel 'available_diagnostics.log']; filReadme=[dirModel 'README']; dirOut=[dirModel 'nctiles_tmp/']; if ~isdir(dirOut); mkdir(dirOut); end; %search in subdirectories subDir=[]; for ff=1:length(listDirs); tmp1=dir([dirModel 'diags/' listDirs{ff} fileModel '*']); if ~isempty(tmp1); subDir=listDirs{ff}; end; end; if isempty(subDir); error(['file ' fileModel ' was not found']); else; dirIn=[dirModel 'diags/' subDir]; nn=length(dir([dirIn fileModel '*data'])); fprintf('%s (%d files) was found in \n %s \n',fileModel,nn,dirIn); end; %set list of variables to process if ~isempty(fldModel); if ischar(fldModel); listFlds={fldModel}; else; listFlds=fldModel; end; else; meta=read_meta([dirIn fileModel '*']); listFlds=meta.fldList; end; %determine map of tile indices (by default tiles=faces) if isempty(whos('tileSize')); tileNo=mygrid.XC; for ff=1:mygrid.nFaces; tileNo{ff}(:)=ff; end; else; tileNo=gcmfaces_loc_tile(tileSize(1),tileSize(2)); end; %now do the actual processing for vv=1:length(listFlds); nameDiag=deblank(listFlds{vv}) %get meta information meta=read_meta([dirIn fileModel '*']); irec=find(strcmp(deblank(meta.fldList),nameDiag)); if length(irec)~=1; error('field not in file\n'); end; %read time series myDiag=rdmds2gcmfaces([dirIn fileModel '*'],NaN,'rec',irec); %replace time series with monthly climatology if doClim; myDiag=compClim(myDiag); end; %set ancilliary time variable nn=length(size(myDiag{1})); nn=size(myDiag{1},nn); %tim=[1:nn]; tim=[1992*ones(nn,1) [1:nn]' 15*ones(nn,1)]; tim=datenum(tim)-datenum([1992 1 0]); timUnits='days since 1992-1-1 0:0:0'; %get time step axis [listTimes]=diags_list_times({[dirModel 'diags/STATE/']},{'state_2d_set1'}); %get units and long name from available_diagnostics.log [avail_diag]=read_avail_diag(filAvailDiag,nameDiag); %get description of estimate from README [rdm]=read_readme(filReadme); disp(rdm'); %convert to MITgcm format (90x1170 array) myFile=[dirOut nameDiag];%first instance is for subdirectory name if ~isdir(myFile); mkdir(myFile); end; myFile=[myFile '/' nameDiag];%second instance is for file name base %get grid params [grid_diag]=set_grid_diag(avail_diag); %apply mask, and convert to land mask msk=grid_diag.msk; if length(size(myDiag{1}))==3; msk=repmat(msk,[1 1 size(myDiag{1},3)]); end; for kk=1:size(myDiag{1},4); myDiag(:,:,:,kk)=myDiag(:,:,:,kk).*msk; end; clear msk; % land=isnan(grid_diag.msk); %set 'coord' attribute if avail_diag.nr~=1; coord='lon lat dep tim'; else; coord='lon lat tim'; end; %replace time series with monthly climatology if doClim; listTimes=listTimes(1:12); timUnits='days since year-1-1 0:0:0'; avail_diag.longNameDiag=[avail_diag.longNameDiag ' (climatology) ']; end; %create netcdf file using write2nctiles (works only with old matlab, thus far ...) doCreate=1; dimlist=write2nctiles(myFile,myDiag,doCreate,{'tileNo',tileNo},... {'fldName',nameDiag},{'longName',avail_diag.longNameDiag},... {'units',avail_diag.units},{'descr',nameDiag},{'coord',coord},{'rdm',rdm}); %determine relevant dimensions for ff=1:length(dimlist); dim.tim{ff}={dimlist{ff}{1}}; dim.twoD{ff}={dimlist{ff}{end-1:end}}; if avail_diag.nr~=1; dim.threeD{ff}={dimlist{ff}{end-2:end}}; dim.dep{ff}={dimlist{ff}{end-2}}; else; dim.threeD{ff}=dim.twoD{ff}; dim.dep{ff}=[]; end; end; %prepare to add fields doCreate=0; %now add fields write2nctiles(myFile,tim,doCreate,{'tileNo',tileNo},... {'fldName','tim'},{'longName','time'},... {'units',timUnits},{'dimIn',dim.tim}); write2nctiles(myFile,listTimes,doCreate,{'tileNo',tileNo},... {'fldName','step'},{'longName','final time step number'},... {'units','1'},{'dimIn',dim.tim}); write2nctiles(myFile,grid_diag.lon,doCreate,{'tileNo',tileNo},... {'fldName','lon'},{'units','degrees_east'},{'dimIn',dim.twoD}); write2nctiles(myFile,grid_diag.lat,doCreate,{'tileNo',tileNo},... {'fldName','lat'},{'units','degrees_north'},{'dimIn',dim.twoD}); write2nctiles(myFile,grid_diag.msk,doCreate,{'tileNo',tileNo},... {'fldName','land'},{'units','1'},{'longName','land mask'},{'dimIn',dim.threeD}); write2nctiles(myFile,grid_diag.RAC,doCreate,{'tileNo',tileNo},... {'fldName','area'},{'units','m^2'},{'longName','grid cell area'},{'dimIn',dim.twoD}); if isfield(grid_diag,'dep'); write2nctiles(myFile,grid_diag.dep,doCreate,{'tileNo',tileNo},... {'fldName','dep'},{'units','m'},{'dimIn',dim.dep}); write2nctiles(myFile,grid_diag.dz,doCreate,{'tileNo',tileNo},... {'fldName','thic'},{'units','m'},{'dimIn',dim.dep}); end; end;%for vv=1:length(listFlds); function [meta]=read_meta(fileName); %read meta file tmp1=dir([fileName '*.meta']); tmp1=tmp1(1).name; tmp2=strfind(fileName,filesep); if ~isempty(tmp2); tmp2=tmp2(end); else; tmp2=0; end; tmp1=[fileName(1:tmp2) tmp1]; fid=fopen(tmp1); while 1; tline = fgetl(fid); if ~ischar(tline), break, end if isempty(whos('tmp3')); tmp3=tline; else; tmp3=[tmp3 ' ' tline]; end; end fclose(fid); %add meta variables to workspace eval(tmp3); %reformat to meta structure meta.dataprec=dataprec; meta.nDims=nDims; meta.nFlds=nFlds; meta.nrecords=nrecords; meta.fldList=fldList; meta.dimList=dimList; if ~isempty(who('timeInterval')); meta.timeInterval=timeInterval; end; if ~isempty(who('timeStepNumber')); meta.timeStepNumber=timeStepNumber; end; %% function [rdm]=read_readme(filReadme); gcmfaces_global; rdm=[]; fid=fopen(filReadme,'rt'); while ~feof(fid); nn=length(rdm); rdm{nn+1} = fgetl(fid); end; fclose(fid); %% function [avail_diag]=read_avail_diag(filAvailDiag,nameDiag); gcmfaces_global; avail_diag=[]; fid=fopen(filAvailDiag,'rt'); while ~feof(fid); tline = fgetl(fid); tmp1=8-length(nameDiag); tmp1=repmat(' ',[1 tmp1]); tname = ['|' sprintf('%s',nameDiag) tmp1 '|']; if ~isempty(strfind(tline,tname)); %e.g. tline=' 235 |SIatmQnt| 1 | |SM U1|W/m^2 |Net atmospheric heat flux, >0 decreases theta'; % tmp1=strfind(tline,'|'); tmp1=tmp1(end-1:end); avail_diag.units=strtrim(tline(tmp1(1)+1:tmp1(2)-1)); avail_diag.longNameDiag=tline(tmp1(2)+1:end); % tmp1=strfind(tline,'|'); tmp1=tmp1(4:5); pars=tline(tmp1(1)+1:tmp1(2)-1); % if strcmp(pars(2),'M'); avail_diag.loc_h='C'; elseif strcmp(pars(2),'U'); avail_diag.loc_h='W'; elseif strcmp(pars(2),'V'); avail_diag.loc_h='S'; end; % avail_diag.loc_z=pars(9); % if strcmp(pars(10),'1'); avail_diag.nr=1; else; avail_diag.nr=length(mygrid.RC); end; end; end; fclose(fid); %% function [grid_diag]=set_grid_diag(avail_diag); gcmfaces_global; %switch for non-tracer point values if strcmp(avail_diag.loc_h,'C'); grid_diag.lon=mygrid.XC; grid_diag.lat=mygrid.YC; grid_diag.msk=mygrid.mskC(:,:,1:avail_diag.nr); elseif strcmp(avail_diag.loc_h,'W'); grid_diag.lon=mygrid.XG; grid_diag.lat=mygrid.YC; grid_diag.msk=mygrid.mskW(:,:,1:avail_diag.nr); elseif strcmp(avail_diag.loc_h,'S'); grid_diag.lon=mygrid.XC; grid_diag.lat=mygrid.YG; grid_diag.msk=mygrid.mskS(:,:,1:avail_diag.nr); end; grid_diag.RAC=mygrid.RAC; %vertical grid if avail_diag.nr~=1; if strcmp(avail_diag.loc_z,'M'); grid_diag.dep=-mygrid.RC; grid_diag.dz=mygrid.DRF; elseif strcmp(avail_diag.loc_z,'L'); grid_diag.dep=-mygrid.RF(2:end); grid_diag.dz=[mygrid.DRC(2:end) ; 228.25];%quick fix else; error('unknown vertical grid'); end; grid_diag.dep=reshape(grid_diag.dep,[1 1 avail_diag.nr]); grid_diag.dz=reshape(grid_diag.dz,[1 1 avail_diag.nr]); end; %%replace time series with monthly climatology function [FLD]=compClim(fld); gcmfaces_global; ndim=length(size(fld{1})); nyear=size(fld{1},ndim)/12; if ndim==3; FLD=NaN*fld(:,:,1:12); end; if ndim==4; FLD=NaN*fld(:,:,:,1:12); end; for mm=1:12; if ndim==3; FLD(:,:,mm)=mean(fld(:,:,mm:12:12*nyear),ndim); end; if ndim==4; FLD(:,:,:,mm)=mean(fld(:,:,:,mm:12:12*nyear),ndim); end; end; gcmfaces/gcmfaces_maps/0000755000435400001440000000000012375431055015002 5ustar gforgetusersgcmfaces/gcmfaces_maps/m_map_gcmfaces_uv.m0000644000435400001440000000525411367366406020630 0ustar gforgetusersfunction []=m_map_gcmfaces_uv(fldU,fldV,varargin); global mygrid; if nargin>2; choicePlot=varargin{1}; else; choicePlot=0; end; if nargin>3; scaleFac=varargin{2}; else; scaleFac=[]; end; if nargin>4; subFac=varargin{3}; else; subFac=1;; end; [fldUe,fldVn]=calc_UEVNfromUXVY(fldU,fldV); if choicePlot==-1; %%m_proj('Miller Cylindrical','lat',[-90 90]); %%m_proj('Equidistant cylindrical','lat',[-90 90]); m_proj('mollweide','lon',[-180 180],'lat',[-89 89]); %m_proj('mollweide','lon',[-100 20],'lat',[0 70]); [uu,vv]=m_map_gcmfaces_uvrotate(fldUe,fldVn); [xx,yy,u]=convert2pcol(mygrid.XC,mygrid.YC,uu); [xx,yy,v]=convert2pcol(mygrid.XC,mygrid.YC,vv); [x,y]=m_ll2xy(xx,yy); %ger rid of nans and subsample: ii=find(~isnan(u.*v)); ii=ii(1:subFac:end); x=x(ii); y=y(ii); u=u(ii); v=v(ii); m_coast('patch',[1 1 1]*.7,'edgecolor','none'); m_grid; hold on; if isempty(scaleFac); quiver(x,y,u,v); else; quiver(x,y,u,v,scaleFac); end; end;%if choicePlot==0|choicePlot==1; if choicePlot==0; subplot(2,1,1); end; if choicePlot==0|choicePlot==1; m_proj('Mercator','lat',[-70 70]); [uu,vv]=m_map_gcmfaces_uvrotate(fldUe,fldVn); [xx,yy,u]=convert2pcol(mygrid.XC,mygrid.YC,uu); [xx,yy,v]=convert2pcol(mygrid.XC,mygrid.YC,vv); [x,y]=m_ll2xy(xx,yy); %ger rid of nans and subsample: ii=find(~isnan(u.*v)); ii=ii(1:subFac:end); x=x(ii); y=y(ii); u=u(ii); v=v(ii); m_coast('patch',[1 1 1]*.7,'edgecolor','none'); m_grid; hold on; if isempty(scaleFac); quiver(x,y,u,v); else; quiver(x,y,u,v,scaleFac); end; end;%if choicePlot==0|choicePlot==1; if choicePlot==0; subplot(2,2,3); end; if choicePlot==0|choicePlot==2; m_proj('Stereographic','lon',0,'lat',90,'rad',40); [uu,vv]=m_map_gcmfaces_uvrotate(fldUe,fldVn); xx=convert2arctic(mygrid.XC,0); yy=convert2arctic(mygrid.YC,0); u=convert2arctic(uu); v=convert2arctic(vv); [x,y]=m_ll2xy(xx,yy); %ger rid of nans and subsample: ii=find(~isnan(u.*v)); ii=ii(1:subFac:end); x=x(ii); y=y(ii); u=u(ii); v=v(ii); m_coast('patch',[1 1 1]*.7,'edgecolor','none'); m_grid; hold on; if isempty(scaleFac); quiver(x,y,u,v); else; quiver(x,y,u,v,scaleFac); end; end;%if choicePlot==0|choicePlot==1; if choicePlot==0; subplot(2,2,4); end; if choicePlot==0|choicePlot==3; m_proj('Stereographic','lon',0,'lat',-90,'rad',40); [uu,vv]=m_map_gcmfaces_uvrotate(fldUe,fldVn); xx=convert2southern(mygrid.XC,0); yy=convert2southern(mygrid.YC,0); u=convert2southern(uu); v=convert2southern(vv); [x,y]=m_ll2xy(xx,yy); %ger rid of nans and subsample: ii=find(~isnan(u.*v)); ii=ii(1:subFac:end); x=x(ii); y=y(ii); u=u(ii); v=v(ii); m_coast('patch',[1 1 1]*.7,'edgecolor','none'); m_grid; hold on; if isempty(scaleFac); quiver(x,y,u,v); else; quiver(x,y,u,v,scaleFac); end; end;%if choicePlot==0|choicePlot==1; gcmfaces/gcmfaces_maps/m_map_gcmfaces_uvrotate.m0000644000435400001440000000142411712072767022040 0ustar gforgetusersfunction [fldUm,fldVm]=m_map_gcmfaces_uvrotate(fldUe,fldVn); %check that m_map is in the path aa=which('m_proj'); if isempty(aa); error('this function requires m_map that is missing'); end; global mygrid; x=mygrid.XC; y=mygrid.YC; u=fldUe; v=fldVn; x(find(x>180))=x(find(x>180))-360; %compute direction: % eps=1e-3; %this value only works for a velocity field in m/s eps=ceil(log10(sqrt(nanmean((u.^2+v.^2))))); eps=10^(-eps-3); %seems to work more generally [xp,yp]=m_ll2xy(x+eps*u,y+eps*v.*cos(y*pi/180),'clip','point'); [x,y]=m_ll2xy(x,y,'clip','point'); complexVec=(xp-x)+i*(yp-y); %scale amplitude complexVec=complexVec./abs(complexVec).*abs(u+i*v); %go back to reals: fldUm=real(complexVec); fldUm(isnan(complexVec))=NaN; fldVm=imag(complexVec); fldVm(isnan(complexVec))=NaN; gcmfaces/gcmfaces_maps/m_map_gcmfaces.m0000644000435400001440000002653612367515746020130 0ustar gforgetusersfunction []=m_map_gcmfaces(fld,varargin); %object: gcmfaces front end to m_map %inputs: fld is the 2D field to be mapped, or a cell (see below). %optional: proj is either the index (integer; 0 by default) of pre-defined % projection(s) or parameters to pass to m_proj (cell) %more so: other optional paramaters can be provided ONLY AFTER proj, % and must take the following form {'name',param1,param2,...} % those that are currently active are % {'myCaxis',myCaxis} is the color axis ('auto' by default) % {'do_m_coast',do_m_coast} adds call to m_coast (1; default) or not (0). % {'myCmap',myCmap} is the colormap name ('jet' by default) % {'doHold',1} indicates to 'hold on' and superimpose e.g. a contour % {'doCbar',1} indicates to include the colorbar (1 by default) % {'doLabl',1} indicates to include the axes labels (1 by default) % {'doFit',1} indicates to exclude white space (0 by default) % {'myShading','flat'} indicates to use flat shading instead of interp % %notes: - for proj==0 (i.e. the default) three panels will be plotted : % a mercator projection over mid-latitude, and two polar % stereographic projections. The other predefined proj are % -1 mollweide or cylindrical projection % 1 mercator projection only % 2 arctic stereographic projection only % 3 antarctic stereographic projection only % 1.1 and 1.2 are atlantic mercator projections % - myTitle is currently not used; it will take the form % {'myTitle',myTitle} is the title (none by default) % - myCaxis can be specified with more than 2 values, in which % case gcmfaces_cb will be used. % - if fld is a 2D field we use pcolor to display it % - if fld is a cell one can specify the plotting tool. % The cell must then have the form {plotType,FLD,varargin} % where plotType is e.g. 'pcolor' or 'contour', FLD is % the 2D field to be plotted, and varargin are options % to pass over to the contour command. % - Hence .e.g. fld={'contour',mygrid.Depth,'r'} will draw % red contours, while fld=mygrid.Depth will color shade. %check that m_map is in the path aa=which('m_proj'); if isempty(aa); error('this function requires m_map that is missing'); end; global mygrid; %get optional parameters if nargin>1; proj=varargin{1}; else; proj=0; end; if iscell(proj); error('not yet implemented'); else; choicePlot=proj; end; %determine the type of plot if iscell(fld); myPlot=fld{1}; else; myPlot='pcolor'; fld={'pcolor',fld}; end; %set more optional paramaters to default values myCaxis=[]; myTitle=''; myShading='interp'; myCmap='jet'; do_m_coast=1; doHold=0; doCbar=1; doLabl=1; doFit=0; %set more optional paramaters to user defined values for ii=2:nargin-1; if ~iscell(varargin{ii}); warning('inputCheck:m_map_gcmfaces_1',... ['As of june 2011, m_map_gcmfaces expects \n'... ' its optional parameters as cell arrays. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help m_map_gcmfaces'' for details.']); elseif ~ischar(varargin{ii}{1}); warning('inputCheck:m_map_gcmfaces_2',... ['As of june 2011, m_map_gcmfaces expects \n'... ' its optional parameters cell arrays \n'... ' to start with character string. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help m_map_gcmfaces'' for details.']); else; if strcmp(varargin{ii}{1},'myCaxis')|... strcmp(varargin{ii}{1},'myCmap')|... strcmp(varargin{ii}{1},'myShading')|... strcmp(varargin{ii}{1},'myTitle')|... strcmp(varargin{ii}{1},'doHold')|... strcmp(varargin{ii}{1},'doCbar')|... strcmp(varargin{ii}{1},'doLabl')|... strcmp(varargin{ii}{1},'doFit')|... strcmp(varargin{ii}{1},'do_m_coast'); eval([varargin{ii}{1} '=varargin{ii}{2};']); else; warning('inputCheck:m_map_gcmfaces_3',... ['unknown option ''' varargin{ii}{1} ''' was ignored']); end; end; end; %make parameter inferences if length(myCaxis)==0; plotCBAR=0; elseif length(myCaxis)==2; plotCBAR=1; else; plotCBAR=2; end; % if choicePlot==0&~doHold; clf; elseif ~doHold; cla; else; hold on; end; %re-group param: param.plotCBAR=plotCBAR; param.myCmap=myCmap; param.myCaxis=myCaxis; param.do_m_coast=do_m_coast; param.doHold=doHold; param.doCbar=doCbar; param.doLabl=doLabl; param.doFit=doFit; param.myPlot=myPlot; %do the plotting: if (choicePlot~=0&choicePlot~=1&choicePlot~=2&choicePlot~=3); do_my_plot(fld,param,choicePlot,myShading); end;%if choicePlot==0|choicePlot==1; if choicePlot==0; subplot(2,1,1); end; if choicePlot==0|choicePlot==1; if mygrid.nFaces~=5&mygrid.nFaces~=6; do_my_plot(fld,param,1,myShading); else; do_my_plot(fld,param,1.1,myShading); end; end;%if choicePlot==0|choicePlot==1; if choicePlot==0; subplot(2,2,3); end; if choicePlot==0|choicePlot==2; do_my_plot(fld,param,2,myShading); end;%if choicePlot==0|choicePlot==1; if choicePlot==0; subplot(2,2,4); end; if choicePlot==0|choicePlot==3; do_my_plot(fld,param,3,myShading); end;%if choicePlot==0|choicePlot==1; if plotCBAR==2&strcmp(myPlot,'pcolor')&doCbar; cbar=gcmfaces_cmap_cbar(myCaxis,{'myCmap',myCmap}); if choicePlot==0; set(cbar,'Position',[0.92 0.15 0.02 0.75]); elseif choicePlot==-1; set(cbar,'Position',[0.92 0.35 0.02 0.3]); elseif choicePlot==1; set(cbar,'Position',[0.92 0.34 0.02 0.35]); else; set(cbar,'Position',[0.92 0.23 0.02 0.55]); % pos=get(cbar,'Position'); pos(1)=pos(1)-0.1; set(cbar,'Position',pos); end; end; if doFit; if doLabl&~doCbar; set(gca,'LooseInset',[0.05 0.02 0.03 0.03]); else; set(gca,'LooseInset',[0.01 0 0.03 0.03]); end; tmp1=get(gca,'PlotBoxAspectRatio'); set(gcf,'PaperPosition',[0 4 8 8/tmp1(1)]); end; function []=do_my_plot(fld,param,proj,shad); gcmfaces_global; %default m_grid params: xloc='bottom'; xtic=[-180:60:180]; xticlab=1; yloc='left'; ytic=[-60:30:60]; yticlab=1; %choice of projection: if proj==-1; %%m_proj('Miller Cylindrical','lat',[-90 90]); %m_proj('Equidistant cylindrical','lat',[-90 90]); %m_proj('mollweide','lon',[-180 180],'lat',[-80 80]); m_proj('mollweide','lon',[-180 180],'lat',[-88 88]); myConv='pcol'; xticlab=0; yticlab=0; elseif proj==1; m_proj('Mercator','lat',[-70 70]); myConv='pcol'; elseif proj==1.1; m_proj('Mercator','lat',[-70 70],'lon',[0 360]+20); myConv='pcol'; xtic=[-360:60:360]; ytic=[-60:30:60]; elseif proj==1.2; m_proj('Equidistant cylindrical','lat',[-90 90],'lon',[0 360]+20); myConv='pcol'; xtic=[-360:60:360]; ytic=[-90:30:90]; elseif proj==1.3; m_proj('Equidistant cylindrical','lat',[15 30],'lon',[190 210]); myConv='pcol'; xtic=[190:5:220]; ytic=[15:3:30]; elseif proj==2; m_proj('Stereographic','lon',0,'lat',90,'rad',40); myConv='convert2arctic'; yloc='bottom'; ytic=[50:10:90]; elseif proj==2.1; m_proj('Stereographic','lon',0,'lat',90,'rad',60); myConv='convert2arctic'; yloc='bottom'; ytic=[30:10:90]; elseif proj==3; m_proj('Stereographic','lon',0,'lat',-90,'rad',40); myConv='convert2southern'; xloc='top'; ytic=[-90:10:-50]; elseif proj==3.1; m_proj('Stereographic','lon',0,'lat',-90,'rad',60); myConv='convert2southern'; xloc='top'; ytic=[-90:10:-30]; elseif proj==4.1; m_proj('mollweide','lat',[25 75],'lon',[-100 30]); myConv='pcol'; xtic=[-100:20:30]; ytic=[30:10:70]; elseif proj==4.2; m_proj('mollweide','lat',[-30 30],'lon',[-65 20]); myConv='pcol'; xtic=[-60:10:20]; ytic=[-30:10:30]; elseif proj==4.3; m_proj('mollweide','lat',[-75 -25],'lon',[-75 25]); myConv='pcol'; xtic=[-70:20:20]; ytic=[-70:10:-30]; xloc='top'; elseif proj==4.4; m_proj('mollweide','lat',[25 75],'lon',[-240 -110]); myConv='pcol'; xtic=[-240:20:-120]; ytic=[30:10:60]; elseif proj==4.5; m_proj('mollweide','lat',[-30 30],'lon',[-240 -70]); myConv='pcol'; xtic=[-240:20:-70]; ytic=[-30:10:30]; elseif proj==4.6; m_proj('mollweide','lat',[-75 -25],'lon',[-215 -60]); myConv='pcol'; xtic=[-210:20:-70]; ytic=[-70:10:-30]; xloc='top'; elseif proj==4.7; m_proj('mollweide','lat',[-30 30],'lon',[15 155]); myConv='pcol'; xtic=[10:20:160]; ytic=[-30:10:30]; xloc='top'; elseif proj==4.8; m_proj('mollweide','lat',[-75 -25],'lon',[15 155]); myConv='pcol'; xtic=[10:20:160]; ytic=[-70:10:-30]; xloc='top'; else; error('undefined projection'); end; if ~param.doLabl; xticlab=0; yticlab=0;end; %omit labels m_grid_opt=['''XaxisLocation'',xloc,''YaxisLocation'',yloc,''xtick'',xtic,''ytick'',ytic']; if xticlab==0; m_grid_opt=[m_grid_opt ',''xticklabel'',[]']; end; if yticlab==0; m_grid_opt=[m_grid_opt ',''yticklabel'',[]']; end; if strcmp(param.myPlot,'pcolor')|strcmp(param.myPlot,'contour'); x=mygrid.XC; %mask out the XC padded zeros if isfield(mygrid,'xtrct'); pt1=mygrid.xtrct.pt1face; pt2=mygrid.xtrct.pt2face; if pt1~=pt2; for iF=1:6; if iF~=pt1&iF~=pt2; x{iF}(:)=NaN; end; end; end; x(x<0)=x(x<0)+360; end; if strcmp(myConv,'pcol'); [xx,yy,z]=convert2pcol(x,mygrid.YC,fld{2}); else; eval(['xx=' myConv '(x);']); eval(['yy=' myConv '(mygrid.YC);']); eval(['z=' myConv '(fld{2});']); end; [x,y]=m_ll2xy(xx,yy); if strcmp(param.myPlot,'pcolor'); if sum(~isnan(x(:)))>0; pcolor(x,y,z); eval(['shading ' shad ';']); end; if param.plotCBAR==0; colormap(param.myCmap); if param.doCbar; colorbar; end; elseif param.plotCBAR==1; caxis(param.myCaxis); colormap(param.myCmap); if param.doCbar; colorbar; end; else; cbar=gcmfaces_cmap_cbar(param.myCaxis,{'myCmap',param.myCmap}); delete(cbar); end; if param.do_m_coast; m_coast('patch',[1 1 1]*.7,'edgecolor','none'); end; eval(['m_grid(' m_grid_opt ');']); elseif strcmp(param.myPlot,'contour'); if ~param.doHold; if param.do_m_coast; m_coast('patch',[1 1 1]*.7,'edgecolor','none'); end; eval(['m_grid(' m_grid_opt ');']); end; if length(fld)==2; fld{3}='k'; end; hold on; contour(x,y,z,fld{3:end}); end; elseif strcmp(param.myPlot,'plot'); if ~param.doHold; if param.do_m_coast; m_coast('patch',[1 1 1]*.7,'edgecolor','none'); end; eval(['m_grid(' m_grid_opt ');']); end; [x,y]=m_ll2xy(fld{2},fld{3}); hold on; plot(x,y,fld{4:end}); elseif strcmp(param.myPlot,'text'); if ~param.doHold; if param.do_m_coast; m_coast('patch',[1 1 1]*.7,'edgecolor','none'); end; eval(['m_grid(' m_grid_opt ');']); end; [x,y]=m_ll2xy(fld{2},fld{3}); if length(fld)>4; cc=fld{5}; else; cc='k'; end; hold on; hold on; text(x,y,fld{4},'Color',cc,'FontSize',16,'FontWeight','bold'); end; %add tag spec. to map & proj generated with this routine set(gca,'Tag',['gfMap' num2str(proj)]); gcmfaces/gcmfaces_maps/m_map_1face_uv.m0000644000435400001440000000433011367633565020034 0ustar gforgetusersfunction []=m_map_1face_uv(fldU,fldV,iFace,varargin); %purpose: % use m_map to display one face in a chosen projection %syntax: % m_map_1face_uv(fldU,fldV,iFace,choiceProj); %inputs: % fldU/fldV are uvel/vvel 2D fields in gcmfaces format % iFace is the face number % choiceProj is the projection choice (0, 1, 2, or 3) % if it is not stated, the default is mollweide (0) %note: % the use of m_map/m_quiver.m is not advised since it distorts amplitudes % at the end of this routine, it is included only to document its syntax %get grid data; global mygrid; if nargin>3; choicePlot=varargin{1}; else; choicePlot=0; end; if nargin>4; scaleFac=varargin{2}; else; scaleFac=[]; end; if nargin>5; subFac=varargin{3}; else; subFac=1;; end; %check that m_map is in the path aa=which('m_proj'); if isempty(aa); error('this function requires m_map that is missing'); end; %set up projection using tracer function m_map_1face(fldU*NaN,iFace,choicePlot); colorbar off; %compute velocity at center point in east/north direction: [fldUe,fldVn]=calc_UEVNfromUXVY(fldU,fldV); x=mygrid.XC; y=mygrid.YC; u=fldUe; v=fldVn; %enforce [-180 180] longitude convention; x(find(x>180))=x(find(x>180))-360; %compute direction: eps=1e-3; [xp,yp]=m_ll2xy(x+eps*u,y+eps*v.*cos(y*pi/180),'clip','point'); [x,y]=m_ll2xy(x,y,'clip','point'); complexVec=(xp-x)+i*(yp-y); %scale amplitude complexVec=complexVec./abs(complexVec).*abs(u+i*v); %go back to reals: u=real(complexVec); u(isnan(complexVec))=NaN; v=imag(complexVec); v(isnan(complexVec))=NaN; %select face: x=x{iFace}; y=y{iFace}; u=u{iFace}; v=v{iFace}; %get rid of nans: ii=1:subFac:size(x,1); jj=1:subFac:size(x,2); x=x(ii,jj); y=y(ii,jj); u=u(ii,jj); v=v(ii,jj); ii=find(~isnan(u.*v)); x=x(ii); y=y(ii); u=u(ii); v=v(ii); %plot: hold on; if isempty(scaleFac); quiver(x,y,u,v); else; quiver(x,y,u,v,scaleFac); end; %syntax to use m_quiver.m if 0; [fldUe,fldVn]=calc_UEVNfromUXVY(fldU,fldV); u=fldUe{iFace}; v=fldVn{iFace}; x=mygrid.XC{iFace}; y=mygrid.YC{iFace}; %get rid of nans: ii=find(~isnan(u.*v)); ii=ii(1:subFac:end); x=x(ii); y=y(ii); u=u(ii); v=v(ii); %plot: hold on; if isempty(scaleFac); m_quiver(x,y,u,v); else; m_quiver(x,y,u,v,scaleFac); end; return; end; gcmfaces/gcmfaces_maps/gcmfaces_cmap_cbar.m0000644000435400001440000002037712167626057020737 0ustar gforgetusersfunction [myColorbar]=gcmfaces_cmap_cbar(vecLimCol,varargin); %object : non linear colormap + colorbar %inputs : vecLimCol, vector of color intervals %optional: optional paramaters take the following form {'name',param1,param2,...} % the two that are currently active are % {'myCmap',myCmap} is the colormap name ('jet' by default) % {'myBW',myBW} put white/black at colorbar edges/center (0 by default) %output : myColorbar, the colorbar handle % %notes: - myBW==0 does nothing; myBW~=0 modifies the colormap as follows % myBW==1; blanks the center of colorscale % myBW==2; blacks the low&high ends and blanks the middle % myBW==-1; blanks the low end % myBW==-2; blacks the low end and blanks the high end % - to remove a resulting colorbar, type delete(myColorbar); % - since this routine regenerates the colormap according to % vecLimCol and there can be only one colormap per figure, you % dont want to change vecLimCol from one subplot to the next. % - the colorbar position is hard coded (for now) as 'to the right % of the parent axis'. You can change it via the myColorbar handle. % - the colormap density is hard coded (for now). It may need to % be increased if you specify a very non-linear colormap such as % [[0:0.5:4] [5:10] [20 30 50 100 500]]; spanning 3 orders of magnitue if isempty(vecLimCol); myColorbar=colorbar; return; end; %set optional paramaters to default values myCmap='jet'; myBW=0; %set more optional paramaters to user defined values for ii=1:nargin-1; if ~iscell(varargin{ii}); warning('inputCheck:gcmfaces_cmap_cbar_1',... ['As of june 2011, gcmfaces_cmap_cbar expects \n'... ' its optional parameters as cell arrays. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help gcmfaces_cmap_cbar'' for details.']); elseif ~ischar(varargin{ii}{1}); warning('inputCheck:gcmfaces_cmap_cbar_2',... ['As of june 2011, gcmfaces_cmap_cbar expects \n'... ' its optional parameters cell arrays \n'... ' to start with character string. \n'... ' Argument no. ' num2str(ii+1) ' was ignored \n'... ' Type ''help gcmfaces_cmap_cbar'' for details.']); else; if strcmp(varargin{ii}{1},'myCmap')|... strcmp(varargin{ii}{1},'myBW'); eval([varargin{ii}{1} '=varargin{ii}{2};']); else; warning('inputCheck:gcmfaces_cmap_cbar_3',... ['unknown option ''' varargin{ii}{1} ''' was ignored']); end; end; end; if strcmp(myCmap,'jetBW1'); myCmap='jet'; myBW=1; end; if strcmp(myCmap,'jetBW2'); myCmap='jet'; myBW=2; end; %vecLimCol must be strickly increasing : tmp1=vecLimCol(2:end)-vecLimCol(1:end-1); if ~isempty(find(tmp1<=0)); fprintf('please use increasing values \n'); myColorbar=-1; return; end; %original colormap precision : %nb_colors=64*3; tmp1=min(vecLimCol(2:end)-vecLimCol(1:end-1)); tmp2=vecLimCol(end)-vecLimCol(1); tmp3=ceil(tmp2/tmp1/64); nb_colors=64*10*tmp3; %nb_colors=64*500*tmp3; %colormap and caxis : if ~isempty(strfind(myCmap,'FLIP')); eval(['tmp_map=colormap(' myCmap(5:end) '(nb_colors));']); tmp_map=flipdim(tmp_map,1); else; eval(['tmp_map=colormap(' myCmap '(nb_colors));']); end; tmp_val=[vecLimCol(1) vecLimCol(end)]; tmp_val=[tmp_val(1) : (tmp_val(2)-tmp_val(1))/(nb_colors-1) : tmp_val(2)]; caxis([tmp_val(1) tmp_val(end)]); %subset of colours : tmp_colors=round( [1:length(vecLimCol)-1] * nb_colors/(length(vecLimCol)-1) ); tmp_colors(1)=1; tmp_colors(end)=nb_colors; tmp_colors=tmp_map(tmp_colors,:); %final colormap : tmp_map2=tmp_map; for kkk=1:nb_colors tmp1=min(find(vecLimCol>=tmp_val(kkk))); if isempty(tmp1) tmp_map2(kkk,:)=tmp_colors(end,:); elseif tmp1==1 tmp_map2(kkk,:)=tmp_colors(1,:); elseif tmp1==length(vecLimCol) tmp_map2(kkk,:)=tmp_colors(end,:); else tmp_map2(kkk,:)=tmp_colors(tmp1-1,:); end end %to blank the center of colorscale: if myBW==1; tmp1=tmp_map2(floor(length(tmp_map2)/2),:); tmp2=find(sum(abs(tmp_map2-ones(length(tmp_map2),1)*tmp1),2)==0); tmp_map2(tmp2,:)=1; end; %to black the lowest/highest range and blank the middle range: %=> if problem with colormap==gray ... if myBW==2; tmp1=tmp_map2(1,:); tmp2=find(sum(abs(tmp_map2-ones(length(tmp_map2),1)*tmp1),2)==0); tmp1=tmp_map2(end,:); tmp3=find(sum(abs(tmp_map2-ones(length(tmp_map2),1)*tmp1),2)==0); tmp_map2(tmp2,:)=0; tmp_map2(tmp3,:)=0; tmp1=tmp_map2(floor(length(tmp_map2)/2),:); tmp2=find(sum(abs(tmp_map2-ones(length(tmp_map2),1)*tmp1),2)==0); tmp_map2(tmp2,:)=1; end; %to blank the lowest range: if myBW==-1; tmp1=tmp_map2(1,:); tmp2=find(sum(abs(tmp_map2-ones(length(tmp_map2),1)*tmp1),2)==0); tmp_map2(tmp2,:)=1; end; %to black the lowest range and blank the highest range: %=> if problem with colormap==gray ... if myBW==-2; tmp1=tmp_map2(1,:); tmp2=find(sum(abs(tmp_map2-ones(length(tmp_map2),1)*tmp1),2)==0); tmp1=tmp_map2(end,:); tmp3=find(sum(abs(tmp_map2-ones(length(tmp_map2),1)*tmp1),2)==0); tmp_map2(tmp2,:)=0; tmp_map2(tmp3,:)=1; end; colormap(tmp_map2); %colorbar : aaa=gca; tmp1=get(aaa,'Position'); tmp1=[sum(tmp1([1 3]))+0.01 tmp1(2) 0.02 tmp1(4)]; %tmp1=get(aaa,'Position'); tmp1=[sum(tmp1([1 3])) tmp1(2) 0.01 tmp1(4)]; myColorbar=axes('position',tmp1); % set(myColorbar,'Position',[0.915 0.26 0.03 0.52]);%to account for m_map set(myColorbar,'Position',tmp1);%to account for m_map tmp1=[1:2]'*ones(1,length(vecLimCol)); tmp2=[1:length(vecLimCol)]; tmp2=[tmp2;tmp2]; tmp3=[0.5*( vecLimCol(2:end)+vecLimCol(1:end-1) ) vecLimCol(end)]; tmp3=[tmp3;tmp3]; pcolor(tmp1,tmp2,tmp3); caxis([vecLimCol(1) vecLimCol(end)]); set(myColorbar,'YAxisLocation','right'); set(myColorbar,'XTick',[]); set(myColorbar,'YTick',[1:length(vecLimCol)]); %straight labels: %--------------- if 1; %set(myColorbar,'YTickLabel',num2str(vecLimCol')); % tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%5.1e',vecLimCol(kcur))); end; %%tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%i',vecLimCol(kcur))); end; %tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%3.3f',vecLimCol(kcur))); end; tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%3.2f',vecLimCol(kcur))); end; % tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%3.2g',vecLimCol(kcur))); end; % tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%3.0f',vecLimCol(kcur))); end; % tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%4.3f',vecLimCol(kcur))); end; %%tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%5.4f',vecLimCol(kcur))); end; %tmp2(1,:)=' '; tmp2(end,:)=' '; %do not display the last value, as it can be exceeded else; test1=max(abs(round(vecLimCol)-vecLimCol)); test2=max(abs(round(vecLimCol*100)-vecLimCol*100)); if ~test1; tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%3.0f',vecLimCol(kcur))); end; elseif ~test2; tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%3.2f',vecLimCol(kcur))); end; else; test3=1; ii=abs(ceil(log10(max(abs(vecLimCol))))); while test3>1e-6; test3=max(abs(round(vecLimCol*10^ii)-vecLimCol*10^ii)); if test3>1e-6; ii=ii+1; end; end; tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%3.0f',vecLimCol(kcur)*10^ii)); end; title(['x 10^{-' num2str(ii) '}'],'FontSize',16); end; tmp2(1,:)=' '; tmp2(end,:)=' '; %do not display the last value, as it can be exceeded end tmp2(1,:)=' '; %do not display the first value tmp2(end,:)=' '; %do not display the last value %scaled labels: %------------- if 0; vecLimCol2=floor(log10(max(abs(vecLimCol)))); fprintf(['cbar labels in 10^' num2str(vecLimCol2) '\n']); vecLimCol2=vecLimCol*10^(-vecLimCol2); tmp2=''; for kcur=1:length(vecLimCol); tmp2=strvcat(tmp2,sprintf('%3.2f',vecLimCol2(kcur))); end; end; set(myColorbar,'YTickLabel',tmp2); %add tag spec. to colorbar generated with this routine set(myColorbar,'Tag','gfCbar'); axes(aaa); gcmfaces/gcmfaces_maps/m_map_1face.m0000644000435400001440000000321311367400177017310 0ustar gforgetusersfunction []=m_map_1face(fld,iFace,varargin); %purpose: % use m_map to display one face in a chosen projection %synthax: % m_map_1face(fld,iFace,choiceProj); %inputs: % fld is a 2D field in gcmfaces format % iFace is the face number % choiceProj is the projection choice (0, 1, 2, or 3) % if it is not stated, the default is mollweide (0) %check that m_map is in the path aa=which('m_proj'); if isempty(aa); error('this function requires m_map that is missing'); end; %get parameters: if nargin>2; choiceProj=varargin{1}; else; choiceProj=0; end; if nargin>3; cc=varargin{2}; else; cc=[]; end; if nargin>4; doPlotCoast=varargin{3}; else; doPlotCoast=1; end; global mygrid; %extract face: x=mygrid.XC{iFace}(:,:); y=mygrid.YC{iFace}(:,:); z=fld{iFace}(:,:); m1=mygrid.mskC{iFace}(:,:,1); if length(size(z))~=2; error('input must be a 2D field in gcmfaces format'); end; %put mask on x and y: x(isnan(m1))=NaN; y(isnan(m1))=NaN; %enforce [-180 180] longitude convention; x(find(x>180))=x(find(x>180))-360; %select lat/lon range: ii=find(~isnan(m1)); ll=[min(x(ii)) max(x(ii))]; LL=[min(y(ii)) max(y(ii))]; if choiceProj==0; %%m_proj('Miller Cylindrical','lon',ll,'lat',LL); %%m_proj('Equidistant cylindrical','lon',ll,'lat',LL); m_proj('mollweide','lon',ll,'lat',LL); elseif choiceProj==1; m_proj('Mercator','lon',ll,'lat',LL); elseif choiceProj==2; m_proj('Stereographic','lon',0,'lat',90,'rad',90-LL(1)); elseif choiceProj==3; m_proj('Stereographic','lon',0,'lat',-90,'rad',90+LL(2) ); end; [x,y]=m_ll2xy(x,y); pcolor(x,y,z); shading flat; if ~isempty(cc); caxis(cc); end; colorbar; if doPlotCoast; m_coast('patch',[1 1 1]*.7,'edgecolor','none'); end; m_grid; gcmfaces/gcmfaces_maps/m_map_gcmfaces_movie.m0000644000435400001440000000530012365534164021302 0ustar gforgetusersfunction []=m_map_gcmfaces_movie(dirFld,nameFld,varargin); %check that m_map is in the path aa=which('m_proj'); if isempty(aa); error('this function requires m_map that is missing'); end; if ~isempty(strfind(nameFld,'ADJ')); inadmod=1; else; inadmod=0; end; choiceV3orV4='v4' if ~isempty(choiceV3orV4)&isempty(whos('mygrid')); gcmfaces_global; dir0=[myenv.gcmfaces_dir '/sample_input/']; dirGrid=[dir0 'GRID' choiceV3orV4 '/']; if strcmp(choiceV3orV4,'v4'); nF=5; fileFormat='compact'; else; nF=1; fileFormat='straight'; end; grid_load(dirGrid,nF,fileFormat); end; dirOut=dirFld; if nargin>2; k=varargin{1}; else; k=1; end; if nargin>3; p=varargin{2}; else; p=0; end; if nargin>4; cc=varargin{3}; else; cc=[]; end; %set up directories: dirCUR=pwd; mkdir([dirOut 'movies/']); mkdir([dirOut 'movies/TMP/']); cd([dirOut 'movies/TMP/']); %get the data: fileList=dir([dirFld nameFld '*.data']); %fileList=fileList(1:6:end);%skip some to go faster... nt=length(fileList); %tmp1=convert2array(mygrid.XC); [n1,n2]=size(tmp1); %fld=convert2array(NaN*zeros(n1,n2,nt)); fld=NaN*mygrid.XC; for tt=1:nt; fld(:,:,tt)=read_bin([dirFld fileList(tt).name],1,k); end; mask=mygrid.hFacC; mask(find(mask==0))=NaN; mask(find(mask>0))=1; if k>0; kk=k; else; kk=1; end; mask=mask(:,:,kk); MASK=convert2array(mask); %take out the first record, to visualize the model drift: %fld0=fld(:,:,1); for tt=1:nt; fld(:,:,tt)=fld(:,:,tt)-fld0; end; %caxis: %cc=input('caxis? e.g. [0 1]\n'); %make movie: %figure; set(gcf,'Units','Normalized','Position',[0.1 0.1 0.4 0.8]); %figure; set(gcf,'Units','Normalized','Position',[0.1 0.1 0.8 0.8]); figure; set(gcf,'Units','Normalized','Position',[0 0.1 0.4 0.4]); nt=size(fld{1},3); %%%nt=10; for tt=1:nt; if tt<10; tt_txt='000'; elseif tt<100; tt_txt='00'; elseif tt<1000; tt_txt='0'; else; tt_txt=''; end; tt_txt=[tt_txt num2str(tt)];; if inadmod==0; tt2=tt; else; tt2=nt-tt; end; if tt2<10; tt2_txt='000'; elseif tt2<100; tt2_txt='00'; elseif tt2<1000; tt2_txt='0'; else; tt2_txt=''; end; tt2_txt=[tt2_txt num2str(tt2)];; m_map_gcmfaces(mask.*fld(:,:,tt),p,cc); title([nameFld ' ' tt2_txt],'Interpreter','none'); eval(['print -dtiff tmp_' nameFld '_' num2str(k) '_' tt_txt '.tiff']); system(['convert tmp_' nameFld '_' num2str(k) '_' tt_txt '.tiff tmp_' nameFld '_' num2str(k) '_' tt_txt '.gif']); end; system(['gifsicle --delay=20 --loop tmp_' nameFld '_' num2str(k) '_*.gif > ' nameFld '_' num2str(k) '.gif']); delete(['tmp_' nameFld '_' num2str(k) '_*.tiff']); delete(['tmp_' nameFld '_' num2str(k) '_*.gif']); %handle files and dirs movefile([nameFld '_' num2str(k) '.gif'] , '../.'); cd .. %rmdir TMP fprintf(['new movie >>>> ' dirFld '/movies/' nameFld '_' num2str(k) '.gif \n']); eval(['cd ' dirCUR ]); gcmfaces/gcmfaces_maps/qwckplot.m0000644000435400001440000000024412006051150017005 0ustar gforgetusersfunction []=qwckplot(fld); %does a quick display of a 2D field according %to imagescnan(convert2array(fld)'); axis xy; imagescnan(convert2array(fld)'); axis xy; gcmfaces/sample_processing/0000755000435400001440000000000012375431055015727 5ustar gforgetusersgcmfaces/sample_processing/example_interp.m0000644000435400001440000000311511650106224021111 0ustar gforgetusersfunction []=example_interp(choiceV3orV4); %object: a interp2 example within gcmfaces %inputs: choiceV3orV4 ('v3' or 'v4') selects the sample GRID gcmfaces_global; if myenv.verbose>0; gcmfaces_msg(['* call example_interp : will define ' ... 'a 2x2 gridded variable (an SSH field here), and then ' ... 'use interp2 to map it to the chosen grid. '],''); end; %%%%%%%%%%%%%%%%% %load parameters: %%%%%%%%%%%%%%%%% dir0=[myenv.gcmfaces_dir '/sample_input/']; dirGrid=[dir0 '/GRID' choiceV3orV4 '/']; dirIn=[dir0 '/SAMPLE' choiceV3orV4 '/']; if strcmp(choiceV3orV4,'v4'); nF=5; fileFormat='compact'; else; nF=1; fileFormat='straight'; end; grid_load(dirGrid,nF,fileFormat); %%%%%%%%%%%%%%%%%%%%%%% %get sample data: V3 SSH dirV3=[myenv.gcmfaces_dir '/sample_input/SAMPLEv3/']; etan=rdmds([dirV3 'DDetan'],0); etan(etan==0)=NaN; dirV3=[myenv.gcmfaces_dir '/sample_input/GRIDv3/']; lon=rdmds([dirV3 'XC']); lat=rdmds([dirV3 'YC']); lon=lon(1:2:end,21:2:140); lat=lat(1:2:end,21:2:140); etan=etan(1:2:end,21:2:140); %%%%%%%%%%%%%%%%%%%%%%% %do the interpolation: x=[lon-360;lon;lon+360]; y=[lat;lat;lat]; z=[etan;etan;etan]; z_interp=gcmfaces(5); for ii=1:mygrid.nFaces; xi=mygrid.XC{ii}; yi=mygrid.YC{ii}; zi = interp2(x',y',z',xi,yi); z_interp{ii}=zi; end; %%%%%%%%%%%%%%%%%%%%%%% %illustrate the result: figure; x=[lon-360;lon]; y=[lat;lat]; z=[etan;etan]; pcolor(x,y,z); axis([-180 180 -90 90]); shading flat; caxis([-2 1]); colorbar; figure; [X,Y,FLD]=convert2pcol(mygrid.XC,mygrid.YC,z_interp); pcolor(X,Y,FLD); axis([-180 180 -90 90]); shading flat; caxis([-2 1]); colorbar; gcmfaces/sample_processing/example_smooth.m0000644000435400001440000000354512274331554021141 0ustar gforgetusers %use the field produced in sample_proccessing/example_bin_average.m if myenv.verbose>0; gcmfaces_msg('* apply land mask (1/NaN) to gridded before smoothing'); end; % fld=obsMap; fld(find(isnan(fld)))=0; fld(find(mygrid.hFacCsurf==0))=NaN; fld=obsMap.*mygrid.mskC(:,:,1); %%%%%%%% isotropic diffusion %%%%%%%% %choose smoothing scale: here 3 X grid spacing if myenv.verbose>0; gcmfaces_msg('* set the smoothing scale to 3 grid points'); end; distXC=3*mygrid.DXC; distYC=3*mygrid.DYC; %do the smoothing: if myenv.verbose>0; gcmfaces_msg(['* call diffsmoth2D : apply smoothing operator ' ... 'that consists in time stepping a diffusion equation ' ... 'with accordingly chosen diffusivity and duration. In particular ' ... 'diffsmoth2D illustrates gradient computations (using calc_T_grad) ' ... 'and convergence computations (using calc_UV_conv).']); end; obsMap_smooth=diffsmooth2D(fld,distXC,distYC); %display results: if myenv.verbose>0; gcmfaces_msg('* crude display of results in array format'); end; figure; qwckplot(obsMap_smooth); caxis([-1 1]*0.4); colorbar; title('smoothed data') %%%%%%%% rotated diffusion %%%%%%%% %choose smoothing scale: here 3 X grid spacing if myenv.verbose>0; gcmfaces_msg('* set anisotropic and rotated smoothing'); end; distLarge=3*sqrt(mygrid.RAC); distSmall=1*sqrt(mygrid.RAC); fldRef=mygrid.YC; %do the smoothing: if myenv.verbose>0; gcmfaces_msg(['* call diffsmoth2Drotated : apply anisotropic smoothing operator ' ... 