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dg_grid_regions_analysis2D_nobias.m
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dg_grid_regions_analysis2D_nobias.m
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% DG 2017-08-30, 2017-11-01, 2017-12-15, 2018-01-04
% this script perform regression analysis for time series data from the MAB taking potential autocorrelation (effective DOF) into account.
% need to run dg_grid_regions_hydroavg.m before this script to calculate the average temperature and salinity for each region of each season.
% setup directories needed for the script
dg_setup_MABclimate_dir
loadmonthlyflag = 1
loadhydroflag = 1
calcflag = 1
seasonbiasflag = 1 % 0 (without seasonalbias) or 1 (with seasonal bias correction)
dataflag = 'depth-averaged' % 'bottom' or 'depth-averaged' or 'bottomSODA' or 'depth-averagedSODA', only the first and last letters matter
saveflag = 1
sodaflag = 0
searchradius = 40000
p = 4
% variable (4): 1-temp, 2-tempshw, 3-salt, 4-saltshw
% region (9): 1-SNE, 2-NYB1, 3-NYB2, 4-SS1, 5-SS2, 6-MAB, 7-GB, 8-ENE, 9-GOM
% season (3): 1-Winter-Spring, 2-Spring-Summer, 3-Fall-Winter
% time period (3): 1-1977-1999, 2-1999-2017, 3-1977-2016
%si = 1 % season (3): 1-Winter-Spring, 2-Spring-Summer, 3-Fall-Winter
%ri = 1 % region (9): 1-SNE, 2-NYB1, 3-NYB2, 4-SS1, 5-SS2, 6-MAB, 7-GB, 8-ENE, 9-GOM
%vi = 1 % variable (4): 1-temp, 2-tempshw, 3-salt, 4-saltshw
%ti = 3 % time period (3): 1-1977-1999, 2-1999-2017, 3-1977-2016
ns = 3;
nr = 9;
nv = 4;
nt = 3;
if sodaflag == 0
tind{1} = [1:23];
tind{2} = [23:40];
tind{3} = [1:40];
elseif sodaflag == 1
tind{1} = [4:23];
tind{2} = [26:37];
tind{3} = [4:39];
end %if
switch seasonbiasflag
case 0
var{1} = 'temp';
var{2} = 'tempshw';
var{3} = 'salt';
var{4} = 'saltshw';
case 1
var{1} = 'temp_nobias';
var{2} = 'tempshw_nobias';
var{3} = 'salt_nobias';
var{4} = 'saltshw_nobias';
end %switch
m = repmat(NaN,[ns,nr,nv,nt]);
b = m;
mloeff = m;
mhieff = m;
mlo = m;
mhi = m;
tsN = m;
tsNstar = m;
tsNeff = m;
hypothesis = m;
lseason = m;
lregion = m;
lvariable = m;
ltimeperiod = m;
if loadmonthlyflag == 1
if ~exist('casts')
load([workdir 'hydroMABcasts.mat']);
end %if
if ~exist('region')
region = dg_grid_regions_define;
end %if
if sodaflag == 0
hydroMABavgmonthlypath = [workdirlocal 'hydroMABavgmonthly_r' num2str(searchradius) '_p' num2str(p) '.mat'];
elseif sodaflag == 1
hydroMABavgmonthlypath = [workdirlocal 'hydroMABavgmonthlySODA_r' num2str(searchradius) '_p' num2str(p) '.mat'];
end %if
load(hydroMABavgmonthlypath);
yyyylist = [1977:2016];
month = [1:12];
regions = [1:9];
mtemp = repmat(NaN,[length(month),length(regions)]);
msalt = mtemp;
mtempshw = mtemp;
msaltshw = mtemp;
mvoltemp = mtemp;
mvolsalt = mtemp;
mvolshw = mtemp;
mvolume = mtemp;
% load regional boundary data and find the time and location of each cast
reg = dg_grid_regions_define_basic;
%region = dg_grid_regions_define;
yyyy = [casts.yr]';
dyd = [casts.dyd]';
yd = [casts.yd]';
mm = str2num(datestr(datenum(yyyy,1,dyd),5));
londata = [casts.lon]';
latdata = [casts.lat]';
if sodaflag == 1
lonind = find(londata > 180);
londata(lonind) = londata(lonind) - 360;
end %if
depth = -double([casts.zdeep])';
for ri = 1:9
for mi = 1:12
mtemp(mi,ri) = hydromom.month(mi).region(ri).mtemp;
