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Copy pathAllVars_Climatology_and_ClimatologyTimeSeries_v3.m
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AllVars_Climatology_and_ClimatologyTimeSeries_v3.m
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% Here I plot out climatologies both spatially and temporally. Spatial
% climatologies will show seasonal patterns, and temporal climatologies
% will show monthly patterns. All variables of interest are analyzed
% within, including MAOD, chl-a, Ice, and wind speed.
%%
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_Depol_Ratio.mat')
load('Total_timetable_CMOD_Surface.mat')
cd /Users/srishtidasarathy/Documents/'Documents - Srishti’s MacBook Pro '/Bowman/Updated_Code_Processing_PhdPhaseOne/New_mat_files_CHL_A_DATA_MONTHLY
load('Aqua.mat')
load('Aqua_Longitude_Subset_BellingshausenSea.mat')
load('Aqua_Latitude_Subset_BellingshausenSea.mat')
load('Master_chlor_a_monthly_full_res.mat')
cd /Users/srishtidasarathy/Documents/'Documents - Srishti’s MacBook Pro '/Bowman/Updated_Code_Processing_PhdPhaseOne/Srishti/Analysis_and_Vars_For_Publication
t1 = datetime(2006,06,01);
t2 = datetime(2018,12,31);
times = t1:calmonths(1):t2;
clear t1 t2
OPTIONS.MaxIter = 1000;
cd /Users/srishtidasarathy/Documents/'Documents - Srishti’s MacBook Pro '/Bowman/Updated_Code_Processing_PhdPhaseOne/Srishti/Analysis_and_Vars_For_Publication/Revisions_Figures
%%
Aqua_Lat = (linspace(Latitude_subset(1), Latitude_subset(end), 15)) ;
Aqua_Lon = (linspace(Longitude_subset(1), Longitude_subset(end), 46));
Aqua_Lat = flip(Aqua_Lat); % this is for plotting purposes because pcolor flips image on y axis.
%%
nAqua_Lat = Latitude_subset(1) : -1 : Latitude_subset(end) ;
nAqua_Lon = Longitude_subset(1) : 1 : Longitude_subset(end);
nAqua_Lat = flip(nAqua_Lat) ;
%%
% I can index out the chlorophyll master array which is 1104 x 360 x 151
% into separate seasons for Winter, Spring, Summer, & Fall
% After that, the climatology would just be the average of those seasons.
% For Winter:
t1 = datetime(2006,06,01);
t2 = datetime(2018,12,31);
times = t1:calmonths(1):t2;
times = times';
[winter_x, winter_y] = find(times.Month >= 6 & times.Month <= 8);
% Can check if this worked by typing 'times(winter_x)' in command window
times(winter_x)
Chl_a_winter = Master_chl_a;
Chl_a_winter = Chl_a_winter(:,:,winter_x);
% For Spring:
[spring_x, spring_y] = find(times.Month >= 9 & times.Month <= 11);
times(spring_x)
Chl_a_spring = Master_chl_a;
Chl_a_spring = Chl_a_spring(:,:, spring_x);
% For Summer:
[summer_x, summer_y] = find(times.Month >= 1 & times.Month <=2 | times.Month == 12);
times(summer_x)
Chl_a_summer = Master_chl_a;
Chl_a_summer = Chl_a_summer(:,:, summer_x);
% For Fall:
[fall_x, fall_y] = find(times.Month >= 3 & times.Month <= 5);
times(fall_x)
Chl_a_fall = Master_chl_a;
Chl_a_fall = Chl_a_fall(:,:, fall_x);
% So now for the raw and smoothn climatologies, you can average all of
% these and plot... (for raw) or average all of them and then smoothn on
% the 2D.