'that acts preferentially along contours of a reference field (here latitude).']); end; obsMap_smooth2=diffsmooth2Drotated(fld,distLarge,distSmall,mygrid.YC); %display results: if myenv.verbose>0; gcmfaces_msg('* crude display of results in array format'); end; figure; qwckplot(obsMap_smooth2); caxis([-1 1]*0.4); colorbar; title('zonally smoothed data') gcmfaces/sample_processing/example_griddata.m0000644000435400001440000000451711650106224021376 0ustar gforgetusersfunction []=example_griddata(choiceV3orV4); %object: a griddata example within gcmfaces %inputs: choiceV3orV4 ('v3' or 'v4') selects the sample GRID gcmfaces_global; if myenv.verbose>0; gcmfaces_msg('==============================================='); gcmfaces_msg(['*** entering example_griddata that will define ' ... 'a 2x2 gridded variable (an SSH field here), and then ' ... 'use griddata to map it to the chosen grid. '],''); end; %%%%%%%%%%%%%%%%% %load parameters: %%%%%%%%%%%%%%%%% dir0=[myenv.gcmfaces_dir '/sample_input/']; dirGrid=[dir0 '/GRID' choiceV3orV4 '/']; dirIn=[dir0 '/SAMPLE' choiceV3orV4 '/']; if strcmp(choiceV3orV4,'v4'); nF=5; fileFormat='compact'; else; nF=1; fileFormat='straight'; end; grid_load(dirGrid,nF,fileFormat); %%%%%%%%%%%%%%%%%%%%%%% %get sample data: V3 SSH if myenv.verbose>0; gcmfaces_msg('* subsample test-case SSH field it to a 2x2 grid'); end; dirV3=[myenv.gcmfaces_dir '/sample_input/SAMPLEv3/']; etan=rdmds([dirV3 'DDetan'],0); etan(etan==0)=NaN; dirV3=[myenv.gcmfaces_dir '/sample_input/GRIDv3/']; lon=rdmds([dirV3 'XC']); lat=rdmds([dirV3 'YC']); lon=lon(1:2:end,21:2:140); lat=lat(1:2:end,21:2:140); etan=etan(1:2:end,21:2:140); %%%%%%%%%%%%%%%%%%%%%%% %make sure to accomodate the two longitude conventions: if myenv.verbose>0; gcmfaces_msg('* accomodate both lon. conventions, then convert to data vector'); end; x=[lon-360;lon;lon+360]; y=[lat;lat;lat]; z=[etan;etan;etan]; jj=find(~isnan(z)); x=x(jj); y=y(jj); z=z(jj); %%%%%%%%%%%%%%%%%%%%%%% %do the interpolation: if myenv.verbose>0; gcmfaces_msg('* map/interpolate data using griddata'); end; z_interp=gcmfaces(5); for ii=1:mygrid.nFaces; xi=mygrid.XC{ii}; yi=mygrid.YC{ii}; zi = griddata(x',y',z',xi,yi); z_interp{ii}=zi; end; %msk=mygrid.hFacC(:,:,1); z_interp(find(msk==0))=NaN; %%%%%%%%%%%%%%%%%%%%%%% %illustrate the result: figure; x=[lon-360;lon]; y=[lat;lat]; z=[etan;etan]; pcolor(x,y,z); axis([-180 180 -90 90]); shading flat; caxis([-2 1]); colorbar; figure; [X,Y,FLD]=convert2pcol(mygrid.XC,mygrid.YC,z_interp); pcolor(X,Y,FLD); axis([-180 180 -90 90]); shading flat; caxis([-2 1]); colorbar; if myenv.verbose>0; gcmfaces_msg('* note of caution : griddata puts values on land. '); gcmfaces_msg('*** leaving example_griddata'); gcmfaces_msg('==============================================='); end; gcmfaces/sample_processing/example_faces2latlon2faces.m0000644000435400001440000001017012057712215023255 0ustar gforgetusersfunction []=example_faces2latlon2faces(choiceGrid); %object: interpolate back and forth between gcmfaces and lat-lon grid if 0; clear all; grid_load('./',6,'cube'); gcmfaces_bindata; gcmfaces_global; lon=[-179:2:179]; lat=[-30:2:30]; [lat,lon] = meshgrid(lat,lon); fld=sin(2*pi/180*mygrid.XC).*sin(2*pi/180*mygrid.YC); fld2=gcmfaces_interp_2d(fld,lon,lat);%go from gcmfaces grid to lat-lon grid end; gcmfaces_global; global mytri; if myenv.verbose>0; gcmfaces_msg('==============================================='); gcmfaces_msg(['*** entering example_faces2latlon2faces that will ' ... 'interpolate a field on the chosen to a lat-lon grid and back' ... 'to the original grid'],''); end; %%%%%%%%%%%%%%%%% %load parameters: %%%%%%%%%%%%%%%%% dir0=[myenv.gcmfaces_dir '/sample_input/']; dirGrid=[dir0 '/GRID' choiceGrid '/']; dirIn=[dir0 '/SAMPLE' choiceGrid '/']; if strcmp(choiceGrid,'v4'); nF=5; fileFormat='compact'; elseif strcmp(choiceGrid,'v3'); nF=1; fileFormat='straight'; elseif strcmp(choiceGrid,'cube'); nF=6; fileFormat='cube'; else; error('unknow grid'); end; grid_load(dirGrid,nF,fileFormat); %store reference grid mygrid_refgrid=mygrid; %%%%%%%%%%%%%%%%%%% %field for testing: %%%%%%%%%%%%%%%%%%% if myenv.verbose>0; gcmfaces_msg('* define a sinusoidal field for testing'); end; fld=sin(2*pi/180*mygrid.XC).*sin(2*pi/180*mygrid.YC); %%%%%%%%%%%%%%%%%%%%%%%%%% %lat-lon grid for testing: %%%%%%%%%%%%%%%%%%%%%%%%%% if myenv.verbose>0; gcmfaces_msg('* define 2x2 lat-lon grid for testing'); end; %define lat-lon grid lon=[-179:2:179]; lat=[-89:2:89]; aa=[-180 180 -90 90]; if max(mygrid_refgrid.XC)>180; lon=[1:2:359]; aa=[0 360 -90 90]; end; % lon=[-179:2:179]; lat=[-30:2:30]; [lat,lon] = meshgrid(lat,lon); %prepare mygrid for lat-lon with no mask mygrid_latlon.nFaces=1; mygrid_latlon.XC=gcmfaces({lon}); mygrid_latlon.YC=gcmfaces({lat}); mygrid_latlon.dirGrid='none'; mygrid_latlon.fileFormat='straight'; mygrid_latlon.ioSize=size(lon); %%%%%%%%%%%%%%%%%%%%%%%%%%%%% %interpolate to lat-lon grid: %%%%%%%%%%%%%%%%%%%%%%%%%%%%% if myenv.verbose>0; gcmfaces_msg('* interpolate test field to lat-lon grid'); end; mygrid=mygrid_latlon; gcmfaces_bindata; veclon=convert2array(mygrid.XC); veclon=veclon(mytri.kk); veclat=convert2array(mygrid.YC); veclat=veclat(mytri.kk); mygrid=mygrid_refgrid; gcmfaces_bindata; vecfld=gcmfaces_interp_2d(fld,veclon,veclat);%go from gcmfaces grid to lat-lon grid mygrid=mygrid_latlon; gcmfaces_bindata; fld_latlon=NaN*convert2array(mygrid.XC); fld_latlon(mytri.kk)=vecfld; fld_latlon=convert2array(fld_latlon); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %interpolate back to ref grid: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if myenv.verbose>0; gcmfaces_msg('* interpolate back to original grid'); end; mygrid=mygrid_refgrid; gcmfaces_bindata; veclon=convert2array(mygrid.XC); veclon=veclon(mytri.kk); veclat=convert2array(mygrid.YC); veclat=veclat(mytri.kk); mygrid=mygrid_latlon; gcmfaces_bindata; vecfld=gcmfaces_interp_2d(fld_latlon,veclon,veclat);%go from gcmfaces grid to lat-lon grid mygrid=mygrid_refgrid; gcmfaces_bindata; fld_refgrid=NaN*convert2array(mygrid.XC); fld_refgrid(mytri.kk)=vecfld; fld_refgrid=convert2array(fld_refgrid); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %get and plot the lat-lon array: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if myenv.verbose>0; gcmfaces_msg('* plot lat-lon grid interpolated field'); end; FLD=fld_latlon{1}; figure; pcolor(lon,lat,FLD); colorbar; axis(aa); title('interpoate lat-lon map'); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %plot difference due to interpolation %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% if myenv.verbose>0; gcmfaces_msg('* plot error due to back and forth interpolation'); end; mygrid=mygrid_refgrid; figure; aa=which('m_proj'); if isempty(aa); [X,Y,FLD]=convert2pcol(mygrid.XC,mygrid.YC,fld_refgrid-fld); pcolor(X,Y,FLD); shading flat; colorbar; else; m_map_gcmfaces(fld_refgrid-fld); end; title('error due to back and forth interpolation'); if myenv.verbose>0; gcmfaces_msg('*** leaving example_faces2latlon2faces'); gcmfaces_msg('==============================================='); end; gcmfaces/sample_processing/example_bin_average.m0000644000435400001440000001000012006053604022040 0ustar gforgetusersfunction []=example_bin_average(choiceGrid,doSmooth); %object: a bin average example within gcmfaces %inputs: choiceGrid ('v3' or 'v4') selects the sample GRID % doSmooth; if set to 1, follow on with smoothing example %%%%%%%%%%%%%%%%% %load parameters: %%%%%%%%%%%%%%%%% gcmfaces_global; dir0=[myenv.gcmfaces_dir '/sample_input/']; dirGrid=[dir0 '/GRID' choiceGrid '/']; dirIn=[dir0 '/SAMPLE' choiceGrid '/']; if strcmp(choiceGrid,'v4'); nF=5; fileFormat='compact'; elseif strcmp(choiceGrid,'v3'); nF=1; fileFormat='straight'; elseif strcmp(choiceGrid,'cube'); nF=6; fileFormat='cube'; else; error('unknow grid'); end; grid_load(dirGrid,nF,fileFormat); gcmfaces_global; if myenv.verbose>0; gcmfaces_msg('==============================================='); % gcmfaces_msg('*** entering example_bin_average that will define',''); % gcmfaces_msg('randomly distributed variable (position and value),',' '); % gcmfaces_msg('then bin average it to the chosen grid,',' '); % gcmfaces_msg('and apply a smoothing filter to it',' '); gcmfaces_msg(['*** entering example_bin_average that will first define ' ... 'randomly distributed variable (position and value), ' ... 'then bin average it to the chosen grid, ' ... 'and finally apply a smoothing filter to it '],''); end; warning('off','MATLAB:dsearch:DeprecatedFunction'); warning('off','MATLAB:delaunay:DuplicateDataPoints'); %%%%%%%%%%%%%%%%%%%%%%% %generate random data if myenv.verbose>0; gcmfaces_msg('* generate random data'); end; nobs=1e6; lat=(rand(nobs,1)-0.5)*2*90; lon=(rand(nobs,1)-0.5)*2*180; %needed for 0-360 longitude convention if mygrid.nFaces==1; xx=find(lon<0);lon(xx)=lon(xx)+360; end; obsPts=(rand(nobs,1)-0.5)*2; %%%%%%%%%%%%%%%%%%%%%%% %generate delaunay triangulation if myenv.verbose>0; gcmfaces_msg('* call gcmfaces_bindata : generate delaunay triangulation'); end; gcmfaces_bindata; %%%%%%%%%%%%%%%%%%%%%%%% %bin average random data if myenv.verbose>0; gcmfaces_msg('* call gcmfaces_bindata : bin average data'); end; obsMap=gcmfaces_bindata(lon,lat,obsPts); %%%%%%%%%%%%%%%%%%%%%%%% %format conversions if myenv.verbose>0; gcmfaces_msg('* call convert2array : convert from gcmfaces to array format'); end; obsArray=convert2array(obsMap);%put in gcmfaces format if myenv.verbose>0; gcmfaces_msg('* call convert2array : convert back to gcmfaces'); end; obsMap2=convert2array(obsArray);%put in gcmfaces format if myenv.verbose>0; gcmfaces_msg('* call convert2gcmfaces : convert from gcmfaces to file format'); end; obsOut=convert2gcmfaces(obsMap); %put in gcm input format if myenv.verbose>0; gcmfaces_msg('* summarizing data formats:'); aa=whos('obs*'); aaa=aa(4); bb=['[' num2str(aaa.size(1)) 'x' num2str(aaa.size(2)) ']']; bb=fprintf(' %8s %8s %12s : data points (vector)\n',aaa.name,aaa.class,bb); aaa=aa(2); bb=['[' num2str(aaa.size(1)) 'x' num2str(aaa.size(2)) ']']; bb=fprintf(' %8s %8s %12s : gridded data (gcmfaces)\n',aaa.name,aaa.class,bb); aaa=aa(1); bb=['[' num2str(aaa.size(1)) 'x' num2str(aaa.size(2)) ']']; bb=fprintf(' %8s %8s %12s : array format\n',aaa.name,aaa.class,bb); aaa=aa(3); bb=['[' num2str(aaa.size(1)) 'x' num2str(aaa.size(2)) ']']; bb=fprintf(' %8s %8s %12s : output format\n',aaa.name,aaa.class,bb); end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %quick display if myenv.verbose>0; gcmfaces_msg('* crude display of results in array format'); end; figure; imagescnan(obsArray','nancolor',[1 1 1]*0.8); axis xy; caxis([-1 1]*0.4); colorbar; title('bin averaged data'); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %now illustrate the smoothing filter if myenv.verbose>0; gcmfaces_msg('* entering example_smooth : apply smoother to gridded data'); end; if doSmooth; example_smooth; end; if myenv.verbose>0; gcmfaces_msg('* leaving example_smooth'); end; if myenv.verbose>0; gcmfaces_msg('*** leaving example_bin_average'); gcmfaces_msg('==============================================='); end; MITprof/0000755000435400001440000000000012375431052011757 5ustar gforgetusersMITprof/ecco_v4/0000755000435400001440000000000012375431055013304 5ustar gforgetusersMITprof/ecco_v4/argo_ctd_demo.m0000644000435400001440000001025712147452752016261 0ustar gforgetusers doLoad=1; doGrid=1; doPlot=1; gcmfaces_global;%global variables and paths %load insitu data (in MITprof format) %------------------------------------ if doLoad; dirIn='/net/nares/raid11/ecco-shared/ecco-version-4/input/input_insitu/'; %load ctd data set (0-9000m) ctd=MITprof_load([dirIn 'ctd_feb2013.nc']); %load argo data subsets (rectricted to 0-2000m) argo1=MITprof_load([dirIn 'argo_feb2013_1992_to_2007.nc']); argo2=MITprof_load([dirIn 'argo_feb2013_2008_to_2010.nc']); argo3=MITprof_load([dirIn 'argo_feb2013_2011_to_2012.nc']); %concatenate (requires same vertical grid) argo=MITprof_concat(argo1,argo2); argo=MITprof_concat(argo,argo3); end; %define global grids (gcmfaces format) %------------------------------------ if doGrid; %ECCO grid (lat-lon-cap) should be in memory at this stage mygrid_llc90=mygrid; %define lat-lon grid lon=[-179:2:179]; lat=[-89:2:89]; [lat,lon] = meshgrid([-89:2:89],[-179:2:179]); %prepare mygrid for lat-lon with no mask mygrid_latlon.nFaces=1; mygrid_latlon.XC=gcmfaces({lon}); mygrid_latlon.YC=gcmfaces({lat}); mygrid_latlon.dirGrid='none'; mygrid_latlon.fileFormat='straight'; mygrid_latlon.ioSize=size(lon); end; %plot number of observations and mean date %----------------------------------------- if doPlot==1; mygrid=mygrid_latlon; global mytri; mytri=[]; gcmfaces_bindata; figureL; [tim,nobs]=gcmfaces_bindata(argo.prof_lon,argo.prof_lat,argo.prof_date); tim0=datenum(1992,1,1); tim=1992+(tim./nobs-tim0)/365; tim(nobs==0)=NaN; % subplot(2,2,1); qwckplot(log10(nobs)); caxis([0 3]); colorbar('horiz'); title('argo log10(#obs)'); % subplot(2,2,2); qwckplot(tim); caxis([1992 2012]); colorbar('horiz'); title('argo mean date'); % [tim,nobs]=gcmfaces_bindata(ctd.prof_lon,ctd.prof_lat,ctd.prof_date); tim0=datenum(1992,1,1); tim=1992+(tim./nobs-tim0)/365; tim(nobs==0)=NaN; % subplot(2,2,3); qwckplot(log10(nobs)); caxis([0 3]); colorbar('horiz'); title('ctd log10(#obs)'); % subplot(2,2,4); qwckplot(tim); caxis([1992 2012]); colorbar('horiz'); title('ctd mean date'); end;%if doPlot==1; %plot individual cruise / instrument tracks (as defined by descr flag) %-------------------------------------------------------------------- if doPlot==2; mygrid=mygrid_llc90; global mytri; mytri=[]; gcmfaces_bindata; %prof=MITprof_subset(ctd,'lat',[-70 -60],'lon',[-120 -90]); prof=MITprof_subset(ctd,'lat',[-70 -60]); list0=prof.list_descr; list1='rgbmc'; figureL; m_map_gcmfaces(mygrid.Depth,3); colormap('gray'); %for k=1:length(list0); for k=length(list1):length(list1):length(list0); list1=circshift(list1,[0 -1]); prof=MITprof_subset(ctd,'descr',list0{k}); jj=mod(k,length(list1)); if jj==0; jj=length(list1); end; [tmp1,II]=sort(prof.prof_date); l=prof.prof_lon(II); L=prof.prof_lat(II); m_map_gcmfaces({'plot',l,L,[list1(jj) '.-']},3,{'doHold',1}); pause(0.1); hold on; end; end;%if doPlot==2; %compile yearly, box averaged, anomaly from climatology %------------------------------------------------------ if doPlot==3; yearly_anom_argo=NaN*zeros(3,20); yearly_anom_ctd=NaN*zeros(3,20); %box definition: l=[-180 180]; L=[-80 -50]; D=[100 200]; %l=[-120 -90]; L=[-80 -50]; D=[100 200]; for yy=1992:2011; d=[datenum(yy,0,0) datenum(yy+1,0,0)]; % prof=MITprof_subset(ctd,'lon',l,'lat',L,'depth',D,'date',d); anom=prof.prof_T(:)-prof.prof_Testim(:); anom=anom(find(~isnan(anom))); if length(anom)>0; yearly_anom_ctd(1,yy-1991)=length(anom); yearly_anom_ctd(2,yy-1991)=mean(anom); yearly_anom_ctd(3,yy-1991)=median(anom); end; % prof=MITprof_subset(argo,'lon',l,'lat',L,'depth',D,'date',d); anom=prof.prof_T(:)-prof.prof_Testim(:); anom=anom(find(~isnan(anom))); if length(anom)>0; yearly_anom_argo(1,yy-1991)=length(anom); yearly_anom_argo(2,yy-1991)=mean(anom); yearly_anom_argo(3,yy-1991)=median(anom); end; end; figureL; subplot(2,1,1); plot(log10(yearly_anom_ctd(1,:)),'.-'); hold on; plot(log10(yearly_anom_argo(1,:)),'r.-'); title('log10(#obs) for ctd (b) and argo (r)'); subplot(2,1,2); plot(yearly_anom_ctd(2,:),'.-'); hold on; plot(yearly_anom_argo(2,:),'r.-'); plot(yearly_anom_ctd(3,:),'c.-'); hold on; plot(yearly_anom_argo(3,:),'m.-'); title('mean/median anomaly for ctd (b/c) and argo (r/m)'); end;%if doPlot==3; MITprof/ecco_v4/insitu_misfit.m0000644000435400001440000001117612273233653016357 0ustar gforgetusersfunction []=insitu_misfit(doComp,varargin); %object: computes or displays cost function statistics %input: doComp states whether to compute & save (1) or load & display (0) %optional must take the following form {'name',param1,param2,...} Active ones are % {'dirData',dirData} is the data directory name ('mat/profiles/output/' by default) % {'listData',data1,data2,...} where data1 e.g. is 'argo_indian.nc' % {'listVar',var1,var2} where var1 and var2 are 'T' and 'S' % {'years',year0,year1} to limit computation to [year0 year1] interval % {'dirMat',dirMat} where dirMat is the output directory ('mat/' by default) % {'suffMat',suffMat} is the mat file suffix ('all' by default) % {'dirTex',dirTex} where dirTex is the tex directory ('tex/' by default) % {'nameTex',nameTex} is the tex file name ('myPlots' by default) % {'addToTex',addToTex} states whether (1) or not (0 default) to % augment an ongoing tex file (see write2tex.m, dirTex) % %example: insitu_misfit('./',1,{'listData','argo_in*'}); vecDepth=[[75 125];[250 350];[900 1100]]; vecCaxis=[[3 3 1];[0.5 0.5 0.2]]; %if nargin>6; vecCaxis=varargin{1}; else; vecCaxis=[]; end; %load paths and grid: %-------------------- global mygrid; if isempty(mygrid); grid_load('GRID/',5,'compact'); end; %set more optional paramaters to default values global myparms; year0=myparms.yearInAve(1); year1=myparms.yearInAve(2); listData={'argo_*_1992_to_2007*','argo_*_2008_to_2010*',... 'argo_*_2011_to_2012*','climode_*',... 'ctd_*','itp_*','seals_*','xbt_*'}; listVar={'T','S'}; %shorter test case: listData={'argo_in*'}; listVar={'T'}; dirData='mat/profiles/output/'; dirMat='mat/'; suffMat='_all'; dirTex='tex/'; addToTex=0; nameTex='myPlots'; %set more optional paramaters to user defined values for ii=1:nargin-1; if strcmp(varargin{ii}{1},'listData'); listData={varargin{ii}{2:end}}; elseif strcmp(varargin{ii}{1},'listVar'); listVar={varargin{ii}{2:end}}; elseif strcmp(varargin{ii}{1},'years'); year0=varargin{ii}{2}; year1=varargin{ii}{3}; elseif strcmp(varargin{ii}{1},'dirMat'); dirMat=varargin{ii}{2}; elseif strcmp(varargin{ii}{1},'suffMat'); suffMat=['_' varargin{ii}{2}]; elseif strcmp(varargin{ii}{1},'dirTex'); dirTex=varargin{ii}{2}; elseif strcmp(varargin{ii}{1},'addToTex'); addToTex=varargin{ii}{2}; elseif strcmp(varargin{ii}{1},'nameTex'); nameTex=varargin{ii}{2}; elseif strcmp(varargin{ii}{1},'dirData'); dirData=varargin{ii}{2}; else; warning('inputCheck:insitu_misfit',... ['unknown option ''' varargin{ii}{1} ''' was ignored']); end; end; if doComp; %initialize delaunay triangulation: gcmfaces_bindata; %time limits: date0=datenum(year0,1,1); date1=datenum(year1,12,31); %number of levels: nk=size(vecDepth,1); for vv=1:length(listVar); varCur=listVar{vv}; %get the misfits (here not normalized): [MITprof]=MITprof_stats_load(dirData,listData,varCur,1); %mask out values that are not in year range: ii=find(MITprof.prof_datedate1); MITprof.prof(ii,:)=NaN; %misfit maps: for kkk=1:size(vecDepth,1); kk=find(MITprof.prof_depth>=vecDepth(kkk,1)&MITprof.prof_depth<=vecDepth(kkk,2)); lon=MITprof.prof_lon; lat=MITprof.prof_lat; obs=nanmean(MITprof.prof(:,kk),2); ii=find(~isnan(obs)); lon=lon(ii); lat=lat(ii); obs=obs(ii); misfit_map=gcmfaces_bindata(lon,lat,obs); eval(['misfit_map_' varCur num2str(kkk) '=misfit_map;']); end; end; if ~isdir([dirMat 'cost/']); mkdir([dirMat 'cost/']); end; eval(['save ' dirMat 'cost/insitu_misfit' suffMat '.mat misfit_map_* vecDepth year* listData listVar;']); else; if isdir([dirMat 'cost/']); dirMat=[dirMat 'cost/']; end; eval(['load ' dirMat 'insitu_misfit' suffMat '.mat;']); nk=size(vecDepth,1); figureL; for vv=1:length(listVar); varCur=listVar{vv}; for kkk=1:size(vecDepth,1); eval(['misfit_map=misfit_map_' varCur num2str(kkk) ';']); dep=mean(vecDepth(kkk,:)); if isempty(vecCaxis); cc=3*sqrt(nanmean(misfit_map.^2)); else; cc=vecCaxis(vv,kkk); end; subplot(nk,length(listVar),vv+(kkk-1)*length(listVar)); m_map_gcmfaces(misfit_map,1,{'myCaxis',[-1 1]*cc},{'myShading','flat'}); title(sprintf('%s misfits at %dm (%d to %d)',varCur,dep,year0,year1)); end; end; myCaption={'Time mean misfit (model-data) for in situ profiles, ',... 'at various depths (rows), for T (left; in K) and S (right; in psu).'}; if addToTex; write2tex([dirTex '/' nameTex '.tex'],2,myCaption,gcf); end; end; MITprof/ecco_v4/glo_oce_cs32_prof_disp.m0000644000435400001440000000173212365531322017770 0ustar gforgetusers dirGrid='./'; gcmfaces_global; grid_load(dirGrid,6,'compact'); test0=isempty(dir('profiles/output/some_TS_atlas.sortedInTime.nc')); if test0; cd profiles mkdir input mkdir output copyfile ../*nc input/. MITprof_gcm2nc('./',{'some_TS_atlas.sortedInTime'}); cd .. end; MITprof=MITprof_load('profiles/output/some_TS_atlas.sortedInTime_model.nc'); %quick and dirty plot of profiles locations figureL; ii=find(~isnan(MITprof.prof_T(:,1))); plot(MITprof.prof_lon(ii),MITprof.prof_lat(ii),'b.'); hold on; ii=find(~isnan(MITprof.prof_Testim(:,1))); plot(MITprof.prof_lon(ii),MITprof.prof_lat(ii),'ro'); %quick and dirty plot of model data figureL; qwckplot(mygrid.Depth.*mygrid.mskC(:,:,1)); title('quickplotting'); %plot of both using m_map figureL; m_map_gcmfaces(mygrid.Depth,0,{'myCaxis',[0 1e4]},{'myCmap','pink'}); ii=find(~isnan(MITprof.prof_T(:,1).*MITprof.prof_Testim(:,1))); m_map_gcmfaces({'plot',MITprof.prof_lon(ii),MITprof.prof_lat(ii),'g.'},0,{'doHold',1}); MITprof/ecco_v4/glo_oce_cs32_prof_prep.m0000644000435400001440000000523512062214535017777 0ustar gforgetusers %load time mean atlas to be turned into MITprof dirGrid='grid/'; gcmfaces_global; grid_load(dirGrid,6,'compact'); dirAtlas='./'; T=read2memory([dirAtlas 'some_T_atlas.bin'],[32 192 50 12]); S=read2memory([dirAtlas 'some_S_atlas.bin'],[32 192 50 12]); T=mean(T,4); S=mean(S,4); T=reshape(T,[32*192 50]); S=reshape(S,[32*192 50]); lon=convert2gcmfaces(mygrid.XC); lon=reshape(lon,[32*192 1]); lat=convert2gcmfaces(mygrid.YC); lat=reshape(lat,[32*192 1]); msk=convert2gcmfaces(mygrid.mskC); msk=reshape(msk,[32*192 50]); T=T.*msk; S=S.*msk; ii=find(~isnan(msk(:,1))); T=T(ii,:); S=S(ii,:); lon=lon(ii); lat=lat(ii); msk=msk(ii,:); descr='some time mean atlas'; %load sample data set dirSample='./'; MITprof=MITprof_load([dirSample 'argo_indian.nc']); %replace everything in it MITprof=rmfield(MITprof,{'prof_basin','prof_point','prof_Terr','prof_Serr','prof_Tflag','prof_Sflag'}); MITprof.np=length(lon); MITprof.nr=length(mygrid.RC); MITprof.nd=length(descr); MITprof.prof_depth=-mygrid.RC+1*(rand(MITprof.nr,1)-0.5); MITprof.prof_date=datenum([1948 1 1 16 0 0])+6/24*(rand(MITprof.np,1)-0.5); fprintf('sort by time and tile in a second version\n'); tmp1=datestr(MITprof.prof_date,30); MITprof.prof_YYYYMMDD=str2num(tmp1(:,1:8)); MITprof.prof_HHMMSS=str2num(tmp1(:,10:15)); MITprof.prof_lon=lon+1*(rand(MITprof.np,1)-0.5); MITprof.prof_lat=lat+1*(rand(MITprof.np,1)-0.5); MITprof.prof_descr=repmat({descr},[MITprof.np 1]); MITprof.list_descr={descr}; MITprof.prof_T=T; MITprof.prof_Testim=T; MITprof.prof_S=S; MITprof.prof_Sestim=S; tmp1=ones(MITprof.np,1)*nanstd(T,1); MITprof.prof_Tweight=1./tmp1./tmp1; MITprof.prof_Tweight(isnan(T))=0; tmp1=ones(MITprof.np,1)*nanstd(S,1); MITprof.prof_Sweight=1./tmp1./tmp1; MITprof.prof_Sweight(isnan(S))=0; %write to new file file_out='some_TS_atlas.nc'; mkdir step1; MITprof_write(['step1/' file_out],MITprof); %add grid information mkdir step2; profiles_prep_mygrid(file_out,'step1/','step2/',16,16); %second version that is sorted in time [tmp1,ii]=sort(MITprof.prof_date); MITprof.prof_date=MITprof.prof_date(ii); MITprof.prof_YYYYMMDD=MITprof.prof_YYYYMMDD(ii); MITprof.prof_HHMMSS=MITprof.prof_HHMMSS(ii); MITprof.prof_lon=MITprof.prof_lon(ii); MITprof.prof_lat=MITprof.prof_lat(ii); MITprof.prof_T=MITprof.prof_T(ii,:); MITprof.prof_Tweight=MITprof.prof_Tweight(ii,:); MITprof.prof_Testim=MITprof.prof_Testim(ii,:); MITprof.prof_S=MITprof.prof_S(ii,:); MITprof.prof_Sweight=MITprof.prof_Sweight(ii,:); MITprof.prof_Sestim=MITprof.prof_Sestim(ii,:); file_out='some_TS_atlas.sortedInTime.nc'; MITprof_write(['step1/' file_out],MITprof); profiles_prep_mygrid(file_out,'step1/','step2/',16,16); MITprof/ecco_v4/insitu_cost.m0000644000435400001440000002035112266764201016027 0ustar gforgetusersfunction []=insitu_cost(doComp,varargin); %object: computes or displays cost function statistics %input: doComp states whether to compute & save (1) or load & display (0) %optional must take the following form {'name',param1,param2,...} Active ones are % {'dirData',dirData} is the data subdirectory name ('profiles/output/' by default) % {'listData',data1,data2,...} where data1 e.g. is 'argo_indian.nc' % {'listVar',var1,var2} where var1 and var2 are 'T' and 'S' % {'years',year0,year1} to limit computation to [year0 year1] interval % {'dirMat',dirMat} where dirMat is the output subdirectory ('mat/' by default) % {'suffMat',suffMat} is the mat file suffix ('all' by default) % {'dirTex',dirTex} where dirTex is the tex directory ('tex/' by default) % {'nameTex',nameTex} is the tex file name ('myPlots' by default) % {'addToTex',addToTex} states whether (1) or not (0 default) to % augment an ongoing tex file (see write2tex.m, dirTex) % %example: insitu_cost('./',1,{'listData','argo_in*'}); %load paths and grid: %-------------------- global mygrid; if isempty(mygrid); grid_load('GRID/',5,'compact'); end; %set more optional paramaters to default values global myparms; year0=myparms.yearInAve(1); year1=myparms.yearInAve(2); listData={'argo_*_1992_to_2007*','argo_*_2008_to_2010*',... 'argo_*_2011_to_2012*','climode_*',... 'ctd_*','itp_*','seals_*','xbt_*'}; listVar={'T','S'}; listBas={'atlExt','pacExt','indExt','arct'}; if sum([90 1170]~=mygrid.ioSize)>0; listBas={}; end; listBasTxt=''; for bb=1:length(listBas); listBasTxt=[listBasTxt ' ' listBas{bb} '*']; end; %shorter test case: listData={'argo_in*'}; listVar={'T'}; dirData='/profiles/output/'; dirMat='mat/'; suffMat='_all'; dirTex='tex/'; addToTex=0; nameTex='myPlots'; %set more optional paramaters to user defined values for ii=1:nargin-1; if strcmp(varargin{ii}{1},'listData'); listData={varargin{ii}{2:end}}; elseif strcmp(varargin{ii}{1},'listVar'); listVar={varargin{ii}{2:end}}; elseif strcmp(varargin{ii}{1},'years'); year0=varargin{ii}{2}; year1=varargin{ii}{3}; elseif strcmp(varargin{ii}{1},'dirMat'); dirMat=varargin{ii}{2}; elseif strcmp(varargin{ii}{1},'suffMat'); suffMat=['_' varargin{ii}{2}]; elseif strcmp(varargin{ii}{1},'dirTex'); dirTex=varargin{ii}{2}; elseif strcmp(varargin{ii}{1},'addToTex'); addToTex=varargin{ii}{2}; elseif strcmp(varargin{ii}{1},'nameTex'); nameTex=varargin{ii}{2}; elseif strcmp(varargin{ii}{1},'dirData'); dirData=varargin{ii}{2}; else; warning('inputCheck:insitu_cost',... ['unknown option ''' varargin{ii}{1} ''' was ignored']); end; end; if doComp; %time limits: date0=datenum(year0,1,1); date1=datenum(year1,12,31); for vv=1:length(listVar); varCur=listVar{vv}; %get the cost square root: [MITprof]=MITprof_stats_load([dirData],listData,varCur); %mask out values that are not in year range: ii=find(MITprof.prof_datedate1); MITprof.prof(ii,:)=NaN; %mean and median: costCur=[nanmean(MITprof.prof(:).^2) nanmedian(MITprof.prof(:).^2)]; fprintf('mean cost for %s: %0.3g (median: %0.3g) \n',varCur,costCur); eval(['costAve' varCur '.mean=costCur(1);']); eval(['costAve' varCur '.median=costCur(2);']); %depth/time mean cost: tmp_date=(MITprof.prof_date-date0)/365; % [x,y,z,n]=MITprof_stats(MITprof.prof_depth,MITprof.prof_depth,... [x,y,z,n]=MITprof_stats(MITprof.prof_depth,[0:200:1000 1500:500:6000],... tmp_date,[0:1/4:1+(year1-year0)],'mean',MITprof.prof.^2); z(n==0)=NaN; n(n==0)=NaN; eval(['depthTimeCost' varCur '.x=x;']); eval(['depthTimeCost' varCur '.y=y;']); eval(['depthTimeCost' varCur '.z=z;']); eval(['depthTimeCost' varCur '.n=n;']); %latitudinal distribution: [x,y,z,n]=MITprof_stats(MITprof.prof_lat,[-90:5:90],MITprof.prof,[-5:0.25:5]); z(n==0)=NaN; n(n==0)=NaN; eval(['misfitDistrib' varCur '.x=x;']); eval(['misfitDistrib' varCur '.y=y;']); eval(['misfitDistrib' varCur '.z=z;']); eval(['misfitDistrib' varCur '.n=n;']); %upper ocean temporal distribution for bb=1:length(listBas); for ll=1:3; bbb=listBas{bb}; if ll==1; Lmin=-90; Lmax=-25; txt=[bbb '_90S25S_misDis' varCur]; elseif ll==2; Lmin=-25; Lmax=25; txt=[bbb '_25S25N_misDis' varCur]; elseif ll==3; Lmin=25; Lmax=90; txt=[bbb '_25N90N_misDis' varCur]; end; msk=v4_basin(bbb); msk(mygrid.YCLmax)=0; % msk=convert2array(msk); MITprof.prof_msk=msk(MITprof.prof_point); MITprofSub=MITprof_subset(MITprof,'msk',1,'depth',[0 700]); % tmp_date=(MITprofSub.prof_date-date0)/365; [x,y,z,n]=MITprof_stats(tmp_date,[0:1/4:1+(year1-year0)],MITprofSub.prof,[-5:0.25:5]); z(n==0)=NaN; n(n==0)=NaN; eval([txt '.x=x;']); eval([txt '.y=y;']); eval([txt '.z=z;']); eval([txt '.n=n;']); end; end; end; if ~isdir([dirMat 'cost/']); mkdir([dirMat 'cost/']); end; eval(['save ' dirMat 'cost/insitu_cost' suffMat '.mat costAve* misfitDistrib* depthTimeCost* year* ' ... 'listData listVar listBas ' listBasTxt ';']); else;%display result if isdir([dirMat 'cost/']); dirMat=[dirMat 'cost/']; end; eval(['load ' dirMat 'insitu_cost' suffMat '.mat;']); figureL; for vv=1:length(listVar); varCur=listVar{vv}; eval(['costCur=[costAve' varCur '.mean costAve' varCur '.median];']); eval(['x=depthTimeCost' varCur '.x;']); eval(['y=depthTimeCost' varCur '.y;']); eval(['z=depthTimeCost' varCur '.z;']); eval(['n=depthTimeCost' varCur '.n;']); z(n<1e2)=NaN; y=y+year0-1; subplot(2,length(listVar),vv); depthStretchPlot('pcolor',{y,x,z},[0:200:1000 1500:500:6000],[0 1000 4000]); caxis([0 8]); shading flat; colorbar; ylabel('depth (in m)'); title(sprintf('mean cost for %s: %0.3g (median: %0.3g)',varCur,costCur)); %latitudinal distribution: eval(['x=misfitDistrib' varCur '.x;']); eval(['y=misfitDistrib' varCur '.y;']); eval(['z=misfitDistrib' varCur '.z;']); eval(['n=misfitDistrib' varCur '.n;']); tmp1=(nansum(n,2)>1e4)*ones(1,size(n,2)); z(tmp1==0)=NaN; subplot(2,length(listVar),vv+length(listVar)); contourf(x,y,z,[0:0.05:0.5]); grid on; caxis([0 0.5]); colorbar; ylabel('normalized misfit'); xlabel('latitude'); title('pdf'); end; myCaption={'Cost function (top) for in situ profiles, as a function of depth and time. ',... 'Distribution of normalized misfits (bottom) as a function of latitude. For T (left) and S (right).'}; if addToTex; write2tex([dirTex '/' nameTex '.tex'],2,myCaption,gcf); end; if ~isempty(listBas); ii=0; ii=ii+1; listPanels(ii).bas='atlExt'; listPanels(ii).ll=3; ii=ii+1; listPanels(ii).bas='pacExt'; listPanels(ii).ll=3; ii=ii+1; listPanels(ii).bas='arct'; listPanels(ii).ll=3; ii=ii+1; listPanels(ii).bas='atlExt'; listPanels(ii).ll=2; ii=ii+1; listPanels(ii).bas='pacExt'; listPanels(ii).ll=2; ii=ii+1; listPanels(ii).bas='indExt'; listPanels(ii).ll=2; ii=ii+1; listPanels(ii).bas='atlExt'; listPanels(ii).ll=1; ii=ii+1; listPanels(ii).bas='pacExt'; listPanels(ii).ll=1; ii=ii+1; listPanels(ii).bas='indExt'; listPanels(ii).ll=1; for vv=1:length(listVar); varCur=listVar{vv}; figureL; for ii=1:9; bbb=listPanels(ii).bas; ll=listPanels(ii).ll; if ll==1; Lmin=-90; Lmax=-25; txt=[bbb '_90S25S_misDis' varCur]; elseif ll==2; Lmin=-25; Lmax=25; txt=[bbb '_25S25N_misDis' varCur]; elseif ll==3; Lmin=25; Lmax=90; txt=[bbb '_25N90N_misDis' varCur]; end; eval(['x=' txt '.x;']); eval(['y=' txt '.y;']); eval(['z=' txt '.z;']); eval(['n=' txt '.n;']); x=x+year0-1; tmp1=(nansum(n,2)>1e4)*ones(1,size(n,2)); z(tmp1==0)=NaN; subplot(3,3,ii); contourf(x,y,z,[0:0.05:0.5]); grid on; caxis([0 0.5]); colorbar; title(txt,'Interpreter','none'); %title([txt ', normalized misfit pdf'],'Interpreter','none'); if mod(ii,3)==1; ylabel('normalized misfit'); end; %if ii<=6; set(gca,'XTick',[]); end; end; myCaption={'Distribution of normalized misfits per basin (panel) as ',... 'a function of latitude, for ',varCur}; if addToTex; write2tex([dirTex '/' nameTex '.tex'],2,myCaption,gcf); end; end; end; end; MITprof/ecco_v4/insitu_diags.m0000644000435400001440000000277412365750066016163 0ustar gforgetusersfunction []=insitu_diags(dirMat,doComp,dirTex,nameTex); %object: driver for insitu_misfit and insitu_cost %inputs: dirMat is the directory where diagnozed .mat files will be saved % -> set it to '' to use the default [dirModel 'mat/'] % doComp states whether to compute (1) or display (0) % dirTex is the directory where tex and fig files will be created % nameTex is the tex file name (default : 'myPlots') % %notes : MITprof files will be used from the myenv.profiles directory % or [dirMat '/profiles/output/'] is myenv.profiles is missing gcmfaces_global; dirMat=[dirMat '/']; if isfield(myenv,'profiles'); dirData=myenv.profiles; else; dirData=[dirMat '/profiles/output/']; end; while ~isdir(dirData)&doComp; fprintf(['directory : ' dirData '\n']) dirData=input(['does not exist. Specify directory of nc file : \n']); end; dirMat={'dirMat',dirMat}; dirData={'dirData',dirData}; if isempty(who('dirTex')); addToTex={'addToTex',0}; dirTex={'dirTex',''}; nameTex={'nameTex',''}; else; if ~ischar(dirTex); error('mis-specified dirTex'); end; if dirTex(1)~='/'; dirTex=[pwd '/' dirTex]; end; %make full path addToTex={'addToTex',1}; dirTex={'dirTex',[dirTex '/']}; if isempty(who('nameTex')); nameTex='myPlots'; end; nameTex={'nameTex',nameTex}; end; if doComp; insitu_misfit(1,dirData,dirMat); insitu_cost(1,dirData,dirMat); else; insitu_misfit(0,dirMat,addToTex,dirTex,nameTex); insitu_cost(0,dirMat,addToTex,dirTex,nameTex); end; MITprof/profiles_process_init.m0000644000435400001440000000247112365556377016566 0ustar gforgetusersclear all gcmfaces_global; myenv.verbose=1; fprintf('\n\n basic MITprof test: started... \n'); if myenv.verbose; fprintf('\nadding directories to your path\n'); fprintf('===============================\n\n') end; MITprof_global; if myenv.verbose; fprintf('\nloading reference grid and climatology\n') fprintf('========================================\n\n') end; profiles_prep_load_fields; if myenv.verbose; fprintf('\nrunning main program on sample data sets\n') fprintf('========================================\n\n') end; %select the data source (and specific params) => wod05 sample dataset=profiles_prep_select('wod05','90CTD'); %process it profiles_prep_main(dataset); % fprintf(['\n\n wod05 sample -- done -- ' dataset.dirOut dataset.fileOut '.nc was created \n\n']); %select the data source (and specific params) => argo sample dataset=profiles_prep_select('argo','indian'); %process it profiles_prep_main(dataset); % fprintf(['\n\nargo sample -- done -- ' dataset.dirOut dataset.fileOut '.nc was created \n\n']); %select the data source (and specific params) => odv sample dataset=profiles_prep_select('odv','ODVcompact_sample'); %process it profiles_prep_main(dataset); % fprintf(['\n\nodv sample -- done -- ' dataset.dirOut dataset.fileOut '.nc was created \n\n']); fprintf('\n basic MITprof test: completed. \n'); MITprof/README0000644000435400001440000000526711550676665012670 0ustar gforgetusers ==========to download this package and test run it as follows======== 1) Download and setup m_map and gcmfaces toolbox 2) Get MITprof toolbox setenv CVSROOT ':pserver:cvsanon@mitgcm.org:/u/gcmpack' cvs login ( enter the CVS password: "cvsanon" ) cvs co -d (profilesMatlabProcessing) MITgcm_contrib/gael/profilesMatlabProcessing 3) Download climatological fields, and put them in the directory (profilesMatlabProcessing)/climatology or set directory names in profiles_prep_load_fields.m in (profilesMatlabProcessing)/profiles_process_main_v2 to indicate where climatological fields must be found. 4) Initialize and test the configuration cd profilesMatlabProcessing matlab -nojvm ( type profiles_process_init) =======then you can process your own data as follow (see <= signs)=== profiles_prep_select.m - Encapsulate the data set information in the 'dataset' structure - Directories, included variables, etc. are specified here. => You append specs for your data set here. Included examples: argo and wod05. profiles_prep_load_fields.m - Load T-S atlases and variance atlas that will be used to detect outliers and to attribute least-squares weights (for ECCO purpose) => You need to get gcmfaces package and binary files for this part. profiles_read_wod05.m/profiles_read_argo.m - Encapsulate the that loads the data set in memory. - The data set file format specifics are handled here. - The calling sequence must be [varargout]=profile_read_wod05(dataset,nf,m); where 'dataset' is the aformentioned structure, nf is the current file index (relative to dataset.fileInList). If m is set to 0, then varargout must be the number of profiles/stations. If m is a profile index, then varargout must be the profileCur structure that contains the current profile/station. => You need to make one of those routines for your data set. The two profiles_read_wod05.m/profiles_read_argo.m provide you the blueprint. profiles_prep_convert.m - does conversions of pressure->depth, and insituT->potT, if needed. - profiles_prep_select.m specifies needed conversions in 'dataset'. - also switch [0 360] lon -> [-180 +180] lon, if needed. profiles_prep_locate.m - get the grid point index of the profiles (on the atlases grid). <= I need to upload gcmfaces_bindata profiles_prep_interp.m - interpolate to standard depth levels, as spec. in profiles_prep_select.m. profiles_prep_weights.m - compute instrumental + representation error profile. - instrumental error estimates (when available) are specified at read time (see profiles_read_argo.m). profiles_prep_tests.m - quality control/outlier detection. profiles_prep_write_nc.m store/write results to temporary .mat files, then final .nc file. MITprof/profiles_stats/0000755000435400001440000000000012375431055015023 5ustar gforgetusersMITprof/profiles_stats/MITprof_stats.m0000644000435400001440000000731612061752220017736 0ustar gforgetusersfunction [xh,yh,zh,varargout]=MITprof_pdf(x,xBinCenters,y,yBinCenters,varargin); %input: % x/y position vectors or 2D arrays % xBinCenters position bin centers % yBinCenters position bin centers % choiceStat [optional] type of statistic (pdf, hist, sum, mean, or var) % z [optional] data vector or 2D array % %note: all inputs are assumed to have be nan-masked accordingly % %output: % xh/yh are the position arrays for the historgam bin centers % zh is the 2D histogram warning('off','MATLAB:dsearch:DeprecatedFunction'); gcmfaces_global; if ~isfield(myenv,'useDelaunayTri'); myenv.useDelaunayTri=~isempty(which('DelaunayTri')); end; if nargin>4; choiceStat=varargin{1}; else; choiceStat='pdf'; end; if nargin>5; z=varargin{2}; else; z=[]; end; %take care of input dimensions: if size(x,1)==1; x=x'; end; if size(y,1)==1; y=y'; end; % if size(y,2)==1; %x is array => make sure y is so if size(x,2)==size(y,1); y=ones(size(x,1),1)*y'; else; y=y*ones(1,size(x,2)); end; end; % if size(x,2)==1; %y is array => make sure x is so if size(y,2)==size(x,1); x=ones(size(y,1),1)*x'; else; x=x*ones(1,size(y,2)); end; end; % if size(z,2)>1;%z is array => make sure x/y are so if size(x,2)==1&size(x,1)==size(z,1); x=x*ones(1,size(z,2)); end; if size(x,2)==1&size(x,1)==size(z,2); x=ones(size(z,1),1)*x'; end; % if size(y,2)==1&size(y,1)==size(z,1); y=y*ones(1,size(z,2)); end; if size(y,2)==1&size(y,1)==size(z,2); y=ones(size(z,1),1)*y'; end; end; if isempty(z); z=NaN*x; end;%to facilitate vector length tests %switch to vector form: x=x(:); y=y(:); z=z(:); %check vectors length: if length(x)~=length(y)|length(x)~=length(z)|length(y)~=length(z); error('inconsistent diemnsions of [x,y[,z]]'); end; %prepare output arrays: if size(xBinCenters,1)==1; xh=xBinCenters'; else; xh=xBinCenters; end; if size(yBinCenters,1)==1; yh=yBinCenters'; else; yh=yBinCenters; end; if size(xh,2)>1|size(yh,2)>1; error('inconsistent diemnsions of [xBinCenters yBinCenters]'); end; xh=xh*ones(1,size(yh,1)); yh=ones(size(xh,1),1)*yh'; %build the histogram if myenv.useDelaunayTri; %the new way, using DelaunayTri&nearestNeighbor mytri.TRI=DelaunayTri(xh(:),yh(:)); else; TRI=delaunay(xh,yh,{'QJ'}); nxy = prod(size(xh)); Stri=sparse(TRI(:,[1 1 2 2 3 3]),TRI(:,[2 3 1 3 1 2]),1,nxy,nxy); end; %compute grid point vector associated with lon/lat vectors if nargin>5; ii=find(~isnan(x.