msalt(mi,ri) = hydromom.month(mi).region(ri).msalt;
mtempshw(mi,ri) = hydromom.month(mi).region(ri).mtempshw;
msaltshw(mi,ri) = hydromom.month(mi).region(ri).msaltshw;
mvoltemp(mi,ri) = hydromom.month(mi).region(ri).voltemp;
mvolsalt(mi,ri) = hydromom.month(mi).region(ri).volsalt;
mvolume(mi,ri) = hydromom.month(mi).region(ri).volume;
end %for mi
end %for ri
ccc.month = month;
ccc.tempmonthly = mtemp;
ccc.saltmonthly = msalt;
ccc.tempshwmonthly = mtempshw;
ccc.saltshwmonthly = msaltshw;
ccc.voltempmonthly = mvoltemp;
ccc.volsaltmonthly = mvolsalt;
ccc.volumemonthly = mvolume;
ccc.ncastsmonthly = repmat(NaN,[length(ccc.month), length(reg)]);
ccc.ncasts = repmat(NaN,[length(yyyylist), length(ccc.month), length(reg)]);
for ri = 1:length(reg)
inregion = inpolygon(londata,latdata,reg(ri).lon,reg(ri).lat);
regionalind = find(inregion == logical(1));
reg(ri).clon = londata(regionalind);
reg(ri).clat = latdata(regionalind);
reg(ri).cdepth = depth(regionalind);
reg(ri).cyyyy = yyyy(regionalind);
reg(ri).cmm = mm(regionalind);
reg(ri).ind = [];
for mi = 1:12
%reg(ri).ind{mi} = find(cmm == mi & cdepth <= 1500);
ccc.ncastsmonthly(mi,ri) = length(find(reg(ri).cmm == mi & reg(ri).cdepth <= 1500));
end %for
for yi = 1:length(yyyylist)
for mi = 1:12
%reg(ri).ind{mi} = find(cmm == mi & cdepth <= 1500);
ccc.ncasts(yi,mi,ri) = length(find(reg(ri).cmm == mi & reg(ri).cyyyy == yyyylist(yi) & reg(ri).cdepth <= 1500));
end %for
end %for
end %for
if saveflag == 1
if sodaflag == 0
save([workdirlocal 'MABmonthly2D_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydromom','ccc','reg','month','yyyylist','-v7.3')
elseif sodaflag == 1
save([workdirlocal 'MABmonthly2D_SODA_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydromom','ccc','reg','month','yyyylist','-v7.3')
end %if
end %if
end %if loadmonthlyflag
if loadhydroflag == 1
if lower(dataflag(1)) == 'd' & dataflag(end) ~= 'A'
hydroMABavgpath = [workdirlocal 'hydroMABavg2Da_r' num2str(searchradius) '_p' num2str(p) '.mat'];
load(hydroMABavgpath);
elseif lower(dataflag(1)) == 'b' & dataflag(end) ~= 'A'
hydroMABavgpath = [workdirlocal 'hydroMABavg2Db_r' num2str(searchradius) '_p' num2str(p) '.mat'];
load(hydroMABavgpath);
hydrom = hydrob;
elseif lower(dataflag(1)) == 'd' & dataflag(end) == 'A'
hydroMABavgpath = [workdirlocal 'hydroMABavg2DaSODA_r' num2str(searchradius) '_p' num2str(p) '.mat'];
load(hydroMABavgpath);
elseif lower(dataflag(1)) == 'b' & dataflag(end) == 'A'
hydroMABavgpath = [workdirlocal 'hydroMABavg2DbSODA_r' num2str(searchradius) '_p' num2str(p) '.mat'];
load(hydroMABavgpath);
hydrom = hydrob;
end %if
if seasonbiasflag == 1
%nobiasMABpath = [workdir 'nobias_ts_2D.mat'];
%nbccc = load(nobiasMABpath);
end %if
if ~exist('region')
region = dg_grid_regions_define;
end %if
yyyy = [1977:2016]';
ccc.yyyy = yyyy;
%season(1).label = 'Year Day 1-125';
%season(2).label = 'Year Day 126-250';
%season(3).label = 'Year Day 251-365';
season(1).label = 'Year Day 1-120';
season(2).label = 'Year Day 121-243';
season(3).label = 'Year Day 244-365';
season(1).name = 'Winter-Spring';
season(2).name = 'Spring-Summer';
season(3).name = 'Fall-Winter';
season(1).month = [1:4];
season(2).month = [5:8];
season(3).month = [9:12];
ccc.season = season;
