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Copy pathSpatial_Correlation_latestversion.m
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Spatial_Correlation_latestversion.m
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%% Now, taking my seasonal grids of CMOD, Ice, Winds, and CHL-A, I will run a correlation through all of them and
% Producing a variant of the surf plot
cd /Users/srishtidasarathy/Documents/'Documents - Srishti’s MacBook Pro '/Bowman/Updated_Code_Processing_PhdPhaseOne/Srishti/Analysis_and_Vars_For_Publication/
%%
load Total_timetable_amsrmf.mat
load Total_timetable_CMOD_Surface.mat
load Total_timetable_Depol_Ratio.mat
cd /Users/srishtidasarathy/Documents/'Documents - Srishti’s MacBook Pro '/Bowman/Updated_Code_Processing_PhdPhaseOne/New_mat_files_CHL_A_DATA_MONTHLY/
load('Master_chlor_a_monthly_full_res.mat')
load('Aqua_Longitude_Subset_BellingshausenSea.mat')
load('Aqua_Latitude_Subset_BellingshausenSea.mat')
% for i = 1:151
% Total_chl_monthly_2(i) = nanmean(Master_chl_a(:,:,i), [1 2]);
% end
%
% Total_chl_a_monthly = Total_chl_monthly_2;
cd /Users/srishtidasarathy/Documents/'Documents - Srishti’s MacBook Pro '/Bowman/Updated_Code_Processing_PhdPhaseOne/Srishti/Analysis_and_Vars_For_Publication/Revisions_Figures
%%
step_Lat = (linspace(Latitude_subset(1), Latitude_subset(end), 15)) ;
step_Lon = (linspace(Longitude_subset(1), Longitude_subset(end), 46));
step_Lat = flip(step_Lat); % this is for plotting purposes because pcolor flips image on y axis.
% At the moment this is just to check how many steps they are and if they
% correspond...
nstep_Lat = Latitude_subset(1) : -1 : Latitude_subset(end) ;
nstep_Lon = Longitude_subset(1) : 1 : Longitude_subset(end);
nstep_Lat = flip(nstep_Lat);
%% Here I am averaging data from each individual season for the temporal range of record.
clear Chl_a_seasons
count = 0;
for i = 1:3:148
count = count+1;
disp(count)
Chl_a_seasons(:,:,count) = mean(Master_chl_a(:,:, i : i+2), 3, 'omitnan');
end
Chl_a_seasons = cat(3,Chl_a_seasons, Master_chl_a(:,:,151)); % concatenating the last month since it's the remainder
%% This is a better way to adjust resolution of chl-a, that way, you can use nanmean for the missing values.
fun = @(block_struct) nanmean(block_struct.data, [ 1 2]);
CHL_SEASONS = blockproc(Chl_a_seasons,...
[length(Chl_a_seasons(:,1, :)) ./ length(step_Lon) length(Chl_a_seasons(1,:, 1)) ./ length(step_Lat)],...
fun);
%% CMOD, Winds, & Ice Now
% CALIPSO didn't start having data until June of 2006. This winter season will be shorter.
TR_winter_2006 = timerange('2006-06-01', '2006-09-01'); % Winter: June 1st to September 1st
TR_winter_2007 = timerange('2007-06-01', '2007-09-01');
TR_winter_2008 = timerange('2008-06-01', '2008-09-01');
TR_winter_2009 = timerange('2009-06-01', '2009-09-01');
TR_winter_2010 = timerange('2010-06-01', '2010-09-01');
TR_winter_2011 = timerange('2011-06-01', '2011-09-01');
TR_winter_2012 = timerange('2012-06-01', '2012-09-01');
TR_winter_2013 = timerange('2013-06-01', '2013-09-01');
TR_winter_2014 = timerange('2014-06-01', '2014-09-01');
TR_winter_2015 = timerange('2015-06-01', '2015-09-01');
TR_winter_2016 = timerange('2016-06-01', '2016-09-01');
TR_winter_2017 = timerange('2017-06-01', '2017-09-01');
TR_winter_2018 = timerange('2018-06-01', '2018-09-01');
% 13
TR_spring_2006 = timerange('2006-09-01', '2006-12-01'); % Spring: Sept 1st to Dec 1st