*y.*z)); else; ii=find(~isnan(x.*y)); end; x=x(ii); y=y(ii); z=z(ii); if myenv.useDelaunayTri; ik = mytri.TRI.nearestNeighbor(x,y); else; ik = dsearch(xh,yh,TRI,x,y,Stri); end; %compute bin sums: nh=zeros(size(xh)); if nargin>5; zh=nh; zh2=zh; end; for k=1:length(ik) nh(ik(k))=nh(ik(k))+1; if nargin>5; zh(ik(k))=zh(ik(k))+z(k); zh2(ik(k))=zh2(ik(k))+z(k)^2; end; end % k=1:length(ik) ii=find(nh(:)==0); nh(ii)=NaN; if nargin>5; zh(ii)=NaN; zh2(ii)=NaN; end; %compute output: if strcmp(choiceStat,'pdf'); %hist + normalization along second dimension zh=nh; zh(isnan(zh))=0; %normalize by total number of samples zh=zh./(nansum(zh,2)*ones(1,size(zh,2))); %normalize by delta(yh) => pdf tmp2=diff(yh,1,2); tmp2=0.5*(tmp2(:,1:end-1)+tmp2(:,2:end)); tmp2=[tmp2(:,1) tmp2 tmp2(:,end)]; zh=zh./tmp2; elseif strcmp(choiceStat,'hist'); zh=nh; elseif strcmp(choiceStat,'sum'); zh=zh; elseif strcmp(choiceStat,'mean'); zh=zh./nh; elseif strcmp(choiceStat,'var'); zh=zh2./nh-(zh./nh).^2; end; if nargout>3; varargout{1}=nh; else; varargout={}; end; %for debugging purposes: if 0; figure; pcolor(xh,yh,zh); colorbar; end; warning('on','MATLAB:dsearch:DeprecatedFunction'); MITprof/profiles_stats/MITprof_stats_load.m0000644000435400001440000001067612152675407020754 0ustar gforgetusersfunction [MITprof]=MITprof_stats_load(dirData,listData,varCur,varargin); %[MITprof]=MITprof_stats_load(dirData,listData,varCur,varargin); %object: loads a series of MITprof files, and computes % normalized misfits for one variable %input: dirData is the data directory name % listData is the data file list (e.g. {'argo_in*'} or {'argo_in*','argo_at*'} ) % varCur is 'T' or 'S' %optional : % EITHER normFactor (optional; double) is the normalization factor (1./prof_?weight by default) % OR varSpec (optional; char) is e.g. 'prof_T' or 'prof_Testim' %output: MITprof.prof is the normalized misfit %note: by assumption, all of the files in listData must share the same vertical grid normFactor=[]; varSpec=''; if nargin>3; if isnumeric(varargin{1}); normFactor=varargin{1}; end; if ischar(varargin{1}); varSpec=varargin{1}; end; end; useExtendedProfDepth=1; %develop listData (that may include wildcards) listData_bak=listData; listData={}; for ii=1:length(listData_bak); tmp1=dir([dirData listData_bak{ii}]); for jj=1:length(tmp1); ii2=length(listData)+1; listData{ii2}=tmp1(jj).name; end; end; %avoid duplicates listData=unique(listData); %loop over files for iFile=1:length(listData); fileData=dir([dirData listData{iFile}]); fileData=fileData.name; fprintf(['loading ' varCur ' from ' fileData '\n']); MITprofCur=MITprof_load([dirData fileData]); % fixes: if ~isfield(MITprofCur,'prof_S'); tmp1=NaN*MITprofCur.prof_T; MITprofCur.prof_S=tmp1; MITprofCur.prof_Sestim=tmp1; MITprofCur.prof_Sweight=tmp1; MITprofCur.prof_Sflag=[]; end; % fixes if ~isfield(MITprofCur,['prof_' varCur 'weight']); eval(['MITprofCur.prof_' varCur 'weight=1+0*MITprofCur.prof_' varCur ';']); end; if ~isempty(normFactor);%replace weights with normFactor eval(['tmp1=MITprofCur.prof_' varCur 'weight;']); tmp1(tmp1>0)=normFactor; eval(['MITprofCur.prof_' varCur 'weight=tmp1;']); end; if varCur=='T'; tmp1=(MITprofCur.prof_Testim-MITprofCur.prof_T).*sqrt(MITprofCur.prof_Tweight); else; tmp1=(MITprofCur.prof_Sestim-MITprofCur.prof_S).*sqrt(MITprofCur.prof_Sweight); end; %nan-mask tmp1(tmp1==0)=NaN; %replace non-masked values with varSpec? if ~isempty(varSpec); eval(['tmp2=MITprofCur.' varSpec ';']); tmp2(isnan(tmp1))=NaN; tmp1=tmp2; end; MITprofCur.prof=tmp1; listRm={'prof_T','prof_Testim','prof_Tweight','prof_Tflag','prof_Terr',... 'prof_S','prof_Sestim','prof_Sweight','prof_Sflag','prof_Serr',... 'prof_D','prof_Destim',... 'prof_T_SOSE59','prof_S_SOSE59','prof_madt_aviso',... 'prof_DRHODR','prof_DRHODRestim','prof_DRHODRweight',... 'prof_RHOP','prof_RHOPestim','prof_RHOPweight'}; for iRm=1:length(listRm); if isfield(MITprofCur,listRm{iRm}); MITprofCur=rmfield(MITprofCur,listRm{iRm}); end; end; MITprofCur.prof_date=datenum(num2str(MITprofCur.prof_YYYYMMDD*1e6+MITprofCur.prof_HHMMSS),'yyyymmddHHMMSS'); %old: ii=find(MITprofCur.prof_datedatenum(2008,12,27)); MITprofCur.prof(ii,:)=NaN; if useExtendedProfDepth; %use extended standard depth vector all_depth=[ 0 5 10 15 20 25 30 35 45 50 55 65 75 85 95 100 ... 105 115 125 135 145 150 155 165 175 185 200 220 240 250 260 280 ... 300 320 340 360 380 400 420 440 460 480 500 550 600 650 700 750 ... 800 850 900 950 1000 1100 1200 1300 1400 1500 1600 1700 1750 1800 1900 2000 2100 ... 2200 2300 2400 2500 2600 2700 2800 2900 3000 3100 3200 3300 3400 3500 3600 3700 ... 3800 3900 4000 4100 4200 4300 4400 4500 4600 4700 4800 4900 5000 5100 5200 5300 ... 5400 5500 5600 5700 5800 5900 6000 6500 7000 7500 8000 8500 9000]; k_depth=NaN*zeros(1,MITprofCur.nr); for kk=1:MITprofCur.nr; k_depth(kk)=find(MITprofCur.prof_depth(kk)==all_depth); end; all_prof=NaN*ones(MITprofCur.np,length(all_depth)); all_prof(:,k_depth)=MITprofCur.prof; MITprofCur.prof=all_prof; MITprofCur.nr=length(all_depth); MITprofCur.prof_depth=all_depth; end; if iFile==1; MITprof=MITprofCur; else; MITprof=MITprof_concat(MITprof,MITprofCur); end; clear MITprofCur; end; MITprof/profiles_misc/0000755000435400001440000000000012375431055014620 5ustar gforgetusersMITprof/profiles_misc/model_addinMITprof.m0000644000435400001440000000275611551411221020474 0ustar gforgetusersfunction model_addinMITprof(ncfile,model,varargin) % function model_addinMITprof(ncfile,model) % add hydrographic profiles from a model interpolated on profile % positions available in a MITprof netcdf file. % % fileIn: path (absolute or relative) to MITprof netcdf file % model is a string used to select the model to be loaded % 'OCCA' : ECCOv4 grid + OCCA atlas % 'SOSE59' : SOSE59 grid + atlas % process file name [pathstr, name, ext] = fileparts(ncfile); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end if isempty(ext) | ~strcmp(ext,'.nc'), ext='.nc'; end ncfile=[pathstr '/' name ext]; % load profiles M=MITprof_load(ncfile); % interpolate model M=model_interp(M,model); % add fields fillval=double(-9999); T=getfield(M,['prof_T_' model])'; T(isnan(T))=fillval; MITprof_addVar(ncfile,['prof_T_' model],'double',{'iDEPTH','iPROF'},T); S=getfield(M,['prof_S_' model])'; S(isnan(S))=fillval; MITprof_addVar(ncfile,['prof_S_' model],'double',{'iDEPTH','iPROF'},S); % add attributes nc=ncopen(ncfile,'write'); ncaddAtt(nc,['prof_T_' model],'long_name',['pot. temp. model ' model]); ncaddAtt(nc,['prof_T_' model],'units','degree C'); ncaddAtt(nc,['prof_T_' model],'missing_value',fillval); ncaddAtt(nc,['prof_T_' model],'_FillValue',fillval); ncaddAtt(nc,['prof_S_' model],'long_name',['salinity model ' model]); ncaddAtt(nc,['prof_S_' model],'units','psu'); ncaddAtt(nc,['prof_S_' model],'missing_value',fillval); ncaddAtt(nc,['prof_S_' model],'_FillValue',fillval); ncclose(nc); MITprof/profiles_misc/aviso_addinMITprof.m0000644000435400001440000000373012365540306020521 0ustar gforgetusersfunction aviso_addinMITprof(ncfile) % function aviso_addinMITprof(ncfile) % add MADT (Maps of Absolute Dynamic Topography) interpolated on profile % positions available in a MITprof netcdf file. % Use OpenDap, through the loaddap function. % % fileIn: path (absolute or relative) to MITprof netcdf file % model is a string used to select the model to be loaded % 'OCCA' : ECCOv4 grid + OCCA atlas % 'SOSE59' : SOSE59 grid + atlas gcmfaces_global; % process file name [pathstr, name, ext] = fileparts(ncfile); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end if isempty(ext) | ~strcmp(ext,'.nc'), ext='.nc'; end ncfile=[pathstr '/' name ext]; if isempty(which('loaddap')), error('loaddap toolbox must be installed'); end % load profiles nc=ncopen(ncfile,'write'); vars=ncvars(nc); ncclose(nc); if ismember('prof_madt_aviso',vars) M=MITprof_load(ncfile,{'prof_date','prof_lat','prof_lon','prof_madt_aviso'}); madt=M.prof_madt_aviso; else fillval=double(-9999); nc=ncopen(ncfile,'write'); ncaddVar(nc,'prof_madt_aviso','double',{'iPROF'}); ncaddAtt(nc,'prof_madt_aviso','long_name',['MADT AVISO']); ncaddAtt(nc,'prof_madt_aviso','units','m'); ncaddAtt(nc,'prof_madt_aviso','missing_value',fillval); ncaddAtt(nc,'prof_madt_aviso','_FillValue',fillval); ncclose(nc); M=MITprof_load(ncfile,{'prof_date','prof_lat','prof_lon'}); madt=M.prof_lat*NaN; end % load and write data I=find(isnan(madt)); loc=[]; buffer=1000; for kk=1:ceil(length(I)/buffer), if myenv.verbose; disp([num2str(kk) ' out of ' num2str(length(I)/buffer)]); end % extract data J=I((kk-1)*buffer+1:min([length(I),kk*buffer])); loc.lat=M.prof_lat(J); loc.lon=M.prof_lon(J); loc.time=M.prof_date(J); grid_aviso=aviso_get_grid; madt_temp=aviso_get_madt(loc,grid_aviso); % write fields madt(J)=madt_temp; M.prof_madt_aviso=madt; MITprof_write(ncfile,M,{'prof_madt_aviso'}); end MITprof/profiles_misc/ncaddVar.m0000644000435400001440000000224511554371626016530 0ustar gforgetusersfunction ncaddVar(ncid,varname,xtype,dimlist); % function ncaddVar(ncid,varname,xtype,dimlist); % add a variable in an existing netcdf file. % The netcdf file must be open in 'write' mode. global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if useNativeMatlabNetcdf; if isempty(dimlist), error('ncaddVar error: no dimension allocated'); end iDim=[]; for ii=1:length(dimlist), iDim(ii)=netcdf.inqDimID(ncid,dimlist{ii}); end netcdf.reDef(ncid); netcdf.defVar(ncid,varname,xtype,iDim); netcdf.endDef(ncid); else;%try to use old mex stuff % inverse the order of list dimensions dimlist=fliplr(dimlist); switch length(dimlist) case 1, eval(sprintf('ncid{''%s''}=nc%s(''%s'');',varname,xtype,dimlist{1})); case 2, eval(sprintf('ncid{''%s''}=nc%s(''%s'',''%s'');',varname,xtype,dimlist{1},dimlist{2})); case 3, eval(sprintf('ncid{''%s''}=nc%s(''%s'',''%s'',''%s'');',varname,xtype,dimlist{1},dimlist{2},dimlist{3})); otherwise error('ncaddVar: number of dimension > 3'); end end; MITprof/profiles_misc/MITprof_concat.m0000644000435400001440000000214411520177122017637 0ustar gforgetusersfunction [MITprof]=MITprof_concat(MITprof1,MITprof2); % [MITprof]=MITprof_concat(MITprof1,MITprof2); % concatenates MITprof1 and MITprof2, which mut % have the same vertical grid % MITprof=MITprof1; fldNames=fieldnames(MITprof); %check that the vertical grids of MITprof1 and MITprof2 are the same: %-------------------------------------------------------------------- tmp1=MITprof1.prof_depth; tmp2=MITprof2.prof_depth; if length(tmp1)~=length(tmp2); error('vertical grids differ => cannot concatenate'); else; if sum(tmp1~=tmp2)>0; error('vertical grids differ => cannot concatenate'); end; end; %concatenate: %------------ for iFld=1:length(fldNames); eval(['tmp1=MITprof1.' fldNames{iFld} ';']); eval(['tmp2=MITprof2.' fldNames{iFld} ';']); if ~strcmp(fldNames{iFld},'prof_depth'); tmp1=[tmp1;tmp2]; end; eval(['MITprof.' fldNames{iFld} '=tmp1;']); end; %add a couple things: %-------------------- MITprof.np=length(MITprof.prof_lon); MITprof.nr=length(MITprof.prof_depth); MITprof.list_descr=unique(MITprof.prof_descr); MITprof.nd=length(MITprof.list_descr); MITprof/profiles_misc/aviso_get_grid.m0000644000435400001440000000173111551702447017766 0ustar gforgetusersfunction grid_aviso=aviso_get_grid % function [grid_aviso]=aviso_get_grid % load grid using loaddap interface to opendap website: % http://opendap.aviso.oceanobs.com/thredds/dodsC/dataset-duacs-dt-ref-global-merged-madt-h % % output: grid_aviso is a structure % grid_aviso.NbLatitudes : latitudes % grid_aviso.NbLongitudes : longitudes % grid_aviso.time : time (matlab julian day) % grid_aviso.Nlat : number of latitudes % grid_aviso.Nlon : number of longitudes % grid_aviso.Ntime : number of time samples URL='http://opendap.aviso.oceanobs.com/thredds/dodsC/dataset-duacs-dt-ref-global-merged-madt-h?NbLatitudes[0:1:914],NbLongitudes[0:1:1079],time[0:1:911]'; grid_aviso=loaddap(URL); if isempty(grid_aviso), error('access problem to aviso data with opendap'); end grid_aviso.time=grid_aviso.time/24+datenum([1950 01 01 0 0 0]); grid_aviso.Nlat=length(grid_aviso.NbLatitudes); grid_aviso.Nlon=length(grid_aviso.NbLongitudes); grid_aviso.Ntime=length(grid_aviso.time); MITprof/profiles_misc/MITprof_struct.m0000644000435400001440000000341212152673524017724 0ustar gforgetusersfunction [MITprof]=MITprof_struct(nProf,dataset,varargin); % [MITprof]=MITprof_struct; % create an empty struct variable using the format MITprof % nProf: number of profiles % prof_depth: list of depth levels % list_var: specify name of created fields % % list of fields always created: % prof_depth [nDepth x 1] % prof_descr {nProf x 1} % prof_date [nProf x 1] % prof_YYYYMMDD [nProf x 1] % prof_HHMMSS [nProf x 1] % prof_lon [nProf x 1] % prof_lat [nProf x 1] % prof_basin [nProf x 1] % prof_point [nProf x 1] % np, nr, list_descr, nd % % list of fields created by default, if list_var not specified % prof_T, prof_Tflag, prof_Terr, prof_Tweight, prof_Testim % prof_S, prof_Sflag, prof_Serr, prof_Sweight, prof_Sestim % array size: [nProf x nLev] prof_depth=dataset.z_std; list_vars={'prof_T','prof_Tweight','prof_Testim','prof_Terr','prof_Tflag',... 'prof_S','prof_Sweight','prof_Sestim','prof_Serr','prof_Sflag'}; if ~strcmp(dataset.coord,'depth'); list_vars={list_vars{:},'prof_D','prof_Destim'}; end; if nargin>2, list_vars=varargin{1}; end MITprof=[]; nLev=length(prof_depth); prof_depth=reshape(prof_depth,length(prof_depth),1); MITprof.prof_depth=prof_depth; MITprof.prof_date=zeros(nProf,1); MITprof.prof_YYYYMMDD=zeros(nProf,1); MITprof.prof_HHMMSS=zeros(nProf,1); MITprof.prof_lon=zeros(nProf,1); MITprof.prof_lat=zeros(nProf,1); MITprof.prof_basin=zeros(nProf,1); MITprof.prof_point=zeros(nProf,1); MITprof.prof_descr=cell(nProf,1); for ii=1:length(list_vars), MITprof=setfield(MITprof,list_vars{ii},zeros(nProf,nLev)); end MITprof.np=nProf; MITprof.nr=nLev; MITprof.nd=0; MITprof.list_descr={}; MITprof/profiles_misc/sw_ptmp.m0000644000435400001440000000711711460113440016462 0ustar gforgetusersfunction PT = sw_ptmp(S,T,P,PR) % SW_PTMP Potential temperature %=========================================================================== % SW_PTMP $Revision: 1.1 $ $Date: 2010/10/21 19:40:16 $ % Copyright (C) CSIRO, Phil Morgan 1992. % % USAGE: ptmp = sw_ptmp(S,T,P,PR) % % DESCRIPTION: % Calculates potential temperature as per UNESCO 1983 report. % % INPUT: (all must have same dimensions) % S = salinity [psu (PSS-78) ] % T = temperature [degree C (IPTS-68)] % P = pressure [db] % PR = Reference pressure [db] % (P & PR may have dims 1x1, mx1, 1xn or mxn for S(mxn) ) % % OUTPUT: % ptmp = Potential temperature relative to PR [degree C (IPTS-68)] % % AUTHOR: Phil Morgan 92-04-06 (morgan@ml.csiro.au) % % DISCLAIMER: % This software is provided "as is" without warranty of any kind. % See the file sw_copy.m for conditions of use and licence. % % REFERENCES: % Fofonoff, P. and Millard, R.C. Jr % Unesco 1983. Algorithms for computation of fundamental properties of % seawater, 1983. _Unesco Tech. Pap. in Mar. Sci._, No. 44, 53 pp. % Eqn.(31) p.39 % % Bryden, H. 1973. % "New Polynomials for thermal expansion, adiabatic temperature gradient % and potential temperature of sea water." % DEEP-SEA RES., 1973, Vol20,401-408. %========================================================================= % CALLER: general purpose % CALLEE: sw_adtg.m %------------- % CHECK INPUTS %------------- if nargin ~= 4 error('sw_ptmp.m: Must pass 4 parameters ') end %if % CHECK S,T,P dimensions and verify consistent [ms,ns] = size(S); [mt,nt] = size(T); [mp,np] = size(P); [mpr,npr] = size(PR); % CHECK THAT S & T HAVE SAME SHAPE if (ms~=mt) | (ns~=nt) error('check_stp: S & T must have same dimensions') end %if % CHECK OPTIONAL SHAPES FOR P if mp==1 & np==1 % P is a scalar. Fill to size of S P = P(1)*ones(ms,ns); elseif np==ns & mp==1 % P is row vector with same cols as S P = P( ones(1,ms), : ); % Copy down each column. elseif mp==ms & np==1 % P is column vector P = P( :, ones(1,ns) ); % Copy across each row elseif mp==ms & np==ns % PR is a matrix size(S) % shape ok else error('check_stp: P has wrong dimensions') end %if [mp,np] = size(P); % CHECK OPTIONAL SHAPES FOR PR if mpr==1 & npr==1 % PR is a scalar. Fill to size of S PR = PR(1)*ones(ms,ns); elseif npr==ns & mpr==1 % PR is row vector with same cols as S PR = PR( ones(1,ms), : ); % Copy down each column. elseif mpr==ms & npr==1 % P is column vector PR = PR( :, ones(1,ns) ); % Copy across each row elseif mpr==ms & npr==ns % PR is a matrix size(S) % shape ok else error('check_stp: PR has wrong dimensions') end %if [mpr,npr] = size(PR); % IF ALL ROW VECTORS ARE PASSED THEN LET US PRESERVE SHAPE ON RETURN. Transpose = 0; if mp == 1 % row vector P = P(:); T = T(:); S = S(:); PR = PR(:); Transpose = 1; end %if %***check_stp %------ % BEGIN %------ % theta1 del_P = PR - P; del_th = del_P.*sw_adtg(S,T,P); th = T + 0.5*del_th; q = del_th; % theta2 del_th = del_P.*sw_adtg(S,th,P+0.5*del_P); th = th + (1 - 1/sqrt(2))*(del_th - q); q = (2-sqrt(2))*del_th + (-2+3/sqrt(2))*q; % theta3 del_th = del_P.*sw_adtg(S,th,P+0.5*del_P); th = th + (1 + 1/sqrt(2))*(del_th - q); q = (2 + sqrt(2))*del_th + (-2-3/sqrt(2))*q; % theta4 del_th = del_P.*sw_adtg(S,th,P+del_P); PT = th + (del_th - 2*q)/6; if Transpose PT = PT'; end %if return %========================================================================= MITprof/profiles_misc/ncsave.m0000644000435400001440000000123111465074756016264 0ustar gforgetusersfunction [] = ncsave(theNetCDFFile, varargin); global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if useNativeMatlabNetcdf; nc=netcdf.open(theNetCDFFile,'write'); else;%try to use old mex stuff nc=netcdf(theNetCDFFile,'write'); end; for ii=1:nargin-1; nameCur=inputname(ii+1); if useNativeMatlabNetcdf; vv = netcdf.inqVarID(nc,nameCur); netcdf.putVar(nc,vv,varargin{ii}'); else;%try to use old mex stuff nc{nameCur}(:)=varargin{ii}; end; end; if useNativeMatlabNetcdf; netcdf.close(nc); else;%try to use old mex stuff close(nc); end; MITprof/profiles_misc/ncload.m0000644000435400001440000000430011576163231016233 0ustar gforgetusersfunction [] = ncload(fileIn, varargin); % ncload -- Load NetCDF variables. % ncload('fileIn', 'var1', 'var2', ...) loads the % given variables of 'fileIn' into the Matlab % workspace of the "caller" of this routine. If no names % are given, all variables are loaded. global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; f = ncopen(fileIn, 'nowrite'); if isempty(f), return, end vars=ncvars(f); if isempty(varargin); varargin = vars; end; if (useNativeMatlabNetcdf); for i = 1:length(varargin) if sum(strcmp(vars,varargin{i}))>0; %get variable varid = netcdf.inqVarID(f,varargin{i}); aa=netcdf.getVar(f,varid); %inverse the order of dimensions bb=length(size(aa)); aa=permute(aa,[bb:-1:1]); %replace missing value with NaN [atts]=ncatts(f,varid); if strcmp(atts,'missing_value')&isreal(aa); spval = double(netcdf.getAtt(f,varid,'missing_value')); elseif strcmp(atts,'_FillValue')&isreal(aa); spval = double(netcdf.getAtt(f,varid,'_FillValue')); else; spval=[]; end; if ~isempty(spval); aa(aa==spval)=NaN; end; else; aa=[]; end; assignin('caller', varargin{i}, aa) end else;%try to use old mex stuff for i = 1:length(varargin) if ~isstr(varargin{i}), varargin{i} = inputname(i+1); end oldfld = f{varargin{i}}(:); spval = f{varargin{i}}.missing_value(:); if isempty(spval); spval = f{varargin{i}}.FillValue_(:); end fld = oldfld; if ~isempty(spval)&~ischar(fld); replace = find(oldfld == spval); nreplace = length(replace); if nreplace>0 fld(replace) = NaN*ones(1,nreplace); end %if end %if %NaN-substitution messes up backward compatibility so I comment it out % assignin('caller', varargin{i}, fld); %and revert to oldfld assignin('caller', varargin{i}, oldfld) end end ncclose(f); MITprof/profiles_misc/ncgetFillVal.m0000644000435400001440000000172411553640622017353 0ustar gforgetusersfunction [FillVal]=ncgetFillVal(ncid,varname); % [FillVal]=ncgetFillVal(ncid,varname) % return the missing_value or _FillValue of varname % return an error if varname does not exist global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; FillVal=[]; if useNativeMatlabNetcdf; varid = netcdf.inqVarID(ncid,varname); [varname,xtype,dimids,natts] = netcdf.inqVar(ncid,varid); [atts]=ncatts(ncid,varid); if any(ismember(atts,'missing_value')) FillVal = netcdf.getAtt(ncid,varid,'missing_value'); elseif any(ismember(atts,'_FillValue')) FillVal = netcdf.getAtt(ncid,varid,'_FillValue'); end if strcmp(xtype,'single') | strcmp(xtype,'double') FillVal=double(FillVal); end else eval(['FillVal = ncid{''' varname '''}.missing_value(:);']); if isempty(FillVal); eval(['FillVal = ncid{''' varname '''}.FillValue_(:);']); end end MITprof/profiles_misc/ncdefVar.m0000644000435400001440000000201511551702316016520 0ustar gforgetusersfunction varid = ncdefVar(ncid,varname,xtype,dimlist); % add a variable in a netcdf file. global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if useNativeMatlabNetcdf; if isempty(dimlist), error('ncdefVar error: no dimension allocated'); end iDim=[]; for ii=1:length(dimlist), iDim(ii)=netcdf.inqDimID(ncid,dimlist{ii}); end netcdf.defVar(ncid,varname,xtype,iDim); else;%try to use old mex stuff % inverse the order of list dimensions dimlist=fliplr(dimlist); switch length(dimlist) case 1, eval(sprintf('ncid{''%s''}=nc%s(''%s'');',varname,xtype,dimlist{1})); case 2, eval(sprintf('ncid{''%s''}=nc%s(''%s'',''%s'');',varname,xtype,dimlist{1},dimlist{2})); case 3, eval(sprintf('ncid{''%s''}=nc%s(''%s'',''%s'',''%s'');',varname,xtype,dimlist{1},dimlist{2},dimlist{3})); otherwise error('ncdefVar: number of dimension > 3'); end end; MITprof/profiles_misc/nccreate.m0000644000435400001440000000066711550664466016603 0ustar gforgetusersfunction [nc] = nccreate(theNetCDFFile, varargin); % create a new netcdf file. % mode: 'write','nowrite' global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; mode='NC_NOCLOBBER'; if nargin>1, mode=varargin{1}; end if useNativeMatlabNetcdf; nc=netcdf.create(theNetCDFFile,mode); else;%try to use old mex stuff nc=netcdf(theNetCDFFile,mode); end; MITprof/profiles_misc/figureL.m0000644000435400001440000000021211464557272016376 0ustar gforgetusers %figure; set(gcf,'Units','Normalized','Position',[0.1 0.2 0.8 0.8]); figure; set(gcf,'Units','Normalized','Position',[0. 0.2 0.4 0.8]); MITprof/profiles_misc/model_load.m0000644000435400001440000001021412331705570017071 0ustar gforgetusersfunction [grid,atlas]=model_load(model,varargin); % [grid,atlas]=model_load(model,[reload]); % % model is a string used to select the model to be loaded % 'OCCA' : ECCOv4 grid + OCCA atlas % 'SOSE59' : SOSE59 grid + atlas % % if reload=0 (default), variables are loaded from .mat files % if reload=1 , variables are loaded from original files, and saved in % the matlab form. % % - grid ("model"_grid.mat) % mygrid : structure containing XC, YC, RAC and RC % mytri : information used for delaunay triangulation % MYBASININDEX : basin index % % - state/variance reference climatologies ("model"_atlas.mat) % atlas : T/S atlas in a structure format % atlas.T, atlas.S are cells of 4-dim arrays with monthly values % % gcmfaces toolbox must be working % % process arguments reload=0; if nargin>1, reload=varargin{1}; end % directory where .mat model files are stored dir_model='/Users/roquet/Documents/MATLAB/MITprof/model_database/'; % try to load .mat files if reload==0 & exist([dir_model model '_grid.mat'],'file') & exist([dir_model model '_atlas.mat'],'file') % load grid and atlas load([dir_model model '_grid.mat']); load([dir_model model '_atlas.mat']); return end % if reload~=0 or fields are not found, generation of .mat files % protect global grid variables global mygrid mytri MYBASININDEX mygrid1=mygrid; mytri1=mytri; MYBASININDEX1=MYBASININDEX; switch model case 'OCCA', % atlas made combining OCCA, PHC in arctic and WOA in marginal seas % using the grid ECCOv4, monthly values % set directories: dir_in='/Users/roquet/Documents/MATLAB/MITprof/climatology/'; dirGrid=[dir_in 'GRIDv4/']; fileBasin=[dir_in 'basin_masks_eccollc_90x50.bin']; fileT=[dir_in 'T_OWPv1_M_eccollc_90x50.bin']; fileS=[dir_in 'S_OWPv1_M_eccollc_90x50.bin']; %load and save grid : grid_load(dirGrid,5,'compact'); gcmfaces_bindata; mygrid=rmfield(mygrid,{'XG','YG','RAC','RAZ','DXC','DYC','DXG','DYG'}); mygrid=rmfield(mygrid,{'hFacC','hFacW','hFacS','Depth','AngleCS','AngleSN'}); mygrid=rmfield(mygrid,{'hFacCsurf','mskW','mskS','DRC','DRF','RF'}); % list_param={'XC','YC','RAC','RC'}; % grid_load(dirGrid,5,list_param); % gcmfaces_bindata; MYBASININDEX=convert2array(read_bin(fileBasin,1,0)); grid.name=model; grid.mygrid=mygrid; grid.mytri=mytri; grid.MYBASININDEX=MYBASININDEX; % read T/S Atlas fldT=mygrid.mskC; fldT(:)=0; fldS=fldT; for tt=1:12; fldT(:,:,:,tt)=read_bin(fileT,tt).*mygrid.mskC; fldS(:,:,:,tt)=read_bin(fileS,tt).*mygrid.mskC; end; atlas.name=model; atlas.T={convert2array(fldT)}; atlas.S={convert2array(fldS)}; case 'SOSE59', % 59th iteration of SOSE, annual climatology % set directories: dir_in='/Users/roquet/Documents/donnees/MODEL/SOSE59/'; dirGrid=[dir_in 'grid/']; %load grid : grid_load(dirGrid,1,'straight'); gcmfaces_bindata; mygrid=rmfield(mygrid,{'XG','YG','RAC','RAZ','DXC','DYC','DXG','DYG'}); mygrid=rmfield(mygrid,{'hFacC','hFacW','hFacS','Depth','AngleCS','AngleSN'}); mygrid=rmfield(mygrid,{'hFacCsurf','mskW','mskS','DRC','DRF','RF'}); % list_param={'XC','YC','RAC','RC'}; % grid_load(dirGrid,1,list_param); % gcmfaces_bindata; MYBASININDEX=convert2array(mygrid.mskC(:,:,1)); MYBASININDEX(isnan(MYBASININDEX))=0; grid.name=model; grid.mygrid=mygrid; grid.mytri=mytri; grid.MYBASININDEX=MYBASININDEX; % load atlas atlas_file=[dir_in 'SOSE59_TS.mat']; load(atlas_file); atlas.name=model; atlas.T={THETA_SOSE59}; atlas.S={SALT_SOSE59}; otherwise error('not a valid model string'); end % save .mat files save([dir_model model '_grid.mat'],'grid'); save([dir_model model '_atlas.mat'],'atlas'); % reload global grid variables mygrid=mygrid1; mytri=mytri1; MYBASININDEX=MYBASININDEX1; MITprof/profiles_misc/ncputvar.m0000644000435400001440000000235411551702316016640 0ustar gforgetusersfunction []=ncputvar(nc,VARname,VARvalue,varargin); % []=ncputvar(ncid,varid,data,[start,count]) % write data to MITprof netcdf file global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if useNativeMatlabNetcdf %get variable id: vv = netcdf.inqVarID(nc,VARname); %flip order of dimensions: bb=length(size(VARvalue)); VARvalue=permute(VARvalue,[bb:-1:1]); if nargin>3; %get and flip position vectors: VARpos=fliplr(varargin); %convert VARpos to start,count: start=[]; count=[]; for ii=1:length(VARpos); start=[start VARpos{ii}(1)-1]; count=[count VARpos{ii}(end)-VARpos{ii}(1)+1]; end; %write to file: netcdf.putVar(nc,vv,start,count,VARvalue); else; %write to file: netcdf.putVar(nc,vv,VARvalue); end; else;%try to use old mex stuff if nargin==4; eval(['nc{''' VARname '''}([' num2str(varargin{1}) '])=VARvalue;']); elseif nargin==5, eval(['nc{''' VARname '''}([' num2str(varargin{1}) '],[' num2str(varargin{2}) '])=VARvalue;']); else; eval(['nc{''' VARname '''}(:)=VARvalue;']); end; end; MITprof/profiles_misc/MITprof_subset.m0000644000435400001440000000475712152673524017722 0ustar gforgetusersfunction [MITprofSub]=MITprof_subset(MITprof,varargin); % [MITprofSub]=MITprof_subset(MITprof,'PropertyName',PropertyValue,...) % load a subset of profiles from MITprof into MITprofSub % % if PropertyName = 'list' : PropertyValue contains the list of profiles % otherwise PropertyName = 'field' : selection on MITprof.prof_field, % range or unique value given in PropertyValue. % if PropertyName = 'list' is used, then it needs to be the first one. % % [MITprofSub]=MITprof_subset(MITprof,'list',1:50); % returns the 50th first profiles in MITprof % [MITprofSub]=MITprof_subset(MITprof,'depth',[50 150]); % returns the subset of MITprof that has prof_depth>=50 and <150 % [MITprofSub]=MITprof_subset(MITprof,'depth',[50 150],'descr',platformName); % ... and prof_descr=platformName; MITprofSub=MITprof; fldNames=fieldnames(MITprof); nSub=(nargin-1)/2; for iSub=1:nSub; if ~strcmp('list',varargin{(iSub-1)*2+1}); eval(['prof_sub=MITprofSub.prof_' varargin{(iSub-1)*2+1} ';']); range_sub=varargin{(iSub-1)*2+2}; if strcmp('descr',varargin{(iSub-1)*2+1}); KK=find(strcmp(prof_sub,range_sub)); elseif length(range_sub)==2 & range_sub(1)=range_sub(1)&prof_sub1, mode=varargin{1}; end if useNativeMatlabNetcdf; nc=netcdf.open(theNetCDFFile,mode); else;%try to use old mex stuff if mode==0, nc=netcdf(theNetCDFFile); else nc=netcdf(theNetCDFFile,mode); end end; MITprof/profiles_misc/ncdefDim.m0000644000435400001440000000055411550664466016523 0ustar gforgetusersfunction ncdefDim(ncid,dimname,dimlen); % add a dimension in a netcdf file. global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if useNativeMatlabNetcdf; netcdf.defDim(ncid,dimname,dimlen); else;%try to use old mex stuff eval(sprintf('ncid(''%s'')=%d;',dimname,dimlen)); end; MITprof/profiles_misc/sw_dpth.m0000755000435400001440000000427711551405622016457 0ustar gforgetusers function DEPTHM = sw_dpth(P,LAT) % SW_DPTH Depth from pressure %=========================================================================== % SW_DPTH $Id: sw_dpth.m,v 1.1 2011/04/13 20:46:10 roquet Exp $ % Copyright (C) CSIRO, Phil Morgan 1992. % % USAGE: dpth = sw_dpth(P,LAT) % % DESCRIPTION: % Calculates depth in metres from pressure in dbars. % % INPUT: (all must have same dimensions) % P = Pressure [db] % LAT = Latitude in decimal degress north [-90..+90] % (lat may have dimensions 1x1 or 1xn where P(mxn). % % OUTPUT: % dpth = depth [metres] % % AUTHOR: Phil Morgan 92-04-06 (morgan@ml.csiro.au) % % DISCLAIMER: % This software is provided "as is" without warranty of any kind. % See the file sw_copy.m for conditions of use and licence. % % REFERENCES: % Unesco 1983. Algorithms for computation of fundamental properties of % seawater, 1983. _Unesco Tech. Pap. in Mar. Sci._, No. 44, 53 pp. %========================================================================= % Modifications % 99-06-25. Lindsay Pender, Fixed transpose of row vectors. % CALLER: general purpose % CALLEE: none %------------- % CHECK INPUTS %------------- [mP,nP] = size(P); [mL,nL] = size(LAT); if mL==1 & nL==1 % LAT scalar - fill to size of P LAT = LAT*ones(size(P)); elseif nP == nL & mL == 1 % LAT is row vector LAT = LAT(ones(1, mP), :); % Coppy down each column elseif mP == mL & nL == 1 % LAT is column vector LAT = LAT(:, ones(1, nP)); % Copy across each row elseif mP == mL & nP == nL % Ok else error('sw_depth.m: Inputs arguments have wrong dimensions') end %if %------------- % BEGIN %------------- % Eqn 25, p26. Unesco 1983. DEG2RAD = pi/180; c1 = +9.72659; c2 = -2.2512E-5; c3 = +2.279E-10; c4 = -1.82E-15; gam_dash = 2.184e-6; LAT = abs(LAT); X = sin(LAT*DEG2RAD); % convert to radians X = X.*X; bot_line = 9.780318*(1.0+(5.2788E-3+2.36E-5*X).*X) + gam_dash*0.5*P; top_line = (((c4*P+c3).*P+c2).*P+c1).*P; DEPTHM = top_line./bot_line; return %=========================================================================== % MITprof/profiles_misc/ncclose.m0000644000435400001440000000044011550664466016432 0ustar gforgetusersfunction [] = ncclose(ncid); % close a netcdf file. global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if useNativeMatlabNetcdf; netcdf.close(ncid); else;%try to use old mex stuff close(ncid); end; MITprof/profiles_misc/ncgetvar.m0000644000435400001440000000240711551702316016606 0ustar gforgetusersfunction [VARvalue]=ncgetvar(nc,VARname,varargin) % function [VARvalue]=ncgetvar(nc,VARname, [index_prof, index_depth] ) % get data to MITprof netcdf file global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if useNativeMatlabNetcdf %get variable id: vv = netcdf.inqVarID(nc,VARname); if nargin>2; %get and flip position vectors: VARpos=fliplr(varargin); %convert VARpos to start,count: start=[]; count=[]; for ii=1:length(VARpos); start=[start VARpos{ii}(1)-1]; count=[count VARpos{ii}(end)-VARpos{ii}(1)+1]; end; %write to file: VARvalue=netcdf.getVar(nc,vv,start,count); else; %write to file: VARvalue=netcdf.getVar(nc,vv); end; %flip order of dimensions: bb=length(size(VARvalue)); VARvalue=permute(VARvalue,[bb:-1:1]); else;%try to use old mex stuff if nargin==3; eval(['VARvalue=nc{''' VARname '''}([' num2str(varargin{1}) ']);']); elseif nargin==4, eval(['VARvalue=nc{''' VARname '''}([' num2str(varargin{1}) '],[' num2str(varargin{2}) ']);']); else; eval(['VARvalue=nc{''' VARname '''}(:);']); end; end; MITprof/profiles_misc/sw_adtg.m0000644000435400001440000000570411460113775016434 0ustar gforgetusersfunction ADTG = sw_adtg(S,T,P) % SW_ADTG Adiabatic temperature gradient %=========================================================================== % SW_ADTG $Revision: 1.1 $ $Date: 2010/10/21 19:43:57 $ % Copyright (C) CSIRO, Phil Morgan 1992. % % adtg = sw_adtg(S,T,P) % % DESCRIPTION: % Calculates adiabatic temperature gradient as per UNESCO 1983 routines. % % INPUT: (all must have same dimensions) % S = salinity [psu (PSS-78) ] % T = temperature [degree C (IPTS-68)] % P = pressure [db] % (P may have dims 1x1, mx1, 1xn or mxn for S(mxn) ) % % OUTPUT: % ADTG = adiabatic temperature gradient [degree_C/db] % % AUTHOR: Phil Morgan 92-04-03 (morgan@ml.csiro.au) % % DISCLAIMER: % This software is provided "as is" without warranty of any kind. % See the file sw_copy.m for conditions of use and licence. % % REFERENCES: % Fofonoff, P. and Millard, R.C. Jr % Unesco 1983. Algorithms for computation of fundamental properties of % seawater. Unesco Tech. Pap. in Mar. Sci., No. 44, 53 pp. Eqn.(31) p.39 % % Bryden, H. 1973. % "New Polynomials for thermal expansion, adiabatic temperature gradient % and potential temperature of sea water." % DEEP-SEA RES., 1973, Vol20,401-408. %========================================================================= %------------- % CHECK INPUTS %------------- if nargin ~= 3 error('sw_adtg.m: Must pass 3 parameters ') end %if % CHECK S,T,P dimensions and verify consistent [ms,ns] = size(S); [mt,nt] = size(T); [mp,np] = size(P); % CHECK THAT S & T HAVE SAME SHAPE if (ms~=mt) | (ns~=nt) error('check_stp: S & T must have same dimensions') end %if % CHECK OPTIONAL SHAPES FOR P if mp==1 & np==1 % P is a scalar. Fill to size of S P = P(1)*ones(ms,ns); elseif np==ns & mp==1 % P is row vector with same cols as S P = P( ones(1,ms), : ); % Copy down each column. elseif mp==ms & np==1 % P is column vector P = P( :, ones(1,ns) ); % Copy across each row elseif mp==ms & np==ns % PR is a matrix size(S) % shape ok else error('check_stp: P has wrong dimensions') end %if [mp,np] = size(P); % IF ALL ROW VECTORS ARE PASSED THEN LET US PRESERVE SHAPE ON RETURN. Transpose = 0; if mp == 1 % row vector P = P(:); T = T(:); S = S(:); Transpose = 1; end %if %***check_stp %------------- % BEGIN %------------- a0 = 3.5803E-5; a1 = +8.5258E-6; a2 = -6.836E-8; a3 = 6.6228E-10; b0 = +1.8932E-6; b1 = -4.2393E-8; c0 = +1.8741E-8; c1 = -6.7795E-10; c2 = +8.733E-12; c3 = -5.4481E-14; d0 = -1.1351E-10; d1 = 2.7759E-12; e0 = -4.6206E-13; e1 = +1.8676E-14; e2 = -2.1687E-16; ADTG = a0 + (a1 + (a2 + a3.*T).*T).*T ... + (b0 + b1.*T).*(S-35) ... + ( (c0 + (c1 + (c2 + c3.*T).*T).*T) + (d0 + d1.*T).*(S-35) ).*P ... + ( e0 + (e1 + e2.*T).*T ).*P.*P; if Transpose ADTG = ADTG'; end %if return %========================================================================== MITprof/profiles_misc/ncvars.m0000644000435400001440000000104711550664466016304 0ustar gforgetusersfunction [vars]=ncvars(ncid); %input: ncid is a netcdf file id %output: vars is the list of its variables name (in cell) global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if useNativeMatlabNetcdf; [numdims, numvars, numglobalatts, unlimdimID] = netcdf.inq(ncid); for ii=1:numvars; aa=netcdf.inqVar(ncid,ii-1); if ii==1; vars={aa}; else; vars=[vars aa]; end; end; else;%try to use old mex stuff vars=ncnames(var(ncid)); end; MITprof/profiles_misc/ncaddAtt.m0000644000435400001440000000240211551406112016505 0ustar gforgetusersfunction ncaddAtt(ncid,varname,attrname,attrvalue); % add an attribute to a variable in an existing netcdf file. global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if isempty(varname), if useNativeMatlabNetcdf; netcdf.reDef(ncid); netcdf.putAtt(ncid,-1,attrname,attrvalue); netcdf.endDef(ncid); else;%try to use old mex stuff if ischar(attrvalue) attrvalue(find(double(attrvalue)==10))=[]; eval(['ncid.' attrname '=''' attrvalue ''';']); else eval(['ncid.' attrname '=' num2str(attrvalue) ';']); end end; else if useNativeMatlabNetcdf; varid=netcdf.inqVarID(ncid,varname); netcdf.reDef(ncid); netcdf.putAtt(ncid,varid,attrname,attrvalue); netcdf.endDef(ncid); else;%try to use old mex stuff if strcmp(attrname,'_FillValue'), attrname='FillValue_'; end if ischar(attrvalue) attrvalue(find(double(attrvalue)==10))=[]; eval(['ncid{''' varname '''}.' attrname '=''' attrvalue ''';']); else eval(['ncid{''' varname '''}.' attrname '=' num2str(attrvalue) ';']); end end; end MITprof/profiles_misc/aviso_get_madt.m0000644000435400001440000000254711553642002017764 0ustar gforgetusersfunction [madt]=aviso_get_madt(loc,grid_aviso) % function [madt]=aviso_get_madt(loc,grid) % extract madt value (mapped absolute dynamic topography) at 1 location % linear interpolation in space and time at each location. % % loc is a structure with three array of size (N,1) : % loc.lat : latitude [deg_north] % loc.lon : longitude [deg_east] % loc.time : date in Matlab julian date format % % grid is the structure returned by aviso_get_grid % % madt is the output array [unit: m], of size (N,1). % N=length(loc.lat); madt=NaN*zeros(N,1); loc.lon(loc.lon<0)=loc.lon(loc.lon<0)+360; Itime=interp1(grid_aviso.time,(1:grid_aviso.Ntime)'-1,loc.time); Ilon=interp1(grid_aviso.NbLongitudes,(1:grid_aviso.Nlon)'-1,loc.lon); Ilat=interp1(grid_aviso.NbLatitudes,(1:grid_aviso.Nlat)'-1,loc.lat); [X,Y,T]=meshgrid([0 1],[0 1],[0 1]); for kk=1:N, if isnan(Itime(kk)*Ilon(kk)*Ilat(kk)), continue, end it=floor(Itime(kk)); il=floor(Ilon(kk)); iL=floor(Ilat(kk)); URL=sprintf('http://opendap.aviso.oceanobs.com/thredds/dodsC/dataset-duacs-dt-ref-global-merged-madt-h?Grid_0001[%d:%d][%d:%d][%d:%d]',... it,it+1,il,il+1,iL,iL+1); a=loaddap(URL);data=a.Grid_0001; % data.Grid_0001 : lon x lat x time if any(data.Grid_0001(:)>1e10), continue, end madt(kk)=interp3(X,Y,T,data.Grid_0001/100,Ilon(kk)-il,Ilat(kk)-iL,Itime(kk)-it); end MITprof/profiles_misc/ncatts.m0000644000435400001440000000057511511500012016256 0ustar gforgetusersfunction [atts]=ncatts(ncid,varid); %input: ncid is a netcdf file id % varid is a netcdf variable id %output: atts is the list of its attributes name (in cell) [varname,xtype,dimids,natts] = netcdf.inqVar(ncid,varid); for ii=1:natts; aa=netcdf.inqAttName(ncid,varid,ii-1); if ii==1; atts={aa}; else; atts=[atts aa]; end; end; if natts==0; atts=[]; end; MITprof/profiles_misc/model_interp.m0000644000435400001440000000351711553640772017472 0ustar gforgetusersfunction [MITprofCur]=model_interp(MITprofCur,model,varargin) % function [MITprofCur]=model_interp(MITprofCur,model,varargin) % interpolate model hydrographic fields at the location of given profiles % % MITprofCur: structure containing profile information % model is a string used to select the model to be loaded % 'OCCA' : ECCOv4 grid + OCCA atlas % 'SOSE59' : SOSE59 grid + atlas % load model [grid,atlas]=model_load(model); % protect global grid variables global mygrid mytri MYBASININDEX mygrid1=mygrid; mytri1=mytri; MYBASININDEX1=MYBASININDEX; mygrid=grid.mygrid; mytri=grid.mytri; MYBASININDEX=grid.MYBASININDEX; % compute index of closest profile MITprofCur.prof_point=gcmfaces_bindata(MITprofCur.prof_lon,MITprofCur.prof_lat); [MITprofCur.ii,MITprofCur.jj]=gcmfaces_bindata(MITprofCur.prof_lon,MITprofCur.prof_lat); % temporal index switch model case 'SOSE59' MITprofCur.imonth=MITprofCur.ii*0+1; case 'OCCA' MITprofCur.imonth=floor(MITprofCur.prof_YYYYMMDD/1e2)-1e2*floor(MITprofCur.prof_YYYYMMDD/1e4); otherwise error('not a valid model string'); end % extract profiles nk=length(mygrid.RC);kk=ones(1,nk); np=length(MITprofCur.ii);pp=ones(np,1); ind2prof=sub2ind(size(atlas.T{1}),MITprofCur.ii*kk,MITprofCur.jj*kk,pp*[1:nk],MITprofCur.imonth*kk); I=find(~isnan(ind2prof)); Tatlas=ind2prof*NaN;Tatlas(I)=atlas.T{1}(ind2prof(I)); Tatlas(Tatlas==0)=NaN; Satlas=ind2prof*NaN;Satlas(I)=atlas.S{1}(ind2prof(I)); Satlas(Satlas==0)=NaN; warning off Tatlas=interp1(-mygrid.RC',Tatlas',MITprofCur.prof_depth)'; Satlas=interp1(-mygrid.RC',Satlas',MITprofCur.prof_depth)'; warning on % record values MITprofCur=setfield(MITprofCur,['prof_T_' model],Tatlas'); MITprofCur=setfield(MITprofCur,['prof_S_' model],Satlas'); % put back global grid values mygrid=mygrid1; mytri=mytri1; MYBASININDEX=MYBASININDEX1; MITprof/profiles_misc/ncputAtt.m0000644000435400001440000000221511550664466016610 0ustar gforgetusersfunction [nc] = ncputAtt(ncid,varname,attrname,attrvalue); % add an attribute to a variable in a netcdf file. global useNativeMatlabNetcdf; if isempty(useNativeMatlabNetcdf); useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end; if isempty(varname), if useNativeMatlabNetcdf; netcdf.putAtt(ncid,-1,attrname,attrvalue); else;%try to use old mex stuff if ischar(attrvalue) attrvalue(find(double(attrvalue)==10))=[]; eval(['ncid.' attrname '=''' attrvalue ''';']); else eval(['ncid.' attrname '=' num2str(attrvalue) ';']); end end; else if useNativeMatlabNetcdf; varid=netcdf.inqVarID(ncid,varname); netcdf.putAtt(ncid,varid,attrname,attrvalue); else;%try to use old mex stuff if strcmp(attrname,'_FillValue'), attrname='FillValue_'; end if ischar(attrvalue) attrvalue(find(double(attrvalue)==10))=[]; eval(['ncid{''' varname '''}.' attrname '=''' attrvalue ''';']); else eval(['ncid{''' varname '''}.' attrname '=' num2str(attrvalue) ';']); end end; end MITprof/profiles_samples/0000755000435400001440000000000012375431055015331 5ustar gforgetusersMITprof/profiles_samples/reference_results/0000755000435400001440000000000012375431057021052 5ustar gforgetusersMITprof/profiles_samples/reference_results/wod05_CTD_1990s.nc0000644000435400001440000331643012365556401023703 0ustar gforgetusersCDF iPROF{iDEPTHYlTXT  description¾Format: MITprof netcdf. This file was created using the matlab toolbox which can be obtained (see README) from http://mitgcm.org/viewvc/MITgcm/MITgcm_contrib/gael/profilesMatlabProcessing/date 28-Jul-2014  prof_depth  long_namedepthunitsme missing_valueÀÇ€ _FillValueÀÇ€È4 prof_flag  long_name$flag = i > 0 for suspicious profile units missing_valueÀÇ€ _FillValueÀÇ€Øü prof_descr  long_nameprofile descriptionlÔ prof_date  long_nameJulian day since Jan-1-0000units missing_valueÀÇ€ _FillValueÀÇ€Ø%@ prof_YYYYMMDD  long_name1year (4 digits), month (2 digits), day (2 digits)units missing_valueÀÇ€ _FillValueÀÇ€Ø) prof_HHMMSS  long_name5hour (2 digits), minute (2 digits), second (2 digits)units missing_valueÀÇ€ _FillValueÀÇ€Ø,ðprof_lon  long_nameLongitude (degree East)units missing_valueÀÇ€ _FillValueÀÇ€Ø0Èprof_lat  long_nameLatitude (degree North)units missing_valueÀÇ€ _FillValueÀÇ€Ø4  prof_basin  long_nameocean basin index (ecco 4g)units missing_valueÀÇ€ _FillValueÀÇ€Ø8x prof_point  long_namegrid point index (ecco 4g)units missing_valueÀÇ€ _FillValueÀÇ€Ø 0 means test i rejected data.units missing_valueÀÇ€ _FillValueÀÇ€V˜ˆprof_S  long_namesalinityunitspsu missing_valueÀÇ€ _FillValueÀÇ€Vî  prof_Sweight  long_namesalinity least-square weightunits(psu)^-2 missing_valueÀÇ€ _FillValueÀÇ€VD¸ prof_Sestim  long_name;salinity atlas (OCCA | PHC in arctic| WOA in marginal seas)unitspsu missing_valueÀÇ€ _FillValueÀÇ€V šÐ prof_Serr  long_namesalinity instrumental errorunitspsu missing_valueÀÇ€ _FillValueÀÇ€V ðè prof_Sflag  long_name(flag = i > 0 means test i rejected data.units missing_valueÀÇ€ _FillValueÀÇ€V G@@.