Chl_a_winter_mean = mean(Chl_a_winter,3 ,'omitnan');
Chl_a_spring_mean = mean(Chl_a_spring, 3 , 'omitnan');
Chl_a_summer_mean = mean(Chl_a_summer, 3, 'omitnan');
Chl_a_fall_mean = mean(Chl_a_fall, 3, 'omitnan');
%% Adjust resolution
%
% step_Lat = Latitude_subset(1) : -1 : Latitude_subset(end) ;
% step_Lon = Longitude_subset(1) : 1 : Longitude_subset(end);
% step_Lat = flip(step_Lat);
step_Lon = Aqua_Lon;
step_Lat = Aqua_Lat;
fun = @(block_struct) nanmean(block_struct.data, [ 1 2]);
Chl_a_winter_mean_one_degree_res = blockproc(Chl_a_winter_mean,...
[length(Chl_a_winter_mean(:,1)) ./ length(Aqua_Lon) length(Chl_a_winter_mean(1,:)) ./ length(Aqua_Lat)], fun);
Chl_a_spring_mean_one_degree_res = blockproc(Chl_a_spring_mean,...
[length(Chl_a_winter_mean(:,1)) ./ length(Aqua_Lon) length(Chl_a_winter_mean(1,:)) ./ length(Aqua_Lat)], fun);
Chl_a_summer_mean_one_degree_res = blockproc(Chl_a_summer_mean,...
[length(Chl_a_winter_mean(:,1)) ./ length(Aqua_Lon) length(Chl_a_winter_mean(1,:)) ./ length(Aqua_Lat)], fun);
Chl_a_fall_mean_one_degree_res = blockproc(Chl_a_fall_mean,...
[length(Chl_a_winter_mean(:,1)) ./ length(Aqua_Lon) length(Chl_a_winter_mean(1,:)) ./ length(Aqua_Lat)], fun);
%
% Chl_a_winter_mean_one_degree_res = BlockMean(Chl_a_winter_mean,...
% (length(Longitude_subset) ./ length(step_Lon)) ,...
% length(Latitude_subset) ./ length(step_Lat));
%
% Chl_a_spring_mean_one_degree_res = BlockMean(Chl_a_spring_mean,...
% (length(Longitude_subset) ./ length(step_Lon)) ,...
% length(Latitude_subset) ./ length(step_Lat));
%
% Chl_a_summer_mean_one_degree_res = BlockMean(Chl_a_summer_mean,...
% (length(Longitude_subset) ./ length(step_Lon)) ,...
% length(Latitude_subset) ./ length(step_Lat));
%
% Chl_a_fall_mean_one_degree_res = BlockMean(Chl_a_fall_mean,...
% (length(Longitude_subset) ./ length(step_Lon)) ,...
% length(Latitude_subset) ./ length(step_Lat));
% climatology chl raw full degree Res
Chl_a_summer_mean_rot = rot90(Chl_a_summer_mean);
Chl_a_spring_mean_rot = rot90(Chl_a_spring_mean);
Chl_a_fall_mean_rot = rot90(Chl_a_fall_mean);
Chl_a_winter_mean_rot = rot90(Chl_a_winter_mean);
% climatology chl raw one degree res
Chl_a_summer_mean_rot = rot90(Chl_a_summer_mean_one_degree_res);
Chl_a_spring_mean_rot = rot90(Chl_a_spring_mean_one_degree_res);
Chl_a_fall_mean_rot = rot90(Chl_a_fall_mean_one_degree_res);
Chl_a_winter_mean_rot = rot90(Chl_a_winter_mean_one_degree_res);
%% plot climatology chl raw figures full resolution:
%%
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_a_spring_mean_rot, ...
step_Lon,...
step_Lat,...
cmocean('algae'), ...
[0 1],...
'Spring');
subplot(3,1,2)
plot_BSea_figure_subplot(Chl_a_summer_mean_rot, ...
step_Lon,...
step_Lat,...
cmocean('algae'), ...
[0 1],...
'Summer');
subplot(3,1,3)
plot_BSea_figure_subplot(Chl_a_fall_mean_rot, ...
step_Lon,...
step_Lat,...
cmocean('algae'), ...
[0 1],...
'Fall');
% subplot(2,2,1)
% plot_BSea_figure_subplot(Chl_a_winter_mean_rot, ...
% step_Lon,...
