def main(args):
f = nc.Dataset(args.infile)
if 'basin' in list(f.variables.keys()):
sys.stdout.write(
'The basin field already appears to be in the static file. Exiting.'
)
exit(1)
if args.outfile is None:
outfile = os.path.basename(args.infile)
outfile = outfile.split('.')
outfile.insert(-1, 'basins')
outfile = str('.').join(outfile)
else:
outfile = args.outfile
if os.path.exists(outfile):
sys.stdout.write(
'File already exists ... would you like to overwrite? (y/n): ')
choice = input().lower()
if choice == 'y':
if args.verbose:
sys.stdout.write('Overwriting file: ' + outfile + '\n')
elif choice == 'n':
exit(1)
else:
sys.stdout.write('Please respond with \'y\' or \'n\'')
geolon = np.array(f.variables['geolon'][:])
geolat = np.array(f.variables['geolat'][:])
deptho = np.array(f.variables['deptho'][:].filled(0))
basin_code = m6toolbox.genBasinMasks(geolon, geolat, deptho, args.verbose)
shutil.copyfile(args.infile, outfile)
nc_out = nc.Dataset(outfile, 'r+', format='NETCDF3_CLASSIC')
basin_out = nc_out.createVariable('basin', np.int32, ('yh', 'xh'))
basin_out.setncattr('long_name', 'Region Selection Index')
basin_out.setncattr('standard_name', 'region')
basin_out.setncattr('units', '1.0')
basin_out.setncattr('interp_method', 'none')
basin_out.setncattr('flag_values', '0 1 2 3 4 5 6 7 8 9 10')
basin_out.setncattr('flag_meanings','global_land southern_ocean atlantic_ocean pacific_ocean '+\
'arctic_ocean indian_ocean mediterranean_sea black_sea hudson_bay baltic_sea red_sea')
basin_out[:] = basin_code[:]
nc_out.close()
exit(0)
def main(cmdLineArgs,stream=None):
if not os.path.exists(cmdLineArgs.gridspec): raise ValueError('Specified gridspec directory/tar file does not exist.')
if os.path.isdir(cmdLineArgs.gridspec):
x = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['x'][::2,::2]
xcenter = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['x'][1::2,1::2]
y = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['y'][::2,::2]
ycenter = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['y'][1::2,1::2]
msk = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_mask.nc').variables['mask'][:]
area = msk*netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['area'][:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_topog.nc').variables['depth'][:]
try: basin_code = netCDF4.Dataset(cmdLineArgs.gridspec+'/basin_codes.nc').variables['basin'][:]
except: basin_code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
elif os.path.isfile(cmdLineArgs.gridspec):
x = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','x')[::2,::2]
xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','x')[1::2,1::2]
y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[::2,::2]
ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[1::2,1::2]
msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_mask.nc','mask')[:]
area = msk*m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','area')[:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_topog.nc','depth')[:]
try: basin_code = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'basin_codes.nc','basin')[:]
except: basin_code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
else:
raise ValueError('Unable to extract grid information from gridspec directory/tar file.')
if stream != None:
if len(stream) != 2:
raise ValueError('If specifying output streams, exactly two streams are needed for this analysis')
rootGroup = netCDF4.MFDataset( cmdLineArgs.annual_file )
if 'vh' in rootGroup.variables:
varName = 'vh'; conversion_factor = 1.e-9
elif 'vmo' in rootGroup.variables:
varName = 'vmo'; conversion_factor = 1.e-9
else: raise Exception('Could not find "vh" or "vmo" in file "%s"'%(cmdLineArgs.annual_file))
if len(rootGroup.variables[varName].shape)==4: VHmod = rootGroup.variables[varName][:].mean(axis=0)
else: VHmod = rootGroup.variables[varName][:]
try: VHmod = VHmod.filled(0.)
except: pass
if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0]
elif 'zw' in rootGroup.variables:
zw = rootGroup.variables['zw'][:]
Zmod = numpy.zeros((zw.shape[0], depth.shape[0], depth.shape[1] ))
for k in range(zw.shape[0]):
Zmod[k] = -numpy.minimum( depth, abs(zw[k]) )
else: raise Exception('Neither a model-space output file or a z-space diagnostic file?')