@9@A€@F€@K€@P@@RÀ@U@@WÀ@Z@@\À@_@@`à@b @c`@d @eà@g @i@k€@n@p@@q€@rÀ@t@u@@v€@wÀ@y@z@@{€@|À@~@@@0@‚À@„P@…à@‡p@‰@Š@Œ @°@@@‘0@’À@”P@•à@—p@™@š@œ @°@Ÿ@@ h@¡0@¡ø@¢À@£ˆ@¤P@¥@¥à@¦¨@§p@¨8@©@©È@ª@«X@¬ @¬è@­°@®x@¯@@°@°h@°Ì@±0@±”@±ø@²\@²À@³$@³ˆ@³ì@´P@´´@µÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€WOD-CTD//29-1103//4. 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ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð@9@@9@9?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð@@@@@@@@@@@@@@@@@@@@@@?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ð?ðMITprof/profiles_samples/reference_results/argo_indian.nc0000644000435400001440000040740412365556401023657 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0Í–ˆ@A Œè),.@Aèà½8¿@A ±Ð@AU6~*á@Apºþ³N@Amµ˜š@A j°1wæ@A#-†„ü@A%·…x@A(@ˆ…´õ@A*°ö‰ã[@A,t@‹A÷@A0ÜyŽ®~@A5_ìÑ@A9XPξ@A<Á¶Ò·ƒ@A@.GH×Ò@ACgLµ@AFS¾ðYß@AI!qYü+@AK¤“Ñ3C@AN¬cÏ_@ARi]0r@AV-µ@‹@AY\íŒód@A[ÙßÃ]ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€@@ÝWÀ@@ÝpÀ@@Ý€@@ݶ@@@Þ@@@ß0@@@áÚà@@ä•&«u‘@@çOåZr@@ék Þ @@ëñ“õA@@RïÏ@@ñÍ€èä@@òÿÅd²@@ôõ:Üäö@@÷ÀîÜ @@ø÷ÒÕ 3@@úæz@@üŶ˜ j@@ÿŒl-Ë@A*z@ö´@A±óIe€@A 0Í–ˆ@A Œè),.@Aèà½8¿@A ±Ð@AU6~*á@Apºþ³N@Amµ˜š@A j°1wæ@A#-†„ü@A%·…x@A(@ˆ…´õ@A*°ö‰ã[@A,t@‹A÷@A0ÜyŽ®~@A5_ìÑ@A9XPξ@A<Á¶Ò·ƒ@A@.GH×Ò@ACgLµ@AFS¾ðYß@AI!qYü+@AK¤“Ñ3C@AN¬cÏ_@ARi]0r@AV-µ@‹@AY\íŒód@A[ÙßÃ]ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€@@ÝWÀ@@ÝpÀ@@Ý€@@ݶ@@@Þ@@@ß0@@@áÚà@@ä•&«u‘@@çOåZr@@ék Þ @@ëñ“õA@@RïÏ@@ñÍ€èä@@òÿÅd²@@ôõ:Üäö@@÷ÀîÜ @@ø÷ÒÕ 3@@úæz@@üŶ˜ j@@ÿŒl-Ë@A*z@ö´@A±óIe€@A 0Í–ˆ@A Œè),.@Aèà½8¿@A ±Ð@AU6~*á@Apºþ³N@Amµ˜š@A j°1wæ@A#-†„ü@A%·…x@A(@ˆ…´õ@A*°ö‰ã[@A,t@‹A÷@A0ÜyŽ®~@A5_ìÑ@A9XPξ@A<Á¶Ò·ƒ@A@.GH×Ò@ACgLµ@AFS¾ðYß@AI!qYü+@AK¤“Ñ3C@AN¬cÏ_@ARi]0r@AV-µ@‹@AY\íŒód@A[ÙßÃ]ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€@@ÝWÀ@@ÝpÀ@@Ý€@@ݶ@@@Þ@@@ß0@@@áÚà@@ä•&«u‘@@çOåZr@@ék Þ 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j°1wæ@A#-†„ü@A%·…x@A(@ˆ…´õ@A*°ö‰ã[@A,t@‹A÷@A0ÜyŽ®~@A5_ìÑ@A9XPξ@A<Á¶Ò·ƒ@A@.GH×Ò@ACgLµ@AFS¾ðYß@AI!qYü+@AK¤“Ñ3C@AN¬cÏ_@ARi]0r@AV-µ@‹@AY\íŒód@A[ÙßÃ]ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€@@ÝWÀ@@ÝpÀ@@Ý€@@ݶ@@@Þ@@@ß0@@@áÚà@@ä•&«u‘@@çOåZr@@ék Þ @@ëñ“õA@@RïÏ@@ñÍ€èä@@òÿÅd²@@ôõ:Üäö@@÷ÀîÜ @@ø÷ÒÕ 3@@úæz@@üŶ˜ j@@ÿŒl-Ë@A*z@ö´@A±óIe€@A 0Í–ˆ@A Œè),.@Aèà½8¿@A ±Ð@AU6~*á@Apºþ³N@Amµ˜š@A j°1wæ@A#-†„ü@A%·…x@A(@ˆ…´õ@A*°ö‰ã[@A,t@‹A÷@A0ÜyŽ®~@A5_ìÑ@A9XPξ@A<Á¶Ò·ƒ@A@.GH×Ò@ACgLµ@AFS¾ðYß@AI!qYü+@AK¤“Ñ3C@AN¬cÏ_@ARi]0r@AV-µ@‹@AY\íŒód@A[ÙßÃ]ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€ÀÇ€@@Û@@@Û¬@@ÛÇ€@@Ûö`@@Þ @@ã, @@ëz @@òá-‘³@@øÞªŸ‡N@@þ(ÃáÓ@A ‚L¼@A&z&(@A ³Ÿ§B@A•Ê“5@AP*DŠ@Aô˜vw»@A‰~·Fí@Aâ›Þ§@A!¢I£uí@A&Ó‚€=¼@A-ÿÆKõ@A3mÁK @A9ã¸Mg@A=£ý9-‹@AB2çPþ½@AEpi5@Q@AH­ëä@AKdèû®@AMÀ˜ŸÞ@AOž˜¡D @AQRn-j@ARž·ƒÊ@ASêÿÛz*@AU&âL&@AUî±1mt@AWã÷@·@AY$qÀÒà@AZR : real time; D : delayed mode; A : real time with adjustment _FillValue  JìINST_REFERENCE  long_nameInstrument type conventionsBrand, type, serial number _FillValue @K WMO_INST_TYPE  long_nameCoded instrument type conventionsArgo reference table 8 _FillValue tRLJULD  long_name?Julian day (UTC) of the station relative to REFERENCE_DATE_TIMEunits"days since 1950-01-01 00:00:00 UTC conventions8Relative julian days with decimal part (as parts of day) _FillValueA.„~èRÀJULD_QC  long_nameQuality on Date and Time conventionsArgo reference table 2 _FillValue  S¨ JULD_LOCATION  long_name@Julian day (UTC) of the location relative to REFERENCE_DATE_TIMEunits"days since 1950-01-01 00:00:00 UTC conventions8Relative julian days with decimal part (as parts of day) _FillValueA.„~èSÈLATITUDE  long_name&Latitude of the station, best estimateunits degree_north _FillValue@øið valid_minÀV€ valid_max@V€èT° LONGITUDE  long_name'Longitude of the station, best estimateunits degree_east _FillValue@øið valid_minÀf€ valid_max@f€èU˜ POSITION_QC  long_name,Quality on position (latitude and longitude) conventionsArgo reference table 2 _FillValue  V€POSITIONING_SYSTEM  long_namePositioning system _FillValue èV PROFILE_PRES_QC  long_name#Global quality flag of PRES profile conventionsArgo reference table 2a _FillValue  WˆPROFILE_TEMP_QC  long_name#Global quality flag of TEMP profile conventionsArgo reference table 2a _FillValue  W¨PROFILE_PSAL_QC  long_name#Global quality flag of PSAL profile conventionsArgo reference table 2a _FillValue  WÈPRES long_name SEA PRESSURE _FillValueGÃO€unitsdecibar valid_min valid_maxF;€comment$In situ measurement, sea surface = 0C_format%7.1fFORTRAN_formatF7.1 resolution=ÌÌÍ4WèPRES_QC  long_name quality flag conventionsArgo reference table 2 _FillValue  Œ PRES_ADJUSTED long_name SEA PRESSURE _FillValueGÃO€unitsdecibar valid_min valid_maxF;€comment$In situ measurement, sea surface = 0C_format%7.1fFORTRAN_formatF7.1 resolution=ÌÌÍ4™ PRES_ADJUSTED_QC  long_name quality flag conventionsArgo reference table 2 _FillValue  Í(PRES_ADJUSTED_ERROR  long_name SEA PRESSURE _FillValueGÃO€unitsdecibarcommentWContains the error on the adjusted values as determined by the delayed mode QC process.C_format%7.1fFORTRAN_formatF7.1 resolution=ÌÌÍ4Ú0TEMP long_name$SEA TEMPERATURE IN SITU ITS-90 SCALE _FillValueGÃO€unitsdegree_Celsius valid_minÀ valid_maxB commentIn situ measurementC_format%9.3fFORTRAN_formatF9.3 resolution:ƒo4LTEMP_QC  long_name quality flag conventionsArgo reference table 2 _FillValue  Bh TEMP_ADJUSTED long_name$SEA TEMPERATURE IN SITU ITS-90 SCALE _FillValueGÃO€unitsdegree_Celsius valid_minÀ valid_maxB commentIn situ measurementC_format%9.3fFORTRAN_formatF9.3 resolution:ƒo4OpTEMP_ADJUSTED_QC  long_name quality flag conventionsArgo reference table 2 _FillValue  ƒŒTEMP_ADJUSTED_ERROR  long_name$SEA TEMPERATURE IN SITU ITS-90 SCALE _FillValueGÃO€unitsdegree_CelsiuscommentWContains the error on the adjusted values as determined by the delayed mode QC process.C_format%9.3fFORTRAN_formatF9.3 resolution:ƒo4”PSAL long_namePRACTICAL SALINITY _FillValueGÃO€unitspsu valid_min valid_maxB(commentIn situ measurementC_format%9.3fFORTRAN_formatF9.3 resolution:ƒo4Ä°PSAL_QC  long_name quality flag conventionsArgo reference table 2 _FillValue  øÌ PSAL_ADJUSTED long_namePRACTICAL SALINITY _FillValueGÃO€unitspsu valid_min valid_maxB(commentIn situ measurementC_format%9.3fFORTRAN_formatF9.3 resolution:ƒo4ÔPSAL_ADJUSTED_QC  long_name quality flag conventionsArgo reference table 2 _FillValue  9ðPSAL_ADJUSTED_ERROR  long_namePRACTICAL SALINITY _FillValueGÃO€unitspsucommentWContains the error on the adjusted values as determined by the delayed mode QC process.C_format%9.3fFORTRAN_formatF9.3 resolution:ƒo4Fø PARAMETER   long_name/List of parameters with calibration information conventionsArgo reference table 3 _FillValue P{SCIENTIFIC_CALIB_EQUATION   long_name'Calibration equation for this parameter _FillValue ‹dSCIENTIFIC_CALIB_COEFFICIENT   long_name*Calibration coefficients for this equation _FillValue dSCIENTIFIC_CALIB_COMMENT   long_name.Comment applying to this parameter calibration _FillValue •dCALIBRATION_DATE  _FillValue HšdHISTORY_INSTITUTION   long_name"Institution which performed action conventionsArgo reference table 4 _FillValue t¨¬ HISTORY_STEP   long_nameStep in data processing conventionsArgo reference table 12 _FillValue t© HISTORY_SOFTWARE   long_name'Name of software which performed action conventionsInstitution dependent _FillValue t©”HISTORY_SOFTWARE_RELEASE   long_name2Version/release of software which performed action conventionsInstitution dependent _FillValue tªHISTORY_REFERENCE   long_nameReference of database conventionsInstitution dependent _FillValue @ª| HISTORY_DATE   long_name#Date the history record was created conventionsYYYYMMDDHHMISS _FillValue ˜±¼HISTORY_ACTION   long_nameAction performed on data conventionsArgo reference table 7 _FillValue t³THISTORY_PARAMETER   long_name(Station parameter action is performed on conventionsArgo reference table 3 _FillValue гÈHISTORY_START_PRES   long_name Start pressure action applied on _FillValueGÃO€unitsdecibartµ˜HISTORY_STOP_PRES   long_nameStop pressure action 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///Users/roquet/Documents/donnees/HYDRO_DB/WOD09/ODV_WOD09_CTD/ODV_WOD09_CTD.odv //2011-04-06T19:20:18 //Ocean //Profiles // Cruise Station Type yyyy-mm-ddThh:mm:ss.sss Longitude [degrees_east] Latitude [degrees_north] Depth [m] QV:WOD Temperature [°C] QV:WOD Salinity [psu] QV:WOD QV:ODV:SAMPLE WOD09_AU002711 7483082 B 1985-10-08T01:21 60.0238 -59.319 0.0 0 1 10.0 0 -0.948 0 33.9270 0 1 20.0 0 -0.947 0 33.9260 0 1 30.0 0 -0.955 0 33.9270 0 1 50.0 0 -1.064 0 33.9490 0 1 75.0 0 -1.044 0 33.9510 0 1 100.0 0 -1.036 0 33.9500 0 1 125.0 0 -1.030 0 33.9510 0 1 150.0 0 -0.966 0 33.9710 0 1 200.0 0 1.464 0 34.4320 0 1 250.0 0 1.761 0 34.4510 0 1 300.0 0 1.871 0 34.5120 0 1 400.0 0 2.024 0 34.6110 0 1 WOD09_AU002711 7483083 B 1985-10-08T07:46 60.0150 -59.526 0.0 0 -1.813 0 33.9400 0 1 10.0 0 -1.823 0 33.9450 0 1 20.0 0 -1.822 0 33.9450 0 1 30.0 0 -1.822 0 33.9490 0 1 50.0 0 -1.818 0 33.9490 0 1 75.0 0 -1.814 0 33.9500 0 1 100.0 0 -1.809 0 33.9510 0 1 125.0 0 -1.806 0 33.9520 0 1 150.0 0 -1.360 0 34.0610 0 1 200.0 0 1.285 0 34.4370 0 1 250.0 0 1.592 0 34.5200 0 1 300.0 0 1.771 0 34.5760 0 1 400.0 0 1.874 0 34.6420 0 1 WOD09_AU002711 10114160 B 1985-10-06T04:16 66.5915 -55.168 0.0 0 0.691 0 33.9930 0 1 10.0 0 0.678 0 34.0000 0 1 20.0 0 0.678 0 34.0030 0 1 30.0 0 0.676 0 34.0020 0 1 50.0 0 0.667 0 34.0040 0 1 75.0 0 0.666 0 34.0060 0 1 100.0 0 0.668 0 34.0090 0 1 125.0 0 0.670 0 34.0080 0 1 150.0 0 0.672 0 34.0070 0 1 200.0 0 1.129 0 34.1270 0 1 250.0 0 1.807 0 34.2800 0 1 300.0 0 1.879 0 34.3400 0 1 400.0 0 2.056 0 34.4580 0 1 WOD09_AU002711 10114161 B 1985-10-08T00:22 60.0120 -59.289 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 1 75.0 0 -1.000 0 33.9390 0 1 100.0 0 -1.011 0 33.9500 0 1 125.0 0 -0.911 0 33.9670 0 1 150.0 0 -0.847 0 33.9930 0 1 200.0 0 1.512 0 34.3610 0 1 250.0 0 1.566 0 34.4120 0 1 300.0 0 1.735 0 34.4850 0 1 400.0 0 1.945 0 34.5860 0 1 500.0 0 1.973 0 34.6440 0 1 600.0 0 1.995 0 34.6840 0 1 700.0 0 1.992 0 34.7200 0 1 800.0 0 1.963 0 34.7360 0 1 900.0 0 1.914 0 34.7500 0 1 WOD09_AU002711 10114163 B 1985-10-08T06:43 60.0130 -59.463 0.0 0 -1.029 0 33.9380 0 1 10.0 0 -1.018 0 33.9270 0 1 20.0 0 -1.016 0 33.9320 0 1 30.0 0 -1.016 0 33.9320 0 1 50.0 0 -1.053 0 33.9230 0 1 75.0 0 -1.590 0 33.9430 0 1 100.0 0 -1.586 0 33.9630 0 1 125.0 0 -1.606 0 33.9630 0 1 150.0 0 -1.608 0 33.9760 0 1 200.0 0 1.073 0 34.3830 0 1 250.0 0 1.660 0 34.5080 0 1 300.0 0 1.857 0 34.5570 0 1 400.0 0 1.942 0 34.6360 0 1 WOD09_AU002711 10114164 B 1985-10-08T10:19 60.0658 -59.660 0.0 0 -1.841 0 33.9960 0 1 10.0 0 -1.839 0 34.0020 0 1 20.0 0 -1.840 0 34.0000 0 1 30.0 0 -1.834 0 34.0030 0 1 50.0 0 -1.831 0 34.0080 0 1 75.0 0 -1.824 0 34.0310 9 1 100.0 0 -1.633 0 34.0740 9 1 125.0 0 -0.508 0 34.2200 9 1 150.0 0 1.200 0 34.4500 9 1 200.0 0 1.556 0 34.5180 0 1 250.0 0 1.692 0 34.5730 0 1 300.0 0 1.823 0 34.6150 0 1 400.0 0 1.879 0 34.6680 0 1 WOD09_AU002711 10114165 B 1985-10-08T13:39 60.1188 -59.961 0.0 0 1 10.0 0 -1.844 0 33.3590 9 1 20.0 0 -1.842 0 33.4230 9 1 30.0 0 -1.838 0 33.4900 9 1 50.0 0 -1.840 0 33.6490 9 1 75.0 0 -1.840 0 33.8460 0 1 100.0 0 -1.828 0 33.9460 0 1 125.0 0 -1.811 0 33.9790 0 1 150.0 0 0.654 0 34.3750 9 1 200.0 0 1.521 0 34.5230 0 1 250.0 0 1.801 0 34.5800 0 1 300.0 0 1.870 0 34.6090 0 1 400.0 0 1.905 0 34.6630 0 1 WOD09_FR008403 3358721 B 1985-03-12T21:28 61.7103 -50.151 0.0 0 1 10.0 0 5.039 0 33.8370 0 1 20.0 0 5.039 0 33.8370 0 1 30.0 0 5.039 0 33.8350 0 1 50.0 0 5.038 0 33.8380 0 1 75.0 0 5.026 0 33.8380 0 1 100.0 0 4.019 0 33.8000 0 1 125.0 0 2.359 0 33.8770 0 1 150.0 0 2.060 0 33.9510 0 1 200.0 0 2.001 0 34.0410 0 1 250.0 0 2.108 0 34.1220 0 1 300.0 0 2.145 0 34.1850 0 1 400.0 0 2.171 0 34.2900 0 1 500.0 0 2.224 0 34.3730 0 1 600.0 0 2.279 0 34.4520 0 1 700.0 0 2.322 0 34.5270 0 1 800.0 0 2.334 0 34.5860 0 1 900.0 0 2.317 0 34.6330 0 1 1000.0 0 2.315 0 34.6640 0 1 1100.0 0 2.297 0 34.6830 0 1 1200.0 0 2.252 0 34.7060 0 1 1300.0 0 2.214 0 34.7220 0 1 1400.0 0 2.168 0 34.7350 0 1 1500.0 0 2.114 0 34.7480 0 1 1750.0 0 1.934 0 34.7580 0 1 2000.0 0 1.747 0 34.7570 0 1 2500.0 0 1.241 0 34.7310 0 1 3000.0 0 0.796 0 34.7040 0 1 3500.0 0 0.467 0 34.6870 0 1 4000.0 0 0.159 0 34.6730 0 1 WOD09_FR008403 3358723 B 1985-03-13T01:24 61.7400 -50.180 0.0 0 5.047 0 33.8390 0 1 10.0 0 5.045 0 33.8390 0 1 20.0 0 5.048 0 33.8380 0 1 30.0 0 5.049 0 33.8380 0 1 50.0 0 5.050 0 33.8380 0 1 75.0 0 5.051 0 33.8390 0 1 100.0 0 4.471 0 33.8380 0 1 125.0 0 2.791 0 33.8900 0 1 150.0 0 2.307 0 33.9300 0 1 200.0 0 1.975 0 33.9820 0 1 250.0 0 1.976 0 34.0590 0 1 300.0 0 2.091 0 34.1490 0 1 400.0 0 2.168 0 34.2700 0 1 500.0 0 2.224 0 34.3770 0 1 600.0 0 2.284 0 34.4620 0 1 700.0 0 2.312 0 34.5210 0 1 800.0 0 2.333 0 34.5660 0 1 900.0 0 2.331 0 34.6120 0 1 1000.0 0 2.321 0 34.6510 0 1 1100.0 0 2.294 0 34.6790 0 1 1200.0 0 2.258 0 34.7060 0 1 1300.0 0 2.219 0 34.7230 0 1 1400.0 0 2.161 0 34.7350 0 1 1500.0 0 2.110 0 34.7460 0 1 1750.0 0 1.942 0 34.7580 0 1 2000.0 0 1.709 0 34.7580 0 1 WOD09_FR008403 3358732 B 1985-03-13T20:40 67.2470 -50.506 0.0 0 4.723 0 33.8660 0 1 10.0 0 4.723 0 33.8650 0 1 20.0 0 4.723 0 33.8650 0 1 30.0 0 4.726 0 33.8640 0 1 50.0 0 4.726 0 33.8650 0 1 75.0 0 4.727 0 33.8650 0 1 100.0 0 3.382 0 33.7560 0 1 125.0 0 1.814 0 33.9270 0 1 150.0 0 1.691 0 33.9530 0 1 200.0 0 1.819 0 34.0810 0 1 250.0 0 1.982 0 34.1840 0 1 300.0 0 2.038 0 34.2470 0 1 400.0 0 2.081 0 34.3170 0 1 500.0 0 2.235 0 34.4250 0 1 600.0 0 2.230 0 34.4880 0 1 700.0 0 2.234 0 34.5530 0 1 800.0 0 2.222 0 34.5990 0 1 900.0 0 2.235 0 34.6490 0 1 1000.0 0 2.247 0 34.6850 0 1 1100.0 0 2.218 0 34.7070 0 1 1200.0 0 2.172 0 34.7250 0 1 1300.0 0 2.102 0 34.7410 0 1 1400.0 0 2.024 0 34.7490 0 1 1500.0 0 1.924 0 34.7530 0 1 1750.0 0 1.680 0 34.7570 0 1 WOD09_FR008403 3358734 B 1985-03-13T21:07 67.2717 -50.506 0.0 0 4.723 0 33.8660 0 1 10.0 0 4.723 0 33.8660 0 1 20.0 0 4.723 0 33.8650 0 1 30.0 0 4.726 0 33.8640 0 1 50.0 0 4.726 0 33.8650 0 1 75.0 0 4.727 0 33.8650 0 1 100.0 0 3.409 0 33.7960 0 1 125.0 0 1.814 0 33.9270 0 1 150.0 0 1.689 0 33.9540 0 1 200.0 0 1.818 0 34.0790 0 1 250.0 0 1.982 0 34.1840 0 1 300.0 0 2.036 0 34.2430 0 1 400.0 0 2.081 0 34.3170 0 1 500.0 0 2.235 0 34.4240 0 1 600.0 0 2.231 0 34.4880 0 1 700.0 0 2.235 0 34.5550 0 1 800.0 0 2.222 0 34.5990 0 1 900.0 0 2.235 0 34.6490 0 1 1000.0 0 2.247 0 34.6850 0 1 1100.0 0 2.218 0 34.7070 0 1 1200.0 0 2.172 0 34.7250 0 1 1300.0 0 2.102 0 34.7410 0 1 1400.0 0 2.024 0 34.7500 0 1 1500.0 0 1.925 0 34.7530 0 1 1750.0 0 1.680 0 34.7570 0 1 WOD09_FR008403 3358735 B 1985-03-13T23:01 67.3070 -50.520 0.0 0 1 10.0 0 4.726 0 33.8670 0 1 20.0 0 4.727 0 33.8660 0 1 30.0 0 4.728 0 33.8660 0 1 50.0 0 4.729 0 33.8660 0 1 75.0 0 4.721 0 33.8650 0 1 100.0 0 2.314 0 33.8830 0 1 125.0 0 1.845 0 33.9310 0 1 150.0 0 1.758 0 33.9380 0 1 200.0 0 1.647 0 33.9990 0 1 250.0 0 1.920 0 34.1420 0 1 300.0 0 1.980 0 34.2000 0 1 400.0 0 2.086 0 34.2990 0 1 500.0 0 2.166 0 34.3950 0 1 WOD09_FR008758 3367559 B 1987-01-14T03:01 63.0300 -56.465 0.0 0 2.350 0 33.9220 0 1 10.0 0 2.353 0 33.9210 0 1 20.0 0 2.353 0 33.9220 0 1 30.0 0 2.354 0 33.9210 0 1 50.0 0 2.350 0 33.9210 0 1 75.0 0 1.836 0 33.9200 0 1 100.0 0 0.973 0 33.9570 0 1 125.0 0 0.649 0 33.9680 0 1 150.0 0 0.391 0 33.9790 0 1 200.0 0 0.934 0 34.1130 0 1 250.0 0 1.549 0 34.3010 0 1 WOD09_FR008758 3367560 B 1987-01-14T05:46 63.0340 -56.484 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 1 75.0 0 1 100.0 0 1 125.0 0 1 150.0 0 1 200.0 0 1 250.0 0 1 300.0 0 1 400.0 0 1 500.0 0 2.070 0 34.5740 0 1 600.0 0 2.132 0 34.6300 0 1 700.0 0 2.131 0 34.6710 0 1 800.0 0 2.105 0 34.6960 0 1 900.0 0 2.097 0 34.7210 0 1 1000.0 0 2.048 0 34.7380 0 1 1100.0 0 1.993 0 34.7480 0 1 1200.0 0 1.932 0 34.7520 0 1 1300.0 0 1.848 0 34.7550 0 1 1400.0 0 1.735 0 34.7560 0 1 1500.0 0 1.637 0 34.7520 0 1 1750.0 0 1.403 0 34.7450 0 1 2000.0 0 1.170 0 34.7320 0 1 2500.0 0 0.744 0 34.7060 0 1 3000.0 0 0.451 0 34.6890 0 1 WOD09_FR008758 3367561 B 1987-01-14T10:16 63.1170 -56.490 0.0 0 2.324 0 33.9300 0 1 10.0 0 2.324 0 33.9290 0 1 20.0 0 2.319 0 33.9270 0 1 30.0 0 2.302 0 33.9250 0 1 50.0 0 2.311 0 33.9290 0 1 75.0 0 1.259 0 33.9440 0 1 100.0 0 0.632 0 33.9650 0 1 125.0 0 0.349 0 33.9740 0 1 150.0 0 0.235 0 33.9970 0 1 200.0 0 1.063 0 34.1780 0 1 250.0 0 1.649 0 34.3290 0 1 300.0 0 1.929 0 34.4300 0 1 400.0 0 2.050 0 34.5270 0 1 500.0 0 2.169 0 34.6090 0 1 600.0 0 2.138 0 34.6480 0 1 700.0 0 2.119 0 34.6900 0 1 800.0 0 2.040 0 34.7090 0 1 900.0 0 2.010 0 34.7280 0 1 1000.0 0 1.931 0 34.7430 0 1 1100.0 0 1.840 0 34.7430 0 1 1200.0 0 1.782 0 34.7490 0 1 1300.0 0 1.717 0 34.7510 0 1 WOD09_FR008758 3367562 B 1987-01-14T13:12 63.1470 -56.490 0.0 0 2.185 0 33.9140 0 1 10.0 0 2.186 0 33.9150 0 1 20.0 0 2.186 0 33.9140 0 1 30.0 0 2.185 0 33.9140 0 1 50.0 0 2.139 0 33.9180 0 1 75.0 0 0.914 0 33.9530 0 1 100.0 0 0.599 0 33.9620 0 1 125.0 0 0.279 0 33.9680 0 1 150.0 0 0.381 0 34.0200 0 1 200.0 0 1.197 0 34.1930 0 1 250.0 0 1.733 0 34.3810 0 1 300.0 0 1.969 0 34.4700 0 1 400.0 0 1.936 0 34.5390 0 1 500.0 0 2.022 0 34.6060 0 1 600.0 0 2.060 0 34.6620 0 1 700.0 0 2.027 0 34.6850 0 1 800.0 0 2.009 0 34.7130 0 1 900.0 0 1.967 0 34.7290 0 1 1000.0 0 1.912 0 34.7410 0 1 1100.0 0 1.855 0 34.7470 0 1 1200.0 0 1.793 0 34.7510 0 1 1300.0 0 1.708 0 34.7530 0 1 1400.0 0 1.627 0 34.7540 0 1 1500.0 0 1.526 0 34.7520 0 1 1750.0 0 1.315 0 34.7430 0 1 2000.0 0 1.051 0 34.7280 0 1 2500.0 0 0.676 0 34.7080 0 1 3000.0 0 0.396 0 34.6930 0 1 3500.0 0 0.179 0 34.6820 0 1 4000.0 0 -0.018 0 34.6710 0 1 4500.0 0 -0.164 0 34.6650 0 1 WOD09_FR008758 3367567 B 1987-01-15T13:15 69.9855 -59.488 0.0 0 1.364 0 33.6830 0 1 10.0 0 1.363 0 33.6820 0 1 20.0 0 1.346 0 33.6830 0 1 30.0 0 1.337 0 33.6840 0 1 50.0 0 0.850 0 33.6880 0 1 75.0 0 -1.163 0 33.7420 0 1 100.0 0 -1.579 0 33.8070 0 1 125.0 0 -1.142 0 33.8970 0 1 150.0 0 -0.718 0 33.9500 0 1 200.0 0 0.929 0 34.2490 0 1 WOD09_FR008758 3367570 B 1987-01-15T20:40 69.9395 -59.516 0.0 0 1.351 0 33.6850 0 1 10.0 0 1.353 0 33.6870 0 1 20.0 0 1.356 0 33.6860 0 1 30.0 0 1.354 0 33.6870 0 1 50.0 0 0.749 0 33.6890 0 1 75.0 0 -1.541 0 33.7730 0 1 100.0 0 -1.412 0 33.8410 0 1 125.0 0 -1.023 0 33.9160 0 1 150.0 0 -0.544 0 33.9990 0 1 200.0 0 1.011 0 34.2510 0 1 250.0 0 1.626 0 34.4020 0 1 300.0 0 1.825 0 34.4780 0 1 400.0 0 1.968 0 34.5650 0 1 500.0 0 2.044 0 34.6250 0 1 600.0 0 2.065 0 34.6720 0 1 700.0 0 2.065 0 34.7010 0 1 800.0 0 2.030 0 34.7180 0 1 900.0 0 1.989 0 34.7390 0 1 1000.0 0 1.938 0 34.7480 0 1 1100.0 0 1.864 0 34.7520 0 1 1200.0 0 1.794 0 34.7560 0 1 1300.0 0 1.695 0 34.7580 0 1 1400.0 0 1.614 0 34.7580 0 1 1500.0 0 1.518 0 34.7560 0 1 1750.0 0 1.301 0 34.7460 0 1 2000.0 0 1.081 0 34.7350 0 1 2500.0 0 0.672 0 34.7100 0 1 3000.0 0 0.407 0 34.6940 0 1 WOD09_FR008758 3367573 B 1987-01-16T02:03 69.9245 -59.472 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 0.643 0 33.6890 0 1 75.0 0 -1.175 0 33.7540 0 1 100.0 0 -1.374 0 33.8290 0 1 125.0 0 -1.137 0 33.8980 0 1 150.0 0 -0.700 0 33.9800 0 1 200.0 0 0.774 0 34.2250 0 1 250.0 0 1.669 0 34.4110 0 1 300.0 0 1.857 0 34.4820 0 1 400.0 0 2.031 0 34.5780 0 1 500.0 0 2.110 0 34.6360 0 1 600.0 0 2.088 0 34.6700 0 1 700.0 0 2.059 0 34.6980 0 1 800.0 0 2.019 0 34.7220 0 1 900.0 0 1.989 0 34.7380 0 1 1000.0 0 1.933 0 34.7510 0 1 1100.0 0 1.862 0 34.7570 0 1 1200.0 0 1.765 0 34.7570 0 1 1300.0 0 1.706 0 34.7590 0 1 1400.0 0 1.613 0 34.7590 0 1 1500.0 0 1.537 0 34.7560 0 1 1750.0 0 1.308 0 34.7470 0 1 2000.0 0 1.083 0 34.7350 0 1 2500.0 0 0.698 0 34.7110 0 1 3000.0 0 0.427 0 34.6980 0 1 3500.0 0 0.194 0 34.6870 0 1 4000.0 0 0.000 0 34.6760 0 1 WOD09_FR008758 3367574 B 1987-01-16T03:15 69.9175 -59.462 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 0.534 0 33.7250 0 1 75.0 0 -1.451 0 33.7920 0 1 100.0 0 -1.347 0 33.8390 0 1 125.0 0 -0.976 0 33.9230 0 1 150.0 0 -0.480 0 34.0080 0 1 200.0 0 0.977 0 34.2430 0 1 250.0 0 1.614 0 34.4000 0 1 300.0 0 1.852 0 34.4830 0 1 400.0 0 2.011 0 34.5740 0 1 500.0 0 2.074 0 34.6240 0 1 600.0 0 2.066 0 34.6710 0 1 700.0 0 2.058 0 34.7060 0 1 800.0 0 2.021 0 34.7230 0 1 900.0 0 1.995 0 34.7360 0 1 1000.0 0 1.948 0 34.7480 0 1 1100.0 0 1.881 0 34.7570 0 1 1200.0 0 1.796 0 34.7570 0 1 1300.0 0 1.711 0 34.7610 0 1 1400.0 0 1.597 0 34.7590 0 1 1500.0 0 1.479 0 34.7550 0 1 1750.0 0 1.297 0 34.7470 0 1 2000.0 0 1.071 0 34.7340 0 1 2500.0 0 0.695 0 34.7110 0 1 3000.0 0 0.421 0 34.6990 0 1 3500.0 0 0.189 0 34.6870 0 1 4000.0 0 0.007 0 34.6760 0 1 WOD09_FR008758 3367575 B 1987-01-16T07:49 69.9597 -59.474 0.0 0 1.349 0 33.6790 0 1 10.0 0 1.342 0 33.6810 0 1 20.0 0 1.333 0 33.6810 0 1 30.0 0 1.194 0 33.6820 0 1 50.0 0 -0.874 0 33.7150 0 1 75.0 0 -1.584 0 33.7970 0 1 100.0 0 -1.500 0 33.8600 0 1 125.0 0 -0.942 0 33.9340 0 1 150.0 0 -0.340 0 34.0420 0 1 200.0 0 1.337 0 34.3320 0 1 250.0 0 1.714 0 34.4340 0 1 300.0 0 1.834 0 34.4900 0 1 400.0 0 1.970 0 34.5700 0 1 500.0 0 2.040 0 34.6260 0 1 600.0 0 2.055 0 34.6710 0 1 700.0 0 2.053 0 34.7060 0 1 800.0 0 2.030 0 34.7270 0 1 900.0 0 1.987 0 34.7390 0 1 1000.0 0 1.920 0 34.7470 0 1 1100.0 0 1.857 0 34.7530 0 1 1200.0 0 1.788 0 34.7580 0 1 1300.0 0 1.696 0 34.7590 0 1 WOD09_FR009984 7728143 B 1993-04-06T05:37 68.4365 -50.683 0.0 0 4.052 0 33.8200 0 1 10.0 0 4.056 0 33.8260 0 1 20.0 0 4.055 0 33.8260 0 1 30.0 0 4.057 0 33.8250 0 1 50.0 0 4.046 0 33.8250 0 1 75.0 0 4.015 0 33.8270 0 1 100.0 0 4.003 0 33.8290 0 1 125.0 0 3.887 0 33.8410 0 1 150.0 0 2.821 0 33.8800 0 1 200.0 0 1.743 0 33.9330 0 1 250.0 0 1.958 0 34.0560 0 1 300.0 0 2.186 0 34.1560 0 1 400.0 0 2.204 0 34.2640 0 1 500.0 0 2.207 0 34.3830 0 1 600.0 0 2.227 0 34.4400 0 1 700.0 0 2.260 0 34.5060 0 1 800.0 0 2.250 0 34.5710 0 1 900.0 0 2.255 0 34.6260 0 1 1000.0 0 2.271 0 34.6660 0 1 1100.0 0 2.240 0 34.6940 0 1 1200.0 0 2.185 0 34.7140 0 1 1300.0 0 2.115 0 34.7340 0 1 1400.0 0 1.980 0 34.7510 0 1 1500.0 0 1.876 0 34.7600 0 1 WOD09_FR009984 7728144 B 1993-04-07T12:46 68.4160 -50.665 0.0 0 4.113 0 33.8220 0 1 10.0 0 4.113 0 33.8230 0 1 20.0 0 4.114 0 33.8230 0 1 30.0 0 4.113 0 33.8230 0 1 50.0 0 4.118 0 33.8230 0 1 75.0 0 4.117 0 33.8230 0 1 100.0 0 4.008 0 33.8280 0 1 125.0 0 3.079 0 33.8440 0 1 150.0 0 2.190 0 33.8880 0 1 200.0 0 2.122 0 34.0320 0 1 250.0 0 2.207 0 34.1280 0 1 300.0 0 2.218 0 34.2020 0 1 400.0 0 2.194 0 34.2830 0 1 WOD09_FR009984 7728146 B 1993-04-15T08:04 61.1437 -51.988 0.0 0 4.176 0 33.8760 0 1 10.0 0 4.173 0 33.8870 0 1 20.0 0 4.168 0 33.8890 0 1 30.0 0 4.167 0 33.8890 0 1 50.0 0 4.168 0 33.8900 0 1 75.0 0 4.155 0 33.8910 0 1 100.0 0 4.029 0 33.8970 0 1 125.0 0 3.343 0 33.9260 0 1 150.0 0 2.506 0 33.9640 0 1 200.0 0 2.107 0 34.0300 0 1 250.0 0 2.123 0 34.0800 0 1 300.0 0 2.212 0 34.1400 0 1 400.0 0 2.289 0 34.2610 0 1 500.0 0 2.327 0 34.3490 0 1 600.0 0 2.354 0 34.4380 0 1 700.0 0 2.355 0 34.4950 0 1 800.0 0 2.361 0 34.5550 0 1 900.0 0 2.336 0 34.6010 0 1 1000.0 0 2.318 0 34.6490 0 1 1100.0 0 2.313 0 34.6770 0 1 1200.0 0 2.288 0 34.6990 0 1 1300.0 0 2.251 0 34.7240 0 1 1400.0 0 2.209 0 34.7410 0 1 1500.0 0 2.146 0 34.7530 0 1 1750.0 0 1.907 0 34.7600 0 1 2000.0 0 1.687 0 34.7570 0 1 2500.0 0 1.216 0 34.7330 0 1 3000.0 0 0.721 0 34.7030 0 1 3500.0 0 0.349 0 34.6820 0 1 4000.0 0 0.098 0 34.6700 0 1 4500.0 0 -0.086 0 34.6610 0 1 WOD09_FR009984 7728147 B 1993-04-16T21:16 61.1385 -52.000 0.0 0 4.060 0 33.8820 0 1 10.0 0 4.074 0 33.8960 0 1 20.0 0 4.074 0 33.8960 0 1 30.0 0 4.067 0 33.8970 0 1 50.0 0 4.053 0 33.8980 0 1 75.0 0 4.034 0 33.8980 0 1 100.0 0 3.991 0 33.9010 0 1 125.0 0 3.592 0 33.9190 0 1 150.0 0 2.562 0 33.9650 0 1 200.0 0 2.194 0 34.0040 0 1 250.0 0 2.063 0 34.0670 0 1 300.0 0 2.135 0 34.1300 0 1 400.0 0 2.304 0 34.2540 0 1 500.0 0 2.329 0 34.3530 0 1 600.0 0 2.347 0 34.4320 0 1 700.0 0 2.352 0 34.4970 0 1 800.0 0 2.338 0 34.5650 0 1 900.0 0 2.336 0 34.6090 0 1 1000.0 0 2.325 0 34.6450 0 1 1100.0 0 2.308 0 34.6730 0 1 1200.0 0 2.287 0 34.7040 0 1 1300.0 0 2.254 0 34.7230 0 1 1400.0 0 2.199 0 34.7390 0 1 1500.0 0 2.102 0 34.7480 0 1 1750.0 0 1.920 0 34.7610 0 1 2000.0 0 1.689 0 34.7580 0 1 2500.0 0 1.250 0 34.7350 0 1 WOD09_FR009984 7728148 B 1993-04-17T00:16 61.1363 -51.975 0.0 0 4.130 0 33.8800 0 1 10.0 0 4.134 0 33.8910 0 1 20.0 0 4.134 0 33.8920 0 1 30.0 0 4.133 0 33.8920 0 1 50.0 0 4.125 0 33.8940 0 1 75.0 0 4.103 0 33.8950 0 1 100.0 0 4.056 0 33.8980 0 1 125.0 0 3.827 0 33.9050 0 1 150.0 0 2.489 0 33.9700 0 1 200.0 0 2.114 0 34.0240 0 1 250.0 0 2.094 0 34.0910 0 1 300.0 0 2.239 0 34.1600 0 1 400.0 0 2.295 0 34.2630 0 1 500.0 0 2.326 0 34.3600 0 1 WOD09_FR009984 7728149 B 1993-04-17T13:01 61.1135 -51.987 0.0 0 4.123 0 33.8860 0 1 10.0 0 4.121 0 33.8910 0 1 20.0 0 4.119 0 33.8920 0 1 30.0 0 4.118 0 33.8920 0 1 50.0 0 4.119 0 33.8930 0 1 75.0 0 4.101 0 33.8940 0 1 100.0 0 4.078 0 33.8950 0 1 125.0 0 3.705 0 33.9070 0 1 150.0 0 2.531 0 33.9640 0 1 200.0 0 2.175 0 34.0140 0 1 250.0 0 2.083 0 34.0760 0 1 300.0 0 2.161 0 34.1350 0 1 400.0 0 2.302 0 34.2560 0 1 500.0 0 2.335 0 34.3650 0 1 600.0 0 2.346 0 34.4390 0 1 700.0 0 2.351 0 34.5040 0 1 800.0 0 2.336 0 34.5640 0 1 900.0 0 2.333 0 34.6140 0 1 1000.0 0 2.319 0 34.6510 0 1 1100.0 0 2.311 0 34.6840 0 1 1200.0 0 2.279 0 34.7070 0 1 1300.0 0 2.241 0 34.7260 0 1 1400.0 0 2.195 0 34.7410 0 1 1500.0 0 2.117 0 34.7480 0 1 1750.0 0 1.945 0 34.7600 0 1 2000.0 0 1.736 0 34.7590 0 1 2500.0 0 1.248 0 34.7360 0 1 3000.0 0 0.763 0 34.7050 0 1 3500.0 0 0.356 0 34.6830 0 1 4000.0 0 0.126 0 34.6720 0 1 4500.0 0 -0.097 0 34.6610 0 1 WOD09_FR009986 7728272 B 1994-02-06T01:48 69.2485 -51.088 0.0 0 3.485 0 33.8960 0 1 10.0 0 3.478 0 33.9015 0 1 20.0 0 3.478 0 33.9076 0 1 30.0 0 3.476 0 33.9083 0 1 50.0 0 3.456 0 33.9108 0 1 75.0 0 3.388 0 33.9137 0 1 100.0 0 3.230 0 33.9170 0 1 125.0 0 2.488 0 33.9346 0 1 150.0 0 1.642 0 33.9554 0 1 200.0 0 1.395 0 33.9696 0 1 250.0 0 1.362 0 34.0231 0 1 300.0 0 1.883 0 34.1608 0 1 400.0 0 2.141 0 34.2943 0 1 500.0 0 2.212 0 34.3949 0 1 600.0 0 2.264 0 34.4868 0 1 700.0 0 2.323 0 34.5457 0 1 800.0 0 2.343 0 34.6018 0 1 900.0 0 2.339 0 34.6430 0 1 1000.0 0 2.320 0 34.6780 0 1 1100.0 0 2.289 0 34.7065 0 1 1200.0 0 2.240 0 34.7282 0 1 1300.0 0 2.198 0 34.7408 0 1 1400.0 0 2.135 0 34.7513 0 1 1500.0 0 2.070 0 34.7589 0 1 1750.0 0 1.863 0 34.7648 0 1 2000.0 0 1.528 0 34.7543 0 1 WOD09_FR009986 7728273 B 1994-02-06T07:15 68.8305 -50.858 0.0 0 3.687 0 33.9016 0 1 10.0 0 3.676 0 33.9021 0 1 20.0 0 3.677 0 33.9020 0 1 30.0 0 3.669 0 33.9028 0 1 50.0 0 3.610 0 33.9121 0 1 75.0 0 3.499 0 33.9138 0 1 100.0 0 3.363 0 33.9147 0 1 125.0 0 2.597 0 33.9311 0 1 150.0 0 1.794 0 33.9572 0 1 200.0 0 1.521 0 34.0036 0 1 250.0 0 1.743 0 34.0973 0 1 300.0 0 2.112 0 34.2099 0 1 400.0 0 2.222 0 34.3083 0 1 500.0 0 2.302 0 34.4082 0 1 600.0 0 2.324 0 34.4883 0 1 700.0 0 2.323 0 34.5519 0 1 800.0 0 2.322 0 34.6156 0 1 900.0 0 2.324 0 34.6558 0 1 1000.0 0 2.312 0 34.6841 0 1 1100.0 0 2.283 0 34.7094 0 1 1200.0 0 2.211 0 34.7238 0 1 1300.0 0 2.160 0 34.7404 0 1 1400.0 0 2.102 0 34.7516 0 1 1500.0 0 2.026 0 34.7612 0 1 1750.0 0 1.815 0 34.7645 0 1 2000.0 0 1.482 0 34.7521 0 1 WOD09_FR009986 7728274 B 1994-02-06T11:36 68.4222 -50.660 0.0 0 3.707 0 33.8955 0 1 10.0 0 3.708 0 33.8954 0 1 20.0 0 3.710 0 33.8952 0 1 30.0 0 3.700 0 33.8951 0 1 50.0 0 3.700 0 33.8947 0 1 75.0 0 3.663 0 33.8990 0 1 100.0 0 3.140 0 33.9107 0 1 125.0 0 2.309 0 33.9224 0 1 150.0 0 1.863 0 33.9340 0 1 200.0 0 1.689 0 33.9816 0 1 250.0 0 1.901 0 34.0942 0 1 300.0 0 2.071 0 34.1859 0 1 WOD09_FR009986 7728275 B 1994-02-06T18:19 68.3910 -50.662 0.0 0 3.698 0 33.8953 0 1 10.0 0 3.698 0 33.8951 0 1 20.0 0 3.699 0 33.8950 0 1 30.0 0 3.700 0 33.8951 0 1 50.0 0 3.702 0 33.8945 0 1 75.0 0 3.703 0 33.8946 0 1 100.0 0 3.581 0 33.9031 0 1 125.0 0 2.552 0 33.9195 0 1 150.0 0 2.118 0 33.9270 0 1 200.0 0 1.659 0 33.9618 0 1 250.0 0 1.909 0 34.0942 0 1 300.0 0 2.099 0 34.1982 0 1 400.0 0 2.175 0 34.3214 0 1 500.0 0 2.268 0 34.4300 0 1 600.0 0 2.301 0 34.5047 0 1 700.0 0 2.320 0 34.5725 0 1 800.0 0 2.323 0 34.6196 0 1 900.0 0 2.263 0 34.6526 0 1 1000.0 0 2.235 0 34.6802 0 1 1100.0 0 2.217 0 34.7056 0 1 1200.0 0 2.165 0 34.7267 0 1 1300.0 0 2.106 0 34.7371 0 1 1400.0 0 1.973 0 34.7522 0 1 1500.0 0 1.812 0 34.7591 0 1 WOD09_FR009986 7728276 B 1994-02-06T21:18 68.3882 -50.665 0.0 0 3.702 0 33.8951 0 1 10.0 0 3.702 0 33.8946 0 1 20.0 0 3.704 0 33.8948 0 1 30.0 0 3.704 0 33.8946 0 1 50.0 0 3.705 0 33.8955 0 1 75.0 0 3.706 0 33.8949 0 1 100.0 0 3.570 0 33.9026 0 1 125.0 0 2.646 0 33.9163 0 1 150.0 0 1.939 0 33.9320 0 1 200.0 0 1.678 0 33.9620 0 1 250.0 0 1.911 0 34.0704 0 1 300.0 0 2.037 0 34.1686 0 1 WOD09_FR009986 7728277 B 1994-02-07T02:28 67.7980 -51.158 0.0 0 3.685 0 33.9062 0 1 10.0 0 3.684 0 33.9063 0 1 20.0 0 3.685 0 33.9065 0 1 30.0 0 3.686 0 33.9065 0 1 50.0 0 3.685 0 33.9071 0 1 75.0 0 3.636 0 33.9108 0 1 100.0 0 3.420 0 33.9149 0 1 125.0 0 1.926 0 33.9446 0 1 150.0 0 1.569 0 33.9501 0 1 200.0 0 1.405 0 33.9782 0 1 250.0 0 1.535 0 34.0664 0 1 300.0 0 2.190 0 34.2181 0 1 400.0 0 2.275 0 34.3255 0 1 500.0 0 2.279 0 34.4019 0 1 600.0 0 2.294 0 34.4744 0 1 700.0 0 2.318 0 34.5401 0 1 800.0 0 2.330 0 34.5929 0 1 900.0 0 2.325 0 34.6313 0 1 1000.0 0 2.320 0 34.6712 0 1 1100.0 0 2.293 0 34.6997 0 1 1200.0 0 2.248 0 34.7220 0 1 1300.0 0 2.194 0 34.7388 0 1 1400.0 0 2.133 0 34.7479 0 1 1500.0 0 2.035 0 34.7555 0 1 1750.0 0 1.643 0 34.7596 0 1 WOD09_FR009986 7728278 B 1994-02-07T08:40 68.4100 -50.718 0.0 0 3.922 0 33.8874 0 1 10.0 0 3.910 0 33.8877 0 1 20.0 0 3.801 0 33.8917 0 1 30.0 0 3.787 0 33.8911 0 1 50.0 0 3.702 0 33.8941 0 1 75.0 0 3.664 0 33.8966 0 1 100.0 0 3.572 0 33.8983 0 1 125.0 0 2.289 0 33.9412 0 1 150.0 0 2.023 0 33.9692 0 1 200.0 0 1.837 0 34.0133 0 1 250.0 0 1.914 0 34.0808 0 1 300.0 0 2.074 0 34.1876 0 1 WOD09_FR009986 7728279 B 1994-02-07T15:36 68.1038 -50.928 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 3.831 0 33.8977 0 1 50.0 0 3.735 0 33.8970 0 1 75.0 0 3.682 0 33.8999 0 1 100.0 0 3.240 0 33.9142 0 1 125.0 0 2.279 0 33.9352 0 1 150.0 0 1.692 0 33.9516 0 1 200.0 0 1.541 0 33.9915 0 1 250.0 0 1.727 0 34.0892 0 1 300.0 0 2.056 0 34.1954 0 1 400.0 0 2.267 0 34.3314 0 1 500.0 0 2.294 0 34.4351 0 1 600.0 0 2.309 0 34.4839 0 1 700.0 0 2.316 0 34.5451 0 1 800.0 0 2.330 0 34.5959 0 1 900.0 0 2.338 0 34.6381 0 1 1000.0 0 2.327 0 34.6666 0 1 1100.0 0 2.286 0 34.7073 0 1 1200.0 0 2.243 0 34.7281 0 1 1300.0 0 2.187 0 34.7421 0 1 1400.0 0 2.134 0 34.7509 0 1 1500.0 0 2.034 0 34.7602 0 1 1750.0 0 1.686 0 34.7597 0 1 WOD09_FR009986 7728280 B 1994-02-08T01:34 67.8152 -50.397 0.0 0 4.143 0 33.8764 0 1 10.0 0 4.144 0 33.8760 0 1 20.0 0 4.140 0 33.8766 0 1 30.0 0 4.140 0 33.8764 0 1 50.0 0 4.141 0 33.8757 0 1 75.0 0 4.092 0 33.8793 0 1 100.0 0 3.744 0 33.8959 0 1 125.0 0 3.070 0 33.9044 0 1 150.0 0 2.215 0 33.9163 0 1 200.0 0 1.672 0 33.9519 0 1 250.0 0 1.741 0 34.0260 0 1 300.0 0 2.024 0 34.1644 0 1 400.0 0 2.180 0 34.3139 0 1 500.0 0 2.208 0 34.4183 0 1 600.0 0 2.237 0 34.4975 0 1 700.0 0 2.280 0 34.5666 0 1 800.0 0 2.313 0 34.6261 0 1 900.0 0 2.254 0 34.6584 0 1 1000.0 0 2.220 0 34.6912 0 1 1100.0 0 2.181 0 34.7166 0 1 1200.0 0 2.112 0 34.7412 0 1 1300.0 0 2.053 0 34.7536 0 1 1400.0 0 1.931 0 34.7560 0 1 WOD09_FR009986 7728281 B 1994-02-08T07:16 68.7353 -50.393 0.0 0 4.312 0 33.8628 0 1 10.0 0 4.308 0 33.8635 0 1 20.0 0 4.320 0 33.8628 0 1 30.0 0 4.322 0 33.8618 0 1 50.0 0 4.300 0 33.8622 0 1 75.0 0 4.196 0 33.8655 0 1 100.0 0 3.631 0 33.8908 0 1 125.0 0 2.441 0 33.9215 0 1 150.0 0 2.254 0 33.9300 0 1 200.0 0 1.770 0 33.9892 0 1 250.0 0 1.781 0 34.0275 0 1 300.0 0 1.805 0 34.0450 0 1 WOD09_FR009986 7728282 B 1994-02-10T14:43 61.9955 -52.010 0.0 0 3.441 0 33.8858 0 1 10.0 0 3.436 0 33.8861 0 1 20.0 0 3.425 0 33.8861 0 1 30.0 0 3.425 0 33.8855 0 1 50.0 0 3.426 0 33.8857 0 1 75.0 0 3.421 0 33.8856 0 1 100.0 0 3.325 0 33.8904 0 1 125.0 0 2.319 0 33.9488 0 1 150.0 0 2.090 0 33.9786 0 1 200.0 0 1.891 0 34.0349 0 1 250.0 0 2.051 0 34.1060 0 1 WOD09_FR009986 7728283 B 1994-02-10T16:40 61.9803 -52.023 0.0 0 3.410 0 33.8861 0 1 10.0 0 3.411 0 33.8862 0 1 20.0 0 3.410 0 33.8862 0 1 30.0 0 3.411 0 33.8863 0 1 50.0 0 3.410 0 33.8863 0 1 75.0 0 3.407 0 33.8863 0 1 100.0 0 3.246 0 33.8938 0 1 125.0 0 2.553 0 33.9282 0 1 150.0 0 2.156 0 33.9578 0 1 200.0 0 1.934 0 34.0230 0 1 250.0 0 1.985 0 34.0993 0 1 WOD09_FR009986 7728284 B 1994-02-10T18:16 61.9750 -52.052 0.0 0 3.406 0 33.8873 0 1 10.0 0 3.402 0 33.8867 0 1 20.0 0 3.399 0 33.8863 0 1 30.0 0 3.398 0 33.8866 0 1 50.0 0 3.400 0 33.8866 0 1 75.0 0 3.399 0 33.8867 0 1 100.0 0 3.288 0 33.8919 0 1 125.0 0 2.723 0 33.9183 0 1 150.0 0 2.223 0 33.9469 0 1 200.0 0 1.546 0 33.9921 0 1 250.0 0 2.016 0 34.1312 0 1 WOD09_FR009986 7728285 B 1994-02-10T19:46 61.9770 -52.080 0.0 0 3.402 0 33.8853 0 1 10.0 0 3.404 0 33.8867 0 1 20.0 0 3.406 0 33.8865 0 1 30.0 0 3.408 0 33.8865 0 1 50.0 0 3.409 0 33.8866 0 1 75.0 0 3.409 0 33.8862 0 1 100.0 0 3.270 0 33.8945 0 1 125.0 0 2.719 0 33.9240 0 1 150.0 0 1.913 0 33.9686 0 1 200.0 0 1.567 0 34.0053 0 1 250.0 0 1.883 0 34.0994 0 1 300.0 0 2.035 0 34.1874 0 1 400.0 0 2.148 0 34.2881 0 1 500.0 0 2.324 0 34.4094 0 1 600.0 0 2.365 0 34.4861 0 1 700.0 0 2.368 0 34.5390 0 1 800.0 0 2.368 0 34.5841 0 1 900.0 0 2.353 0 34.6201 0 1 1000.0 0 2.345 0 34.6545 0 1 1100.0 0 2.324 0 34.6831 0 1 1200.0 0 2.291 0 34.7075 0 1 1300.0 0 2.235 0 34.7321 0 1 1400.0 0 2.198 0 34.7416 0 1 1500.0 0 2.116 0 34.7557 0 1 1750.0 0 1.897 0 34.7651 0 1 2000.0 0 1.540 0 34.7532 0 1 WOD09_FR009986 7728286 B 1994-02-10T22:16 61.9827 -52.100 0.0 0 3.399 0 33.8866 0 1 10.0 0 3.399 0 33.8867 0 1 20.0 0 3.400 0 33.8868 0 1 WOD09_FR009986 7728287 B 1994-02-10T22:51 61.9833 -52.103 0.0 0 1 10.0 0 1 20.0 0 3.388 0 33.8473 0 1 30.0 0 3.390 0 33.8781 0 1 WOD09_FR009986 7728288 B 1994-02-10T23:22 61.9913 -52.107 0.0 0 3.395 0 33.8868 0 1 10.0 0 3.397 0 33.8868 0 1 20.0 0 3.398 0 33.8871 0 1 WOD09_FR009986 7728289 B 1994-02-11T13:13 62.1205 -52.032 0.0 0 3.782 0 33.8817 0 1 10.0 0 3.783 0 33.8812 0 1 20.0 0 3.783 0 33.8812 0 1 30.0 0 3.781 0 33.8813 0 1 50.0 0 3.782 0 33.8809 0 1 75.0 0 3.774 0 33.8815 0 1 100.0 0 3.754 0 33.8821 0 1 125.0 0 3.446 0 33.8947 0 1 150.0 0 2.703 0 33.9222 0 1 200.0 0 1.886 0 34.0298 0 1 250.0 0 2.162 0 34.1311 0 1 300.0 0 2.082 0 34.1815 0 1 WOD09_FR009986 7728290 B 1994-02-12T13:07 61.8115 -52.028 0.0 0 1 10.0 0 3.389 0 33.8908 0 1 20.0 0 3.390 0 33.8912 0 1 30.0 0 3.394 0 33.8912 0 1 50.0 0 3.380 0 33.8916 0 1 75.0 0 3.364 0 33.8922 0 1 100.0 0 3.295 0 33.8946 0 1 125.0 0 2.838 0 33.9120 0 1 150.0 0 2.365 0 33.9276 0 1 200.0 0 1.307 0 33.9792 0 1 250.0 0 1.435 0 34.0699 0 1 WOD09_FR009986 7728291 B 1994-02-12T14:45 61.8183 -52.040 0.0 0 3.338 0 33.8923 0 1 10.0 0 3.338 0 33.8906 0 1 20.0 0 3.338 0 33.8917 0 1 30.0 0 3.337 0 33.8934 0 1 50.0 0 3.339 0 33.8919 0 1 75.0 0 3.340 0 33.8919 0 1 100.0 0 3.267 0 33.8939 0 1 125.0 0 2.829 0 33.9108 0 1 150.0 0 1.874 0 33.9456 0 1 200.0 0 1.357 0 33.9843 0 1 250.0 0 1.228 0 34.0204 0 1 WOD09_FR009986 7728292 B 1994-02-12T15:49 61.8127 -52.055 0.0 0 1 10.0 0 3.300 0 33.8923 0 1 20.0 0 3.299 0 33.8927 0 1 30.0 0 3.301 0 33.8907 0 1 50.0 0 3.303 0 33.8919 0 1 75.0 0 3.294 0 33.8931 0 1 100.0 0 3.114 0 33.9002 0 1 125.0 0 2.380 0 33.9315 0 1 150.0 0 1.681 0 33.9546 0 1 200.0 0 1.245 0 33.9821 0 1 WOD09_FR009986 7728293 B 1994-02-13T03:40 62.2863 -52.110 0.0 0 3.777 0 33.8787 0 1 10.0 0 3.780 0 33.8814 0 1 20.0 0 3.777 0 33.8812 0 1 30.0 0 3.777 0 33.8796 0 1 50.0 0 3.777 0 33.8814 0 1 75.0 0 3.777 0 33.8820 0 1 100.0 0 3.560 0 33.8912 0 1 125.0 0 2.907 0 33.9126 0 1 150.0 0 2.338 0 33.9437 0 1 200.0 0 1.985 0 34.0382 0 1 250.0 0 1.924 0 34.1180 0 1 WOD09_FR009986 7728294 B 1994-02-13T06:10 62.2782 -52.115 0.0 0 3.788 0 33.8825 0 1 10.0 0 3.784 0 33.8821 0 1 20.0 0 3.784 0 33.8808 0 1 30.0 0 3.788 0 33.8821 0 1 50.0 0 3.782 0 33.8823 0 1 75.0 0 3.778 0 33.8817 0 1 100.0 0 3.741 0 33.8834 0 1 125.0 0 2.960 0 33.9119 0 1 150.0 0 2.459 0 33.9346 0 1 200.0 0 1.943 0 34.0354 0 1 WOD09_FR009986 7728295 B 1994-02-13T08:43 62.2245 -52.137 0.0 0 3.786 0 33.8825 