% step_Lat,...
% 'algae', ...
% [0 1.5],...
% 'Winter');
% saveas(gcf, 'Chlorophyll_one_deg_winter_smoothn.png');
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, 'CMOD & chl-{\ita} seasonal correlation coefficient', 'FontSize', 18);
hy = ylabel(h, sprintf('mg m^{-3}'), 'FontSize', 18);
% hy.FontSize = 18;
%%
set(gcf,'PaperPositionMode','auto')
% set(gcf,'PaperPosition','fillpage')
print(gcf,'Updated_CHLA_Climatology_1_1','-dpng','-r300'); % *// 300 dpi
%%
% %% trying to subplot seasonal climatologies so that they are all in the same figure.
%
% % now smoothn full res files, and adjust the resolution
%
% Chl_a_winter_mean_smoothn = smoothn(Chl_a_winter_mean, 'robust', OPTIONS);
% Chl_a_spring_mean_smoothn = smoothn(Chl_a_spring_mean, 'robust', OPTIONS);
% Chl_a_summer_mean_smoothn = smoothn(Chl_a_summer_mean, 'robust', OPTIONS);
% Chl_a_fall_mean_smoothn = smoothn(Chl_a_fall_mean, 'robust', OPTIONS);
%
% Chl_a_winter_mean_one_degree_smoothn = BlockMean(Chl_a_winter_mean_smoothn,...
% (length(Longitude_subset) ./ length(step_Lon)) ,...
% length(Latitude_subset) ./ length(step_Lat));
%
% Chl_a_spring_mean_one_degree_smoothn = BlockMean(Chl_a_spring_mean_smoothn,...
% (length(Longitude_subset) ./ length(step_Lon)) ,...
% length(Latitude_subset) ./ length(step_Lat));
%
% Chl_a_summer_mean_one_degree_smoothn = BlockMean(Chl_a_summer_mean_smoothn,...
% (length(Longitude_subset) ./ length(step_Lon)) ,...
% length(Latitude_subset) ./ length(step_Lat));
%
% Chl_a_fall_mean_one_degree_smoothn = BlockMean(Chl_a_fall_mean_smoothn,...
% (length(Longitude_subset) ./ length(step_Lon)) ,...
% length(Latitude_subset) ./ length(step_Lat));
%
% % chl vars: gaps from full res interpolated before constructing one degree
% % res figures.
%
% % one degree Res vars:
% Chl_a_winter_mean_smoothn_rot = rot90(Chl_a_winter_mean_one_degree_smoothn);
% Chl_a_spring_mean_smoothn_rot = rot90(Chl_a_spring_mean_one_degree_smoothn);
% Chl_a_summer_mean_smoothn_rot = rot90(Chl_a_summer_mean_one_degree_smoothn);
% Chl_a_fall_mean_smoothn_rot = rot90(Chl_a_fall_mean_one_degree_smoothn);
%%
% If you want the image to have land pixels masked, load 'WAP_landmask_updated.mat', below. I felt this was
% unecessary for the purpose of visualizaiton.
% cd /Users/srishtidasarathy/Documents/Bowman/Updated_Code_Processing_PhdPhaseOne/LandPoints
% load('WAP_landmask_updated.mat')
%%
% winter = WAP_landmask_updated .* Chl_a_winter_mean_smoothn_rot;
% spring = WAP_landmask_updated .* Chl_a_spring_mean_smoothn_rot;
% summer = WAP_landmask_updated.*Chl_a_summer_mean_smoothn_rot;
% fall = WAP_landmask_updated .* Chl_a_fall_mean_smoothn_rot;
% % one degree res...
% winter = Chl_a_winter_mean_smoothn_rot;
% spring = Chl_a_spring_mean_smoothn_rot;
% summer = Chl_a_summer_mean_smoothn_rot;
% fall = Chl_a_fall_mean_smoothn_rot;
%
% %%
%
% % here i'm plotting out the full res chl-climatologies that have also been
% % interpolated
%
% 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(2,2,3)
% plot_BSea_figure_subplot(summer, ...