TR_spring_2007 = timerange('2007-09-01', '2007-12-01');
TR_spring_2008 = timerange('2008-09-01', '2008-12-01');
TR_spring_2009 = timerange('2009-09-01', '2009-12-01');
TR_spring_2010 = timerange('2010-09-01', '2010-12-01');
TR_spring_2011 = timerange('2011-09-01', '2011-12-01');
TR_spring_2012 = timerange('2012-09-01', '2012-12-01');
TR_spring_2013 = timerange('2013-09-01', '2013-12-01');
TR_spring_2014 = timerange('2014-09-01', '2014-12-01');
TR_spring_2015 = timerange('2015-09-01', '2015-12-01');
TR_spring_2016 = timerange('2016-09-01', '2016-12-01');
TR_spring_2017 = timerange('2017-09-01', '2017-12-01');
TR_spring_2018 = timerange('2018-09-01', '2018-12-01');
% 13
TR_summer_2006 = timerange('2006-12-01', '2007-03-01'); % Summer: Dec 1st to March 1st
TR_summer_2007 = timerange('2007-12-01', '2008-03-01');
TR_summer_2008 = timerange('2008-12-01', '2009-03-01');
TR_summer_2009 = timerange('2009-12-01', '2010-03-01');
TR_summer_2010 = timerange('2010-12-01', '2011-03-01');
TR_summer_2011 = timerange('2011-12-01', '2012-03-01');
TR_summer_2012 = timerange('2012-12-01', '2013-03-01');
TR_summer_2013 = timerange('2013-12-01', '2014-03-01');
TR_summer_2014 = timerange('2014-12-01', '2015-03-01');
TR_summer_2015 = timerange('2015-12-01', '2016-03-01');
TR_summer_2016 = timerange('2016-12-01', '2017-03-01');
TR_summer_2017 = timerange('2017-12-01', '2018-03-01');
TR_summer_2018 = timerange('2018-12-01', '2019-01-01');
% 13
% TR_fall_2006 = timerange('2006-03-01', '2006-06-01'); % there
% is no CALIPSO DATA in fall of 2006
TR_fall_2007 = timerange('2007-03-01', '2007-06-01'); %% Fall: March 1st to June 1st
TR_fall_2008 = timerange('2008-03-01', '2008-06-01');
TR_fall_2009 = timerange('2009-03-01', '2009-06-01');
TR_fall_2010 = timerange('2010-03-01', '2010-06-01');
TR_fall_2011 = timerange('2011-03-01', '2011-06-01');
TR_fall_2012 = timerange('2012-03-01', '2012-06-01');
TR_fall_2013 = timerange('2013-03-01', '2013-06-01');
TR_fall_2014 = timerange('2014-03-01', '2014-06-01');
TR_fall_2015 = timerange('2015-03-01', '2015-06-01');
TR_fall_2016 = timerange('2016-03-01', '2016-06-01');
TR_fall_2017 = timerange('2017-03-01', '2017-06-01');
TR_fall_2018 = timerange('2018-03-01', '2018-06-01');
% 12
% 51 seasons in total across June 2006 to Dec 2018
%%
Total_CMOD_winter = [];
Total_Lat_CMOD_winter = [];
Total_Lon_CMOD_winter = [];
Total_CMOD_spring = [];
Total_Lat_CMOD_spring = [];
Total_Lon_CMOD_spring = [];
Total_CMOD_summer = [];
Total_Lat_CMOD_summer = [];
Total_Lon_CMOD_summer = [];
Total_CMOD_fall = [];
Total_Lat_CMOD_fall = [];
Total_Lon_CMOD_fall = [];
Total_Ice_winter = [];
Total_Lat_Ice_winter = [];
Total_Lon_Ice_winter = [];
Total_Ice_spring = [];
Total_Lat_Ice_spring = [];
Total_Lon_Ice_spring = [];
Total_Ice_summer = [];
Total_Lat_Ice_summer = [];
Total_Lon_Ice_summer = [];
Total_Ice_fall = [];
Total_Lat_Ice_fall = [];
Total_Lon_Ice_fall = [];
Total_Wind_winter = [];
Total_Lat_Wind_winter = [];
Total_Lon_Wind_winter = [];
Total_Wind_spring = [];
Total_Lat_Wind_spring = [];
Total_Lon_Wind_spring = [];
Total_Wind_summer = [];
Total_Lat_Wind_summer = [];
Total_Lon_Wind_summer = [];
Total_Wind_fall = [];
Total_Lat_Wind_fall = [];
Total_Lon_Wind_fall = [];
clear CMOD_SEASONS SeaIce_SEASONS Winds_SEASONS
for i = 2006:2018
disp(i)
SEASON = {'fall','winter', 'spring', 'summer'};
for j = 1:length(SEASON)
disp(j)
% [eval(sprintf('CMOD_Bin_%d_winter', i)), eval(sprintf('night_%d_winter_occ', i)),...
