created

make_LENS_climatology_plots.py

@@ -7,12 +7,19 @@
 Northern Hemisphere
 """
 print 'loading data'
-pproj = np.load('/glade/scratch/aordonez/pproj.npy')
-iproj = np.load('/glade/scratch/aordonez/iproj.npy')
-tproj = np.load('/glade/scratch/aordonez/tproj.npy') 
-lat,lon = read_stereo_lat_lon()
+psl = read_atm_data('PSL','001')
+icefrac = read_atm_data('ICEFRAC','001')
+ts = read_atm_data('TS','001')
+lat,lon = read_native_lat_lon_atm()
 years = ['1980-1999','2000-2019','2020-2039',
          '2040-2059','2060-2079']
+coldim = psl.shape[2]
+ptmp = np.concatenate((psl[:,:,coldim-5:coldim],psl),axis = 2)
+itmp = np.concatenate((icefrac[:,:,coldim-5:coldim],icefrac),axis = 2)
+lattmp = np.concatenate((lat[:,coldim-5:coldim],lat),axis = 1)
+ptmp = np.concatenate((psl,psl[:,:,5:10]),axis = 2)
+itmp = np.concatenate((icefrac,icefrac[:,:,5:10]),axis = 2)
+lattmp = np.concatenate((lat,lat[:,5:10]),axis = 1)
 
 
 for n in range(0,5):
@@ -21,9 +28,9 @@
     yrs = years[n]
     # min and max ice extent contours over mean extent pcolor
     # 1980-1999
-    icemean = np.nanmean(iproj[start:end,:,:],axis = 0)
-    icemax = np.nanmean(iproj[range(start+73,end,365),:,:],axis = 0)
-    icemin = np.nanmean(iproj[range(start+257,end,365),:,:],axis = 0)
+    icemean = np.nanmean(icefrac[start:end,:,:],axis = 0)
+    icemax = np.nanmean(icefrac[range(start+73,end,365),:,:],axis = 0)
+    icemin = np.nanmean(icefrac[range(start+257,end,365),:,:],axis = 0)
     icemax = np.select([icemax >= 0.15, icemax < 0.15, np.isnan(icemax)],[1, 0, np.nan])
     icemin = np.select([icemin >= 0.15, icemin < 0.15, np.isnan(icemin)],[1, 0, np.nan])
 
@@ -48,7 +55,10 @@
     axs.set_title(yrs + ' ice extent')
     f.savefig('ice_extent_' + yrs + '.png')
 
-    lows = find_cyclone_center(pproj[start:end,:,:],iproj[start:end,:,:],104000,90000)
+
+    lows = find_cyclone_center(ptmp[start:end,:,:],itmp[start:end,:,:],
+                               lattmp,104000,90000)
+    lows = lows[:,:,5:coldim+5]
     lowsmap = np.nansum(lows,axis = 0)
     f,axs = plt.subplots(1,1)
     map = Basemap(projection = proj, lat_0 = 90, lon_0 = 180, boundinglat = 40, round = True, ax = axs)
@@ -57,39 +67,20 @@
     map.fillcontinents(color='white')
     axs.set_title(yrs + ' storm count')
     f.savefig('storm_count_' + yrs + '.png')
+    f.show()
 
-plt.show()
-# mean storm location map
 
+    # mean storm location map
 
-# seasonal storm count bar chart
 
-"""
-Southern Hemisphere
-"""
-print 'loading data'
-pproj = np.load('/glade/scratch/aordonez/PSLSHproj.npy')
-iproj = np.load('/glade/scratch/aordonez/ICEFRACSHproj.npy')
-tproj = np.load('/glade/scratch/aordonez/TSSHproj.npy') 
-lat,lon = read_SHstereo_lat_lon()
-years = ['1980-1999','2000-2019','2020-2039',
-         '2040-2059','2060-2079']
-
-for n in range(0,5):
-    start = 20*365*n 
-    end = start + (20*365)
-    yrs = years[n]
-    # min and max ice extent contours over mean extent pcolor
-    # 1980-1999
-    icemean = np.nanmean(iproj[start:end,:,:],axis = 0)
-    icemax = np.nanmean(iproj[range(start+73,end,365),:,:],axis = 0)
-    icemin = np.nanmean(iproj[range(start+257,end,365),:,:],axis = 0)
-    icemax = np.select([icemax >= 0.15, icemax < 0.15, np.isnan(icemax)],[1, 0, np.nan])
-    icemin = np.select([icemin >= 0.15, icemin < 0.15, np.isnan(icemin)],[1, 0, np.nan])
+   # seasonal storm count bar chart
 
+    """
+    Southern Hemisphere
+    """
     #    map = Basemap(projection = proj, lat_0 = -90, lon_0 = 180,boundinglat = -60, round = True, ax = ax2)
-#    m22 = map.contourf(x,y, pol_freq_mam, ax = ax2)
-    blat = np.arange(40,91,1)
+    #    m22 = map.contourf(x,y, pol_freq_mam, ax = ax2)
+    blat = np.arange(-91,-40,1)
     blon = np.arange(-180,181,1)
     blon,blat = np.meshgrid(blon,blat)
     bground = np.zeros(blon.shape)