% Aqua_Lon,...
% Aqua_Lat,...
% 'algae', ...
% [0 1.5],...
% 'Summer');
%
% subplot(2,2,2)
% plot_BSea_figure_subplot(spring, ...
% Aqua_Lon,...
% Aqua_Lat,...
% 'algae', ...
% [0 1.5],...
% 'Spring');
%
% subplot(2,2,4)
% plot_BSea_figure_subplot(fall, ...
% Aqua_Lon,...
% Aqua_Lat,...
% 'algae', ...
% [0 1.5],...
% 'Fall');
%
%
% subplot(2,2,1)
% plot_BSea_figure_subplot(winter, ...
% Aqua_Lon,...
% Aqua_Lat,...
% 'algae', ...
% [0 1.5],...
% 'Winter');
%
% 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, sprintf('mg m^{-3}'), 'FontSize', 18);
% % hy.FontSize = 18;
%% 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');
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');
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');
% 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');
%%
% Initializing of my variables for the loop below.
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 = [];
%%
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_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))
% 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_CMOD_winter = vertcat(Total_CMOD_winter, OD);
Total_Lat_CMOD_winter = vertcat(Total_Lat_CMOD_winter, Lat_CMOD);
Total_Lon_CMOD_winter = vertcat(Total_Lon_CMOD_winter, Lon_CMOD);
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);
Total_Wind_winter = vertcat(Total_Wind_winter, Wind);
Total_Lat_Wind_winter = vertcat(Total_Lat_Wind_winter, Lat_Wind);
Total_Lon_Wind_winter = vertcat(Total_Lon_Wind_winter, Lon_Wind);
elseif j == 2
Total_CMOD_spring = vertcat(Total_CMOD_spring, OD);
Total_Lat_CMOD_spring = vertcat(Total_Lat_CMOD_spring, Lat_CMOD);
Total_Lon_CMOD_spring = vertcat(Total_Lon_CMOD_spring, Lon_CMOD);
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);
Total_Wind_spring = vertcat(Total_Wind_spring, Wind);
Total_Lat_Wind_spring = vertcat(Total_Lat_Wind_spring, Lat_Wind);
Total_Lon_Wind_spring = vertcat(Total_Lon_Wind_spring, Lon_Wind);
elseif j == 3
Total_CMOD_summer = vertcat(Total_CMOD_summer, OD);
Total_Lat_CMOD_summer = vertcat(Total_Lat_CMOD_summer, Lat_CMOD);
Total_Lon_CMOD_summer = vertcat(Total_Lon_CMOD_summer, Lon_CMOD);
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);
Total_Wind_summer = vertcat(Total_Wind_summer, Wind);
Total_Lat_Wind_summer = vertcat(Total_Lat_Wind_summer, Lat_Wind);
Total_Lon_Wind_summer = vertcat(Total_Lon_Wind_summer, Lon_Wind);
elseif j == 4
Total_CMOD_fall = vertcat(Total_CMOD_fall, OD);
Total_Lat_CMOD_fall = vertcat(Total_Lat_CMOD_fall, Lat_CMOD);
Total_Lon_CMOD_fall = vertcat(Total_Lon_CMOD_fall, Lon_CMOD);
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);
Total_Wind_fall = vertcat(Total_Wind_fall, Wind);
Total_Lat_Wind_fall = vertcat(Total_Lat_Wind_fall, Lat_Wind);
Total_Lon_Wind_fall = vertcat(Total_Lon_Wind_fall, Lon_Wind);
end
end
clear CMOD CMOD_OCC CMOD_STD CMOD_ERR
end
end
%%