% eval(sprintf('night_%d_winter_std')), eval(sprintf('night_%d_winter_err', i))] = ...
if exist(sprintf('TR_%s_%d', SEASON{j}, i),'var') % only keep looping if the variable actually exists
% TR_fall_2006 does not exist, which is why I need this
% statement in here. It will skip fall 2006, which doesn't
% exist, and start with winter 2006, proceeding onwards until
% end of the timeframe..
eval(sprintf('Lat_CMOD = Total_timetable_CMOD_Surface(TR_%s_%d,:).Total_Latitude_Surface;', SEASON{j},i))
eval(sprintf('Lon_CMOD = Total_timetable_CMOD_Surface(TR_%s_%d, :).Total_Longitude_Surface;',SEASON{j}, i))
eval(sprintf('OD = Total_timetable_CMOD_Surface(TR_%s_%d, :).CMOD_Surface;', SEASON{j}, i))
eval(sprintf('Lat_Ice = Total_timetable_Depol_Ratio(TR_%s_%d,:).Total_Latitude_Ice;', SEASON{j},i))
eval(sprintf('Lon_Ice = Total_timetable_Depol_Ratio(TR_%s_%d,:).Total_Longitude_Ice;', SEASON{j},i))
eval(sprintf('Ice = Total_timetable_Depol_Ratio(TR_%s_%d,:).Total_Surface_532_Integrated_Depolarization_Ratio;', SEASON{j},i))
eval(sprintf('Lat_Wind = Total_timetable_amsrmf(TR_%s_%d,:).Total_Latitude_Wind;', SEASON{j}, i))
eval(sprintf('Lon_Wind = Total_timetable_amsrmf(TR_%s_%d,:).Total_Longitude_Wind;', SEASON{j}, i))
eval(sprintf('Wind = Total_timetable_amsrmf(TR_%s_%d,:).Total_windamsrMF;', SEASON{j}, i))
[CMOD, CMOD_OCC, CMOD_STD, CMOD_ERR] = hist_wt_occ_tot(Lat_CMOD, Lon_CMOD, OD, step_Lat', step_Lon');
[SeaIce, SeaIce_OCC, SeaIce_STD, SeaIce_ERR] = hist_wt_occ_tot(Lat_Ice, Lon_Ice, Ice, step_Lat', step_Lon');
[Winds, Winds_OCC, Winds_STD, Winds_ERR] = hist_wt_occ_tot(Lat_Wind, Lon_Wind, Wind, step_Lat', step_Lon');
% CMOD 3D Seasons Now
if ~exist('CMOD_SEASONS', 'var')
CMOD_SEASONS = CMOD;
SeaIce_SEASONS = SeaIce;
Winds_SEASONS = Winds;
CMOD_OCC_SEASONS = CMOD_OCC;
CMOD_STD_SEASONS = CMOD_STD;
CMOD_ERR_SEASONS = CMOD_ERR;
SeaIce_OCC_SEASONS = SeaIce_OCC;
SeaIce_STD_SEASONS = SeaIce_STD;
SeaIce_ERR_SEASONS = SeaIce_ERR;
Winds_OCC_SEASONS = Winds_OCC;
Winds_STD_SEASONS = Winds_STD;
Winds_ERR_SEASONS = Winds_ERR;
else
CMOD_SEASONS(:,:, end + 1) = cat(3, CMOD);
SeaIce_SEASONS(:,:, end + 1) = cat(3, SeaIce);
Winds_SEASONS(:,:, end + 1) = cat(3, Winds);
CMOD_OCC_SEASONS(:,:, end + 1) = cat(3, CMOD_OCC);
CMOD_STD_SEASONS(:,:, end + 1) = cat(3, CMOD_STD);
CMOD_ERR_SEASONS(:,:, end + 1) = cat(3, CMOD_ERR);
SeaIce_OCC_SEASONS(:,:, end + 1) = cat(3, SeaIce_OCC);
SeaIce_STD_SEASONS(:,:, end + 1) = cat(3, SeaIce_STD);
SeaIce_ERR_SEASONS(:,:, end + 1) = cat(3, SeaIce_ERR);
Winds_OCC_SEASONS(:,:, end + 1) = cat(3, Winds_OCC);
Winds_STD_SEASONS(:,:, end + 1) = cat(3, Winds_STD);
Winds_ERR_SEASONS(:,:, end + 1) = cat(3, Winds_ERR);
end
end
clear CMOD CMOD_OCC CMOD_STD CMOD_ERR SeaIce SeaIce_OCC SeaIce_STD SeaIce_ERR Winds Winds_OCC Winds_STD Winds_ERR
end
end
%%
%%
%%%%%% This was the procedure used to get seasonal ice contour lines %%%%%%
% I basically used climatological averages as the contour lines.