def MOCpsi(vh, vmsk=None):
"""Sums 'vh' zonally and cumulatively in the vertical to yield an overturning stream function, psi(y,z)."""
shape = list(vh.shape); shape[-3] += 1
psi = numpy.zeros(shape[:-1])
if len(shape)==3:
for k in range(shape[-3]-1,0,-1):
if vmsk is None: psi[k-1,:] = psi[k,:] - vh[k-1].sum(axis=-1)
else: psi[k-1,:] = psi[k,:] - (vmsk*vh[k-1]).sum(axis=-1)
else:
for n in range(shape[0]):
for k in range(shape[-3]-1,0,-1):
if vmsk is None: psi[n,k-1,:] = psi[n,k,:] - vh[n,k-1].sum(axis=-1)
else: psi[n,k-1,:] = psi[n,k,:] - (vmsk*vh[n,k-1]).sum(axis=-1)
return psi
def plotPsi(y, z, psi, ci, title):
cmap = plt.get_cmap('dunnePM')
plt.contourf(y, z, psi, levels=ci, cmap=cmap, extend='both')
cbar = plt.colorbar()
plt.contour(y, z, psi, levels=ci, colors='k', hold='on')
plt.gca().set_yscale('splitscale',zval=[0,-2000,-6500])
plt.title(title)
cbar.set_label('[Sv]'); plt.ylabel('Elevation [m]')
def findExtrema(y, z, psi, min_lat=-90., max_lat=90., min_depth=0., mult=1.):
psiMax = mult*numpy.amax( mult * numpy.ma.array(psi)[(y>=min_lat) & (y<=max_lat) & (z<-min_depth)] )
idx = numpy.argmin(numpy.abs(psi-psiMax))
(j,i) = numpy.unravel_index(idx, psi.shape)
plt.plot(y[j,i],z[j,i],'kx',hold=True)
plt.text(y[j,i],z[j,i],'%.1f'%(psi[j,i]))
m6plot.setFigureSize(npanels=1)
cmap = plt.get_cmap('dunnePM')
if cmdLineArgs.suptitle != '': suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label
else: suptitle = rootGroup.title + ' ' + cmdLineArgs.label
# Global MOC
z = Zmod.min(axis=-1); psiPlot = MOCpsi(VHmod)*conversion_factor
yy = y[1:,:].max(axis=-1)+0*z
ci=m6plot.pmCI(0.,40.,5.)
plotPsi(yy, z, psiPlot, ci, 'Global MOC [Sv]')
plt.xlabel(r'Latitude [$\degree$N]')
plt.suptitle(suptitle)
findExtrema(yy, z, psiPlot, max_lat=-30.)
findExtrema(yy, z, psiPlot, min_lat=25.)
findExtrema(yy, z, psiPlot, min_depth=2000., mult=-1.)
if stream != None:
plt.savefig(stream[0])
else:
plt.savefig(cmdLineArgs.outdir+'/MOC_global.png')
# Atlantic MOC
plt.clf()
m = 0*basin_code; m[(basin_code==2) | (basin_code==4) | (basin_code==6) | (basin_code==7) | (basin_code==8)]=1
ci=m6plot.pmCI(0.,22.,2.)
z = (m*Zmod).min(axis=-1); psiPlot = MOCpsi(VHmod, vmsk=m*numpy.roll(m,-1,axis=-2))*conversion_factor
yy = y[1:,:].max(axis=-1)+0*z
plotPsi(yy, z, psiPlot, ci, 'Atlantic MOC [Sv]')
plt.xlabel(r'Latitude [$\degree$N]')
plt.suptitle(suptitle)
findExtrema(yy, z, psiPlot, min_lat=26.5, max_lat=27.) # RAPID
findExtrema(yy, z, psiPlot, max_lat=-33.)
findExtrema(yy, z, psiPlot)
findExtrema(yy, z, psiPlot, min_lat=5.)