[CMOD_one_degree_winter, CMOD_OCC_winter, CMOD_STD_winter, CMOD_ERR_winter] = hist_wt_occ_tot(Total_Lat_CMOD_winter, Total_Lon_CMOD_winter, Total_CMOD_winter, Aqua_Lat', Aqua_Lon');
[CMOD_one_degree_spring, CMOD_OCC_spring, CMOD_STD_spring, CMOD_ERR_spring] = hist_wt_occ_tot(Total_Lat_CMOD_spring, Total_Lon_CMOD_spring, Total_CMOD_spring, Aqua_Lat', Aqua_Lon');
[CMOD_one_degree_summer, CMOD_OCC_summer, CMOD_STD_summer, CMOD_ERR_summer] = hist_wt_occ_tot(Total_Lat_CMOD_summer, Total_Lon_CMOD_summer, Total_CMOD_summer, Aqua_Lat', Aqua_Lon');
[CMOD_one_degree_fall, CMOD_OCC_fall, CMOD_STD_fall, CMOD_ERR_fall] = hist_wt_occ_tot(Total_Lat_CMOD_fall, Total_Lon_CMOD_fall, Total_CMOD_fall, Aqua_Lat', Aqua_Lon');
[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, Aqua_Lat', Aqua_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, Aqua_Lat', Aqua_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, Aqua_Lat', Aqua_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, Aqua_Lat', Aqua_Lon');
[Wind_one_degree_winter, Wind_OCC_winter, Wind_STD_winter, Wind_ERR_winter] = hist_wt_occ_tot(Total_Lat_Wind_winter, Total_Lon_Wind_winter, Total_Wind_winter, Aqua_Lat', Aqua_Lon');
[Wind_one_degree_spring, Wind_OCC_spring, Wind_STD_spring, Wind_ERR_spring] = hist_wt_occ_tot(Total_Lat_Wind_spring, Total_Lon_Wind_spring, Total_Wind_spring, Aqua_Lat', Aqua_Lon');
[Wind_one_degree_summer, Wind_OCC_summer, Wind_STD_summer, Wind_ERR_summer] = hist_wt_occ_tot(Total_Lat_Wind_summer, Total_Lon_Wind_summer, Total_Wind_summer, Aqua_Lat', Aqua_Lon');
[Wind_one_degree_fall, Wind_OCC_fall, Wind_STD_fall, Wind_ERR_fall] = hist_wt_occ_tot(Total_Lat_Wind_fall, Total_Lon_Wind_fall, Total_Wind_fall, Aqua_Lat', Aqua_Lon');
%%
winter = Wind_one_degree_winter;
spring = Wind_one_degree_spring;
summer = Wind_one_degree_summer;
fall = Wind_one_degree_fall;
%%
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(2,2,3)
plot_BSea_figure_subplot(summer, ...
Aqua_Lon,...
Aqua_Lat,...
cmocean('amp'), ...
[0 13],...
'Summer');
subplot(2,2,2)
plot_BSea_figure_subplot(spring, ...
Aqua_Lon,...
Aqua_Lat,...
cmocean('amp'), ...
[0 13],...
'Spring');
subplot(2,2,4)
plot_BSea_figure_subplot(fall, ...
Aqua_Lon,...
Aqua_Lat,...
cmocean('amp'), ...
[0 13],...
'Fall');
subplot(2,2,1)
plot_BSea_figure_subplot(winter, ...
Aqua_Lon,...
Aqua_Lat,...
cmocean('amp'), ...
[0 13],...
'Winter');
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, sprintf('m s^{-1}'), 'FontSize', 18);
% hy.FontSize = 18;
%%
set(gcf,'PaperPositionMode','auto')
% set(gcf,'PaperPosition','fillpage')
print(gcf,'Updated_WindSpeed_Climatology_1_1','-dpng','-r300'); % *// 300 dpi
%%
winter = Ice_one_degree_winter;
spring = Ice_one_degree_spring;
summer = Ice_one_degree_summer;
fall = Ice_one_degree_fall;
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(2,2,3)
plot_BSea_figure_subplot(summer, ...
step_Lon,...
step_Lat,...
cmocean('Ice'), ...
[0 0.8],...
'Summer');
subplot(2,2,2)
plot_BSea_figure_subplot(spring, ...
step_Lon,...
step_Lat,...
cmocean('Ice'), ...
[0 0.8],...