% Initializing of my variables for the loop below.
Total_Ice_winter = [];
Total_Lat_Ice_winter = [];
Total_Lon_Ice_winter = [];
Total_Ice_spring = [];
Total_Lat_Ice_spring = [];
Total_Lon_Ice_spring = [];
Total_Ice_summer = [];
Total_Lat_Ice_summer = [];
Total_Lon_Ice_summer = [];
Total_Ice_fall = [];
Total_Lat_Ice_fall = [];
Total_Lon_Ice_fall = [];
%
for i = 2006:2018
disp(i)
SEASON = {'winter', 'spring', 'summer', 'fall'};
for j = 1:length(SEASON)
disp(j)
% [eval(sprintf('CMOD_Bin_%d_winter', i)), eval(sprintf('night_%d_winter_occ', i)),...
% eval(sprintf('night_%d_winter_std')), eval(sprintf('night_%d_winter_err', i))] = ...
if exist(sprintf('TR_%s_%d', SEASON{j}, i),'var') % only keep looping if the variable actually exists
% TR_fall_2006 does not exist, which is why I need this
% statement in here
eval(sprintf('Lat_Ice = Total_timetable_Depol_Ratio(TR_%s_%d,:).Total_Latitude_Ice;', SEASON{j},i))
eval(sprintf('Lon_Ice = Total_timetable_Depol_Ratio(TR_%s_%d,:).Total_Longitude_Ice;', SEASON{j},i))
eval(sprintf('Ice = Total_timetable_Depol_Ratio(TR_%s_%d,:).Total_Surface_532_Integrated_Depolarization_Ratio;', SEASON{j},i))
% I dont need to filter this out anymore since the
% 'Saving_out_CMOD_Ice_Wind.m' file took care of this.
%
% bad_Ice_values = Ice <= -0.2 | Ice > 1.2;
% Ice(bad_Ice_values) = NaN;
%
% nan_ice = isnan(Ice(:,1));
% Ice = Ice(~nan_ice) ;
% Lat_Ice = Lat_Ice(~nan_ice);
% Lon_Ice = Lon_Ice(~nan_ice);
%
eval(sprintf('Lat_Wind = Total_timetable_amsrmf(TR_%s_%d,:).Total_Latitude_Wind;', SEASON{j}, i))
eval(sprintf('Lon_Wind = Total_timetable_amsrmf(TR_%s_%d,:).Total_Longitude_Wind;', SEASON{j}, i))
eval(sprintf('Wind = Total_timetable_amsrmf(TR_%s_%d,:).Total_windamsrMF;', SEASON{j}, i))
if j == 1
Total_Ice_winter = vertcat(Total_Ice_winter, Ice);
Total_Lat_Ice_winter = vertcat(Total_Lat_Ice_winter, Lat_Ice);
Total_Lon_Ice_winter = vertcat(Total_Lon_Ice_winter, Lon_Ice);
elseif j == 2
Total_Ice_spring = vertcat(Total_Ice_spring, Ice);
Total_Lat_Ice_spring = vertcat(Total_Lat_Ice_spring, Lat_Ice);
Total_Lon_Ice_spring = vertcat(Total_Lon_Ice_spring, Lon_Ice);
elseif j == 3
Total_Ice_summer = vertcat(Total_Ice_summer, Ice);
Total_Lat_Ice_summer = vertcat(Total_Lat_Ice_summer, Lat_Ice);
Total_Lon_Ice_summer = vertcat(Total_Lon_Ice_summer, Lon_Ice);
elseif j == 4
Total_Ice_fall = vertcat(Total_Ice_fall, Ice);
Total_Lat_Ice_fall = vertcat(Total_Lat_Ice_fall, Lat_Ice);
Total_Lon_Ice_fall = vertcat(Total_Lon_Ice_fall, Lon_Ice);
end
end
clear CMOD CMOD_OCC CMOD_STD CMOD_ERR
end
end
%
[Ice_one_degree_winter, Ice_OCC_winter, Ice_STD_winter, Ice_ERR_winter] = hist_wt_occ_tot(Total_Lat_Ice_winter, Total_Lon_Ice_winter, Total_Ice_winter, step_Lat', step_Lon');
[Ice_one_degree_spring, Ice_OCC_spring, Ice_STD_spring, Ice_ERR_spring] = hist_wt_occ_tot(Total_Lat_Ice_spring, Total_Lon_Ice_spring, Total_Ice_spring, step_Lat', step_Lon');
[Ice_one_degree_summer, Ice_OCC_summer, Ice_STD_summer, Ice_ERR_summer] = hist_wt_occ_tot(Total_Lat_Ice_summer, Total_Lon_Ice_summer, Total_Ice_summer, step_Lat', step_Lon');
[Ice_one_degree_fall, Ice_OCC_fall, Ice_STD_fall, Ice_ERR_fall] = hist_wt_occ_tot(Total_Lat_Ice_fall, Total_Lon_Ice_fall, Total_Ice_fall, step_Lat', step_Lon');
%
winter_contour = Ice_one_degree_winter;