if stream != None:
plt.savefig(stream[1])
else:
plt.savefig(cmdLineArgs.outdir+'/MOC_Atlantic.png')
def main(cmdLineArgs, stream=None):
if not os.path.exists(cmdLineArgs.gridspec):
raise ValueError(
'Specified gridspec directory/tar file does not exist.')
if os.path.isdir(cmdLineArgs.gridspec):
x = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['x'][::2, ::2]
xcenter = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['x'][1::2, 1::2]
y = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['y'][::2, ::2]
ycenter = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['y'][1::2, 1::2]
msk = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_mask.nc').variables['mask'][:]
area = msk * netCDF4.Dataset(
cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['area'][:, :].reshape(
[msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_topog.nc').variables['depth'][:]
try:
basin_code = netCDF4.Dataset(
cmdLineArgs.gridspec + '/basin_codes.nc').variables['basin'][:]
except:
basin_code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
elif os.path.isfile(cmdLineArgs.gridspec):
x = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc',
'x')[::2, ::2]
xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'ocean_hgrid.nc', 'x')[1::2, 1::2]
y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc',
'y')[::2, ::2]
ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'ocean_hgrid.nc', 'y')[1::2, 1::2]
msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_mask.nc',
'mask')[:]
area = msk * m6toolbox.readNCFromTar(
cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'area')[:, :].reshape(
[msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_topog.nc',
'depth')[:]
try:
basin_code = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'basin_codes.nc', 'basin')[:]
except:
basin_code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
else:
raise ValueError(
'Unable to extract grid information from gridspec directory/tar file.'
)
if stream != None:
if len(stream) != 2:
raise ValueError(
'If specifying output streams, exactly two streams are needed for this analysis'
)
rootGroup = netCDF4.MFDataset(cmdLineArgs.annual_file)
if 'vh' in rootGroup.variables:
varName = 'vh'
conversion_factor = 1.e-9
elif 'vmo' in rootGroup.variables:
varName = 'vmo'
conversion_factor = 1.e-9
else:
raise Exception('Could not find "vh" or "vmo" in file "%s"' %
(cmdLineArgs.annual_file))
if len(rootGroup.variables[varName].shape) == 4:
VHmod = rootGroup.variables[varName][:].mean(axis=0)
else:
VHmod = rootGroup.variables[varName][:]
try:
VHmod = VHmod.filled(0.)
except:
pass
if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0]
elif 'zw' in rootGroup.variables:
zw = rootGroup.variables['zw'][:]
Zmod = numpy.zeros((zw.shape[0], depth.shape[0], depth.shape[1]))
for k in range(zw.shape[0]):
Zmod[k] = -numpy.minimum(depth, abs(zw[k]))
else:
raise Exception(
'Neither a model-space output file or a z-space diagnostic file?')
def MOCpsi(vh, vmsk=None):
"""Sums 'vh' zonally and cumulatively in the vertical to yield an overturning stream function, psi(y,z)."""
shape = list(vh.shape)
shape[-3] += 1
psi = numpy.zeros(shape[:-1])
if len(shape) == 3:
for k in range(shape[-3] - 1, 0, -1):
if vmsk is None:
psi[k - 1, :] = psi[k, :] - vh[k - 1].sum(axis=-1)
else:
psi[k - 1, :] = psi[k, :] - (vmsk * vh[k - 1]).sum(axis=-1)
else:
for n in range(shape[0]):
for k in range(shape[-3] - 1, 0, -1):
if vmsk is None:
psi[n, k -
1, :] = psi[n, k, :] - vh[n, k - 1].sum(axis=-1)
else:
psi[n, k -
1, :] = psi[n, k, :] - (vmsk *
vh[n, k - 1]).sum(axis=-1)
return psi
def plotPsi(y, z, psi, ci, title):
cmap = plt.get_cmap('dunnePM')
plt.contourf(y, z, psi, levels=ci, cmap=cmap, extend='both')
cbar = plt.colorbar()
plt.contour(y, z, psi, levels=ci, colors='k', hold='on')
plt.gca().set_yscale('splitscale', zval=[0, -2000, -6500])
plt.title(title)
cbar.set_label('[Sv]')
plt.ylabel('Elevation [m]')
def findExtrema(y,
z,
psi,
min_lat=-90.,
max_lat=90.,
min_depth=0.,
mult=1.):
psiMax = mult * numpy.amax(
mult * numpy.ma.array(psi)[(y >= min_lat) & (y <= max_lat) &
(z < -min_depth)])
idx = numpy.argmin(numpy.abs(psi - psiMax))
(j, i) = numpy.unravel_index(idx, psi.shape)
plt.plot(y[j, i], z[j, i], 'kx', hold=True)
plt.text(y[j, i], z[j, i], '%.1f' % (psi[j, i]))
m6plot.setFigureSize(npanels=1)
cmap = plt.get_cmap('dunnePM')
if cmdLineArgs.suptitle != '':
suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label
else:
suptitle = rootGroup.title + ' ' + cmdLineArgs.label
# Global MOC
z = Zmod.min(axis=-1)
psiPlot = MOCpsi(VHmod) * conversion_factor
yy = y[1:, :].max(axis=-1) + 0 * z
ci = m6plot.pmCI(0., 40., 5.)
