Global Index (short | long) | Local contents | Local Index (short | long)
Define ENSO years somehow here.
| This script calls | |
|---|---|
clear
cd ~/matlab/NMC/Data
load cti2.mat
ct = standardize(ct2);
yr = [(1948+1/24):1/12:(2002+5/24)];
ctlp = rave(ct, 5);
%ctlp = standardize(ctlp);
figure_tall(1); cla;
for i = 1:4;
subplot(4,1,i); cla;
tind = 180*(i-1)+[1:180];
if i == 4; tind = tind(tind <= 651); end
hh = plot(yr(tind), ct(tind), 'k', yr(tind), ctlp(tind), 'r');
set(hh, 'linewidth', 2);
axis([min(yr(tind))-1/12 min(yr(tind))+15+1/12 -3 3]);
hold on;
hline([-1 1], '--k');
hold off;
set(gca, 'XTick', 1940:2020);
grid on;
end
% Define El Nino and La Nina years
warmyr = yr(find(ctlp > 1));
unique(floor(warmyr)) % Evaluate individual years to determine which
% are El Nino years. Make sure there are at
% least 3 months of continuous positive (>1std)
% ctlp, to define.
warmyr = [1957 1963 1965 1968 1969 1972 1976 1982 1986 1987 1991 1994 ...
1997];
coldyr = yr(find(ctlp < -1));
unique(floor(coldyr)) % as above
coldyr = [1949 1955 1964 1970 1973 1975 1984 1988 1998 1999];
% Now, plot CTI for these years.
nwy = length(warmyr);
warmind = repmat(NaN, nwy, 25);
for i = 1:nwy;
warmind(i,:) = 12*(warmyr(i)-1948+1)+1+[-12:12];
end
ctwarm = ct(warmind);
ncy = length(coldyr);
coldind = repmat(NaN, ncy, 25);
for i = 1:ncy;
coldind(i,:) = 12*(coldyr(i)-1948+1)+1+[-12:12];
end
ctcold = ct(coldind);
figure_tall(2); clf;
global_axes(6.5, 4, 0.7, 0.5, 1.3);
subplot2(1,1); cla
hh = plot(-12:12, ctwarm', '-', -12:12, mean(ctwarm), '--k');
set(hh(nwy+1), 'linewidth', 3);
axis([-15 15 -3 4]);
for i = 1:nwy;
t1 = text(-12.2, ctwarm(i,1), num2str(warmyr(i)));
set(t1, 'horizontalalignment', 'right', 'fontsize', 8);
t2 = text(12.2, ctwarm(i,end), num2str(warmyr(i)+1));
set(t2, 'horizontalalignment', 'left', 'fontsize', 8);
end
t3 = title('\bf CTI for El Nino Events', 'fontsize', 12);
set(gca, 'XTick', -13:3:11, 'YTick', -3:4);
hold on;
vline([-10:3:11], ':k');
hline([-2:3], ':k', [-12 12]);
hold off;
subplot2(1,2); cla
hh = plot(-12:12, ctcold', '-', -12:12, mean(ctcold), '--k');
set(hh(ncy+1), 'linewidth', 3);
axis([-15 15 -3 4]);
for i = 1:nwy;
t1 = text(-12.2, ctcold(i,1), num2str(coldyr(i)));
set(t1, 'horizontalalignment', 'right', 'fontsize', 8);
t2 = text(12.2, ctcold(i,end), num2str(coldyr(i)+1));
set(t2, 'horizontalalignment', 'left', 'fontsize', 8);
end
t3 = title('\bf CTI for La Nina Events', 'fontsize', 12);
set(gca, 'XTick', -13:3:11, 'YTick', -3:4);
hold on;
vline([-10:3:11], ':k');
hline([-2:3], ':k', [-12 12]);
hold off;
% Now, have a look at some composites
% Start with SST
tim = 1:648;
lims = [0 360 -75 75];
cd /home/disk/tao/data/nmc.reanalysis/monthly
[dat, lat, lon] = getnc2('skt.mon.mean.nc', 'skt', lims, 1, tim);
[ntim, nlat, nlon] = size(dat);
dat = annave(dat); % Just assume grand mean is deleted
if 0;
dat2 = repmat(NaN, size(dat));
for i = 1:12;
ind = i-1+[1:12:ntim];
dat2(ind,:,:) = lin_remove(dat(ind,:,:), ct(ind));
dat2(ind,:,:) = standardize(dat2(ind,:,:));
end
end
dat2 = standardize(dat);
datw1 = repmat(NaN, [8 nlat nlon]);
datw2 = datw1;
datc1 = datw1;
datc2 = datw1;
for i = 1:8;
ind = 3*(i-1)+[2:4];
tind = warmind(:,ind);
tind = tind(:);
datw1(i,:,:) = mean(dat(tind,:,:));
datw2(i,:,:) = mean(dat2(tind,:,:));
tind = coldind(:,ind);
tind = tind(:);
datc1(i,:,:) = mean(dat(tind,:,:));
datc2(i,:,:) = mean(dat2(tind,:,:));
end
% Now, plot the data
figure_tall(3); clf
global_axes(6.5, 3.75, 1, 0.5, 1.5);
global_latlon(lat, lon, lims);
seas = cell(8,1);
[seas{1}, seas{2}, seas{3}] = deal('FMA (-1)', 'MJJ (-1)', 'ASO (-1)');
[seas{4}, seas{5}, seas{6}] = deal('NDJ (-1)', 'FMA (0)', 'MJJ (0)');