ccc.temp = repmat(NaN,[length(yyyy), 3, 9]);
ccc.salt = repmat(NaN,[length(yyyy), 3, 9]);
ccc.tempshw = ccc.temp;
ccc.saltshw = ccc.salt;
ccc.voltemp = ccc.temp;
ccc.volsalt = ccc.salt;
ccc.volshw = ccc.salt;
ccc.tempfilt = ccc.temp;
ccc.saltfilt = ccc.salt;
ccc.tempshwfilt = ccc.temp;
ccc.saltshwfilt = ccc.salt;
ccc.tempavg = repmat(NaN,[3, 9]);
ccc.tempstd = ccc.tempavg;
ccc.saltavg = ccc.tempavg;
ccc.saltstd = ccc.tempavg;
ccc.tempshwavg = ccc.tempavg;
ccc.tempshwstd = ccc.tempavg;
ccc.saltshwavg = ccc.tempavg;
ccc.saltshwstd = ccc.tempavg;
ccc.tempfilt_nobias = repmat(NaN,[length(yyyy), 3, 9]);;
ccc.saltfilt_nobias = repmat(NaN,[length(yyyy), 3, 9]);;
ccc.tempshwfilt_nobias = repmat(NaN,[length(yyyy), 3, 9]);;
ccc.saltshwfilt_nobias = repmat(NaN,[length(yyyy), 3, 9]);;
ccc.tempavg_nobias = repmat(NaN,[3, 9]);
ccc.tempstd_nobias = repmat(NaN,[3, 9]);
ccc.saltavg_nobias = repmat(NaN,[3, 9]);
ccc.saltstd_nobias = repmat(NaN,[3, 9]);
ccc.tempshwavg_nobias = repmat(NaN,[3, 9]);
ccc.tempshwstd_nobias = repmat(NaN,[3, 9]);
ccc.saltshwavg_nobias = repmat(NaN,[3, 9]);
ccc.saltshwstd_nobias = repmat(NaN,[3, 9]);
for yi = 1:length(yyyy)
for si = 1:3
[yi si]
ccc.temp(yi,si,:) = [hydrom(yi).season(si).region(:).temp];
ccc.salt(yi,si,:) = [hydrom(yi).season(si).region(:).salt];
ccc.tempshw(yi,si,:) = [hydrom(yi).season(si).region(:).tempshw];
ccc.saltshw(yi,si,:) = [hydrom(yi).season(si).region(:).saltshw];
ccc.voltemp(yi,si,:) = [hydrom(yi).season(si).region(:).voltemp];
ccc.volsalt(yi,si,:) = [hydrom(yi).season(si).region(:).volsalt];
ccc.volshw(yi,si,:) = [hydrom(yi).season(si).region(:).volshw];
end %for si
end %for yi
for si = 1:ns
for ri = 1:nr
ccc.tempfilt(:,si,ri) = dg_extrema_remove(ccc.temp(:,si,ri),1);
ccc.saltfilt(:,si,ri) = dg_extrema_remove(ccc.salt(:,si,ri),1);
ccc.tempshwfilt(:,si,ri) = dg_extrema_remove(ccc.tempshw(:,si,ri),1);
ccc.saltshwfilt(:,si,ri) = dg_extrema_remove(ccc.saltshw(:,si,ri),1);
ccc.tempavg(si,ri) = nanmean(ccc.tempfilt(:,si,ri));
ccc.tempstd(si,ri) = nanstd(ccc.tempfilt(:,si,ri));
ccc.saltavg(si,ri) = nanmean(ccc.saltfilt(:,si,ri));
ccc.saltstd(si,ri) = nanstd(ccc.saltfilt(:,si,ri));
ccc.tempshwavg(si,ri) = nanmean(ccc.tempshwfilt(:,si,ri));
ccc.tempshwstd(si,ri) = nanstd(ccc.tempshwfilt(:,si,ri));
ccc.saltshwavg(si,ri) = nanmean(ccc.saltshwfilt(:,si,ri));
ccc.saltshwstd(si,ri) = nanstd(ccc.saltshwfilt(:,si,ri));
end %for
end %for
% seasonal bias correction calculations
ccc.deltaT = repmat(NaN,[length(yyyy),ns,nr]);
ccc.deltaS = repmat(NaN,[length(yyyy),ns,nr]);
ccc.deltaTshw = repmat(NaN,[length(yyyy),ns,nr]);
ccc.deltaSshw = repmat(NaN,[length(yyyy),ns,nr]);
for yi = 1:length(ccc.yyyy)
for si = 1:ns
for ri = 1:nr
ccc.deltaT(yi,si,ri) = nanmean(ccc.tempmonthly(season(si).month,ri)) - nansum(ccc.tempmonthly(season(si).month,ri) .* ccc.ncasts(yi,season(si).month,ri)') / nansum(ccc.ncasts(yi,season(si).month,ri));
ccc.deltaS(yi,si,ri) = nanmean(ccc.saltmonthly(season(si).month,ri)) - nansum(ccc.saltmonthly(season(si).month,ri) .* ccc.ncasts(yi,season(si).month,ri)') / nansum(ccc.ncasts(yi,season(si).month,ri));
ccc.deltaTshw(yi,si,ri) = nanmean(ccc.tempshwmonthly(season(si).month,ri)) - nansum(ccc.tempshwmonthly(season(si).month,ri) .* ccc.ncasts(yi,season(si).month,ri)') / nansum(ccc.ncasts(yi,season(si).month,ri));