spring_contour = Ice_one_degree_spring;
summer_contour = Ice_one_degree_summer;
fall_contour = Ice_one_degree_fall;
%%
%%%%% Keeping track of my seasons here %%%%%%%%%%%%
t1 = datetime(2006,06,01);
t2 = datetime(2018,12,31);
times = t1:calmonths(1):t2;
clear t1 t2
times_seasons = times(1) : calmonths(3) : times(end);
%%
% You are not using this function in the updated version of this
% manuscript, so commenting it out:
%
% CMOD_SEASONS_SMOOTHN = zeros(size(CMOD_SEASONS));
for i = 1:50
CMOD_SEASONS_SMOOTHN(:,:,i) = smoothn(CMOD_SEASONS(:,:,i), 'robust') ;
end
CMOD_SEASONS_SMOOTHN(:,:,39) = CMOD_SEASONS(:,:,39);
CMOD_SEASONS_SMOOTHN(:,:,11) = CMOD_SEASONS(:,:,11);
CMOD_SEASONS_SMOOTHN(:,:,31) = CMOD_SEASONS(:,:,31);
CMOD_SEASONS_SMOOTHN(:,:,35) = CMOD_SEASONS(:,:,35);
CMOD_SEASONS_SMOOTHN(:,:,19) = CMOD_SEASONS(:,:,19);
CMOD_SEASONS_SMOOTHN(:,:,47) = CMOD_SEASONS(:,:,47);
%%
% Throw out last month of December because it's not a full season:
CMOD_SEASONS = CMOD_SEASONS(:,:, 1:50);
% CMOD_SEASONS_SMOOTHN = CMOD_SEASONS_SMOOTHN(:,:, 1:50);
Winds_SEASONS = Winds_SEASONS(:,:,1:50);
SeaIce_SEASONS = SeaIce_SEASONS(:,:,1:50);
CHL_SEASONS = rot90(CHL_SEASONS); % this should be the correct orientation!
CHL_SEASONS = CHL_SEASONS(:,:, 1:50);
%%
% I need to find the mean of each season and then plot out how it's changing from that mean across time.
%% SeaIce Test with masking values below 0.15
SeaIce_SEASONS_masked = SeaIce_SEASONS;
SeaIce_SEASONS_masked(SeaIce_SEASONS_masked < 0.15) = NaN;
%%
%%%%%%%%% Here I start calculating the spatial correlation between seasons %%%%%%%%%
% Matrix preallocation
CMOD_CHL_RHO_MATRIX = zeros(15,46,4) ;
CMOD_CHL_PVAL_MATRIX = zeros(15,46,4) ;
CMOD_ICE_RHO_MATRIX = zeros(15,46,4) ;
CMOD_ICE_PVAL_MATRIX = zeros(15,46,4) ;
CMOD_WIND_RHO_MATRIX = zeros(15,46,4) ;
CMOD_WIND_PVAL_MATRIX = zeros(15,46,4) ;
CHL_ICE_RHO_MATRIX = zeros(15,46,4) ;
CHL_ICE_PVAL_MATRIX = zeros(15,46,4) ;
CHL_WIND_RHO_MATRIX = zeros(15,46,4) ;
CHL_WIND_PVAL_MATRIX = zeros(15,46,4) ;
WIND_ICE_RHO_MATRIX = zeros(15,46,4) ;
WIND_ICE_PVAL_MATRIX = zeros(15,46,4) ;
%%
clear x y z k
for i = 1 : length(step_Lat(1,:))
% disp(i)
for j = 1 : length(step_Lon(1,:))
% disp(j)
for s = 1:4
x = squeeze(CMOD_SEASONS(i,j,s:4:end));
y = squeeze(CHL_SEASONS(i,j,s:4:end));
z = squeeze(SeaIce_SEASONS_masked(i,j,s:4:end));
k = squeeze(Winds_SEASONS(i,j,s:4:end));
% CMOD & CHL
if sum(isnan(x)) || sum(isnan(y)) <= 3
[CMOD_CHL_RHO_MATRIX(i, j,s), CMOD_CHL_PVAL_MATRIX(i, j, s)] = corr(x, y,'Type', 'Pearson', 'rows', 'pairwise');
elseif sum(isnan(x)) || sum(isnan(y)) > 3
isnan([CMOD_CHL_RHO_MATRIX(i, j,s) , CMOD_CHL_PVAL_MATRIX(i, j, s)]);
end
% CMOD & Ice
if sum(isnan(x)) || sum(isnan(z)) <= 3
[CMOD_ICE_RHO_MATRIX(i, j,s), CMOD_ICE_PVAL_MATRIX(i, j,s)] = corr(x, z, 'Type', 'Pearson', 'rows', 'pairwise');
elseif sum(isnan(x)) || sum(isnan(z)) > 3
isnan([CMOD_ICE_RHO_MATRIX(i, j,s) , CMOD_ICE_PVAL_MATRIX(i, j,s)]);
end
% CMOD & Wind
if sum(isnan(x)) || sum(isnan(k)) <= 3
[CMOD_WIND_RHO_MATRIX(i, j,s), CMOD_WIND_PVAL_MATRIX(i, j,s)] = corr(x, k, 'Type', 'Pearson', 'rows', 'pairwise');
elseif sum(isnan(x)) || sum(isnan(k)) > 3
isnan([CMOD_WIND_RHO_MATRIX(i, j,s) , CMOD_WIND_PVAL_MATRIX(i, j,s)]);
end
% CHL & Ice
if sum(isnan(z)) || sum(isnan(y)) <= 3