0 1 10.0 0 3.784 0 33.8822 0 1 20.0 0 3.781 0 33.8816 0 1 30.0 0 3.779 0 33.8790 0 1 50.0 0 3.776 0 33.8816 0 1 75.0 0 3.773 0 33.8812 0 1 100.0 0 3.708 0 33.8833 0 1 125.0 0 2.983 0 33.9106 0 1 150.0 0 2.522 0 33.9265 0 1 200.0 0 1.731 0 34.0057 0 1 250.0 0 2.090 0 34.1129 0 1 300.0 0 2.127 0 34.1775 0 1 400.0 0 2.157 0 34.2663 0 1 500.0 0 2.302 0 34.3824 0 1 600.0 0 2.362 0 34.4687 0 1 700.0 0 2.367 0 34.5368 0 1 800.0 0 2.356 0 34.5891 0 1 900.0 0 2.350 0 34.6287 0 1 1000.0 0 2.339 0 34.6605 0 1 1100.0 0 2.305 0 34.6911 0 1 1200.0 0 2.277 0 34.7124 0 1 1300.0 0 2.233 0 34.7351 0 1 1400.0 0 2.186 0 34.7457 0 1 1500.0 0 2.134 0 34.7540 0 1 1750.0 0 1.926 0 34.7642 0 1 2000.0 0 1.699 0 34.7603 0 1 2500.0 0 1.280 0 34.7386 0 1 3000.0 0 0.835 0 34.7103 0 1 3500.0 0 0.448 0 34.6882 0 1 4000.0 0 0.113 0 34.6723 0 1 WOD09_FR009986 7728296 B 1994-02-13T13:58 62.2165 -52.187 0.0 0 1 10.0 0 3.735 0 33.8826 0 1 20.0 0 3.737 0 33.8829 0 1 30.0 0 3.731 0 33.8833 0 1 50.0 0 3.648 0 33.8835 0 1 75.0 0 3.519 0 33.8843 0 1 100.0 0 3.437 0 33.8845 0 1 125.0 0 2.774 0 33.9197 0 1 150.0 0 1.973 0 33.9760 0 1 200.0 0 1.933 0 34.0555 0 1 250.0 0 2.131 0 34.1357 0 1 300.0 0 2.051 0 34.1899 0 1 400.0 0 2.222 0 34.2896 0 1 500.0 0 2.255 0 34.3635 0 1 600.0 0 2.350 0 34.4511 0 1 700.0 0 2.365 0 34.5080 0 1 WOD09_FR009986 7728297 B 1994-02-13T15:31 62.2223 -52.193 0.0 0 1 10.0 0 3.761 0 33.8824 0 1 20.0 0 3.757 0 33.8828 0 1 30.0 0 3.750 0 33.8832 0 1 50.0 0 3.572 0 33.8847 0 1 75.0 0 3.464 0 33.8831 0 1 100.0 0 3.171 0 33.9031 0 1 125.0 0 2.452 0 33.9381 0 1 150.0 0 1.934 0 33.9849 0 1 200.0 0 1.961 0 34.0659 0 1 250.0 0 2.084 0 34.1314 0 1 300.0 0 2.154 0 34.1940 0 1 400.0 0 2.235 0 34.3056 0 1 WOD09_FR009986 7728298 B 1994-02-14T01:49 62.0957 -52.257 0.0 0 1 10.0 0 3.442 0 33.8855 0 1 20.0 0 3.437 0 33.8861 0 1 30.0 0 3.438 0 33.8846 0 1 50.0 0 3.436 0 33.8869 0 1 75.0 0 3.408 0 33.8857 0 1 100.0 0 3.342 0 33.8877 0 1 125.0 0 3.008 0 33.9050 0 1 150.0 0 2.119 0 33.9650 0 1 200.0 0 1.499 0 34.0055 0 1 250.0 0 1.866 0 34.1221 0 1 300.0 0 2.037 0 34.1946 0 1 400.0 0 2.101 0 34.2823 0 1 500.0 0 2.280 0 34.3852 0 1 600.0 0 2.358 0 34.4567 0 1 700.0 0 2.372 0 34.5161 0 1 WOD09_FR009986 7728299 B 1994-02-14T04:37 62.1178 -52.290 0.0 0 3.432 0 33.8861 0 1 10.0 0 3.429 0 33.8864 0 1 20.0 0 3.430 0 33.8865 0 1 30.0 0 3.429 0 33.8863 0 1 50.0 0 3.432 0 33.8863 0 1 75.0 0 3.362 0 33.8873 0 1 100.0 0 3.023 0 33.9016 0 1 125.0 0 2.358 0 33.9412 0 1 150.0 0 1.942 0 33.9779 0 1 200.0 0 1.656 0 34.0397 0 1 250.0 0 2.019 0 34.1516 0 1 WOD09_FR009986 7728300 B 1994-02-14T09:28 62.1257 -52.307 0.0 0 3.436 0 33.8903 0 1 10.0 0 3.434 0 33.8899 0 1 20.0 0 3.431 0 33.8891 0 1 30.0 0 3.435 0 33.8878 0 1 50.0 0 3.432 0 33.8882 0 1 75.0 0 3.436 0 33.8863 0 1 100.0 0 3.368 0 33.8889 0 1 125.0 0 2.622 0 33.9273 0 1 150.0 0 2.229 0 33.9467 0 1 200.0 0 1.631 0 34.0181 0 1 250.0 0 2.018 0 34.1326 0 1 300.0 0 2.035 0 34.1791 0 1 400.0 0 2.265 0 34.3022 0 1 500.0 0 2.327 0 34.4048 0 1 600.0 0 2.363 0 34.4899 0 1 700.0 0 2.363 0 34.5462 0 1 800.0 0 2.362 0 34.5912 0 1 900.0 0 2.352 0 34.6351 0 1 1000.0 0 2.346 0 34.6608 0 1 1100.0 0 2.313 0 34.6916 0 1 1200.0 0 2.277 0 34.7146 0 1 1300.0 0 2.218 0 34.7374 0 1 1400.0 0 2.173 0 34.7478 0 1 1500.0 0 2.108 0 34.7569 0 1 1750.0 0 1.923 0 34.7657 0 1 2000.0 0 1.691 0 34.7625 0 1 2500.0 0 1.232 0 34.7360 0 1 3000.0 0 0.751 0 34.7062 0 1 3500.0 0 0.398 0 34.6894 0 1 4000.0 0 0.156 0 34.6741 0 1 4500.0 0 -0.051 0 34.6650 0 1 WOD09_FR009986 7728301 B 1994-02-14T19:00 62.4240 -52.115 0.0 0 3.774 0 33.8792 0 1 10.0 0 3.774 0 33.8806 0 1 20.0 0 3.775 0 33.8807 0 1 30.0 0 3.773 0 33.8817 0 1 50.0 0 3.769 0 33.8823 0 1 75.0 0 3.749 0 33.8828 0 1 100.0 0 3.694 0 33.8837 0 1 125.0 0 2.773 0 33.9169 0 1 150.0 0 2.113 0 33.9498 0 1 WOD09_FR009986 7728324 B 1994-03-01T17:07 61.9712 -59.478 0.0 0 1.264 0 33.7692 0 1 10.0 0 1.264 0 33.7682 0 1 20.0 0 1.265 0 33.7680 0 1 30.0 0 1.265 0 33.7683 0 1 50.0 0 1.266 0 33.7684 0 1 75.0 0 0.164 0 33.8467 0 1 100.0 0 -0.946 0 33.9245 0 1 125.0 0 -1.102 0 33.9825 0 1 150.0 0 -0.331 0 34.1186 0 1 200.0 0 1.226 0 34.3587 0 1 250.0 0 1.680 0 34.4603 0 1 WOD09_FR009986 7728325 B 1994-03-01T20:01 61.9310 -59.483 0.0 0 1.263 0 33.7693 0 1 10.0 0 1.262 0 33.7707 0 1 20.0 0 1.261 0 33.7705 0 1 30.0 0 1.262 0 33.7709 0 1 50.0 0 1.264 0 33.7686 0 1 75.0 0 0.382 0 33.8372 0 1 100.0 0 -1.066 0 33.9342 0 1 125.0 0 -1.111 0 33.9851 0 1 150.0 0 -0.486 0 34.1063 0 1 200.0 0 1.081 0 34.3358 0 1 250.0 0 1.668 0 34.4584 0 1 300.0 0 1.914 0 34.5338 0 1 400.0 0 2.038 0 34.6097 0 1 500.0 0 2.022 0 34.6480 0 1 600.0 0 2.003 0 34.6844 0 1 700.0 0 1.991 0 34.7102 0 1 800.0 0 1.904 0 34.7229 0 1 900.0 0 1.853 0 34.7369 0 1 1000.0 0 1.774 0 34.7416 0 1 1100.0 0 1.711 3 34.7453 0 1 1200.0 0 1.622 3 34.7463 0 1 1300.0 0 1.535 3 34.7455 0 1 1400.0 0 1.437 3 34.7421 0 1 1500.0 0 1.328 3 34.7383 0 1 1750.0 0 1.102 3 34.7245 0 1 2000.0 0 0.916 0 34.7145 0 1 2500.0 0 0.542 0 34.6922 0 1 3000.0 0 0.267 0 34.6776 0 1 3500.0 0 0.081 0 34.6699 0 1 4000.0 0 -0.080 0 34.6631 0 1 4500.0 0 -0.173 0 34.6583 0 1 WOD09_FR009986 7728326 B 1994-03-02T10:13 62.0160 -58.000 0.0 0 1.531 0 33.7878 0 1 10.0 0 1.531 0 33.7882 0 1 20.0 0 1.532 0 33.7889 0 1 30.0 0 1.536 0 33.7903 0 1 50.0 0 1.543 0 33.7913 0 1 75.0 0 1.568 0 33.7967 0 1 100.0 0 -0.240 0 33.9422 0 1 125.0 0 -0.445 0 33.9525 0 1 150.0 0 -0.520 0 33.9805 0 1 200.0 0 0.708 0 34.2417 0 1 250.0 0 1.463 0 34.4005 0 1 WOD09_FR009986 7728327 B 1994-03-02T11:52 62.0303 -58.017 0.0 0 1.522 0 33.7868 0 1 10.0 0 1.520 0 33.7867 0 1 20.0 0 1.519 0 33.7869 0 1 30.0 0 1.519 0 33.7871 0 1 50.0 0 1.517 0 33.7874 0 1 75.0 0 1.562 0 33.8008 0 1 100.0 0 -0.346 0 33.9460 0 1 125.0 0 -0.529 0 33.9564 0 1 150.0 0 -0.472 0 34.0156 0 1 200.0 0 0.698 0 34.2583 0 1 250.0 0 1.449 0 34.4058 0 1 WOD09_FR009986 7728328 B 1994-03-02T15:33 62.0775 -58.050 0.0 0 1.532 0 33.7888 0 1 10.0 0 1.532 0 33.7882 0 1 20.0 0 1.529 0 33.7885 0 1 30.0 0 1.530 0 33.7886 0 1 50.0 0 1.568 0 33.7954 0 1 75.0 0 0.637 0 33.8867 0 1 100.0 0 -0.364 0 33.9495 0 1 125.0 0 -0.434 0 33.9613 0 1 150.0 0 -0.564 0 34.0037 0 1 200.0 0 0.587 0 34.2476 0 1 250.0 0 1.576 0 34.3976 0 1 300.0 0 1.787 0 34.4782 0 1 400.0 0 2.077 0 34.5806 0 1 500.0 0 2.108 0 34.6351 0 1 600.0 0 2.125 0 34.6773 0 1 700.0 0 2.108 0 34.7039 0 1 800.0 0 2.054 0 34.7265 0 1 900.0 0 1.990 0 34.7402 0 1 1000.0 0 1.927 0 34.7488 0 1 1100.0 0 1.825 0 34.7521 0 1 1200.0 0 1.739 0 34.7538 0 1 1300.0 0 1.636 0 34.7524 0 1 1400.0 0 1.547 0 34.7498 0 1 1500.0 0 1.447 0 34.7444 0 1 1750.0 0 1.218 0 34.7345 0 1 2000.0 0 0.955 0 34.7176 0 1 2500.0 0 0.569 0 34.6940 0 1 3000.0 0 0.281 0 34.6784 0 1 3500.0 0 0.087 0 34.6693 0 1 4000.0 0 -0.074 0 34.6628 0 1 4500.0 0 -0.177 0 34.6582 0 1 WOD09_FR009986 7728329 B 1994-03-03T16:19 61.9875 -56.510 0.0 0 2.333 0 33.8744 0 1 10.0 0 2.341 0 33.8757 0 1 20.0 0 2.343 0 33.8763 0 1 30.0 0 2.340 0 33.8759 0 1 50.0 0 2.339 0 33.8755 0 1 75.0 0 2.343 0 33.8762 0 1 100.0 0 2.345 0 33.8780 0 1 125.0 0 0.617 0 33.9964 0 1 150.0 0 0.605 0 34.0274 0 1 200.0 0 0.947 0 34.1367 0 1 250.0 0 1.418 0 34.2654 0 1 WOD09_FR009986 7728330 B 1994-03-03T18:25 61.9683 -56.517 0.0 0 2.237 0 33.8649 0 1 10.0 0 2.239 0 33.8655 0 1 20.0 0 2.236 0 33.8647 0 1 30.0 0 2.243 0 33.8652 0 1 50.0 0 2.249 0 33.8659 0 1 75.0 0 2.262 0 33.8680 0 1 100.0 0 2.199 0 33.8730 0 1 125.0 0 0.502 0 34.0076 0 1 150.0 0 0.525 0 34.0397 0 1 200.0 0 0.864 0 34.1145 0 1 250.0 0 1.355 0 34.2427 0 1 300.0 0 1.631 0 34.3360 0 1 400.0 0 1.852 0 34.4406 0 1 500.0 0 2.084 0 34.5348 0 1 600.0 0 2.197 0 34.6064 0 1 700.0 0 2.204 0 34.6515 0 1 800.0 0 2.162 0 34.6836 0 1 900.0 0 2.118 0 34.7099 0 1 1000.0 0 2.062 0 34.7280 0 1 1100.0 0 1.997 0 34.7360 0 1 1200.0 0 1.946 0 34.7426 0 1 1300.0 0 1.852 0 34.7492 0 1 WOD09_FR009986 7728331 B 1994-03-04T04:04 61.9905 -55.000 0.0 0 3.022 0 33.8944 0 1 10.0 0 3.031 0 33.8956 0 1 20.0 0 3.014 0 33.8937 0 1 30.0 0 3.015 0 33.8935 0 1 50.0 0 3.016 0 33.8939 0 1 75.0 0 3.020 0 33.8938 0 1 100.0 0 3.017 0 33.8939 0 1 125.0 0 2.618 0 33.9095 0 1 150.0 0 1.343 0 33.9498 0 1 200.0 0 0.882 0 33.9733 0 1 WOD09_FR009986 7728332 B 1994-03-04T06:07 62.0130 -55.010 0.0 0 3.067 0 33.8925 0 1 10.0 0 3.071 0 33.8924 0 1 20.0 0 3.034 0 33.8929 0 1 30.0 0 3.028 0 33.8926 0 1 50.0 0 3.023 0 33.8927 0 1 75.0 0 3.023 0 33.8927 0 1 100.0 0 3.021 0 33.8929 0 1 125.0 0 2.947 0 33.8956 0 1 150.0 0 1.364 0 33.9542 0 1 200.0 0 1.085 0 33.9921 0 1 250.0 0 1.290 0 34.0902 0 1 WOD09_FR009986 7728333 B 1994-03-04T11:39 62.0932 -55.040 0.0 0 3.127 0 33.8933 0 1 10.0 0 3.122 0 33.8923 0 1 20.0 0 3.079 0 33.8924 0 1 30.0 0 3.032 0 33.8926 0 1 50.0 0 3.024 0 33.8921 0 1 75.0 0 3.023 0 33.8923 0 1 100.0 0 3.019 0 33.8926 0 1 125.0 0 2.996 0 33.8934 0 1 150.0 0 2.217 0 33.9251 0 1 200.0 0 1.137 0 33.9640 0 1 250.0 0 1.190 0 34.0528 0 1 300.0 0 1.689 0 34.1805 0 1 400.0 0 2.017 0 34.3242 0 1 500.0 0 2.201 0 34.4340 0 1 600.0 0 2.266 0 34.5046 0 1 700.0 0 2.284 0 34.5656 0 1 800.0 0 2.285 0 34.6129 4 1 900.0 0 2.276 0 34.6555 0 1 1000.0 0 2.259 0 34.6838 4 1 1100.0 0 2.229 0 34.7083 4 1 1200.0 0 2.186 0 34.7286 4 1 1300.0 0 2.134 0 34.7421 0 1 1400.0 0 2.066 0 34.7499 0 1 1500.0 0 1.980 0 34.7549 0 1 1750.0 0 1.775 0 34.7589 0 1 2000.0 0 1.549 0 34.7514 0 1 2500.0 0 1.083 0 34.7234 0 1 3000.0 0 0.666 0 34.6978 0 1 3500.0 0 0.337 0 34.6798 0 1 4000.0 0 0.070 0 34.6676 0 1 4500.0 0 -0.111 0 34.6595 0 1 WOD09_FR009986 7728334 B 1994-03-05T11:40 61.9998 -53.505 0.0 0 3.206 0 33.8987 0 1 10.0 0 3.206 0 33.8989 0 1 20.0 0 3.207 0 33.8989 0 1 30.0 0 3.207 0 33.8992 0 1 50.0 0 3.204 0 33.8993 0 1 75.0 0 3.207 0 33.8993 0 1 100.0 0 3.199 0 33.8998 0 1 125.0 0 1.435 0 33.9604 0 1 150.0 0 1.228 0 33.9745 0 1 200.0 0 1.197 0 34.0310 0 1 250.0 0 1.541 0 34.1457 0 1 WOD09_FR009986 7728335 B 1994-03-05T14:12 61.9865 -53.518 0.0 0 3.203 0 33.8857 0 1 10.0 0 3.203 0 33.8857 0 1 20.0 0 3.203 0 33.8857 0 1 30.0 0 3.204 0 33.8882 0 1 50.0 0 3.207 0 33.8977 0 1 75.0 0 3.206 0 33.8986 0 1 100.0 0 2.835 0 33.9133 0 1 125.0 0 1.401 0 33.9711 0 1 150.0 0 1.179 0 33.9895 0 1 200.0 0 1.201 0 34.0136 0 1 250.0 0 1.367 0 34.0926 0 1 300.0 0 1.595 0 34.1926 0 1 400.0 0 1.868 0 34.3325 0 1 500.0 0 2.128 0 34.4310 0 1 600.0 0 2.242 0 34.5202 0 1 700.0 0 2.270 0 34.5847 0 1 800.0 0 2.298 0 34.6354 0 1 900.0 0 2.282 0 34.6716 0 1 1000.0 0 2.253 0 34.6982 0 1 1100.0 0 2.214 0 34.7186 0 1 1200.0 0 2.179 0 34.7329 0 1 1300.0 0 2.119 0 34.7435 0 1 1400.0 0 2.065 0 34.7504 0 1 1500.0 0 2.016 0 34.7570 0 1 1750.0 0 1.827 0 34.7615 0 1 WOD09_FR009986 7728336 B 1994-03-07T10:21 61.9945 -52.010 0.0 0 1 10.0 0 1 20.0 0 3.622 0 33.8884 0 1 30.0 0 3.622 0 33.8893 0 1 WOD09_FR009986 7728337 B 1994-03-07T21:48 61.9908 -50.503 0.0 0 4.114 0 33.8828 0 1 10.0 0 4.117 0 33.8825 0 1 20.0 0 4.118 0 33.8825 0 1 30.0 0 4.118 0 33.8825 0 1 50.0 0 4.118 0 33.8827 0 1 75.0 0 4.114 0 33.8828 0 1 100.0 0 4.121 0 33.8821 0 1 125.0 0 3.211 0 33.9128 0 1 150.0 0 2.474 0 33.9448 0 1 200.0 0 2.063 0 34.0111 0 1 250.0 0 2.202 0 34.0986 0 1 WOD09_FR009986 7728338 B 1994-03-08T00:55 62.0010 -50.515 0.0 0 4.107 0 33.8834 0 1 10.0 0 4.108 0 33.8829 0 1 20.0 0 4.109 0 33.8829 0 1 30.0 0 4.109 0 33.8829 0 1 50.0 0 4.113 0 33.8828 0 1 75.0 0 4.115 0 33.8831 0 1 100.0 0 4.117 0 33.8826 0 1 125.0 0 3.408 0 33.9023 0 1 150.0 0 2.463 0 33.9458 0 1 200.0 0 2.069 0 34.0104 0 1 250.0 0 2.199 0 34.0959 0 1 300.0 0 2.129 0 34.1549 0 1 400.0 0 2.242 0 34.2571 0 1 500.0 0 2.291 0 34.3434 0 1 600.0 0 2.357 0 34.4222 0 1 700.0 0 2.354 0 34.4837 0 1 800.0 0 2.371 0 34.5525 0 1 900.0 0 2.362 0 34.6026 0 1 1000.0 0 2.350 0 34.6411 0 1 1100.0 0 2.327 0 34.6752 0 1 1200.0 0 2.306 0 34.6977 0 1 1300.0 0 2.278 0 34.7155 0 1 1400.0 0 2.233 0 34.7318 0 1 1500.0 0 2.173 0 34.7456 0 1 1750.0 0 1.988 0 34.7600 0 1 2000.0 0 1.741 0 34.7600 0 1 2500.0 0 1.283 0 34.7361 0 1 3000.0 0 0.854 0 34.7089 0 1 3500.0 0 0.486 0 34.6872 0 1 4000.0 0 0.155 0 34.6713 0 1 4500.0 0 -0.041 0 34.6610 0 1 WOD09_FR009986 7728343 B 1994-03-14T02:57 68.4162 -50.665 0.0 0 4.360 0 33.8739 0 1 10.0 0 4.363 0 33.8734 0 1 20.0 0 4.362 0 33.8731 0 1 30.0 0 4.360 0 33.8734 0 1 50.0 0 4.309 0 33.8737 0 1 75.0 0 3.936 0 33.8874 0 1 100.0 0 3.275 0 33.9138 0 1 125.0 0 2.611 0 33.9554 0 1 150.0 0 2.330 0 33.9736 0 1 200.0 0 2.125 0 34.0296 0 1 250.0 0 1.972 0 34.0517 0 1 300.0 0 1.939 0 34.0944 0 1 WOD09_FR009986 7728344 B 1994-03-14T04:42 68.4180 -50.672 0.0 0 4.350 0 33.8742 0 1 10.0 0 4.347 0 33.8737 0 1 20.0 0 4.341 0 33.8738 0 1 30.0 0 4.348 0 33.8735 0 1 50.0 0 4.340 0 33.8737 0 1 75.0 0 3.974 0 33.8867 0 1 100.0 0 3.010 0 33.9274 0 1 125.0 0 2.423 0 33.9715 0 1 150.0 0 2.386 0 33.9961 0 1 200.0 0 2.157 0 34.0336 0 1 250.0 0 1.947 0 34.0518 0 1 300.0 0 1.900 0 34.0995 0 1 400.0 0 2.058 0 34.1871 0 1 500.0 0 2.163 0 34.3025 0 1 600.0 0 2.214 0 34.4185 0 1 700.0 0 2.236 0 34.5157 0 1 800.0 0 2.254 0 34.5782 0 1 900.0 0 2.257 0 34.6301 0 1 1000.0 0 2.224 0 34.6741 0 1 1100.0 0 2.205 0 34.7006 0 1 1200.0 0 2.166 0 34.7229 0 1 1300.0 0 2.108 0 34.7375 0 1 1400.0 0 2.001 0 34.7484 0 1 WOD09_FR014108 10025047 B 1995-10-11T08:19 61.9978 -50.508 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 1 75.0 0 1.985 0 33.8576 0 1 100.0 0 1.975 0 33.8578 0 1 125.0 0 1.877 0 33.8589 0 1 150.0 0 1.843 0 33.8602 0 1 200.0 0 1.794 0 33.8676 0 1 250.0 0 1.732 0 33.9533 0 1 300.0 0 2.044 0 34.0805 0 1 WOD09_FR014108 10025048 B 1995-10-11T10:10 61.9915 -50.520 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1.954 0 33.8608 0 1 50.0 0 1.953 0 33.8583 0 1 75.0 0 1.957 0 33.8582 0 1 100.0 0 1.941 0 33.8600 0 1 125.0 0 1.929 0 33.8616 0 1 150.0 0 1.814 0 33.8644 0 1 200.0 0 1.736 0 33.8876 0 1 250.0 0 1.787 0 33.9764 0 1 300.0 0 2.122 0 34.1194 0 1 400.0 0 2.182 0 34.2375 0 1 500.0 0 2.230 0 34.3312 0 1 600.0 0 2.307 0 34.4027 0 1 700.0 0 2.340 0 34.4729 0 1 800.0 0 2.373 0 34.5411 0 1 900.0 0 2.374 0 34.5803 0 1 1000.0 0 2.366 0 34.6199 0 1 WOD09_FR014108 10025049 B 1995-10-11T17:31 62.0090 -50.548 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1.952 0 33.8637 0 1 50.0 0 1.948 0 33.8640 0 1 75.0 0 1.861 0 33.8656 0 1 100.0 0 1.824 0 33.8632 0 1 125.0 0 1.814 0 33.8639 0 1 150.0 0 1.806 0 33.8651 0 1 200.0 0 1.835 0 33.9026 0 1 250.0 0 1.896 0 33.9770 0 1 300.0 0 2.066 0 34.0905 0 1 400.0 0 2.177 0 34.2102 0 1 500.0 0 2.202 0 34.2914 0 1 600.0 0 2.284 0 34.3829 0 1 700.0 0 2.347 0 34.4783 0 1 800.0 0 2.372 0 34.5373 0 1 900.0 0 2.374 0 34.5790 0 1 1000.0 0 2.368 0 34.6123 0 1 1100.0 0 2.347 0 34.6538 0 1 1200.0 0 2.312 0 34.6820 0 1 1300.0 0 2.274 0 34.7053 0 1 1400.0 0 2.220 0 34.7201 0 1 1500.0 0 2.163 0 34.7294 3 1 1750.0 0 1.986 0 34.7469 0 1 2000.0 0 1.766 0 34.7476 0 1 2500.0 0 1.260 0 34.7234 0 1 3000.0 0 0.826 0 34.6974 0 1 3500.0 0 0.488 0 34.6793 0 1 4000.0 0 0.151 0 34.6627 0 1 WOD09_FR014108 10025050 B 1995-10-12T08:31 61.9335 -52.000 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1.779 0 33.9072 0 1 50.0 0 1.771 0 33.9084 0 1 75.0 0 1.739 0 33.9136 0 1 100.0 0 1.731 0 33.9155 0 1 125.0 0 1.739 0 33.9185 0 1 150.0 0 1.731 0 33.9225 0 1 200.0 0 1.685 0 33.9416 0 1 250.0 0 1.989 0 34.0603 0 1 300.0 0 2.141 0 34.1598 0 1 WOD09_FR014108 10025051 B 1995-10-12T10:25 61.8988 -52.010 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 1.637 0 33.9277 0 1 75.0 0 1.630 0 33.9283 0 1 100.0 0 1.630 0 33.9279 0 1 125.0 0 1.629 0 33.9283 0 1 150.0 0 1.626 0 33.9287 0 1 200.0 0 1.610 0 33.9314 0 1 250.0 0 2.042 0 34.0843 0 1 300.0 0 2.141 0 34.1665 0 1 400.0 0 2.104 0 34.2706 0 1 500.0 0 2.220 0 34.3644 0 1 600.0 0 2.292 0 34.4469 0 1 700.0 0 2.342 0 34.5080 0 1 800.0 0 2.346 0 34.5669 0 1 900.0 0 2.348 0 34.6144 0 1 WOD09_FR014108 10025052 B 1995-10-12T14:00 61.9870 -51.993 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1.831 0 33.9015 0 1 50.0 0 1.817 0 33.9020 0 1 75.0 0 1.802 0 33.9027 0 1 100.0 0 1.803 0 33.9030 0 1 125.0 0 1.716 0 33.9213 0 1 150.0 0 1.642 0 33.9375 0 1 200.0 0 2.016 0 34.0546 0 1 250.0 0 2.090 0 34.1070 0 1 300.0 0 2.139 0 34.1662 0 1 400.0 0 2.174 0 34.2607 0 1 500.0 0 2.194 0 34.3471 0 1 600.0 0 2.269 0 34.4219 0 1 700.0 0 2.344 0 34.5073 0 1 800.0 0 2.370 0 34.5508 0 1 900.0 0 2.366 0 34.6080 0 1 1000.0 0 2.350 0 34.6438 0 1 1100.0 0 2.339 0 34.6770 0 1 1200.0 0 2.312 0 34.7011 0 1 1300.0 0 2.269 0 34.7230 0 1 1400.0 0 2.217 0 34.7405 0 1 1500.0 0 2.157 0 34.7523 0 1 1750.0 0 1.969 0 34.7657 0 1 2000.0 0 1.721 0 34.7616 0 1 2500.0 0 1.275 0 34.7402 0 1 3000.0 0 0.716 0 34.7068 0 1 WOD09_FR014108 10025053 B 1995-10-12T16:34 61.9830 -51.995 0.0 0 1.813 0 33.8956 0 1 10.0 0 1.815 0 33.9038 0 1 20.0 0 1.816 0 33.9023 0 1 30.0 0 1.816 0 33.9016 0 1 50.0 0 1.817 0 33.9024 0 1 75.0 0 1.794 0 33.9035 0 1 100.0 0 1.793 0 33.9035 0 1 125.0 0 1.788 0 33.9070 0 1 150.0 0 1.662 0 33.9323 0 1 200.0 0 1.763 0 33.9815 0 1 250.0 0 2.095 0 34.1126 0 1 300.0 0 2.151 0 34.1748 0 1 WOD09_FR014108 10025054 B 1995-10-12T23:37 62.0415 -52.035 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1.776 0 33.9072 0 1 50.0 0 1.772 0 33.9074 0 1 75.0 0 1.734 0 33.9155 0 1 100.0 0 1.727 0 33.9163 0 1 125.0 0 1.723 0 33.9163 0 1 150.0 0 1.646 0 33.9290 0 1 200.0 0 1.627 0 33.9372 0 1 250.0 0 1.912 0 34.0311 0 1 300.0 0 2.119 0 34.1575 0 1 WOD09_FR014108 10025055 B 1995-10-13T18:46 62.1392 -52.045 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 1 75.0 0 1.691 0 33.9191 0 1 100.0 0 1.667 0 33.9224 0 1 125.0 0 1.661 0 33.9230 0 1 150.0 0 1.653 0 33.9242 0 1 200.0 0 1.576 0 33.9373 0 1 250.0 0 1.851 0 34.0289 0 1 300.0 0 2.134 0 34.1632 0 1 WOD09_FR014108 10025056 B 1995-10-13T23:42 62.1207 -52.097 0.0 0 1 10.0 0 1.613 0 33.9324 0 1 20.0 0 1.614 0 33.9328 0 1 30.0 0 1.614 0 33.9328 0 1 50.0 0 1.614 0 33.9319 0 1 75.0 0 1.615 0 33.9318 0 1 100.0 0 1.609 0 33.9316 0 1 125.0 0 1.614 0 33.9317 0 1 150.0 0 1.618 0 33.9333 0 1 200.0 0 1.571 0 33.9383 0 1 250.0 0 1.759 0 34.0110 0 1 300.0 0 2.120 0 34.1564 0 1 WOD09_FR014108 10025057 B 1995-10-14T05:16 62.1833 -52.083 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 1.606 0 33.9304 0 1 75.0 0 1.607 0 33.9299 0 1 100.0 0 1.608 0 33.9297 0 1 125.0 0 1.609 0 33.9298 0 1 150.0 0 1.608 0 33.9300 0 1 200.0 0 1.591 0 33.9353 0 1 250.0 0 2.039 0 34.0991 0 1 300.0 0 2.125 0 34.1802 0 1 WOD09_FR014108 10025058 B 1995-10-14T11:15 62.1500 -52.083 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 1.640 0 33.9310 0 1 75.0 0 1.612 0 33.9300 0 1 100.0 0 1.612 0 33.9298 0 1 125.0 0 1.613 0 33.9297 0 1 150.0 0 1.601 0 33.9311 0 1 200.0 0 1.640 0 33.9663 0 1 250.0 0 2.033 0 34.0996 0 1 300.0 0 2.126 0 34.1724 0 1 WOD09_FR014108 10025059 B 1995-10-14T17:27 62.2703 -52.088 0.0 0 1 10.0 0 1.778 0 33.9060 0 1 20.0 0 1.779 0 33.9087 0 1 30.0 0 1.774 0 33.9176 0 1 50.0 0 1.757 0 33.9262 0 1 75.0 0 1.723 0 33.9220 0 1 100.0 0 1.699 0 33.9246 0 1 125.0 0 1.664 0 33.9258 0 1 150.0 0 1.653 0 33.9262 0 1 200.0 0 1.516 0 33.9453 0 1 250.0 0 1.891 0 34.0328 0 1 300.0 0 2.108 0 34.1639 0 1 400.0 0 2.191 0 34.2898 0 1 WOD09_FR014108 10025060 B 1995-10-14T23:06 62.2920 -52.108 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1.633 0 33.9268 0 1 50.0 0 1.634 0 33.9272 0 1 75.0 0 1.636 0 33.9270 0 1 100.0 0 1.638 0 33.9276 0 1 125.0 0 1.638 0 33.9275 0 1 150.0 0 1.615 0 33.9302 0 1 200.0 0 1.788 0 33.9932 0 1 250.0 0 1.975 0 34.0765 0 1 300.0 0 2.035 0 34.1456 0 1 WOD09_FR014108 10025061 B 1995-10-16T12:30 62.5652 -52.103 0.0 0 1 10.0 0 1 20.0 0 1.584 0 33.9311 0 1 30.0 0 1.587 0 33.9311 0 1 50.0 0 1.588 0 33.9310 0 1 75.0 0 1.581 0 33.9325 0 1 100.0 0 1.569 0 33.9348 0 1 125.0 0 1.570 0 33.9361 0 1 150.0 0 1.479 0 33.9421 0 1 200.0 0 1.364 0 33.9447 0 1 250.0 0 1.309 4 33.9528 0 1 300.0 0 1.441 6 34.0242 0 1 WOD09_FR014108 10025062 B 1995-10-16T17:27 62.5598 -52.128 0.0 0 1 10.0 0 1.585 0 33.9297 0 1 20.0 0 1.585 0 33.9297 0 1 30.0 0 1.585 0 33.9299 0 1 50.0 0 1.587 0 33.9296 0 1 75.0 0 1.587 0 33.9303 0 1 100.0 0 1.589 0 33.9304 0 1 125.0 0 1.583 0 33.9332 0 1 150.0 0 1.561 0 33.9395 0 1 200.0 0 1.702 0 33.9833 0 1 250.0 0 1.776 0 34.0436 0 1 300.0 0 1.906 0 34.1146 0 1 400.0 0 2.014 0 34.2253 0 1 WOD09_FR014108 10025063 B 1995-10-16T23:10 62.4198 -52.165 0.0 0 1.670 0 33.9256 0 1 10.0 0 1.671 0 33.9250 0 1 20.0 0 1.671 0 33.9251 0 1 30.0 0 1.671 0 33.9249 0 1 50.0 0 1.670 0 33.9254 0 1 75.0 0 1.644 0 33.9293 0 1 100.0 0 1.639 0 33.9308 0 1 125.0 0 1.604 0 33.9354 0 1 150.0 0 1.589 0 33.9407 0 1 200.0 0 1.567 0 33.9729 0 1 250.0 0 2.006 0 34.0758 0 1 300.0 0 1.876 0 34.1301 0 1 WOD09_FR014108 10025064 B 1995-10-17T14:43 62.0040 -53.498 0.0 0 1.340 0 33.9633 0 1 10.0 0 1.341 0 33.9642 0 1 20.0 0 1.342 0 33.9643 0 1 30.0 0 1.342 0 33.9641 0 1 50.0 0 1.341 0 33.9641 0 1 75.0 0 1.342 0 33.9641 0 1 100.0 0 1.305 0 33.9655 0 1 125.0 0 1.225 0 33.9680 0 1 150.0 0 1.016 0 33.9822 0 1 200.0 0 1.136 0 34.0128 0 1 250.0 0 1.879 0 34.1655 0 1 300.0 0 1.924 0 34.2396 0 1 WOD09_FR014108 10025065 B 1995-10-17T17:07 61.9927 -53.502 0.0 0 1.346 0 33.9645 0 1 10.0 0 1.347 0 33.9641 0 1 20.0 0 1.348 0 33.9643 0 1 30.0 0 1.349 0 33.9640 0 1 50.0 0 1.349 0 33.9641 0 1 75.0 0 1.345 0 33.9641 0 1 100.0 0 1.310 0 33.9657 0 1 125.0 0 1.211 0 33.9695 0 1 150.0 0 0.996 0 33.9824 0 1 200.0 0 1.204 0 34.0362 0 1 250.0 0 1.992 0 34.2000 0 1 300.0 0 1.988 0 34.2578 0 1 400.0 0 2.203 0 34.3812 0 1 500.0 0 2.227 0 34.4406 0 1 600.0 0 2.295 0 34.5139 0 1 700.0 0 2.316 0 34.5743 0 1 800.0 0 2.306 0 34.6167 0 1 900.0 0 2.333 0 34.6493 0 1 1000.0 0 2.273 0 34.6781 0 1 WOD09_FR014108 10025066 B 1995-10-17T19:34 61.9845 -53.505 0.0 0 1.348 0 33.9645 0 1 10.0 0 1.348 0 33.9641 0 1 20.0 0 1.347 0 33.9643 0 1 30.0 0 1.348 0 33.9641 0 1 50.0 0 1.348 0 33.9642 0 1 75.0 0 1.348 0 33.9639 0 1 100.0 0 1.311 0 33.9656 0 1 125.0 0 1.271 0 33.9671 0 1 150.0 0 1.038 0 33.9785 0 1 200.0 0 1.009 0 34.0094 0 1 250.0 0 1.992 0 34.1895 0 1 300.0 0 1.956 0 34.2411 0 1 400.0 0 2.141 0 34.3453 0 1 500.0 0 2.185 0 34.4245 0 1 600.0 0 2.312 0 34.5064 0 1 700.0 0 2.312 0 34.5603 0 1 800.0 0 2.315 0 34.6144 0 1 900.0 0 2.266 0 34.6535 0 1 1000.0 0 2.258 0 34.6815 0 1 1100.0 0 2.247 0 34.7045 0 1 1200.0 0 2.241 0 34.7265 0 1 1300.0 0 2.195 0 34.7416 0 1 1400.0 0 2.136 0 34.7514 0 1 1500.0 0 2.080 0 34.7573 0 1 1750.0 0 1.879 0 34.7645 0 1 2000.0 0 1.625 0 34.7593 0 1 2500.0 0 1.102 0 34.7291 0 1 3000.0 0 0.618 0 34.7000 0 1 3500.0 0 0.322 0 34.6836 0 1 4000.0 0 0.074 0 34.6721 0 1 WOD09_FR014108 10025067 B 1995-10-18T07:52 61.9957 -54.993 0.0 0 1 10.0 0 0.811 0 33.9810 0 1 20.0 0 0.812 0 33.9810 0 1 30.0 0 0.812 0 33.9807 0 1 50.0 0 0.801 0 33.9812 0 1 75.0 0 0.725 0 33.9831 0 1 100.0 0 0.700 0 33.9828 0 1 125.0 0 0.716 0 33.9819 0 1 150.0 0 0.672 0 33.9834 0 1 200.0 0 0.393 0 33.9887 0 1 250.0 0 0.191 6 33.9929 0 1 300.0 0 1.667 0 34.1829 0 1 WOD09_FR014108 10025068 B 1995-10-18T09:54 62.0335 -54.993 0.0 0 1 10.0 0 0.766 0 33.9849 0 1 20.0 0 0.767 0 33.9843 0 1 30.0 0 0.761 0 33.9848 0 1 50.0 0 0.684 0 33.9870 0 1 75.0 0 0.624 0 33.9848 0 1 100.0 0 0.625 0 33.9840 0 1 125.0 0 0.523 0 33.9858 0 1 150.0 0 0.308 0 33.9893 0 1 200.0 0 0.270 0 33.9955 0 1 250.0 0 0.213 6 33.9955 0 1 300.0 0 1.963 0 34.2788 0 1 400.0 0 2.120 0 34.3988 0 1 500.0 0 2.269 0 34.5070 0 1 600.0 0 2.253 0 34.5548 0 1 700.0 0 2.256 0 34.6025 0 1 800.0 0 2.271 0 34.6386 0 1 900.0 0 2.214 0 34.6656 0 1 1000.0 0 2.236 0 34.7022 0 1 WOD09_FR014108 10025069 B 1995-10-18T13:09 62.0888 -54.992 0.0 0 1 10.0 0 0.787 0 33.9860 0 1 20.0 0 0.790 0 33.9861 0 1 30.0 0 0.791 0 33.9861 0 1 50.0 0 0.711 0 33.9854 0 1 75.0 0 0.697 0 33.9851 0 1 100.0 0 0.630 0 33.9845 0 1 125.0 0 0.555 0 33.9852 0 1 150.0 0 0.496 0 33.9860 0 1 200.0 0 0.253 0 33.9887 0 1 250.0 0 0.341 6 34.0117 0 1 300.0 0 1.921 0 34.2780 0 1 400.0 0 2.116 0 34.3899 0 1 500.0 0 2.270 0 34.4990 0 1 600.0 0 2.253 0 34.5570 0 1 700.0 0 2.265 0 34.6052 0 1 800.0 0 2.272 0 34.6452 0 1 900.0 0 2.201 0 34.6788 0 1 1000.0 0 2.225 0 34.7066 0 1 1100.0 0 2.204 0 34.7245 0 1 1200.0 0 2.163 0 34.7362 0 1 1300.0 0 2.103 0 34.7477 0 1 1400.0 0 2.012 0 34.7562 0 1 1500.0 0 1.956 0 34.7612 0 1 1750.0 0 1.689 0 34.7572 0 1 2000.0 0 1.474 0 34.7495 0 1 2500.0 0 0.965 0 34.7192 0 1 3000.0 0 0.534 0 34.6945 0 1 3500.0 0 0.235 0 34.6798 0 1 4000.0 0 0.021 0 34.6694 0 1 WOD09_FR014108 10025070 B 1995-10-19T12:33 62.0010 -57.998 0.0 0 -1.293 0 33.7323 0 1 10.0 0 -1.291 0 33.7338 0 1 20.0 0 -1.299 0 33.7374 0 1 30.0 0 -1.299 0 33.7393 0 1 50.0 0 -1.273 0 33.7841 0 1 75.0 0 -1.143 0 33.7989 0 1 100.0 0 -0.371 0 33.9794 0 1 125.0 0 -0.341 0 34.0010 0 1 150.0 0 -0.365 0 34.0035 0 1 200.0 0 -0.396 0 34.0055 0 1 250.0 0 1.476 0 34.3175 0 1 300.0 0 1.773 0 34.4110 0 1 WOD09_FR014108 10025071 B 1995-10-19T14:18 61.9900 -57.995 0.0 0 1 10.0 0 -1.281 0 33.7403 0 1 20.0 0 -1.276 0 33.7659 0 1 30.0 0 -1.267 0 33.7888 0 1 50.0 0 -0.957 0 33.8251 0 1 75.0 0 -0.682 0 33.8722 0 1 100.0 0 -0.336 0 33.9951 0 1 125.0 0 -0.373 0 34.0004 0 1 150.0 0 -0.368 0 34.0021 0 1 200.0 0 -0.400 0 34.0042 0 1 250.0 0 1.359 0 34.2947 0 1 300.0 0 1.699 0 34.3839 0 1 400.0 0 1.976 0 34.5064 0 1 500.0 0 2.099 0 34.5927 0 1 600.0 0 2.091 0 34.6386 0 1 700.0 0 2.098 0 34.6787 0 1 800.0 0 2.067 0 34.7144 0 1 900.0 0 2.005 0 34.7273 0 1 1000.0 0 1.958 0 34.7394 0 1 WOD09_FR014108 10025072 B 1995-10-19T17:09 61.9360 -58.010 0.0 0 -1.300 0 33.7299 0 1 10.0 0 -1.301 0 33.7295 0 1 20.0 0 -1.301 0 33.7294 0 1 30.0 0 -1.296 0 33.7346 0 1 50.0 0 -1.260 0 33.8044 0 1 75.0 0 -0.885 0 33.8479 0 1 100.0 0 -0.305 0 33.9856 0 1 125.0 0 -0.335 0 33.9980 0 1 150.0 0 -0.300 0 34.0027 0 1 200.0 0 -0.348 0 34.0058 0 1 250.0 0 1.517 0 34.3200 0 1 300.0 0 1.777 0 34.4000 0 1 400.0 0 1.998 0 34.5085 0 1 500.0 0 2.015 0 34.5825 0 1 600.0 0 2.091 0 34.6369 0 1 700.0 0 2.093 0 34.6805 0 1 800.0 0 2.085 0 34.7069 0 1 900.0 0 2.021 0 34.7225 0 1 1000.0 0 1.995 0 34.7377 0 1 1100.0 0 1.960 0 34.7490 0 1 1200.0 0 1.880 0 34.7533 0 1 1300.0 0 1.791 0 34.7562 0 1 1400.0 0 1.684 0 34.7557 0 1 1500.0 0 1.551 0 34.7520 0 1 1750.0 0 1.308 0 34.7417 0 1 2000.0 0 1.049 0 34.7263 0 1 2500.0 0 0.618 0 34.6993 0 1 3000.0 0 0.299 0 34.6825 0 1 3500.0 0 0.099 0 34.6736 0 1 4000.0 0 -0.079 0 34.6656 0 1 4500.0 0 -0.168 0 34.6618 0 1 WOD09_FR014108 10025073 B 1995-10-20T09:52 62.0487 -58.828 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 1 75.0 0 1 100.0 0 -1.821 0 33.9304 0 1 125.0 0 -1.617 0 33.9780 0 1 150.0 0 0.087 0 34.2405 7 1 200.0 0 1.681 0 34.5204 0 1 250.0 0 1.759 0 34.5602 0 1 300.0 0 1.801 0 34.5908 0 1 WOD09_FR014108 10025074 B 1995-10-20T11:34 62.0715 -58.833 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 -1.824 0 33.9236 0 1 75.0 0 -1.823 0 33.9237 0 1 100.0 0 -1.819 0 33.9271 0 1 125.0 0 -1.733 0 33.9531 0 1 150.0 0 0.209 0 34.2456 9 1 200.0 0 1.600 0 34.4935 0 1 250.0 0 1.744 0 34.5548 0 1 300.0 0 1.803 0 34.5953 0 1 400.0 0 1.845 0 34.6479 0 1 500.0 0 1.883 4 34.6931 0 1 600.0 0 1.850 6 34.7117 0 1 700.0 0 1.805 6 34.7276 0 1 800.0 0 1.724 6 34.7358 0 1 900.0 0 1.659 6 34.7421 0 1 1000.0 0 1.595 6 34.7458 0 1 WOD09_FR014108 10025075 B 1995-10-20T22:40 62.2775 -58.675 0.0 0 1 10.0 0 1 20.0 0 -1.615 0 33.9219 0 1 30.0 0 -1.614 0 33.9216 0 1 50.0 0 -1.618 0 33.9213 0 1 75.0 0 -1.628 0 33.9212 0 1 100.0 0 -1.329 0 33.9674 0 1 125.0 0 -0.450 0 34.0606 0 1 150.0 0 0.643 0 34.2260 7 1 200.0 0 1.700 0 34.4288 0 1 250.0 0 1.798 0 34.4879 0 1 300.0 0 1.874 0 34.5440 0 1 WOD09_FR014108 10025076 B 1995-10-21T02:04 62.3293 -58.688 0.0 0 1 10.0 0 1 20.0 0 -1.745 0 33.9329 0 1 30.0 0 -1.746 0 33.9332 0 1 50.0 0 -1.754 0 33.9331 0 1 75.0 0 -1.747 0 33.9333 0 1 100.0 0 -1.740 0 33.9364 0 1 125.0 0 -1.735 0 33.9395 0 1 150.0 0 -1.734 0 33.9540 0 1 200.0 0 0.857 0 34.2975 0 1 250.0 0 1.658 0 34.4671 0 1 300.0 0 1.801 0 34.5355 0 1 400.0 0 1.947 0 34.6160 0 1 500.0 0 1.930 4 34.6628 0 1 600.0 0 1.918 4 34.6949 0 1 700.0 0 1.894 4 34.7178 0 1 800.0 0 1.850 4 34.7343 0 1 900.0 0 1.768 4 34.7397 0 1 1000.0 0 1.713 4 34.7469 0 1 1100.0 0 1.615 3 34.7481 0 1 1200.0 0 1.513 3 34.7456 0 1 1300.0 0 1.438 3 34.7449 0 1 1400.0 0 1.331 3 34.7398 0 1 1500.0 0 1.213 3 34.7337 0 1 1750.0 0 0.954 3 34.7172 0 1 2000.0 0 0.747 0 34.7054 0 1 2500.0 0 0.430 0 34.6870 0 1 3000.0 0 0.188 0 34.6754 0 1 3500.0 0 0.000 0 34.6676 0 1 4000.0 0 -0.138 0 34.6618 0 1 4500.0 0 -0.226 0 34.6579 0 1 WOD09_FR014108 10025077 B 1995-10-21T07:34 62.5132 -58.625 0.0 0 1 10.0 0 1 20.0 0 -1.722 0 33.9394 0 1 30.0 0 -1.722 0 33.9407 0 1 50.0 0 -1.726 0 33.9361 0 1 75.0 0 -1.721 0 33.9358 0 1 100.0 0 -1.706 0 33.9376 0 1 125.0 0 -1.743 0 33.9446 0 1 150.0 0 -0.813 0 34.0055 0 1 200.0 0 1.025 0 34.3321 0 1 250.0 0 1.639 0 34.4795 0 1 300.0 0 1.791 0 34.5371 0 1 WOD09_FR014108 10025078 B 1995-10-21T12:18 62.5093 -58.607 0.0 0 -1.673 0 33.9369 0 1 10.0 0 -1.648 0 33.9367 0 1 20.0 0 -1.630 0 33.9366 0 1 30.0 0 -1.632 0 33.9370 0 1 50.0 0 -1.642 0 33.9368 0 1 75.0 0 -1.637 0 33.9366 0 1 100.0 0 -1.642 0 33.9371 0 1 125.0 0 -1.591 0 33.9622 0 1 150.0 0 -0.433 0 34.0853 0 1 200.0 0 1.469 0 34.3997 0 1 250.0 0 1.752 0 34.4879 0 1 300.0 0 1.803 0 34.5303 0 1 WOD09_FR014108 10025079 B 1995-10-21T19:13 62.7528 -58.387 0.0 0 1 10.0 0 -1.779 0 33.9217 0 1 20.0 0 -1.794 0 33.9261 0 1 30.0 0 -1.795 0 33.9259 0 1 50.0 0 -1.804 0 33.9288 0 1 75.0 0 -1.808 0 33.9303 0 1 100.0 0 -1.808 0 33.9313 0 1 125.0 0 -1.802 0 33.9341 0 1 150.0 0 -1.792 0 33.9377 0 1 200.0 0 0.821 0 34.2951 0 1 250.0 0 1.629 0 34.4620 0 1 300.0 0 1.840 0 34.5259 0 1 WOD09_FR014108 10025080 B 1995-10-21T22:58 62.6547 -58.310 0.0 0 1 10.0 0 -1.585 0 33.9020 0 1 20.0 0 -1.580 0 33.9033 0 1 30.0 0 -1.568 0 33.9070 0 1 50.0 0 -1.564 0 33.9096 0 1 75.0 0 -1.565 0 33.9144 0 1 100.0 0 -1.571 0 33.9162 0 1 125.0 0 -1.687 0 33.9263 0 1 150.0 0 -1.806 0 33.9366 0 1 200.0 0 -1.729 6 33.9622 0 1 250.0 0 1.664 0 34.4013 0 1 300.0 0 1.825 0 34.4834 0 1 WOD09_FR014108 10025081 B 1995-10-22T08:52 63.0793 -58.343 0.0 0 1 10.0 0 -1.755 0 33.9352 0 1 20.0 0 -1.762 0 33.9353 0 1 30.0 0 -1.765 0 33.9355 0 1 50.0 0 -1.779 0 33.9357 0 1 75.0 0 -1.778 0 33.9358 0 1 100.0 0 -1.777 0 33.9361 0 1 125.0 0 -1.768 0 33.9369 0 1 150.0 0 -1.473 0 33.9723 0 1 200.0 0 1.333 0 34.3451 0 1 250.0 0 1.636 0 34.4384 0 1 300.0 0 1.795 0 34.5177 0 1 WOD09_FR014108 10025082 B 1995-10-22T16:24 63.2368 -58.323 0.0 0 -1.551 0 33.8973 0 1 10.0 0 -1.551 0 33.8964 0 1 20.0 0 -1.550 0 33.8958 0 1 30.0 0 -1.548 0 33.8988 0 1 50.0 0 -1.555 0 33.9128 0 1 75.0 0 -1.602 0 33.9145 0 1 100.0 0 -1.550 0 33.9198 0 1 125.0 0 -1.154 0 33.9541 0 1 150.0 0 -0.638 0 34.0001 0 1 200.0 0 1.214 0 34.3102 0 1 250.0 0 1.785 0 34.4481 0 1 300.0 0 1.892 0 34.5041 0 1 WOD09_FR014108 10025083 B 1995-10-22T23:09 63.4152 -58.342 0.0 0 -1.626 0 33.8638 0 1 10.0 0 -1.625 0 33.8639 0 1 20.0 0 -1.623 0 33.8638 0 1 30.0 0 -1.624 0 33.8649 0 1 50.0 0 -1.633 0 33.8682 0 1 75.0 0 -1.645 0 33.8703 0 1 100.0 0 -1.577 0 33.8806 0 1 125.0 0 -1.340 0 33.9222 0 1 150.0 0 -0.737 0 33.9741 0 1 200.0 0 0.895 0 34.2481 0 1 250.0 0 1.780 0 34.4363 0 1 300.0 0 1.877 0 34.4908 0 1 WOD09_FR014108 10025084 B 1995-10-23T04:22 63.5333 -58.317 0.0 0 -1.597 0 33.8656 0 1 10.0 0 -1.607 0 33.8689 0 1 20.0 0 -1.610 0 33.8688 0 1 30.0 0 -1.600 0 33.8713 0 1 50.0 0 -1.593 0 33.8726 0 1 75.0 0 -1.593 0 33.8729 0 1 100.0 0 -1.589 0 33.8751 0 1 125.0 0 -1.559 0 33.8942 0 1 150.0 0 -1.251 0 33.9274 0 1 200.0 0 -0.479 0 34.0272 0 1 250.0 0 1.691 0 34.4116 0 1 300.0 0 1.906 0 34.4964 0 1 400.0 0 2.009 0 34.5751 0 1 500.0 0 2.061 0 34.6309 0 1 600.0 0 2.070 0 34.6674 0 1 700.0 0 2.064 0 34.6981 0 1 800.0 0 2.008 0 34.7170 0 1 900.0 0 1.969 0 34.7317 0 1 1000.0 0 1.916 0 34.7409 0 1 WOD09_FR014108 10025085 B 1995-10-23T10:28 63.7000 -58.333 0.0 0 -1.563 0 33.8392 0 1 10.0 0 -1.587 0 33.8404 0 1 20.0 0 -1.600 0 33.8419 0 1 30.0 0 -1.610 0 33.8422 0 1 50.0 0 -1.609 0 33.8424 0 1 75.0 0 -1.611 0 33.8424 0 1 100.0 0 -1.596 0 33.8442 0 1 125.0 0 -1.276 0 33.9031 0 1 150.0 0 -0.790 0 33.9785 0 1 200.0 0 1.244 0 34.3034 0 1 250.0 0 1.728 0 34.4211 0 1 300.0 0 1.932 0 34.4990 0 1 WOD09_FR014108 10025086 B 1995-10-23T14:33 63.8500 -58.283 0.0 0 -1.476 0 33.8329 0 1 10.0 0 -1.481 0 33.8332 0 1 20.0 0 -1.488 0 33.8327 0 1 30.0 0 -1.498 0 33.8335 0 1 50.0 0 -1.525 0 33.8349 0 1 75.0 0 -1.526 0 33.8356 0 1 100.0 0 -1.526 0 33.8364 0 1 125.0 0 -1.519 0 33.8440 0 1 150.0 0 -0.982 0 33.9452 0 1 200.0 0 0.237 0 34.1416 0 1 250.0 0 1.722 0 34.4152 0 1 300.0 0 1.892 0 34.4765 0 1 400.0 0 2.036 0 34.5630 0 1 500.0 0 2.064 0 34.6249 0 1 600.0 0 2.070 0 34.6540 0 1 700.0 0 2.073 0 34.6930 0 1 800.0 0 2.016 0 34.7125 0 1 900.0 0 1.919 0 34.7247 0 1 1000.0 0 1.931 0 34.7452 0 1 WOD09_FR014108 10025087 B 1995-10-23T16:22 63.8667 -58.283 0.0 0 -1.490 0 33.8317 0 1 10.0 0 -1.492 0 33.8317 0 1 20.0 0 -1.493 0 33.8320 0 1 30.0 0 -1.496 0 33.8321 0 1 50.0 0 -1.533 0 33.8343 0 1 75.0 0 -1.528 0 33.8374 0 1 100.0 0 -1.542 0 33.8382 0 1 125.0 0 -1.449 0 33.8605 0 1 150.0 0 -0.776 0 33.9644 0 1 200.0 0 0.792 0 34.2215 0 1 250.0 0 1.722 0 34.4170 0 1 300.0 0 1.925 0 34.4895 0 1 WOD09_FR014108 10025088 B 1995-10-23T22:19 63.9167 -58.250 0.0 0 1 10.0 0 -1.523 0 33.8288 0 1 20.0 0 -1.521 0 33.8290 0 1 30.0 0 -1.516 0 33.8296 0 1 50.0 0 -1.514 0 33.8305 0 1 75.0 0 -1.535 0 33.8319 0 1 100.0 0 -1.544 0 33.8355 0 1 125.0 0 -1.406 0 33.8575 0 1 150.0 0 -0.607 0 33.9778 0 1 200.0 0 0.450 0 34.1565 0 1 250.0 0 1.675 0 34.3953 0 1 300.0 0 1.878 0 34.4542 0 1 WOD09_FR014108 10025089 B 1995-10-24T04:24 64.0882 -58.235 0.0 0 -1.479 0 33.8296 0 1 10.0 0 -1.479 0 33.8296 0 1 20.0 0 -1.495 0 33.8301 0 1 30.0 0 -1.501 0 33.8298 0 1 50.0 0 -1.534 0 33.8300 0 1 75.0 0 -1.525 0 33.8316 0 1 100.0 0 -1.374 0 33.8590 0 1 125.0 0 -0.876 0 33.9326 0 1 150.0 0 -0.560 0 33.9832 0 1 200.0 0 -0.201 0 34.0450 0 1 250.0 0 1.463 0 34.3532 0 1 300.0 0 1.840 0 34.4528 0 1 400.0 0 2.021 0 34.5557 0 1 500.0 0 2.079 0 34.6111 0 1 600.0 0 2.080 0 34.6529 0 1 700.0 0 2.085 0 34.6868 0 1 800.0 0 1.969 0 34.7056 0 1 900.0 0 1.918 0 34.7199 0 1 1000.0 0 1.936 0 34.7383 0 1 WOD09_FR014108 10025090 B 1995-10-24T14:19 64.1915 -58.228 0.0 0 -1.409 0 33.8340 0 1 10.0 0 -1.407 0 33.8335 0 1 20.0 0 -1.472 0 33.8337 0 1 30.0 0 -1.482 0 33.8335 0 1 50.0 0 -1.526 0 33.8353 0 1 75.0 0 -1.508 0 33.8464 0 1 100.0 0 -1.453 0 33.8538 0 1 125.0 0 -0.906 0 33.9291 0 1 150.0 0 -0.549 0 33.9818 0 1 200.0 0 -0.171 0 34.0473 0 1 250.0 0 1.599 0 34.3601 0 1 300.0 0 1.849 0 34.4581 0 1 WOD09_FR014108 10025091 B 1995-10-24T16:22 64.2127 -58.227 0.0 0 -1.443 0 33.8341 0 1 10.0 0 -1.441 0 33.8332 0 1 20.0 0 -1.444 0 33.8339 0 1 30.0 0 -1.444 0 33.8337 0 1 50.0 0 -1.499 0 33.8358 0 1 75.0 0 -1.510 0 33.8420 0 1 100.0 0 -1.431 0 33.8561 0 1 125.0 0 -0.995 0 33.9146 0 1 150.0 0 -0.562 0 33.9832 0 1 200.0 0 -0.356 0 34.0198 0 1 250.0 0 1.491 0 34.3298 0 1 300.0 0 1.747 0 34.4276 0 1 400.0 0 1.989 0 34.5340 0 1 500.0 0 2.077 0 34.6135 0 1 600.0 0 2.089 0 34.6427 0 1 700.0 0 2.077 0 34.6813 0 1 800.0 0 2.083 0 34.7038 0 1 900.0 0 2.024 0 34.7234 0 1 1000.0 0 1.905 0 34.7281 0 1 WOD09_FR014108 10025092 B 1995-10-24T22:09 64.3533 -58.233 0.0 0 1 10.0 0 -1.383 0 33.8394 0 1 20.0 0 -1.392 0 33.8398 0 1 30.0 0 -1.443 0 33.8414 0 1 50.0 0 -1.488 0 33.8439 0 1 75.0 0 -1.492 0 33.8494 0 1 100.0 0 -1.486 0 33.8528 0 1 125.0 0 -1.474 0 33.8576 0 1 150.0 0 -1.395 0 33.8792 0 1 200.0 0 0.310 0 34.1524 0 1 250.0 0 1.636 0 34.3711 0 1 300.0 0 1.838 0 34.4467 0 1 WOD09_FR014108 10025093 B 1995-10-25T04:21 64.4192 -58.248 0.0 0 -1.387 0 33.8421 0 1 10.0 0 -1.410 0 33.8444 0 1 20.0 0 -1.416 0 33.8448 0 1 30.0 0 -1.411 0 33.8449 0 1 50.0 0 -1.471 0 33.8474 0 1 75.0 0 -1.475 0 33.8556 0 1 100.0 0 -1.475 0 33.8559 0 1 125.0 0 -1.470 0 33.8586 0 1 150.0 0 -1.397 0 33.8746 0 1 200.0 0 -0.651 0 34.0057 0 1 250.0 0 1.138 0 34.3058 0 1 300.0 0 1.853 0 34.4488 0 1 400.0 0 1.977 0 34.5389 0 1 500.0 0 2.070 0 34.6092 0 1 600.0 0 2.094 0 34.6503 0 1 700.0 0 2.069 0 34.6825 0 1 800.0 0 2.045 0 34.7066 0 1 900.0 0 2.001 0 34.7248 0 1 1000.0 0 1.957 0 34.7402 0 1 WOD09_FR014108 10025094 B 1995-10-25T10:48 64.5095 -58.247 0.0 0 -1.282 0 33.8465 0 1 10.0 0 -1.270 0 33.8467 0 1 20.0 0 -1.333 0 33.8470 0 1 30.0 0 -1.404 0 33.8466 0 1 50.0 0 -1.464 0 33.8541 0 1 75.0 0 -1.457 0 33.8604 0 1 100.0 0 -1.459 0 33.8607 0 1 125.0 0 -1.451 0 33.8626 0 1 150.0 0 -0.795 0 33.9596 0 1 200.0 0 -0.186 0 34.0745 0 1 250.0 0 1.625 0 34.3774 0 1 300.0 0 1.803 0 34.4475 0 1 WOD09_FR014108 10025095 B 1995-10-25T14:28 64.5505 -58.250 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 -1.479 0 33.8568 0 1 75.0 0 -1.475 0 33.8571 0 1 100.0 0 -1.474 0 33.8575 0 1 125.0 0 -1.468 0 33.8588 0 1 150.0 0 -1.206 0 33.9114 0 1 200.0 0 -0.176 0 34.0627 0 1 250.0 0 1.477 0 34.3508 0 1 300.0 0 1.776 0 34.4321 0 1 400.0 0 2.017 0 34.5311 0 1 500.0 0 2.073 0 34.5890 0 1 600.0 0 2.073 0 34.6415 0 1 700.0 0 2.074 0 34.6741 0 1 800.0 0 2.046 0 34.6982 0 1 900.0 0 2.027 0 34.7179 0 1 1000.0 0 1.981 0 34.7335 0 1 WOD09_FR014108 10025096 B 1995-10-25T16:25 64.6283 -58.258 0.0 0 -1.316 0 33.8468 0 1 10.0 0 -1.316 0 33.8470 0 1 20.0 0 -1.314 0 33.8470 0 1 30.0 0 -1.315 0 33.8454 0 1 50.0 0 -1.469 0 33.8524 0 1 75.0 0 -1.480 0 33.8559 0 1 100.0 0 -1.476 0 33.8567 0 1 125.0 0 -1.465 0 33.8601 0 1 150.0 0 -1.316 0 33.8910 0 1 200.0 0 -0.317 0 34.0471 0 1 250.0 0 1.643 0 34.3635 0 1 300.0 0 1.810 0 34.4353 0 1 WOD09_FR014108 10025097 B 1995-10-25T22:24 64.8102 -58.328 0.0 0 -1.272 0 33.8470 0 1 10.0 0 -1.260 0 33.8465 0 1 20.0 0 -1.274 0 33.8470 0 1 30.0 0 -1.262 0 33.8497 0 1 50.0 0 -1.252 0 33.8519 0 1 75.0 0 -1.311 0 33.8518 0 1 100.0 0 -1.292 0 33.8537 0 1 125.0 0 -1.190 0 33.8822 0 1 150.0 0 -0.531 0 33.9679 0 1 200.0 0 -0.567 0 33.9901 0 1 250.0 0 1.089 0 34.2526 0 1 300.0 0 1.758 0 34.4054 0 1 400.0 0 2.001 0 34.5118 0 1 500.0 0 2.086 0 34.5865 0 1 600.0 0 2.096 0 34.6392 0 1 700.0 0 2.084 0 34.6779 0 1 800.0 0 2.068 0 34.7021 0 1 900.0 0 2.036 0 34.7191 0 1 1000.0 0 1.983 0 34.7326 0 1 WOD09_FR014108 10025098 B 1995-10-30T17:10 68.2175 -50.685 0.0 0 1 10.0 0 1.894 0 33.8931 0 1 20.0 0 1.893 0 33.8932 0 1 30.0 0 1.896 0 33.8933 0 1 50.0 0 1.896 0 33.8933 0 1 75.0 0 1.880 0 33.8938 0 1 100.0 0 1.803 0 33.8955 0 1 125.0 0 1.764 0 33.8972 0 1 150.0 0 1.595 0 33.9100 0 1 200.0 0 1.594 0 33.9585 0 1 250.0 0 1.621 0 33.9767 0 1 300.0 0 1.625 4 33.9845 0 1 400.0 0 1.728 3 34.0618 3 1 WOD09_FR014290 10428008 B 1999-01-13 68.8667 -50.767 0.0 0 3.691 0 33.7471 0 1 10.0 0 3.682 0 33.7649 0 1 20.0 0 3.663 0 33.7782 0 1 30.0 0 3.652 0 33.7841 0 1 50.0 0 3.640 0 33.7884 0 1 75.0 0 3.630 0 33.7955 0 1 100.0 0 3.105 0 33.8350 0 1 125.0 0 2.841 0 33.8225 0 1 150.0 0 2.584 0 33.8288 0 1 200.0 0 1.994 0 33.9235 0 1 250.0 0 2.257 0 34.0594 0 1 300.0 0 2.325 0 34.1589 0 1 400.0 0 2.280 0 34.2859 0 1 500.0 0 2.256 0 34.3742 0 1 600.0 0 2.276 0 34.4543 0 1 700.0 0 2.300 0 34.5436 0 1 800.0 0 2.310 0 34.5895 0 1 900.0 0 2.311 0 34.6264 0 1 1000.0 0 2.311 0 34.6639 0 1 1100.0 0 2.275 0 34.6954 0 1 1200.0 0 2.233 0 34.7154 0 1 1300.0 0 2.191 0 34.7248 0 1 1400.0 0 2.125 0 34.7355 0 1 1500.0 0 2.028 0 34.7412 0 1 WOD09_FR014293 10428116 B 1999-03-24T07:27 68.8667 -50.767 0.0 0 4.143 0 33.7911 0 1 10.0 0 4.142 0 33.7909 0 1 20.0 0 4.144 0 33.7908 0 1 30.0 0 4.142 0 33.7905 0 1 50.0 0 4.127 0 33.7911 0 1 75.0 0 4.085 0 33.7921 0 1 100.0 0 3.914 0 33.7897 0 1 125.0 0 2.572 0 33.8620 0 1 150.0 0 2.058 0 33.9053 0 1 200.0 0 1.835 0 33.9826 0 1 250.0 0 1.944 0 34.0711 0 1 300.0 0 2.245 0 34.1690 0 1 400.0 0 2.225 0 34.2694 0 1 500.0 0 2.242 0 34.3805 0 1 600.0 0 2.248 0 34.4698 0 1 700.0 0 2.269 0 34.5403 0 1 800.0 0 2.328 0 34.6097 0 1 900.0 0 2.272 0 34.6448 0 1 1000.0 0 2.249 0 34.6730 0 1 1100.0 0 2.219 0 34.7007 0 1 1200.0 0 2.208 0 34.7294 0 1 1300.0 0 2.130 0 34.7442 0 1 1400.0 0 2.059 0 34.7518 0 1 WOD09_FR014294 10428117 B 1999-04-15T03:12 68.8667 -50.767 0.0 0 3.768 0 33.7972 0 1 10.0 0 3.768 0 33.7966 0 1 20.0 0 3.770 0 33.7971 0 1 30.0 0 3.770 0 33.7972 0 1 50.0 0 3.772 0 33.7970 0 1 75.0 0 3.774 0 33.7964 0 1 100.0 0 3.777 0 33.7955 0 1 125.0 0 3.769 0 33.7942 0 1 150.0 0 3.054 0 33.8378 0 1 200.0 0 1.984 0 33.9581 0 1 250.0 0 1.856 0 