ccc.deltaSshw(yi,si,ri) = nanmean(ccc.saltshwmonthly(season(si).month,ri)) - nansum(ccc.saltshwmonthly(season(si).month,ri) .* ccc.ncasts(yi,season(si).month,ri)') / nansum(ccc.ncasts(yi,season(si).month,ri));
end %for
end %for
end %for
if seasonbiasflag == 1
%cccLW.temp_nobias = nbccc.ccc.temp_nobias;
%cccLW.tempshw_nobias = nbccc.ccc.tempshw_nobias;
%cccLW.salt_nobias = nbccc.ccc.salt_nobias;
%cccLW.saltshw_nobias = nbccc.ccc.saltshw_nobias;
ccc.temp_nobias = ccc.temp + ccc.deltaT;
ccc.tempshw_nobias = ccc.tempshw + ccc.deltaTshw;
ccc.salt_nobias = ccc.salt + ccc.deltaS;
ccc.saltshw_nobias = ccc.saltshw + ccc.deltaSshw;
for si = 1:ns
for ri = 1:nr
ccc.tempfilt_nobias(:,si,ri) = dg_extrema_remove(ccc.temp(:,si,ri),1);
ccc.saltfilt_nobias(:,si,ri) = dg_extrema_remove(ccc.salt(:,si,ri),1);
ccc.tempshwfilt_nobias(:,si,ri) = dg_extrema_remove(ccc.tempshw(:,si,ri),1);
ccc.saltshwfilt_nobias(:,si,ri) = dg_extrema_remove(ccc.saltshw(:,si,ri),1);
ccc.tempavg_nobias(si,ri) = nanmean(ccc.tempfilt_nobias(:,si,ri));
ccc.tempstd_nobias(si,ri) = nanstd(ccc.tempfilt_nobias(:,si,ri));
ccc.saltavg_nobias(si,ri) = nanmean(ccc.saltfilt_nobias(:,si,ri));
ccc.saltstd_nobias(si,ri) = nanstd(ccc.saltfilt_nobias(:,si,ri));
ccc.tempshwavg_nobias(si,ri) = nanmean(ccc.tempshwfilt_nobias(:,si,ri));
ccc.tempshwstd_nobias(si,ri) = nanstd(ccc.tempshwfilt_nobias(:,si,ri));
ccc.saltshwavg_nobias(si,ri) = nanmean(ccc.saltshwfilt_nobias(:,si,ri));
ccc.saltshwstd_nobias(si,ri) = nanstd(ccc.saltshwfilt_nobias(:,si,ri));
end %for
end %for
end %if
if lower(dataflag(1)) == 'd' & dataflag(end) ~= 'A'
ccc.dataflag = 'depth-averaged'
switch seasonbiasflag
case 0
save([workdirlocal 'MABclimate2Da_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrom','ccc','region','season','yyyy','-v7.3')
case 1
save([workdirlocal 'MABclimate2Da_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrom','ccc','region','season','yyyy','-v7.3')
end %switch
elseif lower(dataflag(1)) == 'b' & dataflag(end) ~= 'A'
ccc.dataflag = 'bottom'
switch seasonbiasflag
case 0
save([workdirlocal 'MABclimate2Db_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrob','ccc','region','season','yyyy','-v7.3')
case 1
save([workdirlocal 'MABclimate2Db_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrob','ccc','region','season','yyyy','-v7.3')
end %switch
elseif lower(dataflag(1)) == 'd' & dataflag(end) == 'A'
ccc.dataflag = 'depth-averaged-SODA'
switch seasonbiasflag
case 0
save([workdirlocal 'MABclimate2DaSODA_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrom','ccc','region','season','yyyy','-v7.3')
case 1
save([workdirlocal 'MABclimate2DaSODA_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrom','ccc','region','season','yyyy','-v7.3')
end %switch
elseif lower(dataflag(1)) == 'b' & dataflag(end) == 'A'
ccc.dataflag = 'bottom-SODA'
switch seasonbiasflag
case 0
save([workdirlocal 'MABclimate2DbSODA_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrob','ccc','region','season','yyyy','-v7.3')
case 1
save([workdirlocal 'MABclimate2DbSODA_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrob','ccc','region','season','yyyy','-v7.3')
end %switch
end %if
display('Done loading hydro data.')