plotPsi(yy, z, psiPlot, ci, 'Global MOC [Sv]')
plt.xlabel(r'Latitude [$\degree$N]')
plt.suptitle(suptitle)
findExtrema(yy, z, psiPlot, max_lat=-30.)
findExtrema(yy, z, psiPlot, min_lat=25.)
findExtrema(yy, z, psiPlot, min_depth=2000., mult=-1.)
if stream != None:
plt.savefig(stream[0])
else:
plt.savefig(cmdLineArgs.outdir + '/MOC_global.png')
# Atlantic MOC
plt.clf()
m = 0 * basin_code
m[(basin_code == 2) | (basin_code == 4) | (basin_code == 6) |
(basin_code == 7) | (basin_code == 8)] = 1
ci = m6plot.pmCI(0., 22., 2.)
z = (m * Zmod).min(axis=-1)
psiPlot = MOCpsi(VHmod,
vmsk=m * numpy.roll(m, -1, axis=-2)) * conversion_factor
yy = y[1:, :].max(axis=-1) + 0 * z
plotPsi(yy, z, psiPlot, ci, 'Atlantic MOC [Sv]')
plt.xlabel(r'Latitude [$\degree$N]')
plt.suptitle(suptitle)
findExtrema(yy, z, psiPlot, min_lat=26.5, max_lat=27.) # RAPID
findExtrema(yy, z, psiPlot, max_lat=-33.)
findExtrema(yy, z, psiPlot)
findExtrema(yy, z, psiPlot, min_lat=5.)
if stream != None:
plt.savefig(stream[1])
else:
plt.savefig(cmdLineArgs.outdir + '/MOC_Atlantic.png')
def main(cmdLineArgs,stream=None):
if not os.path.exists(cmdLineArgs.gridspec): raise ValueError('Specified gridspec directory/tar file does not exist.')
if os.path.isdir(cmdLineArgs.gridspec):
xcenter = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['x'][1::2,1::2]
y = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['y'][1::2,1::2].max(axis=-1)
ycenter = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['y'][1::2,1::2]
msk = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_mask.nc').variables['mask'][:]
area = msk*netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['area'][:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_topog.nc').variables['depth'][:]
try: basin = netCDF4.Dataset(cmdLineArgs.gridspec+'/basin_codes.nc').variables['basin'][:]
except: basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
elif os.path.isfile(cmdLineArgs.gridspec):
xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','x')[1::2,1::2]
y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[1::2,1::2].max(axis=-1)
ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[1::2,1::2]
msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_mask.nc','mask')[:]
area = msk*m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','area')[:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_topog.nc','depth')[:]
try: basin = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'basin_codes.nc','basin')[:]
except: basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
else:
raise ValueError('Unable to extract grid information from gridspec directory/tar file.')