[seas{7}, seas{8}] = deal('ASO (0)', 'NDJ (0)');
cint = 0.5;
for num = 1:8;
figure_tall(num); clf;
subplot2(1,1); cla;
map_axis('giso');
[cc1, hh1] = map_contour_pn(datw1(num,:,:), 0.5);
tem = squeeze(datw2(num,:,:));
tem(abs(tem) < 0.2) = NaN;
hold on;
map_surface(tem, -0.5);
hold off;
caxis([-1 1]);
fill_landmap(-1);
gridm on; tightmap;
framem on; set(gca, 'visible', 'off');
colorbar2;
t1 = title(['\bf El Nino Composite: Months ' char(seas{num})]);
set(t1, 'visible', 'on', 'fontsize', 12);
xl = xlabel(['Contour Interval: ' num2str(cint) '^oC']);
set(xl, 'visible', 'on', 'fontsize', 10);
subplot2(1,2); cla;
map_axis('giso');
[cc1, hh1] = map_contour_pn(datc1(num,:,:), 0.5);
tem = squeeze(datc2(num,:,:));
tem(abs(tem) < 0.2) = NaN;
hold on;
map_surface(tem, -0.5);
hold off;
caxis([-1 1]);
fill_landmap(-1);
gridm on; tightmap;
framem on; set(gca, 'visible', 'off');
colorbar2;
t1 = title(['\bf La Nina Composite: Months ' char(seas{num})]);
set(t1, 'visible', 'on', 'fontsize', 12);
xl = xlabel(['Contour Interval: ' num2str(cint) '^oC']);
set(xl, 'visible', 'on', 'fontsize', 10);
% cd /home/disk/tao/dvimont/matlab/NMC/ENSO_Composite_Plots
% eval(['print -dpsc2 -painters SST_num_' num2str(num) '_comp.ps']);
end
% SLP
tim = 1:648;
lims = [0 360 -75 75];
cd /home/disk/tao/data/nmc.reanalysis/monthly
[dat, lat, lon] = getnc2('slp.mon.mean.nc', 'slp', lims, 1, tim);
[ntim, nlat, nlon] = size(dat);
dat = annave(dat); % Just assume grand mean is deleted
if 0;
dat2 = repmat(NaN, size(dat));
for i = 1:12;
ind = i-1+[1:12:ntim];
dat2(ind,:,:) = lin_remove(dat(ind,:,:), ct(ind));
dat2(ind,:,:) = standardize(dat2(ind,:,:));
end
end
dat2 = standardize(dat);
datw1 = repmat(NaN, [8 nlat nlon]);
datw2 = datw1;
datc1 = datw1;
datc2 = datw1;
for i = 1:8;
ind = 3*(i-1)+[2:4];
tind = warmind(:,ind);
tind = tind(:);
datw1(i,:,:) = mean(dat(tind,:,:));
datw2(i,:,:) = mean(dat2(tind,:,:));
tind = coldind(:,ind);
tind = tind(:);
datc1(i,:,:) = mean(dat(tind,:,:));
datc2(i,:,:) = mean(dat2(tind,:,:));
end
% Now, plot the data
figure_tall(3); clf
global_axes(6.5, 3.75, 1, 0.5, 1.5);
global_latlon(lat, lon, lims);
seas = cell(8,1);
[seas{1}, seas{2}, seas{3}] = deal('FMA (-1)', 'MJJ (-1)', 'ASO (-1)');
[seas{4}, seas{5}, seas{6}] = deal('NDJ (-1)', 'FMA (0)', 'MJJ (0)');
[seas{7}, seas{8}] = deal('ASO (0)', 'NDJ (0)');
cint = 0.5;
for num = 1:8;
figure_tall(num); clf;
subplot2(1,1); cla;
map_axis('giso');
[cc1, hh1] = map_contour_pn(datw1(num,:,:), 0.5);
tem = squeeze(datw2(num,:,:));
tem(abs(tem) < 0.2) = NaN;
hold on;
map_surface(tem, -0.5);
hold off;
caxis([-1 1]);
fill_landmap(-1);
gridm on; tightmap;
framem on; set(gca, 'visible', 'off');
colorbar2;
t1 = title(['\bf El Nino Composite: Months ' char(seas{num})]);
set(t1, 'visible', 'on', 'fontsize', 12);
xl = xlabel(['Contour Interval: ' num2str(cint) '^oC']);
set(xl, 'visible', 'on', 'fontsize', 10);
subplot2(1,2); cla;
map_axis('giso');
[cc1, hh1] = map_contour_pn(datc1(num,:,:), 0.5);
tem = squeeze(datc2(num,:,:));
tem(abs(tem) < 0.2) = NaN;
hold on;
map_surface(tem, -0.5);
hold off;
caxis([-1 1]);
fill_landmap(-1);
gridm on; tightmap;
framem on; set(gca, 'visible', 'off');
colorbar2;
t1 = title(['\bf La Nina Composite: Months ' char(seas{num})]);
set(t1, 'visible', 'on', 'fontsize', 12);
xl = xlabel(['Contour Interval: ' num2str(cint) '^oC']);
set(xl, 'visible', 'on', 'fontsize', 10);
% cd /home/disk/tao/dvimont/matlab/NMC/ENSO_Composite_Plots
% eval(['print -dpsc2 -painters SLP_num_' num2str(num) '_comp.ps']);
end
% OLR
tim = 1:327;
lims = [0 360 -75 75];
cd /home/disk/tao/data/olr/interpolated
[dat, lat, lon] = getnc2('olrint.monthly.jun74aug01.nc', 'olr', ...
