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Get ppcs
| This script calls | |
|---|---|
clear
dofilt = 0;
data
load ML_SLP_eof_nhem.mat;
back
mrpcs = rpcs; mlpcs = lpcs; mhpcs = hpcs;
mrper = rper; mlper = lper; mhper = hper;
mrlds = rlds; mllds = llds; mhlds = hlds;
mrlam = rlam; mllam = llam; mhlam = hlam;
if dofilt
uselds = 1*mhlds; usepcs = 1*mhpcs;
uselims = lims;
else
uselds = 1*mrlds; usepcs = 1*mrpcs;
uselims = lims;
end
tim = 101:1000;
slp = getflx('psl', lims, tim);
if dofilt;
[b, a] = butter(9, 2/10);
slp = detrend(slp)-filtfilt(b, a, detrend(slp));
else
slp = detrend(slp);
end;
% Project lds onto slp
[ntim, nlat, nlon] = size(slp);
ppcs = reshape(slp, ntim, nlat*nlon) * uselds ./ ntim;
lims = [-0.1 360 -90 90];
sstc = getnc('temp', lims, 1, tim);
slpc = getflx('psl', lims, tim);
csirod
load ML_ANN_slp.mat;
load ML_ANN_sst.mat; sst = sst2; clear sst2;
back
lims = [-0.1 360 -90 90];
[xk, yk] = keep_var(lims, lon, lat);
slp = slp(:, yk, xk);
sst = sst(:, yk, xk);
ctc = getct;
[xkc, ykc] = keep_var([180 270 -6 6], lon, lat);
ctm = squeeze(mean2(mean2(shiftdim(sst(:,ykc,xkc), 1))));
ctc = detrend(ctc); ctm = detrend(ctm);
if dofilt;
ctm = ctm - filtfilt(b, a, ctm);
ctc = ctc - filtfilt(b, a, ctc);
end
% Get regression maps
if dofilt;
slp = filtfilt(b, a, detrend(slp)); slpc = filtfilt(b, a, detrend(slpc));
sst = filtfilt(b, a, detrend(sst)); sstc = filtfilt(b, a, detrend(sstc));
else
slp = detrend(slp); slpc = detrend(slpc);
sst = detrend(sst); sstc = detrend(sstc);
end
num = 1; pm = sign(corr(usepcs(:,num), ctm));
[reg1m, c1m] = regress_eof(slp, pm*usepcs(:,num), 0);
[reg2m, c2m] = regress_eof(sst, pm*usepcs(:,num), 0);
[reg1c, c1c] = regress_eof(slpc, pm*ppcs(:,num), 0);
[reg2c, c2c] = regress_eof(sstc, pm*ppcs(:,num), 0);
% Plot the data
[lat, lon, depth, lm] = getll('temp', lims);
default_global; FRAME = [105 295 -60 60];
figure(1); fo(1); clf;
sptalk(4,2,1); FRAME = [0 360 -1 90];
mcont3(reg1m, 0.2, 'stereo', [90 270]);
drawmap2(lm, 0.5, -100);
hold on;
mshade3(squeeze(c1m.^2), 0.25, 0.7*[1 1 1]);
hold off;
gridm on;
axis_limits;
title(['ML: Regression on NP\_PC' num2str(num)]);
sptalk(4,2,2); FRAME = [0 360 -1 90];
mcont3(reg1c, 0.2, 'stereo', [90 270]);
drawmap2(lm, 0.5, -100);
hold on;
mshade3(squeeze(c1c.^2), 0.25, 0.7*[1 1 1]);
hold off;
gridm on;
axis_limits;
title(['COUP: Regression on NP\_PPC' num2str(num)]);
sptalk(4,2,3); FRAME = [0 360 -90 1];