if stream != None:
if len(stream) != 4:
raise ValueError('If specifying output streams, exactly four (4) streams are needed for this analysis')
Sobs = netCDF4.Dataset( cmdLineArgs.woa ).variables['salt']
if len(Sobs.shape)==3: Sobs = Sobs[:]
else: Sobs = Sobs[:].mean(axis=0)
Zobs = netCDF4.Dataset( cmdLineArgs.woa ).variables['eta'][:]
rootGroup = netCDF4.MFDataset( cmdLineArgs.annual_file )
if 'salt' in rootGroup.variables: varName = 'salt'
elif 'so' in rootGroup.variables: varName = 'so'
else:raise Exception('Could not find "salt" or "so" in file "%s"'%(cmdLineArgs.annual_file))
if len(rootGroup.variables[varName].shape)==4: Smod = rootGroup.variables[varName][:].mean(axis=0)
else: Smod = rootGroup.variables[varName][:]
if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0]
else: Zmod = Zobs # Using model z-output
def zonalAverage(S, eta, area, mask=1.):
vols = ( mask * area ) * ( eta[:-1] - eta[1:] ) # mask * area * level thicknesses
return numpy.sum( vols * S, axis=-1 ) / numpy.sum( vols, axis=-1 ), (mask*eta).min(axis=-1)
ci=m6plot.pmCI(0.125,2.25,.25)
if cmdLineArgs.suptitle != '': suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label
else: suptitle = rootGroup.title + ' ' + cmdLineArgs.label
# Global
sPlot, z = zonalAverage(Smod, Zmod, area)
sObsPlot, _ = zonalAverage(Sobs, Zobs, area)
if stream != None: objOut = stream[0]
else: objOut = cmdLineArgs.outdir+'/S_global_xave_bias_WOA05.png'
m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.],
suptitle=suptitle, title='''Global zonal-average salinity bias (w.r.t. WOA'05) [ppt]''',
clim=ci, colormap='dunnePM', centerlabels=True, extend='both',
save=objOut)
if stream is None:
m6plot.yzcompare( sPlot, sObsPlot , y, z, splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1='Global zonal-average salinity [ppt]',
title2='''WOA'05 salinity [ppt]''',
clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both',
dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True,
save=cmdLineArgs.outdir+'/S_global_xave_bias_WOA05.3_panel.png')
# Atlantic + Arctic
newMask = 1.*msk; newMask[ (basin!=2) & (basin!=4) ] = 0.
sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask)
sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask)
if stream != None: objOut = stream[1]
else: objOut = cmdLineArgs.outdir+'/S_Atlantic_xave_bias_WOA05.png'
m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.],
suptitle=suptitle, title='''Atlantic zonal-average salinity bias (w.r.t. WOA'05) [ppt]''',
clim=ci, colormap='dunnePM', centerlabels=True, extend='both',
save=objOut)
if stream is None:
m6plot.yzcompare( sPlot, sObsPlot , y, z, splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1='Atlantic zonal-average salinity [ppt]',
title2='''WOA'05 salinity [ppt]''',
clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both',
dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True,
save=cmdLineArgs.outdir+'/S_Atlantic_xave_bias_WOA05.3_panel.png')
# Pacific
newMask = 1.*msk; newMask[ (basin!=3) ] = 0.
sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask)
sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask)
if stream != None: objOut = stream[2]
else: objOut = cmdLineArgs.outdir+'/S_Pacific_xave_bias_WOA05.png'
m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.],
suptitle=suptitle, title='''Pacific zonal-average salinity bias (w.r.t. WOA'05) [ppt]''',
clim=ci, colormap='dunnePM', centerlabels=True, extend='both',
save=objOut)
if stream is None:
m6plot.yzcompare( sPlot, sObsPlot , y, z, splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1='Pacific zonal-average salinity [ppt]',
title2='''WOA'05 salinity [ppt]''',
clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both',
dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True,
save=cmdLineArgs.outdir+'/S_Pacific_xave_bias_WOA05.3_panel.png')
# Indian
newMask = 1.*msk; newMask[ (basin!=5) ] = 0.
sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask)
sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask)
if stream != None: objOut = stream[3]
else: objOut = cmdLineArgs.outdir+'/S_Indian_xave_bias_WOA05.png'
m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.],
suptitle=suptitle, title='''Indian zonal-average salinity bias (w.r.t. WOA'05) [ppt]''',
clim=ci, colormap='dunnePM', centerlabels=True, extend='both',
save=objOut)
if stream is None:
m6plot.yzcompare( sPlot, sObsPlot , y, z, splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1='Indian zonal-average salinity [ppt]',
title2='''WOA'05 salinity [ppt]''',
clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both',
dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True,
save=cmdLineArgs.outdir+'/S_Indian_xave_bias_WOA05.3_panel.png')
msk = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_mask.nc').variables['mask'][:]
area = msk*netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['area'][:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_topog.nc').variables['depth'][:]
elif os.path.isfile(cmdLineArgs.gridspec):
x = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','x')[1::2,1::2]
xg = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','x')[0::2,0::2]
y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[1::2,1::2]
yg = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[0::2,0::2]
msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_mask.nc','mask')[:]
area = msk*m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','area')[:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_topog.nc','depth')[:]
else:
raise ValueError('Unable to extract grid information from gridspec directory/tar file.')
# Basin codes
basin = m6toolbox.genBasinMasks(x, y, depth) # All ocean points seeded from South Atlantic
obsRootGroup = netCDF4.Dataset( cmdLineArgs.woa )
if 'temp' in obsRootGroup.variables: OTvar = 'temp'
else: OTvar = 'ptemp'
Zobs = netCDF4.Dataset( cmdLineArgs.woa ).variables['eta']
rootGroup = netCDF4.Dataset( cmdLineArgs.annual_file )
if 'temp' in rootGroup.variables: varName = 'temp'
elif 'ptemp' in rootGroup.variables: varName = 'ptemp'
elif 'thetao' in rootGroup.variables: varName = 'thetao'
else: raise Exception('Could not find "temp", "ptemp" or "thetao" in file "%s"'%(cmdLineArgs.annual_file))
if len(rootGroup.variables[varName].shape)==4: need_time_average = True
else: need_time_average = False
if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e']
else: Zmod = Zobs # Using model z-output
def main(cmdLineArgs, stream=False):
if not os.path.exists(cmdLineArgs.gridspec):
raise ValueError(
'Specified gridspec directory/tar file does not exist.')
if os.path.isdir(cmdLineArgs.gridspec):
x = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['x'][::2, ::2]
xcenter = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['x'][1::2, 1::2]
y = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['y'][::2, ::2]
ycenter = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['y'][1::2, 1::2]
msk = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_mask.nc').variables['mask'][:]
area = msk * netCDF4.Dataset(
cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['area'][:, :].reshape(
[msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_topog.nc').variables['depth'][:]
try:
basin_code = netCDF4.Dataset(
cmdLineArgs.gridspec + '/basin_codes.nc').variables['basin'][:]
except:
basin_code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
elif os.path.isfile(cmdLineArgs.gridspec):
x = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc',
'x')[::2, ::2]
xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'ocean_hgrid.nc', 'x')[1::2, 1::2]
y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc',
'y')[::2, ::2]
ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'ocean_hgrid.nc', 'y')[1::2, 1::2]
msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_mask.nc',
'mask')[:]
area = msk * m6toolbox.readNCFromTar(
cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'area')[:, :].reshape(
[msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_topog.nc',
'depth')[:]
try:
basin_code = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'basin_codes.nc', 'basin')[:]
except:
basin_code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
else:
raise ValueError(
'Unable to extract grid information from gridspec directory/tar file.'
)
rootGroup = netCDF4.MFDataset(cmdLineArgs.infile)
if 'T_ady_2d' in rootGroup.variables:
varName = 'T_ady_2d'
advective = rootGroup.variables[varName]
advective.data = advective[:].filled(0.)
else:
raise Exception('Could not find "T_ady_2d" in file "%s"' %
(cmdLineArgs.infile))
if 'T_diffy_2d' in rootGroup.variables:
varName = 'T_diffy_2d'
diffusive = rootGroup.variables[varName][:].filled(0.)
else:
diffusive = None
warnings.warn(
'Diffusive temperature term not found. This will result in an underestimation of the heat transport.'