end %if loadhydroflag
if calcflag == 1
for si = 1:ns
for ri = 1:nr
[season(si).name ' ' region(ri).label]
for vi = 1:nv
for ti = 1:nt
%si = 3; ri = 9; vi = 3; ti = 2;
x = ccc.yyyy(tind{ti});
y = eval(['ccc.' var{vi} '(tind{ti},si,ri)']);
%badind = find((detrend(y) > 3.2*nanstd(y)) | (detrend(y) < -3.2*nanstd(y)));
%if ~isempty(badind)
% y(badind) = NaN;
%end %if
rega = dg_DFanalysis_core(x, y);
b(si,ri,vi,ti) = rega.b;
m(si,ri,vi,ti) = rega.m;
mlo(si,ri,vi,ti) = rega.mlo;
mhi(si,ri,vi,ti) = rega.mhi;
mloeff(si,ri,vi,ti) = rega.mloeff;
mhieff(si,ri,vi,ti) = rega.mhieff;
tsN(si,ri,vi,ti) = rega.N;
tsNstar(si,ri,vi,ti) = rega.Nstar;
tsNeff(si,ri,vi,ti) = rega.Neff;
hypothesis(si,ri,vi,ti) = rega.hypothesis;
lseason(si,ri,vi,ti) = si;
lregion(si,ri,vi,ti) = ri;
lvariable(si,ri,vi,ti) = vi;
ltimeperiod(si,ri,vi,ti) = ti;
end %for ti
end %for vi
end %for ri
end %for si
ccc.mlabel = 'season,region,variable,timeperiod';
ccc.season = lseason;
ccc.region = lregion;
ccc.variable = lvariable;
ccc.timeperiod = ltimeperiod;
ccc.b = b;
ccc.m = m;
ccc.mlo = mlo;
ccc.mhi = mhi;
ccc.mloeff = mloeff;
ccc.mhieff = mhieff;
ccc.N = tsN;
ccc.Nstar = tsNstar;
ccc.Neff = round(tsNeff);
ccc.hypothesis = hypothesis;
ccc.season1d = reshape(lseason,[],1);
ccc.region1d = reshape(lregion,[],1);
ccc.variable1d = reshape(lvariable,[],1);
ccc.timeperiod1d = reshape(ltimeperiod,[],1);
ccc.b1d = reshape(b,[],1);
ccc.m1d = reshape(m,[],1);
ccc.mlo1d = reshape(mlo,[],1);
ccc.mhi1d = reshape(mhi,[],1);
ccc.mloeff1d = reshape(mloeff,[],1);
ccc.mhieff1d = reshape(mhieff,[],1);
ccc.N1d = reshape(tsN,[],1);
ccc.Nstar1d = reshape(tsNstar,[],1);
ccc.Neff1d = reshape(tsNeff,[],1);
ccc.hypothesis1d = reshape(hypothesis,[],1);
if saveflag == 1
switch seasonbiasflag
case 0
if lower(dataflag(1)) == 'd' & dataflag(end) ~= 'A'
save([workdirlocal 'MABclimate2Da_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrom','ccc','region','season','yyyy','-v7.3')
xlswrite([workdirlocal 'MAB_summary_table_2Da_r' num2str(searchradius) '_p' num2str(p) '.xlsx'], [ccc.variable1d ccc.region1d ccc.season1d ccc.timeperiod1d ccc.m1d ccc.mlo1d ccc.mhi1d ccc.mloeff1d ccc.mhieff1d ccc.N1d ccc.Nstar1d ccc.Neff1d ccc.hypothesis1d]);
elseif lower(dataflag(1)) == 'b' & dataflag(end) ~= 'A'
save([workdirlocal 'MABclimate2Db_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrob','ccc','region','season','yyyy','-v7.3')
xlswrite([workdirlocal 'MAB_summary_table_2Db_r' num2str(searchradius) '_p' num2str(p) '.xlsx'], [ccc.variable1d ccc.region1d ccc.season1d ccc.timeperiod1d ccc.m1d ccc.mlo1d ccc.mhi1d ccc.mloeff1d ccc.mhieff1d ccc.N1d ccc.Nstar1d ccc.Neff1d ccc.hypothesis1d]);
elseif lower(dataflag(1)) == 'd' & dataflag(end) == 'A'