mcont3(reg1m, 0.2, 'stereo', [-90 270]);
drawmap2(lm, 0.5, -100);
hold on;
mshade3(squeeze(c1m.^2), 0.25, 0.7*[1 1 1]);
hold off;
gridm on;
axis_limits;
sptalk(4,2,4); FRAME = [0 360 -90 1];
mcont3(reg1c, 0.2, 'stereo', [-90 270]);
drawmap2(lm, 0.5, -100);
hold on;
mshade3(squeeze(c1c.^2), 0.25, 0.7*[1 1 1]);
hold off;
gridm on;
axis_limits;
sptalk(4,2,5); FRAME = [105 295 -60 60];
gcont(reg2m, 0.05);
dc2(lm, 0.5, 100);
color_shade(squeeze(c2m.^2), 0.25, 0.7*[1 1 1]);
ylabel('SST');
sptalk(4,2,6);
gcont(reg2c, 0.05);
dc2(lm, 0.5, 100);
color_shade(squeeze(c2c.^2), 0.25, 0.7*[1 1 1]);
data;
load LP9_detrend_L1-7_EOF_yr101-1000.mat;
back
lags = -10:10;
for i = 1:length(lags);
a(i,1) = corr(pm*usepcs(:,num), ctm, lags(i));
a(i,2) = corr(pm*ppcs(:,num), ctc, lags(i));
end
sptalk(4,2,7);
bar(lags, a(:,1));
axis([-11 11 -0.5 0.75]);
grid on;
set(gca, 'XTick', -10:5:10, 'YTick', -0.5:.25:1);
xlabel('PC1 leads CT | CT leads PC1');
ylabel('Lagged Correlation');
sptalk(4,2,8);
bar(lags, a(:,2));
axis([-11 11 -0.5 0.75]);
grid on;
set(gca, 'XTick', -10:5:10, 'YTick', -0.5:.25:1);
xlabel('PPC1 leads CT | CT leads PPC1');
cd ~/matlab/CSIRO/Thesis/Chap5/Plots
%print -dps2 SP_SLP_LP9_PC2_PPC2_Regressions.ps
cd ~/Thesis/Chap5
%print -dps2 NP_SLP_LP9_PC1_PPC1_Regressions.ps
data;
load HP10_detrend_L1-7_EOF_yr101-1000.mat; hcpcs = -pcs;
load COUP_SLP_eof_nhem.mat; slppcs = hpcs;
back
num = 2;
lags = -10:10;
for i = 1:length(lags);
a(i,1) = corr(ppcs(:,num), ctc, lags(i));
a(i,2) = corr(ppcs(:,num), slppcs(:,num), lags(i));
a(i,3) = corr(ppcs(:,num), hcpcs(:,num), lags(i));
end
figure(2); fo(1);% clf
sptalk(3,2,2);
bar(lags, -a(:,1));
axis([-11 11 -0.5 1]);
grid on;
set(gca, 'XTick', -10:5:10, 'YTick', -0.5:.25:1);
xlabel('PPC1 leads CT | CT leads PPC1');
title('Unfiltered');
sptalk(3,2,4);
bar(lags, a(:,2));
axis([-11 11 -0.5 1]);
grid on;
set(gca, 'XTick', -10:5:10, 'YTick', -0.5:.25:1);
xlabel('PPC1 leads SLPPC1 | SLPPC1 leads PPC1');
sptalk(3,2,6);
bar(lags, -a(:,3));
axis([-11 11 -0.5 1]);
grid on;
set(gca, 'XTick', -10:5:10, 'YTick', -0.5:.25:1);
xlabel('PPC1 leads LPPC1 | LPPC1 leads PPC1');
% Look at power spectra
tem1 =
ppcs2 = ppcs(:,1)./std(ppcs(:,1));
nfft = 128; noverlap = 3*nfft/4;
[p1, f1] = spectrum(mrpcs(:,1), nfft, noverlap);
[p2, f2] = spectrum(ppcs2, nfft, noverlap);
f = f1./2;
figure(3); fo(1); clf;
sptalk(3,1,1);
h = semilogy(f, p1(:,1), 'v-k', f, p2(:,1), 'o-k');