34.0364 0 1 300.0 0 2.176 0 34.1446 0 1 400.0 0 2.400 0 34.2802 0 1 500.0 0 2.360 0 34.3837 0 1 600.0 0 2.320 0 34.4557 0 1 700.0 0 2.319 0 34.5127 0 1 800.0 0 2.328 0 34.5771 0 1 900.0 0 2.329 0 34.6178 0 1 1000.0 0 2.327 0 34.6513 0 1 1100.0 0 2.285 0 34.6852 0 1 1200.0 0 2.246 0 34.7127 0 1 1300.0 0 2.185 0 34.7348 0 1 1400.0 0 2.119 0 34.7480 0 1 1500.0 0 2.036 0 34.7541 0 1 WOD09_FR014297 10428122 B 1999-07-13T00:06 68.8667 -50.767 0.0 0 2.336 0 33.8330 0 1 10.0 0 2.336 0 33.8327 0 1 20.0 0 2.339 0 33.8323 0 1 30.0 0 2.339 0 33.8327 0 1 50.0 0 2.342 0 33.8327 0 1 75.0 0 2.345 0 33.8325 0 1 100.0 0 2.344 0 33.8324 0 1 125.0 0 2.344 0 33.8334 0 1 150.0 0 2.346 0 33.8355 0 1 200.0 0 2.267 0 33.9958 0 1 250.0 0 2.108 0 34.0947 0 1 300.0 0 2.143 0 34.1544 0 1 400.0 0 2.458 4 34.3016 0 1 500.0 0 2.422 0 34.3787 0 1 600.0 0 2.373 0 34.4496 0 1 700.0 0 2.308 0 34.5197 0 1 800.0 0 2.343 0 34.5723 0 1 900.0 0 2.330 0 34.6145 0 1 1000.0 0 2.312 0 34.6476 0 1 1100.0 0 2.276 0 34.6857 0 1 1200.0 0 2.247 0 34.7103 0 1 1300.0 0 2.196 0 34.7290 0 1 1400.0 0 2.138 0 34.7424 0 1 WOD09_FR014299 10428133 B 1999-08-14T01:34 68.8667 -50.767 0.0 0 1.964 0 33.8356 0 1 10.0 0 1.965 0 33.8357 0 1 20.0 0 1.969 0 33.8358 0 1 30.0 0 1.971 0 33.8358 0 1 50.0 0 1.972 0 33.8355 0 1 75.0 0 1.975 0 33.8354 0 1 100.0 0 1.995 0 33.8374 0 1 125.0 0 2.018 0 33.8430 0 1 150.0 0 2.030 0 33.8471 0 1 200.0 0 2.293 0 34.0216 0 1 250.0 0 2.251 0 34.1047 0 1 300.0 0 2.263 0 34.1692 0 1 400.0 0 2.187 0 34.2818 0 1 500.0 0 2.246 0 34.4000 0 1 600.0 0 2.294 0 34.4737 0 1 700.0 0 2.293 0 34.5335 0 1 800.0 0 2.328 0 34.5959 0 1 900.0 0 2.315 0 34.6389 0 1 1000.0 0 2.299 0 34.6728 0 1 1100.0 0 2.226 0 34.6974 0 1 1200.0 0 2.203 0 34.7228 0 1 1300.0 0 2.157 0 34.7380 0 1 1400.0 0 2.090 0 34.7474 0 1 WOD09_FR014300 10428145 B 1999-11-29T08:19 68.8667 -50.767 0.0 0 2.388 0 33.8608 0 1 10.0 0 2.388 0 33.8608 0 1 20.0 0 2.388 0 33.8608 0 1 30.0 0 2.388 0 33.8608 0 1 50.0 0 2.388 0 33.8608 0 1 75.0 0 2.386 0 33.8606 0 1 100.0 0 2.337 0 33.8607 0 1 125.0 0 2.178 0 33.8727 0 1 150.0 0 2.020 0 33.8825 0 1 200.0 0 1.590 0 33.9231 0 1 250.0 0 1.704 0 33.9870 0 1 300.0 0 1.856 0 34.0709 0 1 400.0 0 2.084 0 34.1863 0 1 500.0 0 2.328 0 34.3278 0 1 600.0 0 2.328 0 34.4412 0 1 700.0 0 2.303 0 34.5191 0 1 800.0 0 2.320 0 34.5921 0 1 900.0 0 2.253 0 34.6377 0 1 1000.0 0 2.223 0 34.6589 0 1 1100.0 0 2.217 0 34.6907 0 1 1200.0 0 2.180 0 34.7211 0 1 1300.0 0 2.129 0 34.7370 0 1 1400.0 0 2.066 0 34.7483 0 1 WOD09_FR014301 10428147 B 1999-12-18T09:07 68.8667 -50.767 0.0 0 2.980 0 33.8347 0 1 10.0 0 2.980 0 33.8379 0 1 20.0 0 2.966 0 33.8381 0 1 30.0 0 2.924 0 33.8374 0 1 50.0 0 2.849 0 33.8367 0 1 75.0 0 2.630 0 33.8405 0 1 100.0 0 2.479 0 33.8468 0 1 125.0 0 2.435 0 33.8486 0 1 150.0 0 2.262 0 33.8641 0 1 200.0 0 1.697 0 33.9381 0 1 250.0 0 2.043 0 34.0725 0 1 300.0 0 2.303 0 34.1805 0 1 400.0 0 2.367 0 34.3055 0 1 500.0 0 2.380 0 34.4049 0 1 600.0 0 2.356 0 34.4844 0 1 700.0 0 2.329 0 34.5418 0 1 800.0 0 2.320 0 34.5911 0 1 900.0 0 2.303 0 34.6388 0 1 1000.0 0 2.274 0 34.6690 0 1 1100.0 0 2.245 0 34.6954 0 1 1200.0 0 2.202 0 34.7142 0 1 1300.0 0 2.158 0 34.7312 0 1 1400.0 0 2.077 0 34.7434 0 1 WOD09_FR014302 10428149 B 2000-01-16T08:52 68.8667 -50.717 0.0 0 3.543 0 33.8325 0 1 10.0 0 3.543 0 33.8325 0 1 20.0 0 3.541 0 33.8324 0 1 30.0 0 3.536 0 33.8323 0 1 50.0 0 3.511 0 33.8320 0 1 75.0 0 3.401 0 33.8324 0 1 100.0 0 3.108 0 33.8332 0 1 125.0 0 2.138 0 33.8593 0 1 150.0 0 1.779 0 33.8720 0 1 200.0 0 1.559 0 33.9437 0 1 250.0 0 2.058 0 34.0851 0 1 300.0 0 2.364 0 34.1911 0 1 400.0 0 2.432 0 34.3107 0 1 500.0 0 2.400 0 34.3984 0 1 600.0 0 2.369 0 34.4783 0 1 700.0 0 2.354 0 34.5396 0 1 800.0 0 2.339 0 34.5937 0 1 900.0 0 2.327 0 34.6358 0 1 1000.0 0 2.296 0 34.6728 0 1 1100.0 0 2.256 0 34.6996 0 1 1200.0 0 2.214 0 34.7203 0 1 1300.0 0 2.148 0 34.7367 0 1 1400.0 0 2.068 0 34.7470 0 1 1500.0 0 1.993 0 34.7524 0 1 WOD09_FR014306 10428185 B 2000-04-24T11:06 68.8667 -50.767 0.0 0 3.515 0 33.8123 0 1 10.0 0 3.516 0 33.8123 0 1 20.0 0 3.516 0 33.8118 0 1 30.0 0 3.516 0 33.8119 0 1 50.0 0 3.516 0 33.8114 0 1 75.0 0 3.516 0 33.8106 0 1 100.0 0 3.510 0 33.8093 0 1 125.0 0 3.497 0 33.8059 0 1 150.0 0 2.229 0 33.9052 0 1 200.0 0 1.633 0 33.9479 0 1 250.0 0 2.026 0 34.0636 0 1 300.0 0 2.295 0 34.1760 0 1 400.0 0 2.372 0 34.2844 0 1 500.0 0 2.436 0 34.3914 0 1 600.0 0 2.433 0 34.4611 0 1 700.0 0 2.397 0 34.5346 0 1 800.0 0 2.357 0 34.5797 0 1 900.0 0 2.338 0 34.6299 0 1 1000.0 0 2.306 0 34.6726 0 1 1100.0 0 2.273 0 34.6974 0 1 1200.0 0 2.226 0 34.7174 0 1 1300.0 0 2.171 0 34.7323 0 1 1400.0 0 2.114 0 34.7415 0 1 1500.0 0 2.037 0 34.7489 0 1 WOD09_FR014307 10428260 B 2000-05-22T02:57 68.8667 -50.767 0.0 0 3.275 0 33.8151 0 1 10.0 0 3.275 0 33.8151 0 1 20.0 0 3.275 0 33.8150 0 1 30.0 0 3.276 0 33.8148 0 1 50.0 0 3.276 0 33.8145 0 1 75.0 0 3.259 0 33.8156 0 1 100.0 0 3.246 0 33.8157 0 1 125.0 0 3.243 0 33.8144 0 1 150.0 0 3.230 0 33.8123 0 1 200.0 0 1.858 0 33.9358 0 1 250.0 0 1.985 0 34.0577 0 1 300.0 0 2.221 0 34.1405 0 1 400.0 0 2.387 0 34.2797 0 1 500.0 0 2.440 0 34.3717 0 1 600.0 0 2.440 0 34.4575 0 1 700.0 0 2.400 0 34.5206 0 1 800.0 0 2.368 0 34.5719 0 1 900.0 0 2.332 0 34.6200 0 1 1000.0 0 2.292 0 34.6533 0 1 1100.0 0 2.279 0 34.6811 0 1 1200.0 0 2.244 0 34.7065 0 1 1300.0 0 2.179 0 34.7301 0 1 1400.0 0 2.145 0 34.7366 0 1 1500.0 0 2.002 0 34.7391 0 1 WOD09_FR014308 10428262 B 2000-06-07T10:01 68.8667 -50.767 0.0 0 2.931 0 33.8335 0 1 10.0 0 2.932 0 33.8335 0 1 20.0 0 2.934 0 33.8334 0 1 30.0 0 2.934 0 33.8332 0 1 50.0 0 2.920 0 33.8328 0 1 75.0 0 2.884 0 33.8308 0 1 100.0 0 2.863 0 33.8306 0 1 125.0 0 2.857 0 33.8303 0 1 150.0 0 2.856 0 33.8303 0 1 200.0 0 2.539 0 33.8766 0 1 250.0 0 2.071 0 34.0261 0 1 300.0 0 2.259 0 34.1248 0 1 400.0 0 2.385 0 34.2523 0 1 500.0 0 2.440 0 34.3665 0 1 600.0 0 2.437 0 34.4513 0 1 700.0 0 2.405 0 34.5080 0 1 800.0 0 2.376 0 34.5573 0 1 900.0 0 2.366 0 34.6028 0 1 1000.0 0 2.345 0 34.6416 0 1 1100.0 0 2.309 0 34.6734 0 1 1200.0 0 2.264 0 34.6952 0 1 1300.0 0 2.220 0 34.7198 0 1 1400.0 0 2.158 0 34.7349 0 1 1500.0 0 2.084 0 34.7447 0 1 WOD09_FR014311 10428265 B 2000-11-11T22:10 68.8667 -50.767 0.0 0 1.853 0 33.9019 0 1 10.0 0 1.853 0 33.9016 0 1 20.0 0 1.856 0 33.9008 0 1 30.0 0 1.855 0 33.9004 0 1 50.0 0 1.833 0 33.9007 0 1 75.0 0 1.830 0 33.9006 0 1 100.0 0 1.830 0 33.9003 0 1 125.0 0 1.827 0 33.9004 0 1 150.0 0 1.806 0 33.9018 0 1 200.0 0 1.773 0 33.9625 0 1 250.0 0 2.172 0 34.0966 0 1 300.0 0 2.243 0 34.1952 0 1 400.0 0 2.329 0 34.3024 0 1 500.0 0 2.399 0 34.3967 0 1 600.0 0 2.405 0 34.4716 0 1 700.0 0 2.381 0 34.5493 0 1 800.0 0 2.329 0 34.6028 0 1 900.0 0 2.270 0 34.6377 0 1 1000.0 0 2.248 0 34.6796 0 1 1100.0 0 2.191 0 34.6998 0 1 1200.0 0 2.138 0 34.7243 0 1 1300.0 0 2.085 0 34.7373 0 1 1400.0 0 2.030 0 34.7426 0 1 WOD09_FR014313 10428268 B 2001-01-16T00:19 68.4167 -50.650 0.0 0 3.682 0 33.8606 0 1 10.0 0 3.682 0 33.8606 0 1 20.0 0 3.682 0 33.8606 0 1 30.0 0 3.683 0 33.8613 0 1 50.0 0 3.654 0 33.8662 0 1 75.0 0 3.113 0 33.8708 0 1 100.0 0 2.705 0 33.8742 0 1 125.0 0 2.059 0 33.8949 0 1 150.0 0 1.579 0 33.9078 0 1 200.0 0 1.368 0 33.9254 0 1 250.0 0 1.775 0 34.0228 0 1 300.0 0 1.962 0 34.1120 0 1 400.0 0 2.290 0 34.2817 0 1 500.0 0 2.341 0 34.3861 0 1 600.0 0 2.333 0 34.4749 0 1 700.0 0 2.339 0 34.5487 0 1 800.0 0 2.286 0 34.5935 0 1 900.0 0 2.315 0 34.6382 0 1 1000.0 0 2.234 0 34.6616 0 1 1100.0 0 2.206 0 34.6870 0 1 1200.0 0 2.157 0 34.7071 0 1 1300.0 0 2.022 0 34.7347 0 1 1400.0 0 1.879 0 34.7492 0 1 1500.0 0 1.742 0 34.7554 0 1 WOD09_FR014314 10428270 B 2001-02-04T00:34 68.8667 -50.767 0.0 0 4.288 0 33.8347 0 1 10.0 0 4.254 0 33.8364 0 1 20.0 0 4.101 0 33.8601 0 1 30.0 0 3.973 0 33.8745 0 1 50.0 0 3.948 0 33.8700 0 1 75.0 0 3.889 0 33.8656 0 1 100.0 0 3.088 0 33.8838 0 1 125.0 0 2.004 0 33.9268 0 1 150.0 0 1.819 0 33.9516 0 1 200.0 0 1.667 0 33.9835 0 1 250.0 0 1.972 0 34.0839 0 1 300.0 0 2.207 0 34.1549 0 1 400.0 0 2.332 0 34.2770 0 1 500.0 0 2.401 0 34.3899 0 1 600.0 0 2.420 0 34.4757 0 1 700.0 0 2.394 0 34.5398 0 1 800.0 0 2.364 0 34.5970 0 1 900.0 0 2.313 0 34.6312 0 1 1000.0 0 2.307 0 34.6621 0 1 1100.0 0 2.276 0 34.6864 0 1 1200.0 0 2.245 0 34.7127 0 1 1300.0 0 2.180 0 34.7315 0 1 1400.0 0 2.106 0 34.7417 0 1 WOD09_FR014322 10428827 B 2002-01-14T19:30 68.4167 -50.667 0.0 0 4.096 0 33.8659 0 1 10.0 0 4.097 0 33.8659 0 1 20.0 0 4.100 0 33.8659 0 1 30.0 0 4.100 0 33.8659 0 1 50.0 0 4.085 0 33.8669 0 1 75.0 0 4.000 0 33.8712 0 1 100.0 0 3.031 0 33.8992 0 1 125.0 0 2.600 0 33.9076 0 1 150.0 0 2.292 0 33.9178 0 1 200.0 0 1.953 0 33.9419 0 1 250.0 0 1.941 0 34.0020 0 1 300.0 0 2.134 0 34.1243 0 1 400.0 0 2.265 0 34.2774 0 1 500.0 0 2.360 0 34.3809 0 1 600.0 0 2.344 0 34.4492 0 1 700.0 0 2.300 0 34.5209 0 1 800.0 0 2.299 0 34.5859 0 1 900.0 0 2.276 0 34.6305 0 1 1000.0 0 2.252 0 34.6616 0 1 1100.0 0 2.210 0 34.6880 0 1 1200.0 0 2.148 0 34.7104 0 1 1300.0 0 2.075 0 34.7285 0 1 1400.0 0 1.970 0 34.7398 0 1 1500.0 0 1.841 0 34.7463 0 1 WOD09_FR014324 10428833 B 2002-02-14T23:58 68.8500 -50.767 0.0 0 5.003 0 33.8640 0 1 10.0 0 5.002 0 33.8640 0 1 20.0 0 4.992 0 33.8641 0 1 30.0 0 4.972 0 33.8642 0 1 50.0 0 4.847 0 33.8677 0 1 75.0 0 4.386 0 33.8783 0 1 100.0 0 3.143 0 33.9004 0 1 125.0 0 2.531 0 33.9250 0 1 150.0 0 2.237 0 33.9362 0 1 200.0 0 2.057 0 34.0080 0 1 250.0 0 2.128 0 34.0944 0 1 300.0 0 2.185 0 34.1460 0 1 400.0 0 2.246 0 34.2054 0 1 500.0 0 2.321 0 34.3483 0 1 600.0 0 2.338 0 34.4628 0 1 700.0 0 2.360 0 34.5359 0 1 800.0 0 2.310 0 34.5899 0 1 900.0 0 2.281 0 34.6329 0 1 1000.0 0 2.245 0 34.6726 0 1 1100.0 0 2.200 0 34.6983 0 1 1200.0 0 2.158 0 34.7179 0 1 1300.0 0 2.123 0 34.7370 0 1 1400.0 0 2.041 0 34.7465 0 1 WOD09_FR014329 10429008 B 2002-05-09T22:34 68.8667 -50.767 0.0 0 3.584 0 33.8462 0 1 10.0 0 3.584 0 33.8462 0 1 20.0 0 3.586 0 33.8537 0 1 30.0 0 3.584 0 33.8569 0 1 50.0 0 3.583 0 33.8631 0 1 75.0 0 3.580 0 33.8642 0 1 100.0 0 3.569 0 33.8653 0 1 125.0 0 3.460 0 33.8735 0 1 150.0 0 2.532 0 33.9675 0 1 200.0 0 2.266 0 34.0343 0 1 250.0 0 2.298 0 34.1061 0 1 300.0 0 2.372 0 34.1688 0 1 400.0 0 2.404 0 34.3013 0 1 500.0 0 2.404 0 34.3817 0 1 600.0 0 2.413 0 34.4734 0 1 700.0 0 2.401 0 34.5450 0 1 800.0 0 2.365 0 34.5911 0 1 900.0 0 2.362 0 34.6326 0 1 1000.0 0 2.326 0 34.6694 0 1 1100.0 0 2.296 0 34.6949 0 1 1200.0 0 2.250 0 34.7172 0 1 1300.0 0 2.197 0 34.7327 0 1 1400.0 0 2.150 0 34.7418 0 1 1500.0 0 2.060 0 34.7505 0 1 WOD09_FR014331 10429012 B 2002-06-05T16:55 68.8667 -50.767 0.0 0 3.047 0 33.8647 0 1 10.0 0 3.047 0 33.8647 0 1 20.0 0 3.038 0 33.8695 0 1 30.0 0 3.034 0 33.8692 0 1 50.0 0 3.030 0 33.8691 0 1 75.0 0 3.027 0 33.8692 0 1 100.0 0 3.026 0 33.8687 0 1 125.0 0 3.021 0 33.8688 0 1 150.0 0 2.910 0 33.9045 0 1 200.0 0 2.357 0 34.0403 0 1 250.0 0 2.362 0 34.1110 0 1 300.0 0 2.344 0 34.1709 0 1 400.0 0 2.408 0 34.2764 0 1 500.0 0 2.417 0 34.3660 0 1 600.0 0 2.397 0 34.4508 0 1 700.0 0 2.390 0 34.5121 0 1 800.0 0 2.374 0 34.5826 0 1 900.0 0 2.358 0 34.6267 0 1 1000.0 0 2.335 0 34.6664 0 1 1100.0 0 2.288 0 34.6945 0 1 1200.0 0 2.229 0 34.7211 0 1 1300.0 0 2.193 0 34.7329 0 1 1400.0 0 2.124 0 34.7417 0 1 1500.0 0 2.060 0 34.7502 0 1 WOD09_FR014576 10802970 B 2004-01-26T08:37 63.0167 -56.500 0.0 0 2.715 0 1 10.0 0 2.720 0 1 20.0 0 2.708 0 33.9340 0 1 30.0 0 2.705 0 33.9230 0 1 50.0 0 2.704 0 33.9230 0 1 75.0 0 2.701 0 33.9230 0 1 100.0 0 2.635 0 33.9210 0 1 125.0 0 1.723 0 33.9510 0 1 150.0 0 1.283 0 33.9960 0 1 200.0 0 1.239 0 34.0810 0 1 250.0 0 1.850 0 34.2150 0 1 300.0 0 1.941 0 34.2960 0 1 400.0 0 2.170 0 34.4140 0 1 500.0 0 2.234 0 34.4970 0 1 600.0 0 2.255 0 34.5720 0 1 700.0 0 2.277 0 34.6220 0 1 800.0 0 2.225 0 34.6550 0 1 900.0 0 2.153 0 34.6820 0 1 1000.0 0 2.119 0 34.7100 0 1 1100.0 0 2.063 0 34.7290 0 1 1200.0 0 2.058 0 34.7500 0 1 1300.0 0 2.009 0 34.7610 0 1 1400.0 0 1.953 0 34.7680 0 1 1500.0 0 1.846 0 34.7670 0 1 1750.0 0 1.640 0 34.7660 0 1 2000.0 0 1.398 0 34.7560 0 1 2500.0 0 0.938 0 34.7270 0 1 3000.0 0 0.588 0 34.7070 0 1 3500.0 0 0.310 0 34.6930 0 1 4000.0 0 0.111 0 34.6830 0 1 4500.0 0 -0.073 0 34.6740 0 1 WOD09_FR014576 10802971 B 2004-01-26T13:13 63.0167 -56.500 0.0 0 2.741 0 1 10.0 0 2.740 0 1 20.0 0 2.747 0 33.9460 0 1 30.0 0 2.738 0 33.9230 0 1 50.0 0 2.703 0 33.9230 0 1 75.0 0 2.700 0 33.9230 0 1 100.0 0 2.579 0 33.9210 0 1 125.0 0 1.608 0 33.9590 0 1 150.0 0 1.178 0 33.9960 0 1 200.0 0 1.508 0 34.1090 0 1 250.0 0 1.834 0 34.2100 0 1 300.0 0 1.975 0 34.3000 0 1 400.0 0 2.236 0 34.4410 0 1 500.0 0 2.265 0 34.5180 0 1 600.0 0 2.237 0 34.5720 0 1 700.0 0 2.277 0 34.6280 0 1 800.0 0 2.186 0 34.6600 0 1 900.0 0 2.152 0 34.6900 0 1 WOD09_FR014576 10802972 B 2004-01-27T10:07 63.0167 -60.000 0.0 0 1.387 0 1 10.0 0 1.400 0 1 20.0 0 1.385 0 33.8090 0 1 30.0 0 1.378 0 33.8150 0 1 50.0 0 1.218 0 33.8380 0 1 75.0 0 0.072 0 33.9770 0 1 100.0 0 -0.401 0 34.0060 0 1 125.0 0 -0.633 0 34.0200 0 1 150.0 0 -0.448 0 34.0850 0 1 200.0 0 1.530 0 34.4170 0 1 250.0 0 1.787 0 34.5080 0 1 300.0 0 1.932 0 34.5700 0 1 400.0 0 2.035 0 34.6420 0 1 500.0 0 1.955 0 34.6810 0 1 600.0 0 1.934 0 34.7110 0 1 700.0 0 1.881 0 34.7350 0 1 800.0 0 1.856 0 34.7500 0 1 900.0 0 1.821 0 34.7610 0 1 WOD09_FR014576 10802973 B 2004-02-02T09:52 68.4167 -50.667 0.0 0 1 10.0 0 4.667 0 1 20.0 0 4.635 0 1 30.0 0 4.482 0 33.8040 0 1 50.0 0 4.328 0 33.8110 0 1 75.0 0 4.221 0 33.8150 0 1 100.0 0 3.760 0 33.8290 0 1 125.0 0 3.081 0 33.8620 0 1 150.0 0 2.480 0 33.8950 0 1 200.0 0 1.768 0 33.9490 0 1 250.0 0 1.791 0 34.0070 0 1 300.0 0 2.193 0 34.1270 0 1 400.0 0 2.270 0 34.2780 0 1 500.0 0 2.313 0 34.3760 0 1 600.0 0 2.380 0 34.4720 0 1 700.0 0 2.344 0 34.5290 0 1 800.0 0 2.292 0 34.5880 0 1 900.0 0 2.313 0 34.6360 0 1 1000.0 0 2.300 0 34.6690 0 1 1100.0 0 2.275 0 34.7010 0 1 1200.0 0 2.203 0 34.7210 0 1 1300.0 0 2.136 0 34.7390 0 1 1400.0 0 2.005 0 34.7580 0 1 1500.0 0 1.868 0 34.7690 0 1 WOD09_FR015502 11701502 B 2005-02-10T07:25 68.4167 -50.667 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 3.782 0 33.8178 0 1 75.0 0 3.789 0 33.8180 0 1 100.0 0 3.722 0 33.8172 0 1 125.0 0 2.553 0 33.8595 0 1 150.0 0 1.683 0 33.8961 0 1 200.0 0 1.497 0 33.9334 0 1 250.0 0 1.707 0 34.0169 0 1 300.0 0 2.000 0 34.1167 0 1 400.0 0 2.260 0 34.2604 0 1 500.0 0 2.275 0 34.3839 0 1 600.0 0 2.287 0 34.4619 0 1 700.0 0 2.308 0 34.5285 0 1 800.0 0 2.299 0 34.5804 0 1 900.0 0 2.284 0 34.6362 0 1 1000.0 0 2.260 0 34.6735 0 1 WOD09_FR015502 11701503 B 2005-02-10T15:25 68.3867 -50.680 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 3.707 0 33.8215 0 1 75.0 0 3.665 0 33.8220 0 1 100.0 0 2.896 0 33.8490 0 1 125.0 0 2.064 0 33.8943 0 1 150.0 0 1.856 0 33.9163 0 1 200.0 0 1.503 0 33.9358 0 1 250.0 0 1.655 0 33.9961 0 1 300.0 0 1.923 0 34.1083 0 1 400.0 0 2.161 0 34.2411 0 1 500.0 0 2.342 0 34.3716 0 1 600.0 0 2.401 0 34.4679 0 1 700.0 0 2.346 0 34.5222 0 1 800.0 0 2.293 0 34.5869 0 1 900.0 0 2.270 0 34.6334 0 1 1000.0 0 2.266 0 34.6714 0 1 1100.0 0 2.220 0 34.7036 0 1 1200.0 0 2.158 0 34.7243 0 1 1300.0 0 2.070 0 34.7412 0 1 1400.0 0 1.987 0 34.7535 0 1 1500.0 0 1.859 0 34.7595 0 1 WOD09_FR015502 11701504 B 2005-02-10T18:12 68.4200 -50.673 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 3.710 0 33.8216 0 1 75.0 0 3.710 0 33.8217 0 1 100.0 0 3.712 0 33.8216 0 1 125.0 0 2.805 0 33.8560 0 1 150.0 0 1.939 0 33.9112 0 1 200.0 0 1.521 0 33.9463 0 1 250.0 0 1.714 0 34.0163 0 1 300.0 0 2.123 0 34.1348 0 1 400.0 0 2.219 0 34.2763 0 1 500.0 0 2.348 0 34.3932 0 1 600.0 0 2.327 0 34.4578 0 1 700.0 0 2.308 0 34.5234 0 1 800.0 0 2.300 0 34.5802 0 1 900.0 0 2.289 0 34.6411 0 1 1000.0 0 2.255 0 34.6755 0 1 1100.0 0 2.189 0 34.7048 0 1 1200.0 0 2.144 0 34.7278 0 1 1300.0 0 2.080 0 34.7446 0 1 1400.0 0 1.971 0 34.7557 0 1 1500.0 0 1.853 0 34.7595 0 1 WOD09_FR015502 11701505 B 2005-02-10T22:30 68.4153 -50.670 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 3.715 0 33.8210 0 1 75.0 0 3.716 0 33.8212 0 1 100.0 0 3.718 0 33.8212 0 1 125.0 0 2.606 0 33.8664 0 1 150.0 0 1.932 0 33.9129 0 1 200.0 0 1.482 0 33.9495 0 1 WOD09_FR015502 11701506 B 2005-02-10T23:31 68.4180 -50.665 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 1 50.0 0 3.715 0 33.8213 0 1 75.0 0 3.717 0 33.8214 0 1 100.0 0 2.725 0 33.8571 0 1 125.0 0 2.030 0 33.8983 0 1 150.0 0 1.863 0 33.9345 0 1 200.0 0 1.627 0 33.9750 0 1 250.0 0 1.923 0 34.0787 0 1 300.0 0 2.182 0 34.1649 0 1 400.0 0 2.191 0 34.2640 0 1 500.0 0 2.324 0 34.3757 0 1 600.0 0 2.351 0 34.4714 0 1 700.0 0 2.308 0 34.5330 0 1 800.0 0 2.291 0 34.5998 0 1 900.0 0 2.282 0 34.6451 0 1 1000.0 0 2.259 0 34.6756 0 1 1100.0 0 2.227 0 34.7011 0 1 1200.0 0 2.163 0 34.7241 0 1 1300.0 0 2.098 0 34.7431 0 1 1400.0 0 1.972 0 34.7550 0 1 1500.0 0 1.822 0 34.7597 0 1 WOD09_FR015502 11701507 B 2005-02-11T03:13 68.4138 -50.670 0.0 0 1 10.0 0 1 20.0 0 1 30.0 0 3.706 0 33.8212 0 1 50.0 0 3.704 0 33.8214 0 1 75.0 0 3.702 0 33.8216 0 1 100.0 0 2.962 0 33.8440 0 1 125.0 0 2.131 0 33.8881 0 1 150.0 0 1.806 0 33.9057 0 1 200.0 0 1.496 0 33.9212 0 1 250.0 0 1.627 0 33.9857 0 1 300.0 0 2.078 0 34.1419 0 1 400.0 0 2.198 0 34.2432 0 1 500.0 0 2.276 0 34.3394 0 1 600.0 0 2.320 0 34.4542 0 1 700.0 0 2.311 0 34.5149 0 1 800.0 0 2.305 0 34.5743 0 1 900.0 0 2.302 0 34.6203 0 1 1000.0 0 2.277 0 34.6621 0 1 1100.0 0 2.235 0 34.6967 0 1 1200.0 0 2.163 0 34.7166 0 1 1300.0 0 2.111 0 34.7379 0 1 1400.0 0 1.985 0 34.7524 0 1 1500.0 0 1.855 0 34.7598 0 1 WOD09_US012972 3255017 B 1978-02-10 60.9770 -59.985 0.0 0 1.659 0 33.8320 0 1 10.0 0 1.633 0 33.8320 0 1 20.0 0 1.627 0 33.8320 0 1 30.0 0 1.592 0 33.8330 0 1 50.0 0 1.530 0 33.8350 0 1 75.0 0 -0.723 0 33.9660 0 1 100.0 0 -0.914 0 34.0330 0 1 125.0 0 -1.147 0 34.0540 0 1 150.0 0 -0.100 0 34.1910 3 1 200.0 0 1.702 0 34.4660 0 1 250.0 0 1.829 0 34.5220 0 1 300.0 0 1.905 0 34.5650 0 1 400.0 0 1.925 0 34.6210 0 1 500.0 0 1.915 4 34.6560 0 1 600.0 0 1.917 4 34.6870 0 1 700.0 0 1.928 0 34.7140 0 1 800.0 0 1.885 0 34.7280 0 1 900.0 0 1.799 4 34.7350 0 1 1000.0 0 1.725 0 34.7410 0 1 1100.0 0 1.606 6 34.7380 0 1 1200.0 0 1.544 3 34.7400 0 1 1300.0 0 1.466 3 34.7400 0 1 1400.0 0 1.354 3 34.7360 0 1 1500.0 0 1.270 3 34.7330 0 1 1750.0 0 1.042 3 34.7210 0 1 2000.0 0 0.847 0 34.7130 0 1 2500.0 0 0.542 0 34.6960 0 1 3000.0 0 0.287 0 34.6840 0 1 3500.0 0 0.079 0 34.6730 0 1 4000.0 0 -0.084 0 34.6650 0 1 4500.0 0 -0.196 0 34.6620 0 1 MITprof/profiles_process_main_v2/0000755000435400001440000000000012375431055016756 5ustar gforgetusersMITprof/profiles_process_main_v2/profiles_prep_mygrid.m0000644000435400001440000000646312365531346023374 0ustar gforgetusersfunction []=profiles_prep_mygrid(fileData,dirIn,dirOut,ni,nj); %[]=profiles_prep_mygrid(fileData,dirIn,dirOut,ni,nj); % %object: add interpolation information for use by MITgcm/pkg/profiles % %input: fileData is the name of the MITprof file to augment % dirIn is the corresponding direcroty name % dirOut is the directory name for the new (augmented) file % ni,nj is the MITgcm tile size % %output: (none -- a file will be created) % %example: % fileData='argo_indian.nc'; % dirIn='processed/'; % dirOut='mygrid/'; % ni=30; nj=30; % profiles_prep_mygrid(fileData,dirIn,dirOut,ni,nj); if strcmp(dirIn,dirOut); error('dirOut must differ from dirIn (to avoid loosing the original file)'); end; gcmfaces_global; if isempty(mygrid); fprintf(['it is a pre-requisiste that you load the grid according to e.g. \n' ... 'grid_load(''./'',5,''compact''); \n']); error('missing grid'); end; dirGrid0=[myenv.gcmfaces_dir '/sample_input/GRIDv4/']; if strcmp(mygrid.dirGrid,dirGrid0); fprintf('\n\n reminder: be sure to specify the grid \n'); fprintf(' directory of your own MITgcm set-up. \n'); fprintf(' By default we use ecco_v4 here.\n\n'); end; %triangulate data and get grid locations: %---------------------------------------- eval(['ncload ' dirIn fileData ' prof_lon prof_lat;']); loc_tile=gcmfaces_loc_tile(ni,nj,prof_lon,prof_lat); %prepare output fields: %---------------------- list_in={'XC11','YC11','XCNINJ','YCNINJ','iTile','jTile','XC','YC'}; list_out={'XC11','YC11','XCNINJ','YCNINJ','i','j','lon','lat'}; for iF=1:length(list_out); eval(['myVec.prof_interp_' list_out{iF} '=loc_tile.' list_in{iF} ';']); end; %use 1 as weight since we do nearest neighbor interp myVec.prof_interp_weights=ones(size(loc_tile.XC)); list_out={list_out{:},'weights'}; %append myVec.* to file: %----------------------- test0=dir([dirOut fileData]); if ~isempty(test0); test1=input(['\n\n !! ' dirOut fileData '\n !! already exists. Type 1 to erase it and proceed or 0 to stop.\n\n']); if test1; system(['rm -f ' dirOut fileData]); else; return; end; end; system(['cp -f ' dirIn fileData ' ' dirOut fileData]); list1d={'prof_interp_XC11','prof_interp_YC11','prof_interp_XCNINJ','prof_interp_YCNINJ'}; list2d={'prof_interp_i','prof_interp_j','prof_interp_lon','prof_interp_lat','prof_interp_weights'}; listAll={list1d{:},list2d{:}}; if (myenv.useNativeMatlabNetcdf); nc=netcdf.open([dirOut fileData],'write'); iPROFid = netcdf.inqDimID(nc,'iPROF'); netcdf.reDef(nc); %add dimension: iINTERPid = netcdf.defDim(nc,'iINTERP',1); %add variables: for ii=1:length(list1d); netcdf.defVar(nc,list1d{ii},'double',iPROFid); end; for ii=1:length(list2d); netcdf.defVar(nc,list2d{ii},'double',[iINTERPid iPROFid]); end; netcdf.endDef(nc); %fill variables: for ii=1:length(listAll); ncputvar(nc,listAll{ii},getfield(myVec,listAll{ii})); end; netcdf.close(nc); else; nc=netcdf([dirOut fileData],'write'); %add dimension: nc('iINTERP') = 1; %add variables: for ii=1:length(list1d); nc{list1d{ii}}=ncdouble('iPROF'); end; for ii=1:length(list2d); nc{list2d{ii}}=ncdouble('iPROF','iINTERP'); end; %fill variables: for ii=1:length(listAll); ncputvar(nc,listAll{ii},getfield(myVec,listAll{ii})); end; close(nc); end; MITprof/profiles_process_main_v2/profiles_isopycnal_interp.m0000644000435400001440000000477412152673561024440 0ustar gforgetusersfunction [profileCur]=profiles_isopycnal_interp(dataset,profileCur); %t_Err (s_Err) contains the depth inversion index (depth) that now need t be interpolated %interpolation for T : z_std=dataset.z_std; t_std=NaN*z_std; tE_std=t_std; if dataset.inclS; s_std=t_std; sE_std=t_std; end; z=profileCur.z; t=profileCur.t; if dataset.inclS; s=profileCur.s; end; t_ERR=profileCur.t_ERR; if dataset.inclS; s_ERR=profileCur.s_ERR; end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%SPEC STUFF if ~isempty(t)&length(find(~isnan(z.*t)))>1; tmp1=find( ~isnan(t) & ~isnan(z) ); %compact z_in=z(tmp1); t_in=t(tmp1); tE_in=t_ERR(tmp1); [z_in,tmp1]=sort(z_in); t_in=t_in(tmp1); tE_in=tE_in(tmp1);%sort tmp1=[find(z_in(1:end-1)~=z_in(2:end)) length(z_in)]; z_in=z_in(tmp1); t_in=t_in(tmp1); tE_in=tE_in(tmp1); %avoid duplicate if length(t_in)>5 %...expected to avoid isolated values t_std = interp1(z_in,t_in,z_std); tE_std = interp1(z_in,tE_in,z_std); end end%if ~isempty(t); t_std(find(isnan(t_std)))=dataset.fillval; profileCur.t_std=t_std; tE_std(find(isnan(tE_std)))=dataset.fillval; profileCur.tE_std=tE_std; %interpolation for S : %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%SPEC STUFF if dataset.inclS; if ~isempty(s)&length(find(~isnan(z.*s)))>1; tmp1=find( ~isnan(s) & ~isnan(z) ); %compact z_in=z(tmp1); s_in=s(tmp1); sE_in=s_ERR(tmp1); [z_in,tmp1]=sort(z_in); s_in=s_in(tmp1); sE_in=sE_in(tmp1);%sort tmp1=[find(z_in(1:end-1)~=z_in(2:end)) length(z_in)]; z_in=z_in(tmp1); s_in=s_in(tmp1); sE_in=sE_in(tmp1); %avoid duplicate if length(s_in)>5 s_std = interp1(z_in,s_in,z_std); sE_std = interp1(z_in,sE_in,z_std); end end%if ~isempty(s) s_std(find(isnan(s_std)))=dataset.fillval; profileCur.s_std=s_std; sE_std(find(isnan(sE_std)))=dataset.fillval; profileCur.sE_std=sE_std; end %interpolation for depth : z_std=dataset.z_std; depth_std=NaN*z_std; z=profileCur.z; depth=profileCur.depth; if ~isempty(depth)&length(find(~isnan(z.*depth)))>1; tmp1=find( ~isnan(depth) & ~isnan(z) ); %compact z_in=z(tmp1); depth_in=depth(tmp1); [z_in,tmp1]=sort(z_in); depth_in=depth_in(tmp1); %sort tmp1=[find(z_in(1:end-1)~=z_in(2:end)) length(z_in)]; z_in=z_in(tmp1); depth_in=depth_in(tmp1); %avoid duplicate if length(depth_in)>5 %...expected to avoid isolated values depth_std = interp1(z_in,depth_in,z_std); end end%if ~isempty(t); depth_std(find(isnan(depth_std)))=dataset.fillval; profileCur.depth_std=depth_std; MITprof/profiles_process_main_v2/profiles_prep_tests_cmpatlas.m0000644000435400001440000000562312152673561025124 0ustar gforgetusersfunction [MITprofCur]=profiles_prep_tests_cmpatlas(dataset,MITprofCur,atlas); % [MITprofCur]=profiles_prep_tests_cmpatlas(MITprofCur,atlas) % range tests based on comparison with the reference climatology % flag excessively large distance to climatologies to 5 % require gcmfaces % % set profilCur.t_test (and profilCur.s_test) following the code: % 0 = valid data % 1 = not enough data near standard level % 2 = absurd sal value % 3 = doubtful profiler (based on our own evaluations) % 4 = doubtful profiler (based on Argo grey list) % 5 = high climatology/atlas cost - all four of them % 6 = bad Pressure vector % % set MITprofCur.prof_Testim and MITprofCur.prof_Sestim as the nearest % climatological T/S profile % % global variable mygrid must be set. global mygrid nk=length(mygrid.RC); kk=ones(1,nk); np=length(MITprofCur.ii); pp=ones(np,1); ind2prof=sub2ind(size(atlas.T{1}),MITprofCur.ii*kk,MITprofCur.jj*kk,pp*[1:nk],MITprofCur.imonth*kk); isSal=isfield(MITprofCur,'prof_S'); warning('off','MATLAB:interp1:NaNinY'); for ff=1:length(atlas.T); t_equi=atlas.T{ff}(ind2prof);%collocate t_equi=interp1(-mygrid.RC',t_equi',MITprofCur.prof_depth)';%vert. interp. if ff==1; MITprofCur.prof_Testim=t_equi; t_cost=NaN*t_equi; end; tmp_cost=MITprofCur.prof_Tweight.*((MITprofCur.prof_T-t_equi).^2); t_cost( (isnan(t_cost)&~isnan(tmp_cost)) | (tmp_costthresholdVAL) ); MITprofCur.prof_Tflag(ii)=10*MITprofCur.prof_Tflag(ii)+5; if isSal; ii=find( (MITprofCur.prof_S~=MITprofCur.fillval)&(s_cost>thresholdVAL) ); MITprofCur.prof_Sflag(ii)=10*MITprofCur.prof_Sflag(ii)+5; end; %take account of the tests results by setting zero weight: MITprofCur.prof_Tweight(MITprofCur.prof_T==-9999|MITprofCur.prof_Tflag>0)=0; MITprofCur.prof_Testim(isnan(MITprofCur.prof_Testim))=-9999; if isSal; MITprofCur.prof_Sweight(MITprofCur.prof_S==-9999|MITprofCur.prof_Sflag>0)=0; MITprofCur.prof_Sestim(isnan(MITprofCur.prof_Sestim))=-9999; end; MITprof/profiles_process_main_v2/profiles_isopycnal_fields.m0000644000435400001440000000272612152673561024400 0ustar gforgetusersfunction []=profiles_isopycnal_fields(dataset); %1) compute density at depth levels (as in diags_COR1) %2) interpolate density to target grid (as in profiles_prep_weights & profiles_prep_tests_cmpatlas) if ~strcmp(dataset.coord,'sig0')&~strcmp(dataset.coord,'sig1'); error('not implemeneted yet'); end; gcmfaces_global; global atlas sigma; dirAtlases=[myenv.gcmfaces_dir 'sample_input/OCCAetcONv4GRID/']; atlasT=['T_OWPv1_M_eccollc_90x50_' dataset.coord '.bin']; atlasS=['S_OWPv1_M_eccollc_90x50_' dataset.coord '.bin']; atlasD=['D_OWPv1_M_eccollc_90x50_' dataset.coord '.bin']; sigmaT=['sigma_T_mad_feb2013_' dataset.coord '.bin']; sigmaS=['sigma_S_mad_feb2013_' dataset.coord '.bin']; nr=length(dataset.z_std); tmp1=read2memory([dirAtlases atlasT],[90 1170 nr 12]); tmp1(tmp1==0)=NaN; atlas.T{1}=convert2array(convert2gcmfaces(tmp1)); nr=length(dataset.z_std); tmp1=read2memory([dirAtlases atlasS],[90 1170 nr 12]); tmp1(tmp1==0)=NaN; atlas.S{1}=convert2array(convert2gcmfaces(tmp1)); tmp1=read2memory([dirAtlases atlasD],[90 1170 nr 12]); tmp1(tmp1==0)=NaN; atlas.D{1}=convert2array(convert2gcmfaces(tmp1)); nr=length(dataset.z_std); tmp1=read2memory([dirAtlases sigmaT],[90 1170 nr]); tmp1(tmp1==0)=NaN; sigma.T=convert2array(convert2gcmfaces(tmp1)); nr=length(dataset.z_std); tmp1=read2memory([dirAtlases sigmaS],[90 1170 nr]); tmp1(tmp1==0)=NaN; sigma.S=convert2array(convert2gcmfaces(tmp1)); mygrid.RC=-dataset.z_std;%negative sign follows from gcm convention : RC=-depth MITprof/profiles_process_main_v2/profiles_prep_write_nc.m0000644000435400001440000001075412365531346023711 0ustar gforgetusersfunction [varargout]=profiles_prep_write_nc(dataset,profileCur,mode,varargin); % [MITprofCur]=profiles_prep_write_nc(dataset,profileCur,mode,(MITprofCur)) % function used to write data in the MITprof netcdf format % % dataset : structure describing the dataset (generated by % profiles_prep_select) % profileCur : structure with profile data to record % mode : string describing the mode to be used % 'init' : initialize global variables % (in this mode, profileCur is not recorded) % 'add' : record the profile in the global variables % 'write' : write data from the global variables to the netcdf file % % Important: this function use global variables, that must not be changed % before the end of the writing process!! % dirOut=dataset.dirOut; fileOut=dataset.fileOut; fill_value_output=dataset.fillval; dmod=dataset.z_std; buffer_size=10000; nb_lev=length(dmod); nb_char=30; if fill_value_output~=-9999; fprintf('MITgcm assumes fill_value_output=-9999 \n'); return; end switch mode, case 'init', % init global variables MITprofCur=MITprof_struct(buffer_size,dataset); MITprofCur.num_cur_tmpfile=0; MITprofCur.np=0; %reset auxiliary files created during a previous computation: test0=dir([dataset.dirOut dataset.fileOut '*.mat']); if ~isempty(test0); system(['rm ' dataset.dirOut dataset.fileOut '*.mat']); end; varargout{1}=MITprofCur; case 'add', % retrieve buffer MITprofCur=varargin{1}; % number of profiles +1 pp=MITprofCur.np+1; MITprofCur.np=pp; % store profile data MITprofCur.prof_YYYYMMDD(pp)=profileCur.ymd; MITprofCur.prof_HHMMSS(pp)=profileCur.hms; MITprofCur.prof_descr{pp}=profileCur.pnum_txt; MITprofCur.prof_lon(pp)=profileCur.lon; MITprofCur.prof_lat(pp)=profileCur.lat; MITprofCur.prof_point(pp)=profileCur.point; MITprofCur.prof_basin(pp)=profileCur.basin; MITprofCur.prof_T(pp,:)=profileCur.t_std; MITprofCur.prof_Tflag(pp,:)=profileCur.t_test; MITprofCur.prof_Tweight(pp,:)=profileCur.t_w; MITprofCur.prof_Terr(pp,:)=profileCur.tE_std; MITprofCur.prof_Testim(pp,:)=profileCur.t_equi; if dataset.inclS; MITprofCur.prof_S(pp,:)=profileCur.s_std; MITprofCur.prof_Sflag(pp,:)=profileCur.s_test; MITprofCur.prof_Sweight(pp,:)=profileCur.s_w; MITprofCur.prof_Serr(pp,:)=profileCur.sE_std; MITprofCur.prof_Sestim(pp,:)=profileCur.s_equi; end; if ~strcmp(dataset.coord,'depth'); MITprofCur.prof_D(pp,:)=profileCur.depth_std; MITprofCur.prof_Destim(pp,:)=profileCur.depth_equi; end; % if buffer is full, save profiles in a .mat temporary file if pp>buffer_size-1, MITprofCur.prof_date=datenum(num2str(MITprofCur.prof_YYYYMMDD*1e6+MITprofCur.prof_HHMMSS),'yyyymmddHHMMSS'); num_cur_tmpfile=MITprofCur.num_cur_tmpfile+1; eval(['save ' dirOut '/' fileOut num2str(num_cur_tmpfile) '.mat MITprofCur' ]); MITprofCur=MITprof_struct(buffer_size,dataset); MITprofCur.num_cur_tmpfile=num_cur_tmpfile; MITprofCur.np=0; end; varargout{1}=MITprofCur; case 'write', % retrieve buffer MITprofCur=varargin{1}; % save profiles in buffer MITprofCur=MITprof_subset(MITprofCur,'list',1:MITprofCur.np); MITprofCur.prof_date=datenum(num2str(MITprofCur.prof_YYYYMMDD*1e6+MITprofCur.prof_HHMMSS),'yyyymmddHHMMSS'); num_cur_tmpfile=MITprofCur.num_cur_tmpfile+1; eval(['save ' dirOut '/' fileOut num2str(num_cur_tmpfile) '.mat MITprofCur' ]); % build the MITprof variable with all profiles MITprof_final=MITprof_struct(0,dataset); for cur_tmpfile=1:num_cur_tmpfile, eval(['load ' dirOut fileOut num2str(cur_tmpfile) '.mat;' ]); MITprof_final=MITprof_concat(MITprof_final,MITprofCur); end %write data to file: nb_prof=length(MITprof_final.prof_lon); if nb_prof~=0, MITprof_write([dirOut fileOut],MITprof_final); end % clean folders for cur_tmpfile=1:num_cur_tmpfile system(['rm -f ' dirOut '/' fileOut num2str(cur_tmpfile) '.mat;' ]); end end MITprof/profiles_process_main_v2/profiles_prep_convert.m0000644000435400001440000000236111551405734023547 0ustar gforgetusersfunction [profileCur]=profiles_prep_convert(dataset,profileCur); %[profileCur]=profiles_prep_convert(dataset,profileCur); % applies lat/lon/depth/temp conversions % to profileCur depending on dataset specs %check lat/lon ranges: profileCur.lonlatISbad=0; if profileCur.lat<-90|profileCur.lat>90; profileCur.lonlatISbad=1; warning('wrong latitude'); end; if profileCur.lon<-180|profileCur.lon>360; profileCur.lonlatISbad=1; warning('wrong longitude'); end; %fix lon range if necessary: if ~profileCur.lonlatISbad&profileCur.lon>180; profileCur.lon=profileCur.lon-360; end; if profileCur.lonlatISbad; profileCur.lon=0; profileCur.lat=-89.99; end; %convert pressure to depth (if necessary) if dataset.inclZ==0; p=profileCur.p; tmp1=find(~isnan(p)); if ~isempty(tmp1); p( tmp1 ) = sw_dpth(p(tmp1),profileCur.lat); end; profileCur.z=p; end %convert T in situ to T potential (if necessary) if dataset.TPOTfromTINSITU==1; tmpP=0.981*1.027*profileCur.z; tmpS=35*ones(size(profileCur.t)); tmpT=profileCur.t; tmpIND=find(tmpT~=dataset.fillval); if ~isempty(tmpIND) tmpT(tmpIND)=sw_ptmp(tmpS(tmpIND),tmpT(tmpIND),tmpP(tmpIND),0); end profileCur.t=tmpT; end MITprof/profiles_process_main_v2/profiles_isopycnal_z.m0000644000435400001440000000545012132776054023377 0ustar gforgetusersfunction [profileCur]=profiles_isopycnal_z(dataset,profileCur,choiceDensity); %aa=which('density'); if isempty(aa); addpath /data4/gforget/matlab_diags/TOOLS/DIVERS/; end; %aa=which('gamma_n'); if isempty(aa); addpath /data4/gforget/DIAG_ecco/TOOLS/gamma_n/gamma_ml/; end; kk=find(~isnan(profileCur.t.*profileCur.s.*profileCur.z)); if ~isempty(kk); if strcmp(choiceDensity,'gamma'); lon=profileCur.lon; lat=profileCur.lat; if lon<0; lon=lon+180; end; if (lon<0|lon>360|lat<-80|lat>64|length(kk)<3); profileCur.dens=NaN*profileCur.z; else; temp = sw_temp(profileCur.s(kk)',profileCur.t(kk)',profileCur.z(kk)',0); [g,dgl,dgh] = gamma_n(profileCur.s(kk)',temp,profileCur.z(kk)',profileCur.lon,profileCur.lat); g(find(g<-99))=NaN;%get rid of errors tmp1=NaN*profileCur.z; tmp1(kk)=g; g=tmp1;%complete profile profileCur.dens=g; end; else; [RHOP,RHOIS,RHOR] = density(profileCur.t(kk),profileCur.s(kk),profileCur.z(kk),1000); tmp1=NaN*profileCur.z; tmp1(kk)=RHOP; RHOP=tmp1;%complete profile tmp1=NaN*profileCur.z; tmp1(kk)=RHOIS; RHOIS=tmp1;%complete profile tmp1=NaN*profileCur.z; tmp1(kk)=RHOR; RHOR=tmp1;%complete profile if strcmp(choiceDensity,'sig0'); profileCur.dens=RHOP-1000; elseif strcmp(choiceDensity,'sig1'); profileCur.dens=RHOR-1000; elseif strcmp(choiceDensity,'insitu'); profileCur.dens=RHOIS-1000; else; fprintf('error in profiles_prep_switch2isopycnal\n'); return; end; end; profileCur.dens(find(~isreal(profileCur.dens)|~isfinite(profileCur.dens)))=NaN; else; profileCur.dens=NaN*profileCur.z; end; %replace z with density profileCur.depth=profileCur.z; profileCur.z=profileCur.dens; %check for density inversions: kk=find(~isnan(profileCur.dens.*profileCur.depth)); tmp_dens=profileCur.dens(kk); tmp_depth=profileCur.depth(kk); [tmp_depth,kk] = sort(tmp_depth); tmp_dens=tmp_dens(kk); if length(tmp_dens)>1; test0=100*length(find(diff(tmp_dens)<0))/(length(tmp_dens)-1); else; test0=100; end; %store in prof.t_ERR and s_ERR: profileCur.t_ERR=test0*ones(size(profileCur.t)); profileCur.s_ERR=profileCur.depth; %t_ERR and s_ERR will be interpolated if 0; %code to test the various computations kk=find(~isnan(profileCur.t.*profileCur.s.*profileCur.z)); [profileCur.dens_sig,profileCur.dens_insitu,profileCur.dens_sig1] = density(profileCur.t,profileCur.s,profileCur.z,1000); [g,dgl,dgh] = gamma_n(profileCur.s',profileCur.t',profileCur.z',profileCur.lon',profileCur.lat'); profileCur.dens_gamman=g'; figure; subplot(2,2,1); plot(profileCur.dens_insitu(kk),-profileCur.z(kk),'.-'); title('insitu'); subplot(2,2,2); plot(profileCur.dens_sig(kk),-profileCur.z(kk),'.-'); title('sig'); subplot(2,2,3); plot(profileCur.dens_sig1(kk),-profileCur.z(kk),'.-'); title('sig1'); subplot(2,2,4); plot(profileCur.dens_gamman(kk),-profileCur.z(kk),'.-'); title('gamman'); end; MITprof/profiles_process_main_v2/profiles_prep_load_fields.m0000644000435400001440000000646112365556400024342 0ustar gforgetusersfunction []=profiles_prep_load_fields(varargin); % []=profiles_prep_load_fields([loadFromMat,saveToMat]); % - object : load grid and atlas data to global variables % - optional inputs : % if loadFromMat=0 (default) then variables are loaded from gcmfaces/sample_input/ files % if loadFromMat=1 then variables are loaded from mat files prepared by users % if saveToMat=1 then variables are saved to mat files % - result consists of global variables : % mygrid : structure containing XC, YC, RAC and RC from the ECCOv4 grid % mytri : information used for delaunay triangulation % MYBASININDEX : basin index % atlas : T/S atlas in a structure format % atlas.T, atlas.S are monthly mean 3D T/S climatologies (OCCA by default) % sigma : T/S observational standard deviation in a structure format % sigma.T and sigma.S are 3D fields (updated Forget and Wunsch 2007 by default) % by assumption: the uncertainty fields contain non-zero values % (which avoid the complication of handling horiz interpolation here) % and we do not mask the data (the model will do this, given a mask) % - note : gcmfaces toolbox is required % % process arguments loadFromMat=0; if nargin==1, loadFromMat=varargin{1}; end saveToMat=0; if nargin==2, saveToMat=varargin{1}; end %set global variables gcmfaces_global; global mytri MYBASININDEX atlas sigma; % set directories: dirClim=myenv.MITprof_climdir; dirGrid=myenv.MITprof_griddir; %%%%%% part 1 : default usage %%%%%%% file_basin=[dirClim 'basin_masks_eccollc_90x50.bin']; file_atlasT=[dirClim 'T_OWPv1_M_eccollc_90x50.bin']; file_atlasS=[dirClim 'S_OWPv1_M_eccollc_90x50.bin']; file_varT=[dirClim 'sigma_T_mad_feb2013.bin']; file_varS=[dirClim 'sigma_S_mad_feb2013.bin']; if loadFromMat==0, % read grid : disp(['load grid from ' myenv.MITprof_griddir]); mygrid=[]; grid_load(dirGrid,5,'compact'); gcmfaces_bindata; mygrid=rmfield(mygrid,{'XG','YG','RAC','RAZ','DXC','DYC','DXG','DYG'}); mygrid=rmfield(mygrid,{'hFacC','hFacW','hFacS','Depth','AngleCS','AngleSN'}); mygrid=rmfield(mygrid,{'hFacCsurf','mskW','mskS','DRC','DRF','RF'}); MYBASININDEX=convert2array(read_bin(file_basin,1,0)); % read T/S Atlas disp(['load atlas from ' myenv.MITprof_climdir]); atlas=[]; fldT=mygrid.mskC; fldT(:)=0; fldS=fldT; for tt=1:12; fldT(:,:,:,tt)=read_bin(file_atlasT,tt).*mygrid.mskC; fldS(:,:,:,tt)=read_bin(file_atlasS,tt).