[CHL_ICE_RHO_MATRIX(i, j,s), CHL_ICE_PVAL_MATRIX(i, j,s)] = corr(z, y, 'Type', 'Pearson', 'rows', 'pairwise');
elseif sum(isnan(z)) || sum(isnan(y)) > 3
isnan([CHL_ICE_RHO_MATRIX(i, j,s) , CHL_ICE_PVAL_MATRIX(i, j,s)]);
end
% CHL & Wind
if sum(isnan(k)) || sum(isnan(y)) <= 3
[CHL_WIND_RHO_MATRIX(i,j,s), CHL_WIND_PVAL_MATRIX(i,j,s)] = corr(k, y, 'Type', 'Pearson', 'rows', 'pairwise');
elseif sum(isnan(k)) || sum(isnan(y)) > 3
isnan([CHL_WIND_RHO_MATRIX(i,j,s) , CHL_WIND_PVAL_MATRIX(i,j,s)]);
end
% Wind & Ice
if sum(isnan(k)) || sum(isnan(z)) <= 3
[WIND_ICE_RHO_MATRIX(i,j,s), WIND_ICE_PVAL_MATRIX(i,j,s)] = corr(k, z, 'Type', 'Pearson', 'rows', 'pairwise');
elseif sum(isnan(k)) || sum(isnan(z)) > 3
isnan([WIND_ICE_RHO_MATRIX(i,j,s) , WIND_ICE_PVAL_MATRIX(i,j,s)]);
end
end
end
end
%%%%%%%%% PLOTTING OF SPATIAL CORRELATION FIGURES BELOW %%%%%%%%%%%%%%%%
%%
make_it_tight = true;
subplot = @(m,n,p) subtightplot (m, n, p, [0.08 0.08], [0.08 0.08], [0.1 0.1]);
if ~make_it_tight, clear subplot; end
fig = figure;clf;
% chl_season = rot90(Chl_a_seasons_one_degree_res);
% test_2 = smoothn(test, 'robust');
subplot(2,2,1)
plot_BSea_figure_subplot(CMOD_ICE_RHO_MATRIX(:,:,1), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Winter');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, winter_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
% clegendm(C,h,'m')
subplot(2,2,2)
plot_BSea_figure_subplot(CMOD_ICE_RHO_MATRIX(:,:,2), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Spring');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, spring_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
subplot(2,2,3)
plot_BSea_figure_subplot(CMOD_ICE_RHO_MATRIX(:,:,3), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Summer');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, summer_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
subplot(2,2,4)
plot_BSea_figure_subplot(CMOD_ICE_RHO_MATRIX(:,:,4), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Fall');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, fall_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
hp4 = get(subplot(2,2,4),'Position');
h = colorbar('Position', [hp4(1)+hp4(3)+0.02 hp4(2)+0.15 0.02 hp4(2)+hp4(3) * 1.3]);
h.FontWeight = 'bold';
h.FontSize = 15;
% hy = ylabel(h, 'CMOD & chl-{\ita} seasonal correlation coefficient', 'FontSize', 18);
hy = ylabel(h, 'MAOD & Ice seasonal correlation coefficient', 'FontSize', 18);
%%
cd /Users/srishtidasarathy/Documents/'Documents - Srishti’s MacBook Pro '/Bowman/Updated_Code_Processing_PhdPhaseOne/Srishti/Analysis_and_Vars_For_Publication/Revisions_Figures
set(gcf,'PaperPositionMode','auto')
% set(gcf,'PaperPosition','fillpage')
print(fig,'Updated_MAOD_Ice_Correlation_1_1_newcolormap_masked','-dpdf','-r300'); % *// 300 dpi
% print(gcf, 'Ju
%%
make_it_tight = true;
subplot = @(m,n,p) subtightplot (m, n, p, [0.08 0.08], [0.08 0.08], [0.1 0.1]);
if ~make_it_tight, clear subplot; end
fig = figure;clf;
% chl_season = rot90(Chl_a_seasons_one_degree_res);
% test_2 = smoothn(test, 'robust');
subplot(2,2,1)
plot_BSea_figure_subplot(CMOD_ICE_PVAL_MATRIX(:,:,1), ...
step_Lon,...
step_Lat,...
[0 0.2],...
'Winter');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, winter_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