'Spring');
subplot(2,2,4)
plot_BSea_figure_subplot(fall, ...
step_Lon,...
step_Lat,...
cmocean('Ice'), ...
[0 0.8],...
'Fall');
subplot(2,2,1)
plot_BSea_figure_subplot(winter, ...
step_Lon,...
step_Lat,...
cmocean('Ice'), ...
[0 0.8],...
'Winter');
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, 'Depolarization Ratio \delta', 'FontSize', 16);
% hy.FontSize = 18;
%%
set(gcf,'PaperPositionMode','auto')
% set(gcf,'PaperPosition','fillpage')
print(gcf,'Updated_Ice_Climatology_1_1','-dpng','-r300'); % *// 300 dpi
%%
% Smoothn Climatologies
%
% CMOD_winter_smoothn = smoothn(CMOD_one_degree_winter);
% CMOD_spring_smoothn = smoothn(CMOD_one_degree_spring);
% CMOD_summer_smoothn = smoothn(CMOD_one_degree_summer);
% CMOD_fall_smoothn = smoothn(CMOD_one_degree_fall);
%
%
% %%
% winter = CMOD_winter_smoothn;
% spring = CMOD_spring_smoothn;
% summer = CMOD_summer_smoothn;
% fall = CMOD_fall_smoothn;
%%
winter = CMOD_one_degree_winter;
spring = CMOD_one_degree_spring;
summer = CMOD_one_degree_summer;
fall = CMOD_one_degree_fall;
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(2,2,3)
plot_BSea_figure_subplot(summer, ...
Aqua_Lon,...
Aqua_Lat,...
cmocean('tempo'), ...
[0 .08],...
'Summer');
subplot(2,2,2)
plot_BSea_figure_subplot(spring, ...
Aqua_Lon,...
Aqua_Lat,...
cmocean('tempo'), ...
[0 .08],...
'Spring');
subplot(2,2,4)
plot_BSea_figure_subplot(fall, ...
Aqua_Lon,...
Aqua_Lat,...
cmocean('tempo'), ...
[0 .08],...
'Fall');
subplot(2,2,1)
plot_BSea_figure_subplot(winter, ...
Aqua_Lon,...
Aqua_Lat,...
cmocean('tempo'), ...
[0 .08],...
'Winter');
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, 'MAOD', 'FontSize', 18);
% hy.FontSize = 18;
%%
set(gcf,'PaperPositionMode','auto')
% set(gcf,'PaperPosition','fillpage')
print(gcf,'Updated_MAOD_Climatology_1_1','-dpng','-r300'); % *// 300 dpi
%%
% %%
% Wind_winter_smoothn = smoothn(Wind_one_degree_winter);
% Wind_spring_smoothn = smoothn(Wind_one_degree_spring);
% Wind_summer_smoothn = smoothn(Wind_one_degree_summer);
% Wind_fall_smoothn = smoothn(Wind_one_degree_fall);
%
% %%
% winter = Wind_winter_smoothn;
% spring = Wind_spring_smoothn;
% summer = Wind_summer_smoothn;
% fall = Wind_fall_smoothn;
% %
%
% %%
% 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(2,2,3)
% plot_BSea_figure_subplot(summer, ...
% step_Lon,...
% step_Lat,...
% 'amp', ...
% [0 20],...
% 'Summer');
%
% subplot(2,2,2)
% plot_BSea_figure_subplot(spring, ...
% step_Lon,...
% step_Lat,...
% 'amp', ...
% [0 20],...
% 'Spring');
%
% subplot(2,2,4)
% plot_BSea_figure_subplot(fall, ...
% step_Lon,...
% step_Lat,...
% 'amp', ...
% [0 20],...
% 'Fall');
%
%
% subplot(2,2,1)
% plot_BSea_figure_subplot(winter, ...
% step_Lon,...
% step_Lat,...
% 'amp', ...
% [0 20],...
