print ' clim => ' + str(ni0) + ', ' + str(
nj0) + ', (' + vdic['F_T_OBS_3D_12'] + ')'
print ' NEMO => ' + str(ni) + ', ' + str(nj)
sys.exit(0)
if cvar in ['sss', 'sst', 'mld']:
# Creating 1D long. and lat.:
ji_lat0 = nmp.argmax(xlat[nj - 1, :])
vlon = nmp.zeros(ni)
vlon[:] = xlon[20, :]
vlat = nmp.zeros(nj)
vlat[:] = xlat[:, ji_lat0]
if cvar == 'ice':
# Extraoplating sea values over continents:
bt.drown(Vnemo[:, :, :], imask, k_ew=2, nb_max_inc=10, nb_smooth=10)
lpix = False
if vdic['ORCA'][:5] == 'ORCA0': lpix = True
for jt in range(nt):
cm = "%02d" % (jt + 1)
cdate = cy + cm
cdatet = cy + '/' + cm
if cvar == 'sst':
bp.plot("2d")(vlon,
vlat,
Vnemo[jt, :, :] - Vclim[jt, :, :],
imask[:, :],
# Getting NEMO mean monthly climatology of sea-ice coverage: cf_nemo_mnmc = vdic['DIAG_D']+'/clim/mclim_'+CONFRUN+'_'+cy1+'-'+cy2+'_'+vdic['FILE_ICE_SUFFIX']+'.nc4' bt.chck4f(cf_nemo_mnmc) id_ice = Dataset(cf_nemo_mnmc) xnemo_frac_03 = id_ice.variables[vdic['NN_ICEF']][2,:,:] xnemo_frac_09 = id_ice.variables[vdic['NN_ICEF']][8,:,:] xnemo_thic_03 = id_ice.variables[vdic['NN_ICET']][2,:,:] xnemo_thic_09 = id_ice.variables[vdic['NN_ICET']][8,:,:] id_ice.close() [ nj, ni ] = xnemo_frac_03.shape ; print ' Shape of sea-ice :', nj, ni, '\n' # Extraoplating sea values on continents: bt.drown(xnemo_frac_03, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xnemo_frac_09, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xnemo_thic_03, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xnemo_thic_09, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xclim03, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xclim09, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) # Time for figures: # ----------------- # # Extending to 90S: (from 78 to 90): # js_ext = 12; nje = nj + js_ext
# Getting NEMO mean monthly climatology of sea-ice coverage: cf_nemo_mnmc = vdic['DIAG_D']+'/clim/mclim_'+CONFEXP+'_'+cy1+'-'+cy2+'_'+vdic['FILE_ICE_SUFFIX']+'.nc4' bt.chck4f(cf_nemo_mnmc) id_ice = Dataset(cf_nemo_mnmc) xnemo_frac_03 = id_ice.variables[vdic['NN_ICEF']][2,:,:] xnemo_frac_09 = id_ice.variables[vdic['NN_ICEF']][8,:,:] xnemo_thic_03 = id_ice.variables[vdic['NN_ICET']][2,:,:] xnemo_thic_09 = id_ice.variables[vdic['NN_ICET']][8,:,:] id_ice.close() [ nj, ni ] = xnemo_frac_03.shape ; print ' Shape of sea-ice :', nj, ni, '\n' # Extraoplating sea values on continents: bt.drown(xnemo_frac_03, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xnemo_frac_09, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xnemo_thic_03, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xnemo_thic_09, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xclim03, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xclim09, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) # Time for figures: # ----------------- # # Extending to 90S: (from 78 to 90): # js_ext = 12; nje = nj + js_ext
if cvar == 'sss' or cvar == 'sst':
if nj != nj0 or ni != ni0:
print 'ERROR (prepare_movies.py): NEMO file and clim do no agree in shape!'
print ' clim => '+str(ni0)+', '+str(nj0)+', '+str(nk0),' ('+vdic['F_T_CLIM_3D_12']+')'
print ' NEMO => '+str(ni)+', '+str(nj)+', '+str(nk)
sys.exit(0)
# Creating 1D long. and lat.:
ji_lat0 = nmp.argmax(xlat[nj-1]) ; #lolo
vlon = nmp.zeros(ni) ; vlon[:] = xlon[20,:]
vlat = nmp.zeros(nj) ; vlat[:] = xlat[:,ji_lat0]
if cvar == 'ice':
# Extraoplating sea values on continents:
bt.drown(Vnemo[:,:,:], imask, k_ew=2, nb_max_inc=10, nb_smooth=10)
for jt in range(nt):
cm = "%02d" % (jt+1)
cdate = cy+cm
if cvar == 'sst':
bp.plot("2d")(vlon, vlat, Vnemo[jt,:,:] - Vclim[jt,:,:],
imask[:,:], tmin, tmax, dtemp,
corca=vdic['ORCA'], lkcont=False, cpal='RdBu_r',
cfignm=path_fig+'/'+cv+'_'+cdate,
cbunit='K', cfig_type=fig_type, lat_min=-65., lat_max=75.,
ctitle='SST (NEMO - obs) '+CONFRUN+' ('+cdate+')',
# Getting NEMO mean monthly climatology of sea-ice coverage: cf_nemo_mnmc = DIAG_D+'/clim/mclim_'+CONFRUN+'_'+cy1+'-'+cy2+'_'+FILE_ICE_SUFFIX+'.nc4' bt.chck4f(cf_nemo_mnmc) id_ice = Dataset(cf_nemo_mnmc) xnemo03 = id_ice.variables[NN_ICEF][2,:,:] xnemo09 = id_ice.variables[NN_ICEF][8,:,:] id_ice.close() [ nj, ni ] = xnemo03.shape ; print ' Shape of sea-ice :', nj, ni, '\n' # Extraoplating sea values on continents: bt.drown(xnemo03, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xnemo09, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xclim03, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) bt.drown(xclim09, xmask, k_ew=2, nb_max_inc=10, nb_smooth=10) # Time for figures: # ----------------- # # Extending to 90S: (from 78 to 90): # js_ext = 12; nje = nj + js_ext xlat0 = nmp.zeros(nje*ni); xlat0.shape = [ nje, ni ] xlon0 = nmp.zeros(nje*ni); xlon0.shape = [ nje, ni ]