% clegendm(C,h,'m')
subplot(2,2,2)
plot_BSea_figure_subplot(CMOD_ICE_PVAL_MATRIX(:,:,2), ...
step_Lon,...
step_Lat,...
[0 0.2],...
'Spring');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, spring_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
subplot(2,2,3)
plot_BSea_figure_subplot(CMOD_ICE_PVAL_MATRIX(:,:,3), ...
step_Lon,...
step_Lat,...
[0 0.2],...
'Summer');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, summer_contour, 'linewi', 5.5, 'LineColor',[ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
subplot(2,2,4)
plot_BSea_figure_subplot(CMOD_ICE_PVAL_MATRIX(:,:,4), ...
step_Lon,...
step_Lat,...
[0 0.2],...
'Fall');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, fall_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
hp4 = get(subplot(2,2,4),'Position');
h = colorbar('Position', [hp4(1)+hp4(3)+0.02 hp4(2)+0.15 0.02 hp4(2)+hp4(3) * 1.3]);
h.FontWeight = 'bold';
h.FontSize = 15;
% hy = ylabel(h, 'CMOD & chl-{\ita} seasonal correlation coefficient', 'FontSize', 18);
hy = ylabel(h, 'CMOD & Ice seasonal p-values', 'FontSize', 18);
%%
make_it_tight = true;
subplot = @(m,n,p) subtightplot (m, n, p, [0.08 0.08], [0.08 0.08], [0.1 0.1]);
if ~make_it_tight, clear subplot; end
fig = figure;clf;
% chl_season = rot90(Chl_a_seasons_one_degree_res);
% test_2 = smoothn(test, 'robust');
subplot(3, 1, 1 )
plot_BSea_figure_subplot(CMOD_CHL_RHO_MATRIX(:,:,2), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Spring');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, spring_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
subplot(3,1, 2)
plot_BSea_figure_subplot(CMOD_CHL_RHO_MATRIX(:,:,3), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Summer');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, summer_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
subplot(3,1, 3)
plot_BSea_figure_subplot(CMOD_CHL_RHO_MATRIX(:,:,4), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Fall');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, fall_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
hp4 = get(subplot(3,1, 3),'Position');
h = colorbar('Position', [hp4(1)+(hp4(3)-0.2) 0.33 0.02 0.4]);
h.FontWeight = 'bold';
h.FontSize = 15;
hy = ylabel(h, 'MAOD & chl-{\ita} seasonal correlation coefficient', 'FontSize', 18);
% hy = ylabel(h, 'CMOD & Ice seasonal correlation coefficient', 'FontSize', 18);
%%
set(gcf,'PaperPositionMode','auto')
% set(gcf,'PaperPosition','fillpage')
print(fig,'Updated_MAOD_CHLA_Correlation_1_1_newcolormap','-dpng','-r300'); % *// 300 dpi
% print(gcf, 'Ju
%%
fig = figure;clf;
% chl_season = rot90(Chl_a_seasons_one_degree_res);
% test_2 = smoothn(test, 'robust');
subplot(2,2,1)
plot_BSea_figure_subplot(CMOD_WIND_RHO_MATRIX(:,:,1), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Winter');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, winter_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13
subplot(2,2,2)
plot_BSea_figure_subplot(CMOD_WIND_RHO_MATRIX(:,:,2), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Spring');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, spring_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13
subplot(2,2,3)