*mygrid.mskC; end; atlas.T={convert2array(fldT)}; atlas.S={convert2array(fldS)}; % read T/S variance fields disp(['load sigma from ' myenv.MITprof_climdir]); sigma.T=convert2array(read_bin(file_varT)); sigma.S=convert2array(read_bin(file_varS)); end %%%%%% part 2 : custom usage %%%%%%% mat_grid=[dirGrid 'MITprof_grid.mat']; mat_clim=[dirClim 'MITprof_clim.mat']; if loadFromMat == 1 if exist(mat_clim,'file') & exist(mat_grid,'file'), % load grid, atlas and sigma load(mat_grid); load(mat_clim); return else error('matlab files could not be found. They need to be generated using profiles_prep_load_fields(1)'); end end; if saveToMat==1; disp('save fields') save(mat_grid,'mygrid','mytri','MYBASININDEX'); save(mat_clim,'atlas','sigma'); end; MITprof/profiles_process_main_v2/profiles_prep_locate.m0000644000435400001440000000126111550675152023336 0ustar gforgetusersfunction [MITprofCur]=profiles_prep_locate(MITprofCur); %[MITprofCur]=profiles_prep_locate(MITprofCur); % locate MITprofCur profiles on ecco-4g grid, and get month index % to do so, set the variables prof_point, prof_basin, ii, jj and imonth % of MITprofCur % % global variables mytri and MYBASININDEX must be set in gcmfaces global mytri MYBASININDEX MITprofCur.prof_point=gcmfaces_bindata(MITprofCur.prof_lon,MITprofCur.prof_lat); MITprofCur.prof_basin=MYBASININDEX(MITprofCur.prof_point); [MITprofCur.ii,MITprofCur.jj]=gcmfaces_bindata(MITprofCur.prof_lon,MITprofCur.prof_lat); MITprofCur.imonth=floor(MITprofCur.prof_YYYYMMDD/1e2)-1e2*floor(MITprofCur.prof_YYYYMMDD/1e4); MITprof/profiles_process_main_v2/profiles_prep_select.m0000644000435400001440000001426512365540307023354 0ustar gforgetusersfunction [dataset]=profiles_prep_select(datasetname,subset,varargin); %[dataset]=profiles_prep_select(datasetname,subset,'PropertyName',PropertyValue); % Specifies 'dataset' structure used as argument of % profiles_prep_main.m to process hydrographic data. % Contains a description of the data to process and processing options. % % datasetname: type of input data. specify which script will be used in % the folder profiles_IO_external to read the data: % ['profiles_read_' datasetname '.m'] % Can be 'argo','wod05','seals' or 'odv' % % subset: name of the dataset used in the output name. % gcmfaces_global; % vertical levels Z_STD=[5:10:185 200:20:500 550:50:1000 1100:100:6000]; %initialize empty data set description: dataset.name=datasetname; dataset.subset=subset; dataset.dirIn=''; dataset.fileInList={}; dataset.dirOut=''; dataset.fileOut=''; dataset.depthrange=[]; dataset.z_std=[]; dataset.inclZ=0;%0 means that only P is provided, which we will convert to depth dataset.inclT=0; dataset.inclS=0; dataset.inclU=0; dataset.inclV=0; dataset.inclPTR=0; dataset.inclSSH=0; dataset.fillval=-9999.; dataset.TPOTfromTINSITU=1;%1 means that only in situ T is provided, which we will convert to pot T dataset.coord='depth';%depth as a coordinate if myenv.verbose==2; fprintf(['by default, we assume that \n'... ' the data vertical coordinate is P \n' ... ' temperature data is in situ (rather than potential) \n' ... ' salinity data exists\n'... ' (you probably want to make sure about those \n things when processing a new data set). \n\n\n']); end; %================================================================================= switch datasetname case 'argo', %Argo profiles: %-------------- dataset.dirIn='profiles_samples/argo_sample/'; dataset.fileInList=dir([dataset.dirIn '*.nc']); dataset.dirOut='profiles_samples/argo_sample/processed/'; dataset.fileOut=['argo_' subset]; dataset.depthrange=[0 2000]; dataset.inclT=1; dataset.inclS=1; %================================================================================= case 'wod05', %data from the World Ocean Data Base 2005: %----------------------------------------- wod_decade=subset(1:2); wod_instr_code=subset(3:end); if strcmp(wod_decade,'00'); wod_decade2=['20' wod_decade 's']; else; wod_decade2=['19' wod_decade 's']; end; dataset.dirIn='profiles_samples/wod05_sample/'; dataset.fileInList=dir([dataset.dirIn '*' wod_instr_code '*']); dataset.dirOut='profiles_samples/wod05_sample/processed/'; dataset.fileOut=['wod05_' wod_instr_code '_' wod_decade2]; dataset.inclZ=1; dataset.inclT=1; dataset.inclS=1; if strcmp(wod_instr_code,'OSD')|strcmp(wod_instr_code,'CTD')|strcmp(wod_instr_code,'OTH'); dataset.depthrange=[0 5400]; elseif strcmp(wod_instr_code,'PFL'); dataset.depthrange=[0 2000]; elseif strcmp(wod_instr_code,'MBT'); dataset.depthrange=[0 300]; dataset.inclS=0; elseif strcmp(wod_instr_code,'XBT'); dataset.depthrange=[0 1000]; dataset.inclS=0; else; error('un-supported wod instrument code'); end;%if strfind(wod_instr_code... %================================================================================= case 'seals', % seal data in ARGO format dataset.dirIn='profiles_samples/seals_sample/'; dataset.fileInList=dir([dataset.dirIn '*' subset '*.nc']); dataset.dirOut='profiles_samples/seals_sample/processed/'; dataset.fileOut=[datasetname '_' subset '_MITprof']; dataset.depthrange=[0 2000]; dataset.inclT=1; dataset.inclS=1; %================================================================================= case 'odv', % seal data in odv format dataset.dirIn='profiles_samples/odv_sample/'; dataset.fileInList=dir([dataset.dirIn '*.txt']); dataset.dirOut='profiles_samples/odv_sample/processed/'; dataset.fileOut=[subset '_MITprof']; dataset.depthrange=[0 2000]; dataset.inclZ=1; dataset.inclT=1; dataset.inclS=1; %================================================================================= otherwise error('un-supported data set'); end;%if strcmp(datasetname,'wod05') % overwrite properties using arguments if nargin>2 if mod(nargin,2)==1, error('problem in argument list'); end for kk=1:(nargin-1)/2, PropertyName=varargin{(kk-1)*2+1}; PropertyValue=varargin{kk*2}; dataset=setfield(dataset,PropertyName,PropertyValue); end; end %if not done yet, set the depth levels now: if isempty(dataset.z_std); kk=find(Z_STD>=dataset.depthrange(1)&Z_STD<=dataset.depthrange(2)); dataset.z_std=Z_STD(kk); end; %set z_top, z_bot: z_std=dataset.z_std; tmp1=(z_std(2:end)+z_std(1:end-1))/2; dataset.z_top=[z_std(1)-(z_std(2)-z_std(1))/2 tmp1]; dataset.z_bot=[tmp1 z_std(end)+(z_std(end)-z_std(end-1))/2]; % determine the output file name, and try to delete it [pathstr, name, ext] = fileparts([dataset.dirOut dataset.fileOut]); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end if isempty(ext) | ~strcmp(ext,'.nc'), ext='.nc'; end dataset.fileOut=[name ext]; if exist([dataset.dirOut dataset.fileOut],'file'), delete([dataset.dirOut dataset.fileOut]); end %create output directory if necessary: tmp1=dir(dataset.dirOut); if isempty(tmp1); eval(['mkdir ' dataset.dirOut ]); end; if myenv.verbose; fprintf(['\n\n generating file : ' dataset.dirOut dataset.fileOut '.nc \n']); fprintf(['\n depth range : ' num2str(dataset.depthrange) ' \n']); fprintf([' compute T pot from T in-situ : ' num2str(dataset.TPOTfromTINSITU) ' \n']); fprintf([' compute Z from P : ' num2str(dataset.inclZ) ' \n']); fprintf([' include T : ' num2str(dataset.inclT) ' \n']); fprintf([' include S : ' num2str(dataset.inclS) ' \n\n']); end; MITprof/profiles_process_main_v2/profiles_prep_main.m0000644000435400001440000001220612365540307023012 0ustar gforgetusersfunction profiles_prep_main(dataset) % profiles_prep_main(dataset) % % main routine to process hydrographic data set : % 1) read, resample vertically and save hydrographic data in the MITprof netcdf format % 2) set quality flag, colocated climatologial data and weights for each profile % % input: dataset is a struct generated by profiles_prep_select, and % describing the dataset that must be processed, and processing options. % % Important: some important variables are set as global: % mygrid mytri MYBASININDEX atlas sigma % These variables are loaded by the function profiles_prep_load_fields % However, if mygrid is non-empty, no attempt to reload these variables will % be made. % gcmfaces_global; global mytri MYBASININDEX atlas sigma global useNativeMatlabNetcdf if isempty(myenv.verbose), myenv.verbose=0; end if isempty(mygrid) | isempty(mytri) | isempty(MYBASININDEX) | isempty(atlas) | isempty(sigma), profiles_prep_load_fields; end if isempty(useNativeMatlabNetcdf), useNativeMatlabNetcdf = ~isempty(which('netcdf.open')); end %% STEP 1: read, resample vertically and save hydrographic data in the MITprof netcdf format if myenv.verbose; disp('step 1: convert into MITprof netcdf format'); end % determine the full output file name [pathstr, name, ext] = fileparts([dataset.dirOut dataset.fileOut]); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end if isempty(ext) | ~strcmp(ext,'.nc'), ext='.nc'; end dataset.fileOut=[name ext]; %get the list of files to be treated : nfiles=length(dataset.fileInList); if nfiles==0, disp('no files to process'); return, end % init global variables used to store temporary loaded profiles MITprofCur=profiles_prep_write_nc(dataset,[],'init'); % main loop for nf=1:nfiles % FILE LOOP if myenv.verbose & mod(nf,10)==0, fprintf('%s : %04d --> %04d \n',dataset.name,nf,nfiles); end; % load file information: eval(['dataset=profiles_read_' dataset.name '(dataset,nf,0);']); % extract and process individual profiles nprofiles=dataset.nprofiles; for np=1:nprofiles; if myenv.verbose & mod(np,100)==0, fprintf('\t : %04d --> %04d\n',np,nprofiles); end % read 1 profile: eval(['profileCur=profiles_read_' dataset.name '(dataset,nf,np);']); if isempty(profileCur), continue, end %conversions of p->z, Tinsitu->Tpot, and 0-360 lon to -180+180 lon: profileCur=profiles_prep_convert(dataset,profileCur); %interpolate to standard levels: if strcmp(dataset.coord,'depth'); profileCur=profiles_prep_interp(dataset,profileCur); else; %switch to isopycnal coordinate: profileCur=profiles_isopycnal_z(dataset,profileCur,dataset.coord); profileCur=profiles_isopycnal_interp(dataset,profileCur); end; %placeholders: profileCur.point=0; profileCur.basin=0; profileCur.t_equi=0; profileCur.t_w=0; if ~strcmp(dataset.coord,'depth'); profileCur.depth_equi=0; end; if dataset.inclS; profileCur.s_equi=0; profileCur.s_w=0; end; %(the corresponding arrays will be filled in %profiles_prep_tests/part2 and profiles_prep_weights) %carry basic tests: profileCur=profiles_prep_tests_basic(dataset,profileCur); %store/write results in global variables (and in .mat files if buffer is full): MITprofCur=profiles_prep_write_nc(dataset,profileCur,'add',MITprofCur); end % LOCATION LOOP end % FILE LOOP % write profiles in the MITprof netcdf file profiles_prep_write_nc(dataset,profileCur,'write',MITprofCur); if ~exist([dataset.dirOut dataset.fileOut],'file'), return, end %% STEP 2: set quality flag, colocated climatologial data and weights for each profile if myenv.verbose; disp('step 2: weights and tests'); end %test whether gcmfaces package is in the path... gcmfacesISavailable=~isempty(which('gcmfaces')); if ~gcmfacesISavailable; error('gcmfaces absent of matlab path => no atlas or weights were included'); end %load standardized data set: MITprofCur=MITprof_load([dataset.dirOut dataset.fileOut]); %locate profile on grid: MITprofCur=profiles_prep_locate(MITprofCur); if ~strcmp(dataset.coord,'depth'); profiles_isopycnal_fields(dataset); end; if ~strcmp(dataset.coord,'depth'); MITprofCur.prof_Terr(:)=0; MITprofCur.prof_Serr(:)=0; end; %instrumental + representation error profile: MITprofCur=profiles_prep_weights(dataset,MITprofCur,sigma); %carry tests vs atlases: MITprofCur.fillval=dataset.fillval; [MITprofCur]=profiles_prep_tests_cmpatlas(dataset,MITprofCur,atlas); %overwrite file with completed arrays: MITprof_write([dataset.dirOut dataset.fileOut],MITprofCur); %specify atlas names: ncid=ncopen([dataset.dirOut dataset.fileOut],'write'); ncaddAtt(ncid,'prof_Testim','long_name','pot. temp. atlas (OCCA | PHC in arctic| WOA in marginal seas)'); ncaddAtt(ncid,'prof_Sestim','long_name','salinity atlas (OCCA | PHC in arctic| WOA in marginal seas)'); ncclose(ncid); if ~strcmp(dataset.coord,'depth'); mygrid=[]; atlas=[]; sigma=[]; end; MITprof/profiles_process_main_v2/profiles_prep_tests_basic.m0000644000435400001440000000433612151727245024377 0ustar gforgetusersfunction [profileCur]=profiles_prep_tests_basic(dataset,profileCur); % [profileCur]=profiles_prep_tests_basic(dataset,profileCur) % basic range and resolution tests % % set profilCur.t_test (and profilCur.s_test) following the code: % 0 = valid data % 1 = not enough data near standard level % 2 = absurd sal value % 3 = doubtful profiler (based on our own evaluations) % 4 = doubtful profiler (based on Argo grey list) % 5 = high climatology/atlas cost - all four of them % 6 = bad Pressure vector % profileCur.t_test=zeros(size(profileCur.t_std)); profileCur.s_test=profileCur.t_test; %test for 'not enough data near standard level' tmp1=ones(size(profileCur.z))'*dataset.z_top-profileCur.z'*ones(size(dataset.z_top)); tmp2=ones(size(profileCur.z))'*dataset.z_bot-profileCur.z'*ones(size(dataset.z_bot)); tmp1=tmp1<0; tmp2=tmp2>=0; tmp3=sum(tmp1.*tmp2,1); profileCur.t_test((tmp3<=0)&(profileCur.t_std~=dataset.fillval))=1; if dataset.inclS; profileCur.s_test((tmp3<=0)&(profileCur.s_std~=dataset.fillval))=1; end; %test for "absurd" salinity values : if dataset.inclS; profileCur.s_test(find( (profileCur.s_std>42)&(profileCur.s_std~=dataset.fillval) ))=2; profileCur.s_test(find( (profileCur.s_std<25)&(profileCur.s_std~=dataset.fillval) ))=2; end; %bad pressure flag: if profileCur.PorZisBAD; profileCur.t_test(:)=10*profileCur.t_test(:)+6; if dataset.inclS; profileCur.s_test(:)=10*profileCur.s_test(:)+6; end; end; if isfield(profileCur,'DATA_MODE')&isfield(dataset,'greyList'); test1=strcmp(profileCur.DATA_MODE,'R');%is real time profile test2=sum(strcmp(dataset.greyList.pnum,profileCur.pnum_txt));%is in grey list if test1&test2; II=find(strcmp(dataset.greyList.pnum,profileCur.pnum_txt)); for ii=II; time0=datenum(dataset.greyList.start{ii}); timeP=datenum(num2str(profileCur.ymd*1e6+profileCur.hms),'yyyymmddHHMMSS'); if (time01; tmp1=find( ~isnan(t) & ~isnan(z) ); %compact z_in=z(tmp1); t_in=t(tmp1); tE_in=t_ERR(tmp1); [z_in,tmp1]=sort(z_in); t_in=t_in(tmp1); tE_in=tE_in(tmp1);%sort tmp1=[find(z_in(1:end-1)~=z_in(2:end)) length(z_in)]; z_in=z_in(tmp1); t_in=t_in(tmp1); tE_in=tE_in(tmp1); %avoid duplicate if length(t_in)>5 %...expected to avoid isolated values t_std = interp1(z_in,t_in,z_std); tE_std = interp1(z_in,tE_in,z_std); end end%if ~isempty(t); t_std(find(isnan(t_std)))=dataset.fillval; profileCur.t_std=t_std; tE_std(find(isnan(tE_std)))=dataset.fillval; profileCur.tE_std=tE_std; %interpolation for S : if dataset.inclS; if ~isempty(s)&length(find(~isnan(z.*s)))>1; tmp1=find( ~isnan(s) & ~isnan(z) ); %compact z_in=z(tmp1); s_in=s(tmp1); sE_in=s_ERR(tmp1); [z_in,tmp1]=sort(z_in); s_in=s_in(tmp1); sE_in=sE_in(tmp1);%sort tmp1=[find(z_in(1:end-1)~=z_in(2:end)) length(z_in)]; z_in=z_in(tmp1); s_in=s_in(tmp1); sE_in=sE_in(tmp1); %avoid duplicate if length(s_in)>5 s_std = interp1(z_in,s_in,z_std); sE_std = interp1(z_in,sE_in,z_std); end end%if ~isempty(s) s_std(find(isnan(s_std)))=dataset.fillval; profileCur.s_std=s_std; sE_std(find(isnan(sE_std)))=dataset.fillval; profileCur.sE_std=sE_std; end MITprof/profiles_process_main_v2/profiles_prep_weights.m0000644000435400001440000000246011550672616023545 0ustar gforgetusersfunction [MITprofCur]=profiles_prep_weights(dataset,MITprofCur,sigma); %[MITprofCur]=profiles_prep_weights(dataset,MITprofCur,sigma); % Attributes least square weights to MITprofCur % based upon dataset specs, instrumental and % representation error estimates % %by assumption: % neither the representation error fields (sigma.T and sigma.S) % nor the data is 'land-masked'. And sigma.T/S>0 everywhere. % % global variable mygrid must be set. global mygrid nk=size(sigma.T,3); kk=ones(1,nk); np=length(MITprofCur.ii); pp=ones(np,1); ind2prof=sub2ind(size(sigma.T),MITprofCur.ii*kk,MITprofCur.jj*kk,pp*[1:nk]); %collocate sigma.T to profiles locations: sig_in=sigma.T(ind2prof); %interpolate in the vertical: sig_out=interp1(-mygrid.RC',sig_in',MITprofCur.prof_depth)'; %add instrumental error and compute weight: sig_instr=MITprofCur.prof_Terr; sig_instr(sig_instr==dataset.fillval)=0; MITprofCur.prof_Tweight=1./(sig_out.^2+sig_instr.^2); if dataset.inclS; %collocate sigma.S to profiles locations: sig_in=sigma.S(ind2prof); %interpolate in the vertical: sig_out=interp1(-mygrid.RC',sig_in',MITprofCur.prof_depth)'; %add instrumental error and compute weight: sig_instr=MITprofCur.prof_Serr; sig_instr(sig_instr==dataset.fillval)=0; MITprofCur.prof_Sweight=1./(sig_out.^2+sig_instr.^2); end; MITprof/MITprof_global.m0000644000435400001440000000261112365556377015016 0ustar gforgetusersfunction []=MITprof_global(varargin); %object: take care of path and global variables (mygrid and mitprofenv), % and sends global variables to caller routine workspace %notes: - in any call, if this has not yet been done, % this routine also adds MITprof subdirectories % to the matlab path, and it defines mitprofenv. % - this routine replaces MITprof_path %get/define global variables: gcmfaces_global; %take care of path: test0=which('MITprof_load.m'); if isempty(test0); test0=which('MITprof_global.m'); ii=strfind(test0,filesep); mydir=test0(1:ii(end)); % addpath(fullfile(mydir)); addpath(fullfile(mydir,'profiles_process_main_v2')); addpath(fullfile(mydir,'profiles_IO_v2')); addpath(fullfile(mydir,'profiles_IO_external')); addpath(fullfile(mydir,'profiles_misc')); addpath(fullfile(mydir,'profiles_stats')); addpath(fullfile(mydir,'ecco_v4')); addpath(fullfile(mydir,'profiles_devel')); end; %environment variables: if ~isfield(myenv,'MITprof_dir'); test0=which('MITprof_global.m'); ii=strfind(test0,filesep); myenv.MITprof_dir=test0(1:ii(end)); myenv.MITprof_griddir=fullfile(myenv.gcmfaces_dir,'sample_input','GRIDv4',filesep); myenv.MITprof_climdir=fullfile(myenv.gcmfaces_dir,'sample_input','OCCAetcONv4GRID',filesep); end; %send to workspace: evalin('caller','global mygrid mitprofenv'); MITprof/profiles_process_example.m0000644000435400001440000000136011550677237017244 0ustar gforgetusers %% select the data source (and specific params) => wod05 sample cd /Users/roquet/Documents/MATLAB/MITprof dataset=profiles_prep_select('wod05','90CTD'); profiles_prep_main(dataset); fprintf(['\n\n wod05 sample -- done -- \n\n']); %% select the data source (and specific params) => argo sample cd /Users/roquet/Documents/MATLAB/MITprof dataset=profiles_prep_select('argo','indian'); profiles_prep_main(dataset); fprintf(['\n\n argo sample -- done -- \n\n']); %% select the data source (and specific params) => odv sample cd /Users/roquet/Documents/MATLAB/MITprof dataset=profiles_prep_select('odv','ODVcompact_sample'); profiles_prep_main(dataset); fprintf(['\n\n odv sample -- done -- \n\n']); %% fprintf('\n basic MITprof test: completed. \n'); MITprof/profiles_IO_external/0000755000435400001440000000000012375431055016076 5ustar gforgetusersMITprof/profiles_IO_external/profiles_read_wod05.m0000644000435400001440000001413611561330057022111 0ustar gforgetusersfunction [varargout]=profile_read_wod05(dataset,nf,m,varargin); % read hydrographic data in the WOD05 csv format % return the m-th profile from the nf-th file referenced in % dataset.fileInList. % % if m=0 : % return the information on the nf-th file referenced in % dataset.fileInList. % dataset=profile_read_wod05(dataset,nf,0); % dataset.nprofiles: number of profiles in the nf-th file % dataset.index_prof: list of position number for each profile block % % if m~=0 : % return the m-th profile from the nf-th file referenced in % dataset.fileInList. % profileCur=profile_read_odv(dataset,nf,m); % % profileCur = % pnum_txt: 'WOD-CTD//29-1103//4.' % ymd: 19900210 % hms: 82659 % lat: 40.94 % lon: 2.6467 % direc: 2 % PorZisBAD: 0 % t: [1x998 double] % s: [1x998 double] % z: [1x998 double] % t_ERR: [1x998 double] % s_ERR: [1x998 double] fileIn=[dataset.dirIn dataset.fileInList(nf).name]; instrType=dataset.subset(3:end); if m==0; % return the number of profiles in the file % also build an index of first-line prosition of profiles: index_prof fid_cur=fopen(fileIn,'rt'); prof_cur=0;index_prof=[]; while ~feof(fid_cur); line_cur = fgetl(fid_cur); if ~isempty(findstr(line_cur,'NODC Cruise ID')); prof_cur=prof_cur+1; index_prof(end+1)=ftell(fid_cur)-length(line_cur)-1; %to jump over second possible occurence of NODC Cruise ID while isempty(findstr(line_cur,'END OF VARIABLES SECTION')); line_cur = fgetl(fid_cur); end; end; end; fclose(fid_cur); dataset.nprofiles=prof_cur; dataset.index_prof=index_prof; varargout(1) = {dataset}; else;%if m==0; % index_prof: position of beginning of each profile block in the .txt index_prof=dataset.index_prof; fid_cur=fopen(fileIn,'rt'); fseek(fid_cur,index_prof(m),'bof'); data_cur=NaN*zeros(10000,3); %array that is used to store one profile line_cur = fgetl(fid_cur); while isempty(findstr(line_cur,'NODC Cruise ID')); line_cur = fgetl(fid_cur); end; tmp1=findstr(line_cur,',,'); pnum_txt=['WOD-' instrType '//' deblank(line_cur(tmp1(1)+2:tmp1(2)-1))]; probe_type='-1'; Time=12.0; lon=[]; lat=[]; Year=[]; Month=[]; Day=[]; while isempty(findstr(line_cur,'VARIABLES')); line_cur = fgetl(fid_cur); var_cur=textscan(line_cur,'%s','delimiter',','); var_cur=var_cur{1}; if ~isempty(findstr(cell2mat(var_cur(1)),'Latitude')); lat=str2num(cell2mat(var_cur(3))); end; if ~isempty(findstr(cell2mat(var_cur(1)),'Longitude')); lon=str2num(cell2mat(var_cur(3))); end; if ~isempty(findstr(cell2mat(var_cur(1)),'Year')); Year=str2num(cell2mat(var_cur(3))); end; if ~isempty(findstr(cell2mat(var_cur(1)),'Month')); Month=str2num(cell2mat(var_cur(3))); end; if ~isempty(findstr(cell2mat(var_cur(1)),'Day')); Day=str2num(cell2mat(var_cur(3))); end; if ~isempty(findstr(cell2mat(var_cur(1)),'Time')); Time=str2num(cell2mat(var_cur(3))); end; if ~isempty(findstr(cell2mat(var_cur(1)),'probe_type')); probe_type=cell2mat(var_cur(3)); end; end; %case when necessary information missing: put dummy info if isempty(lon)|isempty(lat)|isempty(Year)|isempty(Month)|isempty(Day) lat=-89.9; lon=0.1; Year=1800; Month=1; Day=1; elseif Day==0; lat=-89.9; lon=0.1; Year=1800; Month=1; Day=1; end; if lon < 0; lon=lon+360;end; pnum_txt=[pnum_txt '//' deblank(probe_type)]; var_cur=textscan(line_cur,'%s','delimiter',','); var_cur=var_cur{1}; v_cur=[]; for ii=1:length(var_cur); tmp1=cell2mat(var_cur(ii)); if ~isempty(findstr(tmp1,'Depth')); v_cur=[v_cur; [1 ii]]; end; if ~isempty(findstr(tmp1,'Temperatur')); v_cur=[v_cur; [2 ii]]; end; if ~isempty(findstr(tmp1,'Salinity')); v_cur=[v_cur; [3 ii]]; end; end; line_cur = fgetl(fid_cur); line_cur = fgetl(fid_cur); data_tmp=cell2mat(textscan(line_cur,'%f','delimiter',',','treatAsEmpty',{'Prof-Flag'})); qc_cast=zeros(1,3); %get cast qc?? qc_cast(v_cur(:,1))=data_tmp(v_cur(:,2)+1)'; qc_cast=1*(qc_cast==2|qc_cast==3|qc_cast==9); %if ~isempty(find(qc_cast>0)); fprintf(['cast qc: ' num2str(qc_cast) ' for ' fileIn ' m=' num2str(m) '\n']); end; % data_cur(:)=NaN; line_cur = fgetl(fid_cur); count_cur=1; data_tmp=cell2mat(textscan(line_cur,'%f','delimiter',',','treatAsEmpty',{'---.---','**********'})); while ~isempty(data_tmp); %store data: data_cur(count_cur,v_cur(:,1))=data_tmp(v_cur(:,2))'; %apply loc and global QC: qc_loc=zeros(1,3); qc_loc(v_cur(:,1))=data_tmp(v_cur(:,2)+1)'; qc_bad=find(qc_loc(v_cur(:,1))>0|qc_cast(v_cur(:,1))>0); data_cur(count_cur,v_cur(qc_bad,1))=NaN; %read the next line: line_cur = fgetl(fid_cur); count_cur=count_cur+1; data_tmp=cell2mat(textscan(line_cur,'%f','delimiter',',','treatAsEmpty',{'---.---','**********'})); end fclose(fid_cur); z=data_cur(1:count_cur-1,1); t=data_cur(1:count_cur-1,2); s=data_cur(1:count_cur-1,3); t_ERR=zeros(size(t)); s_ERR=t_ERR; z_ERR=[]; ymd=1e4*Year+1e2*Month+Day; tmp1=(Time-floor(Time))*3600; tmp2=floor(tmp1-floor(tmp1/60)*60); tmp1=floor(tmp1/60); hms=1e4*floor(Time)+1e2*tmp1+tmp2; direc=2; PorZisBAD=0; profileCur.pnum_txt=pnum_txt; profileCur.ymd=ymd; profileCur.hms=hms; profileCur.lat=lat; profileCur.lon=lon; profileCur.direc=direc; profileCur.PorZisBAD=PorZisBAD; profileCur.t=t'; profileCur.s=s'; profileCur.z=z'; profileCur.t_ERR=t_ERR'; profileCur.s_ERR=s_ERR'; profileCur.z_ERR=z_ERR'; %by convention profileCur.z etc are line vectors varargout = {profileCur}; end; MITprof/profiles_IO_external/profiles_read_argo.m0000644000435400001440000001437212151772536022115 0ustar gforgetusersfunction [varargout]=profile_read_argo(dataset,nf,m,varargin); % read hydrographic data in the ARGO netcdf format % return the m-th profile from the nf-th file referenced in % dataset.fileInList. % % if m=0 : % dataset=profile_read_argo(dataset,nf,0); % dataset.nprofiles: number of profiles in the nf-th file % dataset.data_argo: argo data in a struct variable % % if m~=0 : % profileCur=profile_read_argo(dataset,nf,m); % % profileCur = (m-th profile of nf-th file) % pnum_txt: '5900841' % ymd: 20060101 % hms: 3207 % lat: -46.709 % lon: 137.501 % direc: 1 % t: [1x115 single] % s: [1x115 single] % p: [1x115 single] % t_ERR: [1x115 single] % s_ERR: [1x115 single] % PorZisBAD: 0 % fileIn=[dataset.dirIn dataset.fileInList(nf).name]; if m==0; % return the number of profile. %get the number of profiles: list_var={'JULD','LATITUDE','LONGITUDE','DIRECTION','PLATFORM_NUMBER','DATA_MODE',... 'PRES_ADJUSTED_QC','PRES_QC','TEMP_ADJUSTED_QC','TEMP_QC','PSAL_ADJUSTED_QC','PSAL_QC'}; argo_data=[]; for ii=1:length(list_var), ncload(fileIn,list_var{ii}); data=eval(list_var{ii}); if ~isempty(data); nc=ncopen(fileIn); FillVal=ncgetFillVal(nc,list_var{ii}); ncclose(nc); if ischar(FillVal), data(strcmp(data,FillVal))=' '; else data(data==FillVal)=NaN; end end argo_data=setfield(argo_data,list_var{ii},data); end list_var={'PRES_ADJUSTED','PRES','TEMP_ADJUSTED','TEMP','TEMP_ADJUSTED_ERROR',... 'PSAL_ADJUSTED','PSAL','PSAL_ADJUSTED_ERROR'}; for ii=1:length(list_var), ncload(fileIn,list_var{ii}); data=double(eval(list_var{ii})); if ~isempty(data); nc=ncopen(fileIn); FillVal=ncgetFillVal(nc,list_var{ii}); ncclose(nc); data(data==FillVal)=NaN; end; argo_data=setfield(argo_data,list_var{ii},data); end dataset.argo_data=argo_data; dataset.nprofiles = length(JULD); if ~isfield(dataset,'greyList'); if ~isempty(dir([dataset.dirIn '../../ar_greylist.txt'])); fidgrey=fopen([dataset.dirIn '../../ar_greylist.txt'],'rt'); tmp1=fgetl(fidgrey); greylist=[]; ii=0; while ~feof(fidgrey); tmp1=fgetl(fidgrey); tmp2=strfind(tmp1,','); cur_pnum=double(tmp1(1:tmp2(1)-1)); cur_pnum=cur_pnum(find(cur_pnum~=0&cur_pnum~=32)); cur_pnum=char(cur_pnum); date_ref=double(tmp1(tmp2(2)+1:tmp2(3)-1)); date_ref=date_ref(find(date_ref~=0&date_ref~=32)); date_ref=char(date_ref); date_ref=[str2num(date_ref(1:4)) str2num(date_ref(5:6)) str2num(date_ref(7:8)) 0 0 0]; vnam=tmp1(tmp2(1)+1:tmp2(2)-1); ii=ii+1; greylist(ii).pnum=cur_pnum; greylist(ii).start=date_ref; greylist(ii).vnam=vnam; end; fclose(fidgrey); dataset.greyList.pnum={greylist(:).pnum}; dataset.greyList.start={greylist(:).start}; dataset.greyList.vnam={greylist(:).vnam}; else; dataset.greyList.pnum=[]; dataset.greyList.start=[]; dataset.greyList.vnam=[]; end; end; varargout{1}=dataset; else;%if m==0; % load data argo_data=dataset.argo_data; %date, position, etc juld=argo_data.JULD(m)+datenum(1950,1,1); [Y, M, D, H, MN, S] = datevec(juld); ymd=Y*1e4+M*1e2+D; hms=H*1e4+MN*1e2+S; lat=argo_data.LATITUDE(m); lon=argo_data.LONGITUDE(m); if lon < 0; lon=lon+360;end; direction=argo_data.DIRECTION(m); direc=0; if(direction=='A');direc=1;end; if(direction=='D');direc=2;end pnum_txt=deblank(argo_data.PLATFORM_NUMBER(m,:)); pnum_txt=pnum_txt(ismember(pnum_txt,'0123456789')); pnum=str2num(pnum_txt); if isempty(pnum_txt); pnum_txt='9999'; pnum=9999; disp(['no name for profile ' num2str(m)]); end; % pressure data p=argo_data.PRES_ADJUSTED(m,:); p_QC=argo_data.PRES_ADJUSTED_QC(m,:); if all(isnan(p)), p=argo_data.PRES(m,:); p_QC=argo_data.PRES_QC(m,:); end p_QC(isnan(p))='5'; for n=1:length(p)-1; % doubles tmp1=find(p(n+1:end)==p(n)); p(n+tmp1)=NaN; p_QC(n+tmp1)='5'; end bad_P=0; tmp1=find(p_QC=='4'); if(length(tmp1)<=5); %get rid of these few bad points and keep the profile p(tmp1)=NaN;p_QC(tmp1)='5'; else; %flag the profile (will be masked in the main file) %but keep the bad points (to interp and be able to CHECK) bad_P=1; end; % temperature data t=argo_data.TEMP_ADJUSTED(m,:); t_QC=argo_data.TEMP_ADJUSTED_QC(m,:); t_ERR=argo_data.TEMP_ADJUSTED_ERROR(m,:); t_ERR(isnan(t_ERR))=0; if all(isnan(t)), t=argo_data.TEMP(m,:); t_QC=argo_data.TEMP_QC(m,:); end %accomodate files that have no salinity if isempty(argo_data.PSAL); argo_data.PSAL=NaN*argo_data.TEMP; argo_data.PSAL_QC=char(32*ones(size(argo_data.TEMP_ADJUSTED_QC))); argo_data.PSAL_ADJUSTED=NaN*argo_data.TEMP; argo_data.PSAL_ADJUSTED_ERROR=NaN*argo_data.TEMP; argo_data.PSAL_ADJUSTED_QC=char(32*ones(size(argo_data.TEMP_ADJUSTED_QC))); end; % salinity data s=argo_data.PSAL_ADJUSTED(m,:); s_QC=argo_data.PSAL_ADJUSTED_QC(m,:); s_ERR=argo_data.PSAL_ADJUSTED_ERROR(m,:); s_ERR(isnan(s_ERR))=0; if all(isnan(s)), s=argo_data.PSAL(m,:); s_QC=argo_data.PSAL_QC(m,:); end if isnan(t(1)); %this file does not contain temperature data... t=NaN*p; t_ERR=0*p; else; t(~ismember(t_QC,'12'))=NaN; end; if isnan(s(1)); %this file does not contain salinity data... s=NaN*p; s_ERR=0*p; else; s(~ismember(s_QC,'12'))=NaN; end; profileCur.pnum_txt=pnum_txt; profileCur.ymd=ymd; profileCur.hms=hms; profileCur.lat=lat; profileCur.lon=lon; profileCur.direc=direc; profileCur.t=t; profileCur.s=s; profileCur.p=p; profileCur.t_ERR=t_ERR; profileCur.s_ERR=s_ERR; profileCur.PorZisBAD=bad_P; profileCur.DATA_MODE=argo_data.DATA_MODE(m); varargout = {profileCur}; end; MITprof/profiles_IO_external/profiles_read_odv.m0000644000435400001440000001461112266602313021741 0ustar gforgetusersfunction [varargout]=profile_read_odv(dataset,nf,m,varargin) % read seal data in the odv spreadsheet format % % if m=0 : % return the information on the nf-th file referenced in % dataset.fileInList. % dataset=profile_read_odv(dataset,nf,0); % dataset.nprofiles: number of profiles in the nf-th file % dataset.Iprofile: index referencing the profile for each dataline % % if m~=0 : % return the m-th profile from the nf-th file referenced in % dataset.fileInList. % profileCur=profile_read_odv(dataset,nf,m); % % profileCur = (m-th profile of nf-th file) % pnum_txt: '5900841' % ymd: 20060101 % hms: 3207 % lat: -46.709 % lon: 137.501 % direc: 1 % t: [1x115 single] % s: [1x115 single] % p: [1x115 single] % t_ERR: [1x115 single] % s_ERR: [1x115 single] % PorZisBAD: 0 % % IMPORTANT: Use three global variables: pnum Date and Data. global pnum Date Data fileIn=[dataset.dirIn dataset.fileInList(nf).name]; if m==0; % return the number of profiles in the file % also build an index of first-line prosition of profiles: index_prof fid_cur=fopen(fileIn,'rt'); nprofiles=0;index_prof=[]; % jump comment line at the beginning line_cur = fgetl(fid_cur); while ~feof(fid_cur) & strcmp(line_cur(1:2),'//') line_cur = fgetl(fid_cur); continue end % analyse data description line I=[0 find(double(line_cur)==9) length(line_cur)+1]; format=[]; % column index for (in this order) : % Cruise, Station, Date, Lon, Lat, Dep, Dep_qv, Temp, % Temp_qv, Sal, Sal_qv for ii=1:length(I)-1, field=line_cur(I(ii)+1:I(ii+1)-1); field=field(1:min([6 length(field)])); switch field case 'Cruise' format(1)=ii; case 'Statio' format(2)=ii; case 'yyyy-m' format(3)=ii; case {'Longit'} format(4)=ii; case {'Latitu'} format(5)=ii; case {'Depth '} format([6 7])=[ii ii+1]; case {'Temper'} format([8 9])=[ii ii+1]; case {'Salini'} format([10 11])=[ii ii+1]; end end % read end of the textfile nlines=0;nbuffer=100000;niter=0; while ~feof(fid_cur); niter=niter+1; data_odv=cell(length(format)-1,nbuffer); for ii=1:nbuffer, tline=fgets(fid_cur); nlines=nlines+1; I_sep=[0 find(double(tline)==9)]; data_odv{1,ii}=[ tline(I_sep(format(1))+1:I_sep(format(1)+1)-1) '//' ... tline(I_sep(format(2))+1:I_sep(format(2)+1)-1) ]; data_odv{2,ii}=tline(I_sep(format(3))+1:I_sep(format(3)+1)-1); for kk=4:length(format), I=I_sep(format(kk))+1:I_sep(format(kk)+1)-1; if length(I)>1, data_odv{kk-1,ii}=tline(I); elseif isempty(I), data_odv{kk-1,ii}='99999'; else val=tline(I); if val==0, data_odv{kk-1,ii}='99999'; else data_odv{kk-1,ii}=val; end end end if feof(fid_cur), break, end end data_odv=data_odv(:,1:ii); data=data_odv(3:length(format)-1,:); datanum=sscanf(sprintf('%s,',data{:}), '%g,'); datanum(datanum==99999)=NaN; %no salinity case if dataset.inclS, datanum=reshape(datanum(:),8,ii); else datanum=reshape(datanum(:),6,ii); end fprintf('%d lines\n',nlines); if niter==1, pnum=data_odv(1,:); Date=data_odv(2,:); Data=datanum; else pnum=[pnum data_odv(1,:)]; Date=[Date data_odv(2,:)]; Data=[Data datanum]; end end fclose(fid_cur); % get rid of empty indicator string [pnum_txt_list,Iprof]=unique(pnum); if size(Iprof,2)==1; Iprof=Iprof'; end; for kk=1:length(pnum), if strcmp(pnum_txt_list{kk},'//'), pnum_txt_list=pnum_txt_list(setdiff(1:length(pnum_txt_list),kk)); Iprof(kk)=[]; break end end % sort index of profile [Iprof_sort,J]=sort(Iprof); pnum_txt_sort=pnum_txt_list(J); % write index of profile Iprof_sort=[Iprof_sort nlines+1]; Iprofile=zeros(nlines,1); for kk=1:length(Iprof_sort)-1, for ii=Iprof_sort(kk):Iprof_sort(kk+1)-1, Iprofile(ii)=kk; end end dataset.Iprofile=Iprofile; % number of profiles dataset.nprofiles=length(Iprof); varargout(1) = {dataset}; else;%if m==0; % profile coordinates Iprof=find(dataset.Iprofile==m); pnum_txt=pnum{Iprof(1)}; lon=Data(1,Iprof(1)); lat=Data(2,Iprof(1)); strdate=Date{Iprof(1)}; if length(strdate)<10, varargout = {[]}; return; end ymd=str2num(strdate([1:4 6:7 9:10])); hms=0; if length(strdate)==19, hms=str2num(strdate([12:13 15:16 18:19])); end if length(strdate)==16, hms=str2num(strdate([12:13 15:16]))*100; end if length(strdate)==13, hms=str2num(strdate([12:13]))*10000; end %case when necessary information missing: dont retrieve profile if isempty(lon)|isempty(lat)|isempty(ymd), varargout = {[]}; return; end if lon < 0; lon=lon+360; end; % get T/S data z=Data(3,Iprof); z_qv=Data(4,Iprof);z_qv(isempty(z_qv))=1; t=Data(5,Iprof); t_qv=Data(6,Iprof);t_qv(isempty(t_qv))=1; if dataset.inclS, s=Data(7,Iprof); s_qv=Data(8,Iprof);s_qv(isempty(s_qv))=1; else s=t*NaN; s_qv=t*NaN; s_ERR=t*NaN; end I=find(isnan(z)|z_qv~=0); z(I)=[]; t(I)=[]; t_qv(I)=[]; t(t_qv~=0)=NaN; t_ERR=t*0; if dataset.inclS, s_qv(I)=[]; s(I)=[]; s(s_qv~=0)=NaN; s_ERR=s*0; end direc=2; PorZisBAD=0; profileCur.pnum_txt=pnum_txt; profileCur.ymd=ymd; profileCur.hms=hms; profileCur.lat=lat; profileCur.lon=lon; profileCur.direc=direc; profileCur.PorZisBAD=PorZisBAD; profileCur.t=t; profileCur.s=s; profileCur.z=z; profileCur.t_ERR=t_ERR; profileCur.s_ERR=s_ERR; varargout = {profileCur}; end; MITprof/profiles_process_check.m0000644000435400001440000000256312365522670016667 0ustar gforgetusers MITprof_global; fprintf('strike return after visualizing each plot is 0\n'); for ii=3; if ii==1; nameSample='argo'; nameFile='argo_indian.nc'; elseif ii==2; nameSample='wod05'; nameFile='wod05_CTD_1990s.nc'; elseif ii==3; nameSample='odv'; nameFile='ODVcompact_sample_MITprof.nc'; end; MITprof_ref=MITprof_read(['profiles_samples/reference_results/' nameFile]); MITprof_new=MITprof_read(['profiles_samples/' nameSample '_sample/processed/' nameFile]); figureL; imagesc(MITprof_new.prof_T-MITprof_ref.prof_T); colorbar; title('prof_T'); pause; close; figureL; imagesc(MITprof_new.prof_Testim-MITprof_ref.prof_Testim); colorbar; title('prof_Testim'); pause; close; figureL; imagesc((MITprof_new.prof_Tweight-MITprof_ref.prof_Tweight)./MITprof_ref.prof_Tweight); colorbar; title('prof_Tweight'); pause; close; figureL; imagesc(MITprof_new.prof_Tflag-MITprof_ref.prof_Tflag); colorbar; title('prof_Tflag'); pause; close; figureL; imagesc(MITprof_new.prof_S-MITprof_ref.prof_S); colorbar; title('prof_S'); pause; close; figureL; imagesc(MITprof_new.prof_Sestim-MITprof_ref.prof_Sestim); colorbar; title('prof_Sestim'); pause; close; figureL; imagesc((MITprof_new.prof_Sweight-MITprof_ref.prof_Sweight)./MITprof_ref.prof_Sweight); colorbar; title('prof_Sweight'); pause; close; figureL; imagesc(MITprof_new.prof_Sflag-MITprof_ref.prof_Sflag); colorbar; title('prof_Sflag'); pause; close; end; MITprof/profiles_devel/0000755000435400001440000000000012375431055014764 5ustar gforgetusersMITprof/profiles_devel/README0000644000435400001440000000017411511447326015645 0ustar gforgetusers This directory is meant for routines that are in early stage development -- until they find a place in another directory. MITprof/profiles_devel/profiles_subgrid_stats_format.m0000644000435400001440000000203312153004364023261 0ustar gforgetusersfunction [my3dFld]=profiles_subgrid_stats_format(VV,choiceFld,COORD); %VV variable choice %choiceFld stat choice %COORD is the coordinate type doSave=1; %========= PART 1 : load grid & atlases ======== gcmfaces_global; listSGN=[0 45 30 18 15 10 9 6 5 3 2 1]; %========= PART 2 : load and average estimates of std ======== dirData='./'; if strcmp(COORD,'depth'); nlev=length(mygrid.RC); else; eval(['load ' myenv.gcmfaces_dir 'gcmfaces_devel/RCsig0.mat RCsig0;']); nlev=length(RCsig0); end; dirRaw=[dirData 'stats/']; dirAssembled=[dirData 'stats/']; listStats={'prc10','mea','med','prc90','std','iqr','mad'}; suff=listStats{choiceFld}; my3dFld=mygrid.mskC; for lev=1:nlev-1; test0=dir([dirAssembled VV '_k' num2str(lev) '_' suff '.mat']); if ~isempty(test0); eval(['load ' dirAssembled VV '_k' num2str(lev) '_' suff '.mat;']); else; myFld=NaN*mygrid.RAC; end; my3dFld(:,:,lev)=myFld; end; my3dFld(:,:,nlev)=my3dFld{1}(1,1,nlev-1); if doSave; tmp1=convert2gcmfaces(my3dFld); write2file([dirData VV '_' suff '.bin'],tmp1); end; MITprof/profiles_devel/MITprof_platforms.m0000644000435400001440000001342211617065217020554 0ustar gforgetusers doPart1=0; doDisplay=1; doPlatformCheck=1; if doPart1; %load paths and grid: %-------------------- gcmfaces_global; grid_load([myenv.gcmfaces_dir '/sample_input/GRIDv4/'],5,'compact'); %load data set: %-------------- dirData='/Users/gforget/mywork/projects_inprogress/ecco_v4/costs/insitu/nc/'; % dirData='/Users/gforget/mywork/projects_inprogress/ecco_v4/costs/insitu/iter3/'; % fileData='seals_MITprof_latest.nc'; % fileData='argo_pacific_MITprof_latest.nc'; fileData='argo_atlantic_MITprof_latest.nc'; % fileData='argo_indian_MITprof_latest.nc'; MITprof=MITprof_load([dirData fileData]); %assign nameData: %---------------- ii=strfind(fileData,'_MITprof_latest.nc'); if ~isempty(ii); nameData=fileData(1:ii-1); else; ii=strfind(fileData,'_MITprof.nc'); if ~isempty(ii); nameData=fileData(1:ii-1); else; ii=strfind(fileData,'.nc'); nameData=fileData(1:ii-1); end; end; eval(['MITprof_' nameData '=MITprof;']); %get platforms list: %------------------- prof_descrInd={}; prof_countInd=[]; prof_lonInd=[]; prof_latInd=[]; prof_dateInd=[]; npInd=0; for pp=1:MITprof.np; test0=isempty(find(strcmp(prof_descrInd,MITprof.prof_descr{pp}))); if test0; %MITprof.prof_descr{pp} npInd=npInd+1; prof_descrInd{npInd}=MITprof.prof_descr{pp}; test1=find(strcmp(prof_descrInd{npInd},MITprof.prof_descr)); prof_countInd=[prof_countInd length(test1)]; prof_lonInd=[prof_lonInd median(MITprof.prof_lon(test1))]; prof_latInd=[prof_latInd median(MITprof.prof_lat(test1))]; prof_dateInd=[prof_dateInd median(MITprof.prof_date(test1))]; end; end; [prof_countInd,ii]=sort(prof_countInd,'descend'); prof_descrInd=prof_descrInd(ii); prof_lonInd=prof_lonInd(ii); prof_latInd=prof_latInd(ii); prof_dateInd=prof_dateInd(ii); %store stats to structure: %------------------------- eval(['platform_stats_' nameData '.prof_descrInd=prof_descrInd;']); eval(['platform_stats_' nameData '.prof_countInd=prof_countInd;']); eval(['platform_stats_' nameData '.prof_lonInd=prof_lonInd;']); eval(['platform_stats_' nameData '.prof_latInd=prof_latInd;']); eval(['platform_stats_' nameData '.prof_dateInd=prof_dateInd;']); end; %display all platforms tracks: %----------------------------- if doDisplay>1; cols='krymbw'; figure; set(gcf,'Units','Normalized','Position',[0.1 0.3 0.4 0.6]); [X,Y,FLD]=convert2pcol(mygrid.XC,mygrid.YC,mygrid.mskC); pcolor(X,Y,FLD); axis([-180 180 -90 90]); shading flat; xlabel('longitude'); ylabel('latitude'); for ppInd=1:npInd; ii=circshift([1:length(cols)],[0 ppInd-1]); ii=ii(1); cc=cols(ii); jj=find(strcmp(MITprof.prof_descr,prof_descrInd{ppInd})); if length(jj)>20; hold on; plot(MITprof.prof_lon(jj),MITprof.prof_lat(jj),[cc '.']); title(prof_descrInd{ppInd}); pause(0.01); end; end; end;%if doDisplay>0; %refined analysis of a platform's data: %-------------------------------------- if doPlatformCheck; for ii=51:250:2290; MITprofSub=MITprof_subset(MITprof,'descr',prof_descrInd{ii}); if doDisplay>0; % figure; set(gcf,'Units','Normalized','Position',[0.1 0.1 0.8 0.8]); figure; set(gcf,'Units','Normalized','Position',[-0.45 0.1 0.4 0.8]); subplot(3,1,1); [X,Y,FLD]=convert2pcol(mygrid.XC,mygrid.YC,mygrid.mskC); pcolor(X,Y,FLD); axis([-180 180 -90 90]); shading flat; xlabel('longitude'); ylabel('latitude'); hold on; plot(MITprofSub.prof_lon,MITprofSub.prof_lat,'k.'); ccT=prctile(MITprofSub.prof_T(:),[5 95]); ccS=prctile(MITprofSub.prof_S(:),[5 95]); if isnan(ccS(1)); ccS=[34 36]; end; subplot(3,2,3); imagescnan(MITprofSub.prof_T'); caxis(ccT); colorbar; title('T obs'); subplot(3,2,4); imagescnan(MITprofSub.prof_S'); caxis(ccS); colorbar; title('S obs'); subplot(3,2,5); imagescnan(MITprofSub.prof_Testim'); caxis(ccT); colorbar; title('T estim'); subplot(3,2,6); imagescnan(MITprofSub.prof_Sestim'); caxis(ccS); colorbar; title('S estim'); %pause; end; MITprofSub=MITprof_subset(MITprofSub,'depth',[50 150]); misfT=(MITprofSub.prof_T-MITprofSub.prof_Testim).