% 'Winter');
%
% 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, sprintf('m s^{-1}'), 'FontSize', 18);
% % hy.FontSize = 18;
%% Time Series Climatologies...
cd /Users/srishtidasarathy/Documents/'Documents - Srishti’s MacBook Pro '/Bowman/Updated_Code_Processing_PhdPhaseOne/Srishti/Analysis_and_Vars_For_Publication
load('Depol_Ratio_Monthly_avg_Vars.mat')
load('amsrmf_Monthly_avg_Vars.mat')
load('CMOD_Monthly_avg_Vars_Surface.mat')
cd /Users/srishtidasarathy/Documents/'Documents - Srishti’s MacBook Pro '/Bowman/Updated_Code_Processing_PhdPhaseOne/Srishti/Analysis_and_Vars_For_Publication/Revisions_Figures
t1 = datetime(2006,06,01);
t2 = datetime(2018,12,31);
times = t1:calmonths(1):t2;
t1 = datetime(2007,01,01);
t2 = datetime(2007,12,31);
times_months = t1:calmonths(1):t2;
times_months_num = month(times_months);
times = times';
Ice_Vector = double(Depol_Ratio_Monthly_avg(:,1));
Ice_Vector(117,:) = [];
CMOD_Vector = CMOD_Monthly_avg_Surface(:,1);
CMOD_Vector(117,:) = [];
Wind_Vector = amsrmf_Monthly_avg;
times_without_feb = times;
times_without_feb(117,:) = []; %
times_for_wind = times;
times_for_wind(117,:) =[];
times_for_wind(64:73,:) = [];
Wind_Vector(117,:) = [];
Wind_Vector(64:73,:)=[];
[Ac_CMOD, tc_CMOD] = climatology(CMOD_Vector,times_without_feb, 'monthly');
[Ac_Ice, tc_Ice] = climatology(Ice_Vector, times_without_feb, 'monthly');
[Ac_Wind, tc_Wind] = climatology(Wind_Vector, times_for_wind, 'monthly');
Master_chl_a(isnan(Master_chl_a)) = 0;
[Ac_Chl, tc_Chl] = climatology(Master_chl_a, times, 'monthly');
for i = 1:12
Ac_Chl_monthly(i) = mean2(Ac_Chl(:,:,i));
end
Ac_Chl_monthly(Ac_Chl_monthly <= 0) = NaN;
%%
% this is for standard deviation calculation, check cdt monthly to see what
% I did
jan_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[1], @mad);
feb_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[2], @mad);
mar_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[3], @mad);
apr_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[4], @mad);
may_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[5], @mad);
jun_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[6], @mad);
jul_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[7], @mad);
aug_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[8], @mad);
sep_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[9], @mad);
oct_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[10], @mad);
nov_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[11], @mad);
dec_CMOD_mad = monthly(CMOD_Vector,times_without_feb,[12], @mad);
[Ac_Ice, tc_Ice] = climatology(Ice_Vector, times_without_feb, 'monthly');
jan_Ice_mad = monthly(Ice_Vector,times_without_feb,[1], @mad);
feb_Ice_mad = monthly(Ice_Vector,times_without_feb,[2], @mad);
mar_Ice_mad = monthly(Ice_Vector,times_without_feb,[3], @mad);
apr_Ice_mad = monthly(Ice_Vector,times_without_feb,[4], @mad);
may_Ice_mad = monthly(Ice_Vector,times_without_feb,[5], @mad);
jun_Ice_mad = monthly(Ice_Vector,times_without_feb,[6], @mad);
jul_Ice_mad = monthly(Ice_Vector,times_without_feb,[7], @mad);