plot_BSea_figure_subplot(CMOD_WIND_RHO_MATRIX(:,:,3), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Summer');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, summer_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13
subplot(2,2,4)
plot_BSea_figure_subplot(CMOD_WIND_RHO_MATRIX(:,:,4), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Fall');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, fall_contour, 'linewi', 5.5, 'LineColor',[ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13
hp4 = get(subplot(2,2,4),'Position');
h = colorbar('Position', [hp4(1)+hp4(3)+0.02 hp4(2)+0.15 0.02 hp4(2)+hp4(3) * 1.3]);
h.FontWeight = 'bold';
h.FontSize = 15;
% hy = ylabel(h, 'CMOD & chl-{\ita} seasonal correlation coefficient', 'FontSize', 18);
hy = ylabel(h, 'MAOD & Wind seasonal correlation coefficient', 'FontSize', 18);
% hy = ylabel(h, 'CMOD & Ice seasonal correlation coefficient', 'FontSize', 18);
%%
set(gcf,'PaperPositionMode','auto')
% set(gcf,'PaperPosition','fillpage')
print(fig,'Updated_MAOD_Wind_Correlation_1_1_newcolormap.png','-dpng','-r300'); % *// 300 dpi
% print(gcf, 'Ju
%%
make_it_tight = true;
subplot = @(m,n,p) subtightplot (m, n, p, [0.08 0.08], [0.08 0.08], [0.1 0.1]);
if ~make_it_tight, clear subplot; end
fig = figure;clf;
subplot(3, 1, 1)
plot_BSea_figure_subplot(CHL_ICE_RHO_MATRIX(:,:,2), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Spring');
hold on ;
[C, h] = m_contour(step_Lon, step_Lat, spring_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
subplot(3, 1, 2)
plot_BSea_figure_subplot(CHL_ICE_RHO_MATRIX(:,:,3), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Summer');
hold on ;
[C, h] = m_contour(step_Lon, step_Lat, summer_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
subplot(3, 1, 3)
plot_BSea_figure_subplot(CHL_ICE_RHO_MATRIX(:,:,4), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Fall');
hold on ;
[C, h] = m_contour(step_Lon, step_Lat, fall_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
hp4 = get(subplot(3, 1 ,3),'Position');
h = colorbar('Position', [hp4(1)+(hp4(3)-0.25) 0.2 0.02 0.6]);
h.FontWeight = 'bold';
h.FontSize = 15;
hy = ylabel(h, 'Ice & chl-{\ita} seasonal correlation coefficient', 'FontSize', 18);
%%
set(gcf,'PaperPositionMode','auto')
% set(gcf,'PaperPosition','fillpage')
print(fig,'Updated_CHLA_Ice_Correlation_newcolormap_masked','-dpng','-r300'); % *// 300 dpi
% print(gcf, 'Ju
%%
make_it_tight = true;
subplot = @(m,n,p) subtightplot (m, n, p, [0.08 0.08], [0.08 0.08], [0.1 0.1]);
if ~make_it_tight, clear subplot; end
fig = figure;clf;
subplot(2,2,1)
plot_BSea_figure_subplot(WIND_ICE_RHO_MATRIX(:,:,1), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Winter');
hold on;
[C, h] = m_contour(step_Lon, step_Lat, winter_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
% clegendm(C,h,'m')
subplot(2, 2, 2)
plot_BSea_figure_subplot(WIND_ICE_RHO_MATRIX(:,:,2), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Spring');
hold on ;
[C, h] = m_contour(step_Lon, step_Lat, spring_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);
subplot(2, 2, 3)
plot_BSea_figure_subplot(WIND_ICE_RHO_MATRIX(:,:,3), ...
step_Lon,...
step_Lat,...
redblue,...
[-1 1],...
'Summer');
hold on ;
[C, h] = m_contour(step_Lon, step_Lat, summer_contour, 'linewi', 5.5, 'LineColor', [ 0 0 0]);
h.LevelList = 0.65 ;
% clabel(C, h,'fontsize',13);