*sqrt(MITprofSub.prof_Tweight); misfT=misfT(find(~isnan(misfT)&misfT~=0)); misfS=(MITprofSub.prof_S-MITprofSub.prof_Sestim).*sqrt(MITprofSub.prof_Sweight); misfS=misfS(find(~isnan(misfS)&misfS~=0)); if doDisplay>0; % figure; set(gcf,'Units','Normalized','Position',[0.1 0.1 0.8 0.8]); figure; set(gcf,'Units','Normalized','Position',[-0.45 0.1 0.4 0.8]); subplot(2,2,1); [X,Y,FLD]=convert2pcol(mygrid.XC,mygrid.YC,mygrid.mskC); pcolor(X,Y,FLD); axis([-180 180 -90 90]); shading flat; xlabel('longitude'); ylabel('latitude'); hold on; plot(MITprofSub.prof_lon,MITprofSub.prof_lat,'k.'); subplot(2,2,2); plot(MITprofSub.prof_T,MITprofSub.prof_S,'bx'); hold on; xlabel('T'); ylabel('S'); plot(MITprofSub.prof_Testim,MITprofSub.prof_Sestim,'rx'); title('blue: obs red: estim'); subplot(2,2,3); hist(misfT(find(~isnan(misfT))),[-8:0.25:8]); aa=axis; aa(1:2)=[-1 1]*10; axis(aa); title('T normalized misfit'); subplot(2,2,4); hist(misfS(find(~isnan(misfS))),[-8:0.25:8]); aa=axis; aa(1:2)=[-1 1]*10; axis(aa); title('S normalized misfit'); %pause; end; % close; close; end; end;%if doPlatformCheck; MITprof/profiles_devel/profiles_subgrid_dist.m0000644000435400001440000001307012145176107021527 0ustar gforgetusersfunction [myStat]=profiles_subgrid_stats(choiceProf,choiceLevel,choiceVar,choiceGrid,subGridN); %note : in wod09 ctd, we will use kk=2 to 33 % subGridN=8;%on the cs24 grid % subGridN=18;%on the llc grid %next things I need to do : % IO/memory store % loop over subGridN % proper treatment of choiceLevel %global variables: gcmfaces_global; global lon lat obs point; global choiceGridOld; if isempty(choiceGridOld); choiceGridOld='x'; end; global choiceProfOld; if isempty(choiceProfOld); choiceProfOld='x'; end; global choiceVarOld; if isempty(choiceVarOld); choiceVarOld='x'; end; global choiceLevelOld; if isempty(choiceLevelOld); choiceLevelOld=0; end; %choice of time/depth ranges RC=squeeze(rdmds('/net/weddell/raid3/gforget/ecco_v4/GRID/RC')); RF=squeeze(rdmds('/net/weddell/raid3/gforget/ecco_v4/GRID/RF')); depth0=-RF(1:end-1); depth0(2:end-1)=depth0(1:end-2); depth1=-RF(2:end); depth1(2:end-1)=depth1(3:end); if choiceLevel>=1; depth0=depth0(choiceLevel); depth1=depth1(choiceLevel);%choice of depth range else; error('not implemented'); end; % date0=datenum(1950,1,1); date1=datenum(2049,12,31);%choice of time range %get the grid: if strcmp(choiceGrid,'cs24')&~strcmp(choiceGrid,choiceGridOld); dirGrid='/net/weddell/raid3/gforget/grids/gridCompleted/cube_FM/'; % dirGrid='/Users/gforget/mywork/projects_inprogress/2012mayInputs/insitu/processed/'; grid_load_native([dirGrid 'cube_24/'],6); gcmfaces_bindata; elseif strcmp(choiceGrid,'cs96')&~strcmp(choiceGrid,choiceGridOld); dirGrid='/net/weddell/raid3/gforget/grids/gridCompleted/cube_FM/'; % dirGrid='/Users/gforget/mywork/projects_inprogress/2012mayInputs/insitu/processed/'; grid_load_native([dirGrid 'cube_96/'],6); gcmfaces_bindata; elseif strcmp(choiceGrid,'v4')&~strcmp(choiceGrid,choiceGridOld); dirGrid='/net/nares/raid10/gforget/2012julyIters/GRID/'; %dirGrid='/net/weddell/raid3/gforget/ecco_v4/GRID/'; grid_load(dirGrid,5,'compact'); gcmfaces_bindata; end; % choiceGridOld=choiceGrid; %get the data: if strcmp(choiceProf,'argo'); dirData='/net/nares/raid11/ecco-shared/ecco-version-4/input/input_insitu/'; listData={'argo_june2012_1992_to_2007*','argo_june2012_2008_to_2010*','argo_june2012_2011_to_2012*'}; suffOut='argo'; elseif strcmp(choiceProf,'model'); dirData='/net/nares/raid10/gforget/2012julyIters/ecco_it0003_link/mat/profiles/output/'; listData={'argo_june2012_1992_to_2007_model*','argo_june2012_2008_to_2010_model*','argo_june2012_2011_to_2012_model*'}; suffOut='model'; else; dirData='/net/nares/raid11/gforget/2012mayInputs/insitu/processed/'; listData=dir([dirData '*.nc']); for ii=1:length(listData); listData(ii).name=[listData(ii).name(1:end-3) '*']; end; listData={listData(:).name}; %for ~ backward compatibility: %listRm={'itp_MITprof*','bobbers_MITprof*','CLIMODE_Talley_ctd*','WOD09_XBT*'}; %remove climode and xbts listRm={'bobbers_MITprof*','CLIMODE_Talley_ctd*','WOD09_XBT*'}; for ii=1:length(listRm); tmp1=find(~strcmp(listData,listRm{ii})); listData={listData{tmp1}}; end; suffOut=''; end; % test1=~strcmp(choiceProf,choiceProfOld)|... ~strcmp(choiceVar,choiceVarOld)|... choiceLevel~=choiceLevelOld; if test1; [MITprof]=MITprof_stats_load(dirData,listData,choiceVar,['prof_' choiceVar suffOut]); %in DRHODR case, switch to log10 : if strcmp(choiceVar,'DRHODR'); MITprof.prof=log10(MITprof.prof); end; %mask out values that are not in year range: ii=find(MITprof.prof_datedate1); MITprof.prof(ii,:)=NaN; %restrict to depth range of interest: kk=find(MITprof.prof_depth>=depth0&MITprof.prof_depth<=depth1); lon=MITprof.prof_lon; lat=MITprof.prof_lat; obs=MITprof.prof(:,kk); end; % choiceLevelOld=choiceLevel; choiceVarOld=choiceVar; choiceProfOld=choiceProf; %get indices in full grid: (not necessarily the ecco_v4 one) point=gcmfaces_bindata(lon,lat); if strcmp(choiceVar,'RHOP'); binE=[1015:0.2:1030]; else; error('need to specify binE'); end; nB=length(binE); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %check nearest neighbor mapping: % [tmp1,tmp2]=gcmfaces_bindata(lon,lat,lon); % figureL; qwckplot(log10(tmp2)); % figureL; qwckplot(tmp1./tmp2); %map of full grid indices: (consistent with prof_point2) indGrid=convert2array(mygrid.XC); indGrid(:)=[1:length(indGrid(:))]; indGrid=convert2array(indGrid); %reduce grid and map reduced grid indices: indBox=mygrid.XC; if subGridN==0; %global computation indBox(:)=1; else; %regional computation boxMax=0; for iFace=1:mygrid.nFaces; tmp1=indBox{iFace}; tmp3=ceil([1:size(tmp1,1)]'/subGridN); tmp4=(ceil([1:size(tmp1,2)]/subGridN)-1)*max(tmp3); tmp5=tmp3*ones(1,size(tmp1,2))+ones(size(tmp1,1),1)*tmp4; indBox{iFace}=tmp5+boxMax; boxMax=boxMax+max(tmp5(:)); end; end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %main computational loop: stats for each region in indBox % indBox=convert2array(indBox); box=repmat(indBox(point),[1 size(obs,2)]); box(isnan(obs))=NaN; boxList=unique(indBox(:)); boxList=boxList(find(~isnan(boxList))); % myStat.nb=zeros(360*360,1); myStat.dist=zeros(360*360,nB); % for ii=boxList'; if mod(ii,1000)==0; [choiceLevel ii length(boxList)] end; jj=find(box==ii); if length(jj)>=10; n=histc(obs(jj),binE); jj=find(indBox==ii); myStat.nb(jj)=sum(n); myStat.dist(jj,:)=ones(length(jj),1)*n'/sum(n); end; end; % myStat.nb=reshape(myStat.nb,[360 360]); myStat.dist=reshape(myStat.dist,[360 360 nB]); myStat.nb=convert2array(myStat.nb); myStat.dist=convert2array(myStat.dist); MITprof/profiles_devel/profiles_subgrid_stats.m0000644000435400001440000001112412153004364021712 0ustar gforgetusersfunction [myStat]=profiles_subgrid_stats(KK,VV,TYPE,SUB,COORD); %KK level choice %VV variable choice %TYPE 'obs' 'estim' or 'anom' %SUB is the subsampling rate (box width=SUB) %COORD is the coordinate type %global variables: gcmfaces_global; global lon lat obs point; global COORDOld; if isempty(COORDOld); COORDOld='x'; end; global VVOld; if isempty(VVOld); VVOld='x'; end; global TYPEOld; if isempty(TYPEOld); TYPEOld='x'; end; global KKOld; if isempty(KKOld); KKOld=0; end; %choice of time/depth ranges if strcmp(COORD,'depth'); %KK is ecco v4 level index; kk is corresponding MITprof level indices RC=squeeze(rdmds([myenv.gcmfaces_dir '/sample_input/GRIDv4/RC'])); RF=squeeze(rdmds([myenv.gcmfaces_dir '/sample_input/GRIDv4/RF'])); depth0=-RF(1:end-1); depth0(2:end-1)=depth0(1:end-2); depth1=-RF(2:end); depth1(2:end-1)=depth1(3:end); if KK>=1; depth0=depth0(KK); depth1=depth1(KK);%choice of depth range else; error('not implemented'); end; end; % date0=datenum(1950,1,1); date1=datenum(2049,12,31);%choice of time range %get the grid: grid_load([myenv.gcmfaces_dir '/sample_input/GRIDv4/'],5,'compact'); gcmfaces_bindata; %get the data: dirData='./'; listData=dir([dirData 'argo_2may13_set*.nc']); listData={listData(:).name}; suffOut='argo'; % test1=~strcmp(VV,VVOld)|~strcmp(TYPE,TYPEOld)|KK~=KKOld|~strcmp(COORD,COORDOld); if test1; if strcmp(TYPE,'anom'); [MITprof]=MITprof_stats_load(dirData,listData,VV,1); elseif strcmp(TYPE,'estim'); [MITprof]=MITprof_stats_load(dirData,listData,VV,['prof_' VV 'estim']); else; [MITprof]=MITprof_stats_load(dirData,listData,VV,['prof_' VV]); end; %in DRHODR case, switch to log10 : if strcmp(VV,'DRHODR'); MITprof.prof=log10(MITprof.prof); end; %mask out values that are not in year range: ii=find(MITprof.prof_datedate1); MITprof.prof(ii,:)=NaN; %restrict to depth range of interest: if strcmp(COORD,'depth'); %KK is ecco v4 level index; kk is corresponding MITprof level indices kk=find(MITprof.prof_depth>=depth0&MITprof.prof_depth<=depth1); else; %kk is simply KK; assumes same density grid throughout kk=KK; end; lon=MITprof.prof_lon; lat=MITprof.prof_lat; obs=MITprof.prof(:,kk); end; % KKOld=KK; VVOld=VV; TYPEOld=TYPE; COORDOld=COORD; %get indices in full grid: (not necessarily the ecco_v4 one) point=gcmfaces_bindata(lon,lat); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %check nearest neighbor mapping: % [tmp1,tmp2]=gcmfaces_bindata(lon,lat,lon); % figureL; qwckplot(log10(tmp2)); % figureL; qwckplot(tmp1./tmp2); %map of full grid indices: (consistent with prof_point2) indGrid=convert2array(mygrid.XC); indGrid(:)=[1:length(indGrid(:))]; indGrid=convert2array(indGrid); %reduce grid and map reduced grid indices: indBox=mygrid.XC; if SUB==0; %global computation indBox(:)=1; else; %regional computation boxMax=0; for iFace=1:mygrid.nFaces; tmp1=indBox{iFace}; tmp3=ceil([1:size(tmp1,1)]'/SUB); tmp4=(ceil([1:size(tmp1,2)]/SUB)-1)*max(tmp3); tmp5=tmp3*ones(1,size(tmp1,2))+ones(size(tmp1,1),1)*tmp4; indBox{iFace}=tmp5+boxMax; boxMax=boxMax+max(tmp5(:)); end; end; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %main computational loop: stats for each region in indBox % indBox=convert2array(indBox); box=repmat(indBox(point),[1 size(obs,2)]); box(isnan(obs))=NaN; boxList=unique(indBox(:)); boxList=boxList(find(~isnan(boxList))); % tmp1=convert2array(0*mygrid.XC); myStat.mea=tmp1; myStat.prc90=tmp1; myStat.med=tmp1; myStat.prc10=tmp1; myStat.nb=tmp1; myStat.std=tmp1; myStat.iqr=tmp1; myStat.mad=tmp1; % for ii=boxList'; if mod(ii,1000)==0; [KK ii length(boxList)] end; jj=find(box==ii); if length(jj)>=10; tmpStat=myStats(obs(jj));%need reduced params jj=find(indBox==ii); tmpList=fieldnames(tmpStat); for pp=1:length(tmpList); eval(['myStat.' tmpList{pp} '(jj)=tmpStat.' tmpList{pp} ';']); end; end; end; % tmpList=fieldnames(myStat); for pp=1:length(tmpList); eval(['myStat.' tmpList{pp} '=convert2array(myStat.' tmpList{pp} ');']); end; eval(['save ' dirData 'stats/' VV '_k' num2str(KK) '_' num2str(SUB) '.mat myStat;']); function [myStat]=myStats(obs); myStat.nb=sum(~isnan( obs )); myStat.mea=mean(obs);%sample mean myStat.prc10=prctile(obs,10); myStat.med=median(obs); myStat.prc90=prctile(obs,90); myStat.std=std(obs);%sample standard deviation myStat.iqr=0.7413*iqr(obs);%intequartile range estimate of std myStat.mad=1.4826*mad(obs,1);%median absolute difference estimate of std MITprof/profiles_devel/profiles_subgrid_stats_rename.m0000644000435400001440000000040012365531344023244 0ustar gforgetusers dir0='./'; tmp1=dir([dir0 '*final.mat']); for kk=1:length(tmp1); tmp2=tmp1(kk).name; tmp3=[tmp2(1:end-9) 'prc10.mat']; if ~ispc; system(['mv ' dir0 tmp2 ' ' dir0 tmp3]); else; system(['rename ' dir0 tmp2 ' ' dir0 tmp3]); %DOS equivalent end; end; MITprof/profiles_devel/profiles_subgrid_stats_assemble.m0000644000435400001440000001233512153004364023572 0ustar gforgetusersfunction [myFld,myFld1]=profiles_subgrid_stats_assemble(VV,KK,choiceFld,COORD); %KK level choice %VV variable choice %choiceFld stat choice %COORD is the coordinate type doSave=1; dirData='./'; %========= PART 1 : load grid & atlases ======== gcmfaces_global; listSGN=[0 45 30 18 15 10 9 6 5 3 2 1] global atlas; test0=isempty(atlas);%no previously loaded atlas? if ~test0; test0=~strcmp(atlas.coord,COORD); end;%same coordinate as before? if test0; atlas=[]; atlas.coord=COORD; % dirAtlases=[myenv.gcmfaces_dir 'sample_input/OCCAetcONv4GRID/']; if ~strcmp(atlas.coord,'depth'); eval(['load ' myenv.gcmfaces_dir 'gcmfaces_devel/RCsig0.mat RCsig0;']); atlas.RC=RCsig0; txt=['_' atlas.coord]; else; atlas.RC=-mygrid.RC; txt=''; end; nr=length(atlas.RC); % if ~strcmp(atlas.coord,'depth'); tmp1=read2memory([dirAtlases 'D_OWPv1_M_eccollc_90x50' txt '.bin'],[90 1170 nr 12]); tmp1(tmp1==0)=NaN; atlas.D=convert2gcmfaces(tmp1); % tmp1=1*(sum(~isnan(atlas.D),4)>2); tmp1(tmp1==0)=NaN; % tmp2=nanmean(atlas.D,4); tmp2=1*(tmp2<2000); tmp2(tmp2==0)=NaN; % atlas.mskC=tmp1.*tmp2; else; atlas.mskC=mygrid.mskC; end; % if 0;%only needed for slanted diffusion tmp1=read2memory([dirAtlases 'T_OWPv1_M_eccollc_90x50' txt '.bin'],[90 1170 nr 12]); tmp1(tmp1==0)=NaN; atlas.T=convert2gcmfaces(tmp1); % tmp1=read2memory([dirAtlases 'S_OWPv1_M_eccollc_90x50' txt '.bin'],[90 1170 nr 12]); tmp1(tmp1==0)=NaN; atlas.S=convert2gcmfaces(tmp1); end; end; %========= PART 2 : load and average estimates of std ======== %if result was not completed, then skip: test0=dir([dirData 'stats/' VV '_k' num2str(KK) '_' num2str(1) '.mat']); if isempty(test0); myFld=NaN*mygrid.RAC; myFld1=myFld; return; end; listStats={'prc10','mea','med','prc90','std','iqr','mad'}; myWeightPower=4 for sgn=listSGN; eval(['load ' dirData 'stats/' VV '_k' num2str(KK) '_' num2str(sgn) '.mat myStat;']); %"bootstrap" kk=find(listSGN==sgn); if kk==1; myFld=myStat; w=myStat.nb/(sqrt(90*1170)^myWeightPower); myFld.nb=w; for ff=1:length(listStats); eval(['myFld.' listStats{ff} '=myStat.' listStats{ff} '.*w;']); end; else; w=myStat.nb/(sgn^myWeightPower); myFld.nb=myFld.nb+w; for ff=1:length(listStats); eval(['myFld.' listStats{ff} '=myFld.' listStats{ff} '+myStat.' listStats{ff} '.*w;']); end; end; end; %THIS WAS A BUG : myFld.nb=myFld.nb+w; for ff=1:length(listStats); eval(['myFld.' listStats{ff} '=(myFld.' listStats{ff} './myFld.nb);']); end; myFld.msk=atlas.mskC(:,:,KK); %original value & "local" value forcing: suff=listStats{choiceFld}; eval(['myFld1=myFld.msk.*myFld.' suff ';']); %========= PART 3 : smoothing setup ======== if 0;%simple smoothing, which does not account for no. of obs eval(['myFld.mean=myFld.msk.*atlas.' VV '(:,:,KK);']); myFld.sm0=diffsmooth2D(myFld1,mygrid.DXC*3,mygrid.DYC*3); dxy=3*sqrt(mygrid.RAC); myFld.sm1=diffsmooth2D(myFld1,dxy,dxy); myFld.sm2=diffsmooth2Drotated(myFld1,dxy,dxy/10,myFld.mean); end; %scale the diffusive operator: dxLarge=3*sqrt(mygrid.RAC); dxSmall=0.1*dxLarge; %time scale: tmp0=dxLarge./mygrid.DXC; tmp0(isnan(myFld1))=NaN; tmp00=nanmax(tmp0); tmp0=dxLarge./mygrid.DYC; tmp0(isnan(myFld1))=NaN; tmp00=max([tmp00 nanmax(tmp0)]); nbt=tmp00; nbt=ceil(1.1*2*nbt^2); dt=1; T=nbt*dt; %build diffusion operator: kLarge=dxLarge.*dxLarge/T/2; kSmall=dxSmall.*dxSmall/T/2; if 1;%isotropic diffusion, rather than slanted diffusion Kux=dxLarge.*dxLarge/T/2; Kvy=dxLarge.*dxLarge/T/2; Kuy=[]; Kvx=[]; else;%slanted diffusion eval(['myFld.mean=myFld.msk.*atlas.' VV '(:,:,KK);']); [Kux,Kuy,Kvx,Kvy]=diffrotated(kLarge,kSmall,myFld.mean); end; %finalize diffusion/smoothing problem set-up: myOp.dt=1; % myOp.nbt=nbt; myOp.eps=1e-3; myOp.Kux=Kux; myOp.Kuy=Kuy; myOp.Kvx=Kvx; myOp.Kvy=Kvy; %========= PART 4 : relaxation term setup ======== %1) set relaxation strength: (local <-> smoother) %--------------------------- %use the myFld.nb index, modified as follows w=myFld.nb; %I do a linear transiton in log10 w=log10(w); %by mapping [-2 2] to [2 -1] w=(-1-3*(w-2)/(2+2)); %go back to original units (~nb obs) and scale by nbt (nbt = 1 smoother) w=nbt*exp( w*log(10) ); %ensure stability w(w<1)=1; %enforce minimum forcing w(w>1e3*nbt)=1e3*nbt; if 0; %figureL; m_map_gcmfaces(log10(myFld.nb),0,{'myCaxis',[-4 3]}); figureL; m_map_gcmfaces(log10(w/nbt),0,{'myCaxis',[-2 2]}); return; end; myOp.tau=w*myOp.dt; % myOp.tau=0.5*myOp.dt; % myOp.tau=nbt*myOp.dt; % myOp.tau=nbt; %2) set relaxation field: ("local" value) %------------------------ fldRelax=myFld1; %========= PART 5 : resolve smoothing/relaxation problem ======== % % here we integrate to a balance between % "local" value (relaxation term) % vs smoothing (diffusion) myFld=gcmfaces_timestep(myOp,myFld1,fldRelax); %plot / save result: %=================== if 0; figureL; m_map_gcmfaces(log10(myFld),0,{'myCaxis',[-1.5 0.5]}); end; if doSave; eval(['save ' dirData 'stats/' VV '_k' num2str(KK) '_' suff '.mat myFld myFld1;']); end; MITprof/profiles_IO_v2/0000755000435400001440000000000012375431055014603 5ustar gforgetusersMITprof/profiles_IO_v2/MITprof_load.m0000644000435400001440000000535112266602315017302 0ustar gforgetusersfunction [MITprof]=MITprof_load(fileIn,varargin); %function: MITprof_load %object: read netcdf data files in the "MIT format" %author: Gael Forget (gforget@mit.edu) %date: june 21th, 2006 % %usage: [MITprof]=MITprof_load(fileIn); % ---> loads full data set % [MITprof]=MITprof_load(fileIn,list_vars); % ---> loads only the files listed in list_vars cell % array (e.g. list_vars={'prof_T','prof_Tweight'}) % plus the one dimensional information (prof_lon etc.) % %note: this does the same as MITprof_read, but % - replaces missing values with NaN % - adds a couple fields: np, nr, nd, list_descr % - replaces prof_descr with a cell form % %inputs: fileIn data file name % list_vars variables list (optional) % %outputs: MITprof structure containing the various fields/vectors % check that file exists and add prefix and suffix if necessary [pathstr, name, ext] = fileparts(fileIn); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end if isempty(ext) | ~strcmp(ext,'.nc'), ext='.nc'; end fileIn=[pathstr '/' name ext]; if ~exist(fileIn,'file'), error([fileIn ' : file not found']); end % load data using the low-level function MITprof_read [MITprof]=MITprof_read(fileIn,varargin{:}); % replace missing_values with NaNs fldNames=fieldnames(MITprof); fldNames=setdiff(fldNames,{'prof_depth','depth'}); % no NaNs in prof_depth if isfield(MITprof,'prof_date'), % special case for prof_date fldNames=setdiff(fldNames,'prof_date'); if size(fldNames,2)==1; fldNames=fldNames'; end; fldNames=[fldNames {'prof_YYYYMMDD'}]; end for ii=1:length(fldNames); fld=getfield(MITprof,fldNames{ii}); if ~isempty(fld) f = ncopen(fileIn, 'nowrite'); varname=fldNames{ii}; spval=ncgetFillVal(f,varname); if ~isempty(spval); fld(fld==spval)=NaN; MITprof=setfield(MITprof,fldNames{ii},fld); end; ncclose(f); end end; % missing values for prof_date if isfield(MITprof,'prof_date'), MITprof.prof_date( isnan(MITprof.prof_YYYYMMDD) )=NaN; end %quick fix when date/lon/lat is NaN: %----------------------------------- ii=find(isnan(MITprof.prof_lon.*MITprof.prof_YYYYMMDD.*MITprof.prof_HHMMSS.*MITprof.prof_lat)); MITprof.prof_lon(ii)=0; MITprof.prof_lat(ii)=-90; MITprof.prof_YYYYMMDD(ii)=19000101; MITprof.prof_HHMMSS(ii)=000000; %convert prof_descr into a cell array: %---------------------------------- if isfield(MITprof,'prof_descr') MITprof.prof_descr=cellstr(MITprof.prof_descr); MITprof.list_descr=unique(MITprof.prof_descr); MITprof.nd=length(MITprof.list_descr); end %add a couple things: %-------------------- MITprof.np=length(MITprof.prof_lon); MITprof.nr=length(MITprof.prof_depth); MITprof/profiles_IO_v2/MITprof_read.m0000644000435400001440000000521311553641331017272 0ustar gforgetusers%function: MITprof_read %object: read netcdf data files in the "MIT format". Low-level function. % use MITprof_load instead to load data from a MITprof % netcdf file. %author: Gael Forget (gforget@mit.edu) %date: june 21th, 2006 % %usage: [MITprof]=MITprof_read(fileIn); % ---> loads full data set % [MITprof]=MITprof_read(fileIn,list_vars); % ---> loads only the files listed in list_vars cell % array (e.g. list_vars={'prof_T','prof_Tweight'}) % plus the one dimensional information (prof_lon etc.) % %inputs: fileIn data file name % list_vars variables list (optional) % if no list_vars is provided, all fields are loaded. % %outputs: MITprof structure containing the various fields/vectors function [MITprof]=MITprof_read(fileIn,varargin); % check that file exists, and open it if ~exist(fileIn,'file'), error([fileIn ' : file not found']); end % open netcdf nc=ncopen(fileIn); MITprof=[]; % build the list of variable to load if nargin>1; list_vars=varargin{1}; else, list_vars=ncvars(nc); end if isempty(list_vars), return, end list_vars=[{'prof_lon','prof_lat'} list_vars]; if ismember('prof_date',list_vars), list_vars=[{'prof_YYYYMMDD','prof_HHMMSS'} list_vars]; end [list,m]=unique(list_vars); list_vars=list_vars(sort(m)); % is there only one profile? one_profile=0; data=ncgetvar(nc,'prof_lon'); if length(data)==1, one_profile=1; end % load fields into MITprof struct for ii=1:length(list_vars), data=ncgetvar(nc,list_vars{ii}); if size(data,1)==1 & ~one_profile, data=reshape(data,length(data),1); end MITprof=setfield(MITprof,list_vars{ii},data); end % load depth vector separately (either in prof_depth or depth variable) if ismember('prof_depth', list_vars) data=ncgetvar(nc,'prof_depth'); elseif ismember('depth', list_vars) data=ncgetvar(nc,'depth'); end data=reshape(data,length(data),1); MITprof=setfield(MITprof,'prof_depth',data); % add field prof_date if not already in the nc file if ismember('prof_date',list_vars) & ~isfield(MITprof,'prof_date'); MITprof.prof_date=datenum(num2str(MITprof.prof_YYYYMMDD*1e6+MITprof.prof_HHMMSS),'yyyymmddHHMMSS'); end; % close file ncclose(nc); %make sure that lon is -180+180: %------------------------------- tmp_lon=MITprof.prof_lon; tmp_lon(find(tmp_lon>180))=tmp_lon(find(tmp_lon>180))-360; MITprof.prof_lon=tmp_lon; %get rid of empty variables: %--------------------------- fldNames=fieldnames(MITprof); for iFld=1:length(fldNames); eval(['test0=isempty(MITprof.' fldNames{iFld} ');']); if test0; MITprof=rmfield(MITprof,fldNames{iFld}); end; end; MITprof/profiles_IO_v2/MITprof_nc2odv.m0000644000435400001440000000662611551407456017571 0ustar gforgetusersfunction MITprof_nc2odv(fileIn,varargin) % function MITprof_nc2odv(fileIn,[fileOut]) % % convert a file in MITprof netcdf format into an ODV spreadsheet. % fileIn: path (absolute or relative) to MITprof netcdf file % fileOut: path (absolute or relative) to ODV spreadsheet. % use a .txt prefix (either added or replaced in fileOut name) % by default, fileOut is the same than fileIn but with a .txt suffix % if the file already exist, it will be replaced. fileOut=fileIn; if nargin>1, fileOut=varargin{1}; end [pathstr, name, ext] = fileparts(fileIn); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end fileIn=[pathstr '/' name ext]; [pathstr, name, ext] = fileparts(fileOut); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end if isempty(ext) | ~strcmp(ext,'.txt'), ext='.txt'; end fileOut=[pathstr '/' name ext]; dat=datestr(now,'yyyy-mm-ddTHH:MM:SS'); str={'//ODV Spreadsheet V4.0' ['//' dat ''] ['//MITprof on Matlab ' version ''] ['//' fileIn ''] '//Ocean' '//Profiles' '//' }; % open fileOut fid=fopen(fileOut,'w'); % write headerlines for kk=1:length(str) fprintf(fid,'%s\n',str{kk}); end % load fileIn M=MITprof_load(fileIn); str=['Cruise Station Type yyyy-mm-ddThh:mm:ss.sss ' ... 'Longitude [degrees_east] Latitude [degrees_north] ' ... 'Depth [m] QV:WOD Temperature [¬?C] QV:WOD Salinity [psu] QV:WOD QV:ODV:SAMPLE']; fprintf(fid,'%s\n',str); format_head='%s\t%s\t%s\t%s\t%6.4f\t%6.4f\t'; format_nohead='\t\t\t\t\t\t'; format_TS='%3.1f\t0\t%6.4f\t%d\t%6.4f\t%d\t1\n'; format_Tonly='%3.1f\t0\t%6.4f\t%d\t\t\t1\n'; format_Sonly='%3.1f\t0\t\t\t%6.4f\t%d\t1\n'; for ii=1:length(M.prof_lon), prof_descr=M.prof_descr{ii}; I=strfind(prof_descr,'//'); cruise=prof_descr(1:I-1); station=prof_descr(I+2:end); type='B'; dat=datestr(M.prof_date(ii),'yyyy-mm-ddTHH:MM:SS'); lon=M.prof_lon(ii); lat=M.prof_lat(ii); D=M.prof_depth; T=M.prof_T(ii,:); Tflag=M.prof_Tflag(ii,:); S=M.prof_S(ii,:); Sflag=M.prof_Sflag(ii,:); iFormat=(1:length(D))*0; Its=find(~isnan(T)&~isnan(S));iFormat(Its)=1; It=find(~isnan(T)&isnan(S));iFormat(It)=2; Is=find(isnan(T)&~isnan(S));iFormat(Is)=3; I=find(iFormat~=0); if length(I)==0, continue, end pp=I(1); switch iFormat(pp) case 1 fprintf(fid,[format_head format_TS], ... cruise,station,type,dat,lon,lat,D(pp),T(pp),Tflag(pp),S(pp),Sflag(pp)); case 2 fprintf(fid,[format_head format_Tonly], ... cruise,station,type,dat,lon,lat,D(pp),T(pp),Tflag(pp)); case 3 fprintf(fid,[format_head format_Sonly], ... cruise,station,type,dat,lon,lat,D(pp),S(pp),Sflag(pp)); end for ii=2:length(I), pp=I(ii); switch iFormat(pp) case 1 fprintf(fid,[format_nohead format_TS], ... D(pp),T(pp),Tflag(pp),S(pp),Sflag(pp)); case 2 fprintf(fid,[format_nohead format_Tonly], ... D(pp),T(pp),Tflag(pp)); case 3 fprintf(fid,[format_nohead format_Sonly], ... D(pp),S(pp),Sflag(pp)); end end end fclose(fid); MITprof/profiles_IO_v2/MITprof_gcm2nc.m0000644000435400001440000000717511743621416017544 0ustar gforgetusersfunction []=MITprof_gcm2nc(varargin); %[]=MITprof_gcm2nc; %[]=MITprof_gcm2nc; %object: takes binary output from MITgcm/pkg/profiles (in dir_model) % and recomposes a MITprof netcdf file (in dir_model/input) %optional inputs: % dir_model is the directory where the binary files are ('./' by default) % list_model is the list of the corresponding MITprof files, which % need to be copied or linked to dir_model/input % ({'seals*','WOD09_XBT*','WOD09_CTD*','argo_at*','argo_pa*','argo_in*'} by default) % %e.g. dir_model='./'; % list_model={'seals*','WOD09_XBT*','WOD09_CTD*','argo_at*','argo_pa*','argo_in*'}; % MITprof_gcm2nc(dir_model,list_model); %note: % by assumption, dir_model contains the binaries, % dir_model/input contains the matching MITprof file % that was provided as input to MITgcm/pkg/profiles, and % the recomposed MITprof file will be put in dir_model/output warning off MATLAB:mir_warning_variable_used_as_function; if nargin==2; dir_model=varargin{1}; list_model=varargin{2}; else; dir_model='./'; list_model={'seals*','WOD09_XBT*','WOD09_CTD*','argo_at*','argo_pa*','argo_in*'}; end; dir_out=[dir_model 'output/']; dir_data=[dir_model 'input/']; %loop over files: for ff=1:length(list_model) %initialize the process: clear prof_*; file_data=dir([dir_data list_model{ff} '*.nc']); file_data2=file_data.name; %load the data: MITprof=MITprof_load([dir_data file_data2]); %prepare relevant output: varList={'T','S','U','V','ptr','ssh'}; varNum=zeros(6,1); varCount=0; for v=1:6; vv=varList{v}; if isfield(MITprof,['prof_' vv]); varCount=varCount+1; varNum(v)=varCount; eval(['prof_' vv '=-9999*ones(size(MITprof.prof_' vv ')); prof_' vv 'mask=prof_' vv ';']); end; end; varList={varList{find(varNum)}}; nr=length(MITprof.prof_depth); %list tile/processor model files: eval(['model_list_model=dir(''' dir_model list_model{ff} '*.data'');']); %if no model files then stop if size(model_list_model,1)==0; fprintf(['file: ' file_data2 ' \n, no model files found\n']); else; %loop over model files: for ffM=1:length(model_list_model) file_model2=model_list_model(ffM).name; np=model_list_model(ffM).bytes/8/2/(nr+1)/varCount; tmp_prof=read2memory([dir_model file_model2],[nr+1 2 varCount np],64); for v=1:varCount; vv=varList{v}; tmp1=squeeze(tmp_prof(1:nr,1,v,:))'; tmp2=squeeze(tmp_prof(1:nr,2,v,:))'; tmp3=squeeze(tmp_prof(nr+1,1,v,:)); tmp4=find(tmp3>0); tmp1=tmp1(tmp4,:); tmp2=tmp2(tmp4,:); tmp3=tmp3(tmp4,:); eval(['prof_' vv '(tmp3,:)=tmp1; prof_' vv 'mask(tmp3,:)=tmp2;']); end; end; %for ffM %include in structure: for v=1:varCount; vv=varList{v}; eval(['prof_' vv '(prof_' vv 'mask==0)=-9999; MITprof.prof_' vv 'estim=prof_' vv ';']); end; %prepare fields list: list_out=fieldnames(MITprof)'; ii=find(strncmp(list_out,'prof_U',6)+strncmp(list_out,'prof_S',6)+strncmp(list_out,'prof_T',6)+... strncmp(list_out,'prof_V',6)+strncmp(list_out,'prof_ssh',8)+strncmp(list_out,'prof_ptr',8)); list_out={list_out{ii}}; %prepare other fields: file_out=[file_data2(1:end-3) '_model.nc']; nr=length(MITprof.prof_depth); np=length(MITprof.prof_lon); %write to file: MITprof_write([dir_out file_out],MITprof); fprintf(['file: ' file_data2 ' \n has been processed \n']); end %if size(model_list_model,1)~=0; end%for ff=1:length(list_model) MITprof/profiles_IO_v2/MITprof_create.m0000644000435400001440000001566712152675116017644 0ustar gforgetusersfunction []=MITprof_create(fileOut,nProf,prof_depth,varargin) %function: MITprof_create %object: create a file in the "MIT format". Low-level function. %author: Gael Forget (gforget@mit.edu) %date: june 21th, 2006 % %usage: [MITprof]=MITprof_create(fileOut,nProf,prof_depth); % create an empty MITprof netcdf file % vertical depth levels are set according to prof_depth % create empty variables for all usual T/S fields % % [MITprof]=MITprof_create(fileOut,nProf,prof_depth,list_vars); % same but specifying the list of variables in list_vars cell % array (e.g. list_vars={'prof_T','prof_Tweight'}). % %inputs: fileOut data file name % nProf number of profiles % prof_depth vector of depth levels % list_vars variable list (optional) % % check that file exists and add prefix and suffix if necessary [pathstr, name, ext] = fileparts(fileOut); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end if isempty(ext) | ~strcmp(ext,'.nc'), ext='.nc'; end fileOut=[pathstr '/' name ext]; %define netcdf dimensions : nLev=length(prof_depth); prof_depth=reshape(prof_depth,length(prof_depth),1); iPROF=nProf; iDEPTH=nLev; lTXT=30; fillval=double(-9999); %=============list of variables that will actually be in the file==============% list_vars={'prof_T','prof_Tweight','prof_Testim','prof_Terr','prof_Tflag',... 'prof_S','prof_Sweight','prof_Sestim','prof_Serr','prof_Sflag','prof_D','prof_Destim'}; if nargin>3; list_vars=varargin{1}; end list_vars_plus=[{'prof_depth','prof_descr','prof_date','prof_YYYYMMDD','prof_HHMMSS',... 'prof_lon','prof_lat','prof_basin','prof_point','prof_flag'}... list_vars]; % eliminate doublons [list,m]=unique(list_vars_plus); list_vars_plus=list_vars_plus(sort(m)); %==========masters table of variables, units, names and dimensions=============% mt_v={'prof_depth'}; mt_u={'me'}; mt_n={'depth'}; mt_d={'iDEPTH'}; %mt_v=[mt_v '']; mt_u=[mt_u ' ']; mt_n=[mt_n '']; mt_d=[mt_d '']; mt_v=[mt_v 'prof_date']; mt_u=[mt_u ' ']; mt_n=[mt_n 'Julian day since Jan-1-0000']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_YYYYMMDD']; mt_u=[mt_u ' ']; mt_n=[mt_n 'year (4 digits), month (2 digits), day (2 digits)']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_HHMMSS']; mt_u=[mt_u ' ']; mt_n=[mt_n 'hour (2 digits), minute (2 digits), second (2 digits)']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_lon']; mt_u=[mt_u ' ']; mt_n=[mt_n 'Longitude (degree East)']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_lat']; mt_u=[mt_u ' ']; mt_n=[mt_n 'Latitude (degree North)']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_basin']; mt_u=[mt_u ' ']; mt_n=[mt_n 'ocean basin index (ecco 4g)']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_point']; mt_u=[mt_u ' ']; mt_n=[mt_n 'grid point index (ecco 4g)']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_flag']; mt_u=[mt_u ' ']; mt_n=[mt_n 'flag = i > 0 for suspicious profile ']; mt_d=[mt_d 'iPROF']; % mt_v=[mt_v 'prof_T']; mt_u=[mt_u 'degree C']; mt_n=[mt_n 'potential temperature']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Tweight']; mt_u=[mt_u '(degree C)^-2']; mt_n=[mt_n 'pot. temp. least-square weight']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Testim']; mt_u=[mt_u 'degree C']; mt_n=[mt_n 'pot. temp. estimate (e.g. from atlas)']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Terr']; mt_u=[mt_u 'degree C']; mt_n=[mt_n 'pot. temp. instrumental error']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Tflag']; mt_u=[mt_u ' ']; mt_n=[mt_n 'flag = i > 0 means test i rejected data.']; mt_d=[mt_d 'iPROF,iDEPTH']; % mt_v=[mt_v 'prof_S']; mt_u=[mt_u 'psu']; mt_n=[mt_n 'salinity']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Sweight']; mt_u=[mt_u '(psu)^-2']; mt_n=[mt_n 'salinity least-square weight']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Sestim']; mt_u=[mt_u 'psu']; mt_n=[mt_n 'salinity estimate (e.g. from atlas)']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Serr']; mt_u=[mt_u 'psu']; mt_n=[mt_n 'salinity instrumental error']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Sflag']; mt_u=[mt_u ' ']; mt_n=[mt_n 'flag = i > 0 means test i rejected data.']; mt_d=[mt_d 'iPROF,iDEPTH']; % mt_v=[mt_v 'prof_U']; mt_u=[mt_u 'm/s']; mt_n=[mt_n 'eastward velocity comp.']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Uweight']; mt_u=[mt_u '(m/s)^-2']; mt_n=[mt_n 'east. v. least-square weight']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_V']; mt_u=[mt_u 'm/s']; mt_n=[mt_n 'northward velocity comp.']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Vweight']; mt_u=[mt_u '(m/s)^-2']; mt_n=[mt_n 'north. v. least-square weight']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_ptr']; mt_u=[mt_u 'X']; mt_n=[mt_n 'passive tracer']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_ptrweight']; mt_u=[mt_u '(X)^-2']; mt_n=[mt_n 'pass. tracer least-square weight']; mt_d=[mt_d 'iPROF,iDEPTH']; % mt_v=[mt_v 'prof_D']; mt_u=[mt_u 'me']; mt_n=[mt_n 'variable depth']; mt_d=[mt_d 'iPROF,iDEPTH']; mt_v=[mt_v 'prof_Destim']; mt_u=[mt_u 'me']; mt_n=[mt_n 'variable depth estimate (e.g. from atlas)']; mt_d=[mt_d 'iPROF,iDEPTH']; % mt_v=[mt_v 'prof_bp']; mt_u=[mt_u 'cm']; mt_n=[mt_n 'bottom pressure']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_bpweight']; mt_u=[mt_u '(cm)^-2']; mt_n=[mt_n 'bot. pres. least-square weight']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_ssh']; mt_u=[mt_u 'cm']; mt_n=[mt_n 'sea surface height']; mt_d=[mt_d 'iPROF']; mt_v=[mt_v 'prof_sshweight']; mt_u=[mt_u '(cm)^-2']; mt_n=[mt_n 'ssh least-square weight']; mt_d=[mt_d 'iPROF']; %=============================create the file=================================% % write the netcdf structure ncid=nccreate(fileOut,'clobber'); aa=sprintf(['Format: MITprof netcdf. This file was created using \n' ... 'the matlab toolbox which can be obtained (see README) from \n'... 'http://mitgcm.org/viewvc/MITgcm/MITgcm_contrib/gael/profilesMatlabProcessing/']); ncputAtt(ncid,'','description',aa); ncputAtt(ncid,'','date',date); ncdefDim(ncid,'iPROF',iPROF); ncdefDim(ncid,'iDEPTH',iDEPTH); ncdefDim(ncid,'lTXT',lTXT); for ii=1:length(list_vars_plus); jj=find(strcmp(mt_v,list_vars_plus{ii})); if ~isempty(jj); if strcmp(mt_d{jj},'iPROF,iDEPTH'); ncdefVar(ncid,mt_v{jj},'double',{'iDEPTH','iPROF'});%note the direction flip else; ncdefVar(ncid,mt_v{jj},'double',{mt_d{jj}}); end; ncputAtt(ncid,mt_v{jj},'long_name',mt_n{jj}); ncputAtt(ncid,mt_v{jj},'units',mt_u{jj}); ncputAtt(ncid,mt_v{jj},'missing_value',fillval); ncputAtt(ncid,mt_v{jj},'_FillValue',fillval); else; if strcmp(list_vars_plus{ii},'prof_descr') ncdefVar(ncid,'prof_descr','char',{'lTXT','iPROF'}); ncputAtt(ncid,'prof_descr','long_name','profile description'); else warning([list_vars_plus{ii} ' not included -- it is not a MITprof variable']); end end; end; ncclose(ncid); %=============================set prof_depth=================================% ncid=ncopen(fileOut,'write'); ncputvar(ncid,'prof_depth',prof_depth); ncclose(ncid); MITprof/profiles_IO_v2/MITprof_addVar.m0000644000435400001440000000155311551407455017570 0ustar gforgetusers%function: MITprof_addVar % %usage: []=MITprof_addVar(filenc,varname,xtype,dimlist,varvalue); % ---> add a variable in a MITprof netcdf file % %inputs: filenc MITprof netcdf file name % varname,xtype,dimlist,varvalue: variable information function []=MITprof_addVar(filenc,varname,xtype,dimlist,varvalue); % check that file exists and add prefix and suffix if necessary [pathstr, name, ext] = fileparts(filenc); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end if isempty(ext) | ~strcmp(ext,'.nc'), ext='.nc'; end filenc=[pathstr '/' name ext]; if ~exist(filenc,'file'), error([filenc ' : file not found']); end %open file: nc=ncopen(filenc,'write'); %add variable: vars=ncvars(nc); if isempty(find(ismember(vars,varname))) ncaddVar(nc,varname,xtype,dimlist); end %write data ncputvar(nc,varname,varvalue); %close file: ncclose(nc); MITprof/profiles_IO_v2/MITprof_write.m0000644000435400001440000000664511553641331017523 0ustar gforgetusersfunction []=MITprof_write(fileOut,MITprof,varargin); %function: MITprof_write %object: write data in a MITprof netcdf file %author: Gael Forget (gforget@mit.edu) %date: Nov 5th, 2010 % %usage: []=MITprof_write(fileOut,MITprof, [list_vars] ); % %inputs: fileOut data file name (absolute/relative path) % .nc suffix is added if not already present % MITprof struct containing profile data % list_vars variable list (optional) % % Format description of MITprof struct input variable: % list of fields always available: % prof_depth [nDepth x 1] % prof_descr {nProf x 1} --> will be converted into a char array % prof_date [nProf x 1] % prof_YYYYMMDD [nProf x 1] % prof_HHMMSS [nProf x 1] % prof_lon [nProf x 1] % prof_lat [nProf x 1] % prof_basin [nProf x 1] % prof_point [nProf x 1] % % other fields generally available of size [nProf x nLev] : % prof_T, prof_Tflag, prof_Terr, prof_Tweight, prof_Testim % prof_S, prof_Sflag, prof_Serr, prof_Sweight, prof_Sestim % % if list_vars is not specified, every variables with a name starting % with 'prof_', except prof_depth, will be saved in the MITprof % netcdf file. An error will occur if the program try to save a % variable that is not initialized in the MITprof netcdf file. % % if list_vars is specified, only variables present in the list will be % saved. % % NaN are auomatically replaced by missing_value attribute (or _FillValue). % the file fileOut will be created using MITprof_create if needed. % % check that file exists and add prefix and suffix if necessary [pathstr, name, ext] = fileparts(fileOut); if isempty(pathstr) | strcmp(pathstr,'.'), pathstr=pwd; end if isempty(ext) | ~strcmp(ext,'.nc'), ext='.nc'; end fileOut=[pathstr '/' name ext]; % build the list of variables that must be loaded if nargin>2, list_vars=varargin{1}; else list1=fieldnames(MITprof); list_vars={}; I=strfind(list1,'prof_'); for kk=1:length(I), if I{kk}==1 & ~strcmp(list1{kk},'prof_depth'), list_vars{end+1}=list1{kk}; end end end % stop if there are no profile in MITprof nProf=length(MITprof.prof_lon); if nProf==0, return, end % create the file if needed if ~exist(fileOut,'file'), prof_depth=MITprof.prof_depth; MITprof_create(fileOut,nProf,prof_depth,list_vars); end % prof_descr: convert back from cell 2 array format if isfield(MITprof,'prof_descr') ncload(fileOut,'prof_descr'); nb_char=size(prof_descr,2); prof_descr=char(MITprof.prof_descr); if size(prof_descr,2)nb_char disp('some profile descriptive strings have been shortened'); prof_descr=prof_descr(:,1:nb_char); end MITprof.prof_descr=prof_descr; end % write to file: nc=ncopen(fileOut,'write'); vars=ncvars(nc); list_vars=intersect(vars,list_vars); for ii=1:length(list_vars); varname=list_vars{ii}; data=getfield(MITprof,varname); spval=ncgetFillVal(nc,varname); if isnumeric(data) if isempty(spval), warning(['no FillVal for ' varname ': use of -9999 default value']); spval=double(-9999); end data(isnan(data))=spval; MITprof=setfield(MITprof,varname,data); end ncputvar(nc,varname,data); end ncclose(nc);