Documentation of ct_warmcold

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Help text

  Just a side note here.  Recall that the SSTA pattern 
  used to force this run is weighted by some variable 
  moave which is the mean of the warm event and cold event
  time progressions from SEP to APR.  This is contained
  in ct_sst.nc.  The average value for moave (in units of 
  standard deviations of the CT* pattern) is 1.446.  So,
  I think we want to divide the linear difference between
  warm-cold by 2*1.446 in order to get reasonable values
  for the 500mb response.

Cross-Reference Information

Listing of script ct_warmcold

cd /home/disk/hayes2/dvimont/ccm/ccm3.6/run/sun/ct/data

filin = 'wct.nc';
nc = netcdf(filin, 'nowrite');
  pslw = nc{'PSL'}(:);
  hgtw = nc{'Z3'}(:);
  airtw = nc{'AIRT'}(:);
  psw = nc{'PS'}(:);
  latct = nc{'lat'}(:);
  lonct = nc{'lon'}(:);
  hyam = nc{'hyam'}(:);
  hybm = nc{'hybm'}(:);
  P0 = nc{'P0'}(:);
nc = close(nc);

filin = 'cct.nc';
nc = netcdf(filin, 'nowrite');
  pslc = nc{'PSL'}(:);
  hgtc = nc{'Z3'}(:);
  airtc = nc{'AIRT'}(:);
  psc = nc{'PS'}(:);
nc = close(nc);

pslw = squeeze(mean(pslw));
psw = squeeze(mean(psw));
hgtw = squeeze(mean(hgtw));
airtw = squeeze(mean(airtw));
pslc = squeeze(mean(pslc));
psc = squeeze(mean(psc));
hgtc = squeeze(mean(hgtc));
airtc = squeeze(mean(airtc));

weight = 2*1.446;

global XAX YAX FRAME
XAX = lonct;
YAX = latct;
FRAME = [0 360 -90 90];

lev = 850;
hgtw850 = atlev(hgtw, lev, psw, hyam, hybm, P0);
hgtc850 = atlev(hgtc, lev, psc, hyam, hybm, P0);

tem = (hgtw850-hgtc850)/weight;

lev = 850;
cint = 5;
cint2 = cint;

figure(1)
XAX = lonct;
YAX = latct;
orient tall
sp(1)
     mcont(tem,[-220:cint:220],[90 270])
     title([num2str(lev) 'mb NH CT Response (WARM - COLD)/(2*1.446)'])
     xlabel(['Contour Interval ' num2str(cint) 'm'])
sp(2)
     mcont(tem,[-220:cint2:220],[-90 270])
     title([num2str(lev) 'mb SH CT Response (WARM - COLD)/(2*1.446)'])
     xlabel(['Contour Interval ' num2str(cint2) 'm'])

%  Compare with NMC data

cd /home/disk/tao/data/nmc.reanalysis/monthly
filin = 'hgt.mon.mean.nc'
nc = netcdf(filin, 'nowrite');
  lat = nc{'lat'}(:);
  lon = nc{'lon'}(:);
nc = close(nc);

cd /home/disk/tao/dvimont/matlab/CCM/CT/CT_Plots

ct500_nmc = ct_hgt_nmc(500);
%ct500_coads_time = ct_coads_hgt_nmc(12);
ct200_nmc = ct_hgt_nmc(200);
ct850_nmc = ct_hgt_nmc(850);
ct1000_nmc = ct_hgt_nmc(1000);

XAX = lon;
YAX = lat;

figure(2)
orient tall
tem = ct1000_nmc;
lev = 1000;
cint = 10;

sp(1);
     mcont(tem,[-120:cint:120],[90 270]);
     title(['NMC NH ' num2str(lev) 'mb HGT Regressed on CT*'])
     xlabel(['Contour Interval ' num2str(cint) 'm/STD(CT*)'])
sp(2);
     mcont(tem,[-110:5:110],[-90 270]);
     title(['NMC SH ' num2str(lev) 'mb HGT Regressed on CT*'])
     xlabel(['Contour Interval ' num2str(cint) 'm/STD(CT*)'])

cd /home/disk/tao/dvimont/matlab/CCM/CT/CT_Plots






figure(1)
orient landscape
subplot(2,1,1)
     plot(ctstar)
     set(gca, 'XTick',[37:60:409],'XTickLabel',[65:5:100],'YTick',[-3:3])
     axis([0 409 -3 3.5])
     grid
     title('Unfiltered CT*')
subplot(2,1,2)
     plot(myrunning_ave(ctstar,6))
     set(gca, 'XTick',[37:60:409],'XTickLabel',[65:5:100],'YTick',[-3:3])
     axis([0 409 -3 3.5])
     grid
     title('6 MO Running Mean CT*')