save([workdirlocal 'MABclimate2DaSODA_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrom','ccc','region','season','yyyy','-v7.3')
xlswrite([workdirlocal 'MAB_summary_table_2Da_SODA_r' num2str(searchradius) '_p' num2str(p) '.xlsx'], [ccc.variable1d ccc.region1d ccc.season1d ccc.timeperiod1d ccc.m1d ccc.mlo1d ccc.mhi1d ccc.mloeff1d ccc.mhieff1d ccc.N1d ccc.Nstar1d ccc.Neff1d ccc.hypothesis1d]);
elseif lower(dataflag(1)) == 'b' & dataflag(end) == 'A'
save([workdirlocal 'MABclimate2DbSODA_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrob','ccc','region','season','yyyy','-v7.3')
xlswrite([workdirlocal 'MAB_summary_table_2Db_SODA_r' num2str(searchradius) '_p' num2str(p) '.xlsx'], [ccc.variable1d ccc.region1d ccc.season1d ccc.timeperiod1d ccc.m1d ccc.mlo1d ccc.mhi1d ccc.mloeff1d ccc.mhieff1d ccc.N1d ccc.Nstar1d ccc.Neff1d ccc.hypothesis1d]);
end %switch
case 1
if lower(dataflag(1)) == 'd' & dataflag(end) ~= 'A'
save([workdirlocal 'MABclimate2Da_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrom','ccc','region','season','yyyy','-v7.3')
xlswrite([workdirlocal 'MAB_summary_table_2Da_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.xlsx'], [ccc.variable1d ccc.region1d ccc.season1d ccc.timeperiod1d ccc.m1d ccc.mlo1d ccc.mhi1d ccc.mloeff1d ccc.mhieff1d ccc.N1d ccc.Nstar1d ccc.Neff1d ccc.hypothesis1d]);
elseif lower(dataflag(1)) == 'b' & dataflag(end) ~= 'A'
save([workdirlocal 'MABclimate2Da_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrob','ccc','region','season','yyyy','-v7.3')
xlswrite([workdirlocal 'MAB_summary_table_2Db_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.xlsx'], [ccc.variable1d ccc.region1d ccc.season1d ccc.timeperiod1d ccc.m1d ccc.mlo1d ccc.mhi1d ccc.mloeff1d ccc.mhieff1d ccc.N1d ccc.Nstar1d ccc.Neff1d ccc.hypothesis1d]);
elseif lower(dataflag(1)) == 'd' & dataflag(end) == 'A'
save([workdirlocal 'MABclimate2DaSODA_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrom','ccc','region','season','yyyy','-v7.3')
xlswrite([workdirlocal 'MAB_summary_table_2Da_SODA_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.xlsx'], [ccc.variable1d ccc.region1d ccc.season1d ccc.timeperiod1d ccc.m1d ccc.mlo1d ccc.mhi1d ccc.mloeff1d ccc.mhieff1d ccc.N1d ccc.Nstar1d ccc.Neff1d ccc.hypothesis1d]);
elseif lower(dataflag(1)) == 'b' & dataflag(end) == 'A'
save([workdirlocal 'MABclimate2DaSODA_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.mat'],'hydrob','ccc','region','season','yyyy','-v7.3')
xlswrite([workdirlocal 'MAB_summary_table_2Db_SODA_nobiasDG_r' num2str(searchradius) '_p' num2str(p) '.xlsx'], [ccc.variable1d ccc.region1d ccc.season1d ccc.timeperiod1d ccc.m1d ccc.mlo1d ccc.mhi1d ccc.mloeff1d ccc.mhieff1d ccc.N1d ccc.Nstar1d ccc.Neff1d ccc.hypothesis1d]);
end %if
end %switch
end %if saveflag
end %calcflag