aug_Ice_mad = monthly(Ice_Vector,times_without_feb,[8], @mad);
sep_Ice_mad = monthly(Ice_Vector,times_without_feb,[9], @mad);
oct_Ice_mad = monthly(Ice_Vector,times_without_feb,[10], @mad);
nov_Ice_mad = monthly(Ice_Vector,times_without_feb,[11], @mad);
dec_Ice_mad = monthly(Ice_Vector,times_without_feb,[12], @mad);
[Ac_Wind, tc_Wind] = climatology(Wind_Vector, times_for_wind, 'monthly');
jan_Wind_mad = monthly(Wind_Vector,times_for_wind,[1], @mad);
feb_Wind_mad = monthly(Wind_Vector,times_for_wind,[2], @mad);
mar_Wind_mad = monthly(Wind_Vector,times_for_wind,[3], @mad);
apr_Wind_mad = monthly(Wind_Vector,times_for_wind,[4], @mad);
may_Wind_mad = monthly(Wind_Vector,times_for_wind,[5], @mad);
jun_Wind_mad = monthly(Wind_Vector,times_for_wind,[6], @mad);
jul_Wind_mad = monthly(Wind_Vector,times_for_wind,[7], @mad);
aug_Wind_mad = monthly(Wind_Vector,times_for_wind,[8], @mad);
sep_Wind_mad = monthly(Wind_Vector,times_for_wind,[9], @mad);
oct_Wind_mad = monthly(Wind_Vector,times_for_wind,[10], @mad);
nov_Wind_mad = monthly(Wind_Vector,times_for_wind,[11], @mad);
dec_Wind_mad = monthly(Wind_Vector,times_for_wind,[12], @mad);
% chl and standard deviation calculation
Master_chl_a(isnan(Master_chl_a)) = 0;
[Ac_Chl, tc_Chl] = climatology(Master_chl_a, times, 'monthly');
for i = 1:12
Ac_Chl_monthly(i) = mean2(Ac_Chl(:,:,i));
end
Ac_Chl_monthly(Ac_Chl_monthly <= 0) = NaN;
Ac_Chl_monthly = Ac_Chl_monthly';
for i = 1:12
disp(i)
mad_chl_monthly_2d(:,:,i) = monthly(Master_chl_a, times, [i], 'dim', 3, @mad);
end
mad_chl_monthly = nanmean(mad_chl_monthly_2d, [1 2]);
mad_chl_monthly = squeeze(mad_chl_monthly);
% jan_chl_std = monthly(Master_chl_a,times,[1], 'omitnan', @std);
% jan_chl_std =
% feb_chl_std = monthly(Master_chl_a,times,[2], 'omitnan', @std);
% mar_chl_std = monthly(Master_chl_a,times,[3], 'omitnan', @std);
% apr_chl_std = monthly(Master_chl_a,times,[4], 'omitnan', @std);
% may_chl_std = monthly(Master_chl_a,times,[5], 'omitnan', @std);
% jun_chl_std = monthly(Master_chl_a,times,[6], 'omitnan', @std);
% jul_chl_std = monthly(Master_chl_a,times,[7], 'omitnan', @std);
% aug_chl_std = monthly(Master_chl_a,times,[8], 'omitnan', @std);
% sep_chl_std = monthly(Master_chl_a,times,[9], 'omitnan', @std);
% oct_chl_std = monthly(Master_chl_a,times,[10], 'omitnan', @std);
% nov_chl_std = monthly(Master_chl_a,times,[11], 'omitnan', @std);
% dec_chl_std = monthly(Master_chl_a,times,[12], 'omitnan', @std);
%%
sienna = rgb('sienna');
gray = rgb('gray');
black = rgb('black');
grass_green = rgb('grass green');
ice_blue = rgb('sky blue');
wind_blue = rgb('scarlet');
% Create textbox
% pos = [x-start y-start x-width y-height]
%%
make_it_tight = true;
subplot = @(m,n,p) subtightplot (m, n, p, [0.035 0.05], [0.1 0.05], [0.1 0.05]);
if ~make_it_tight, clear subplot; end
fig = figure(1), clf;
ax(1) = subplot(4,1,1);
grid on
aa_splot(1:12, Ac_CMOD, 'x-',...
'linewidth', 2, ...
'Color', black,...
'MarkerSize', 9,...
'MarkerFaceColor', black,...
'MarkerEdgeColor', black);
ylabel('MAOD')
% xlabel('Months')
xlim([1,12])
ylim([0.01 0.09])
set(gca, 'ytick',0: 0.02: 0.08);
AX=findall(0,'type','axes');