lims, 1, tim);
[ntim, nlat, nlon] = size(dat);
dat = annave(dat); % Just assume grand mean is deleted
if 1;
dat2 = repmat(NaN, size(dat));
for i = 1:12;
disp(['Iteration ' num2str(i) ' of 12'])
ind = [i:12:ntim];
tem = find(~isnan(dat(ind,1,1)));
ind2 = ind(tem);
dat2(ind2,:,:) = lin_remove(dat(ind2,:,:), ct(ind2+12*(1974-1948)+5));
dat2(ind2,:,:) = standardize(dat2(ind2,:,:));
end
end
% dat2 = standardize_NaN(dat);
datw1 = repmat(NaN, [8 nlat nlon]);
datw2 = datw1;
datc1 = datw1;
datc2 = datw1;
olrtim = tim+12*(1974-1948)+5;
for i = 1:8;
ind = 3*(i-1)+[2:4];
tind = warmind(:,ind);
tind = tind(:);
tind = intersect(tind, olrtim)-(12*(1974-1948)+5);
datw1(i,:,:) = mean2(dat(tind,:,:));
datw2(i,:,:) = mean2(dat2(tind,:,:));
tind = coldind(:,ind);
tind = tind(:);
tind = intersect(tind, olrtim)-(12*(1974-1948)+5);
datc1(i,:,:) = mean2(dat(tind,:,:));
datc2(i,:,:) = mean2(dat2(tind,:,:));
end
% Now, plot the data
figure_tall(3); clf
global_axes(6.5, 3.75, 1, 0.5, 1.5);
global_latlon(lat, lon, lims);
seas = cell(8,1);
[seas{1}, seas{2}, seas{3}] = deal('FMA (-1)', 'MJJ (-1)', 'ASO (-1)');
[seas{4}, seas{5}, seas{6}] = deal('NDJ (-1)', 'FMA (0)', 'MJJ (0)');
[seas{7}, seas{8}] = deal('ASO (0)', 'NDJ (0)');
cint = 2.5;
for num = 1:8;
figure_tall(num); clf;
subplot2(1,1); cla;
map_axis('giso');
tem = squeeze(datw1(num,:,:));
tem = smooth([1 2 1], tem')';
[cc1, hh1] = map_contour_pn(tem, cint);
tem = squeeze(datw2(num,:,:));
tem(abs(tem) < 0.2) = NaN;
hold on;
map_surface(tem, -0.5);
hold off;
caxis([-1 1]);
fill_landmap(-1);
gridm on; tightmap;
framem on; set(gca, 'visible', 'off');
colorbar2;
t1 = title(['\bf El Nino Composite: Months ' char(seas{num})]);
set(t1, 'visible', 'on', 'fontsize', 12);
xl = xlabel(['Contour Interval: ' num2str(cint) '^oC']);
set(xl, 'visible', 'on', 'fontsize', 10);
subplot2(1,2); cla;
map_axis('giso');
tem = squeeze(datc1(num,:,:));
tem = smooth([1 2 1], tem')';
[cc1, hh1] = map_contour_pn(tem, cint);
tem = squeeze(datc2(num,:,:));
tem(abs(tem) < 0.2) = NaN;
hold on;
map_surface(tem, -0.5);
hold off;
caxis([-1 1]);
fill_landmap(-1);
gridm on; tightmap;
framem on; set(gca, 'visible', 'off');
colorbar2;
t1 = title(['\bf La Nina Composite: Months ' char(seas{num})]);
set(t1, 'visible', 'on', 'fontsize', 12);
xl = xlabel(['Contour Interval: ' num2str(cint) '^oC']);
set(xl, 'visible', 'on', 'fontsize', 10);
% cd /home/disk/tao/dvimont/matlab/NMC/ENSO_Composite_Plots
% eval(['print -dpsc2 -painters SLP_num_' num2str(num) '_comp.ps']);
end