)
def heatTrans(advective, diffusive=None, vmask=None):
"""Converts vertically integrated temperature advection into heat transport"""
if diffusive != None:
HT = advective[:] + diffusive[:]
else:
HT = advective[:]
if len(HT.shape) == 3:
HT = HT.mean(axis=0)
if advective.units == "Celsius meter3 second-1":
rho0 = 1.035e3
Cp = 3989.
HT = HT * (rho0 * Cp)
HT = HT * 1.e-15 # convert to PW
elif advective.units == "W m-2":
HT = HT * 1.e-15
else:
print('Unknown units')
if vmask != None: HT = HT * vmask
HT = HT.sum(axis=-1)
HT = HT.squeeze() # sum in x-direction
return HT
def plotHeatTrans(y, HT, title, xlim=(-80, 90)):
plt.plot(y, y * 0., 'k', linewidth=0.5)
plt.plot(y, HT, 'r', linewidth=1.5, label='Model')
plt.xlim(xlim)
plt.ylim(-2.5, 3.0)
plt.title(title)
plt.grid(True)
def annotatePlot(label):
fig = plt.gcf()
#fig.text(0.1,0.85,label)
fig.text(0.535, 0.12, label)
def annotateObs():
fig = plt.gcf()
fig.text(
0.1,
0.85,
r"Trenberth, K. E. and J. M. Caron, 2001: Estimates of Meridional Atmosphere and Ocean Heat Transports. J.Climate, 14, 3433-3443.",
fontsize=8)
fig.text(
0.1,
0.825,
r"Ganachaud, A. and C. Wunsch, 2000: Improved estimates of global ocean circulation, heat transport and mixing from hydrographic data.",
fontsize=8)
fig.text(0.13, 0.8, r"Nature, 408, 453-457", fontsize=8)
m6plot.setFigureSize(npanels=1)
# Load Observations
fObs = netCDF4.Dataset(
'/archive/John.Krasting/obs/TC2001/Trenberth_and_Caron_Heat_Transport.nc'
) #Trenberth and Caron
yobs = fObs.variables['ylat'][:]
NCEP = {}
NCEP['Global'] = fObs.variables['OTn']
NCEP['Atlantic'] = fObs.variables['ATLn'][:]
NCEP['IndoPac'] = fObs.variables['INDPACn'][:]
ECMWF = {}
ECMWF['Global'] = fObs.variables['OTe'][:]
ECMWF['Atlantic'] = fObs.variables['ATLe'][:]
ECMWF['IndoPac'] = fObs.variables['INDPACe'][:]
#G and W
Global = {}
Global['lat'] = numpy.array([-30., -19., 24., 47.])
Global['trans'] = numpy.array([-0.6, -0.8, 1.8, 0.6])
Global['err'] = numpy.array([0.3, 0.6, 0.3, 0.1])
Atlantic = {}
Atlantic['lat'] = numpy.array(
[-45., -30., -19., -11., -4.5, 7.5, 24., 47.])
Atlantic['trans'] = numpy.array(
[0.66, 0.35, 0.77, 0.9, 1., 1.26, 1.27, 0.6])
Atlantic['err'] = numpy.array(
[0.12, 0.15, 0.2, 0.4, 0.55, 0.31, 0.15, 0.09])
IndoPac = {}
IndoPac['lat'] = numpy.array([-30., -18., 24., 47.])
IndoPac['trans'] = numpy.array([-0.9, -1.6, 0.52, 0.])
IndoPac['err'] = numpy.array([
0.3,
0.6,
0.2,
0.05,
])
GandW = {}
GandW['Global'] = Global
GandW['Atlantic'] = Atlantic
GandW['IndoPac'] = IndoPac
def plotGandW(lat, trans, err):
low = trans - err
high = trans + err
for n in range(0, len(low)):
if n == 0:
plt.plot([lat[n], lat[n]], [low[n], high[n]],
'c',
linewidth=2.0,
label='G&W')
else:
plt.plot([lat[n], lat[n]], [low[n], high[n]],
'c',
linewidth=2.0)
plt.scatter(lat, trans, marker='s', facecolor='cyan')
if cmdLineArgs.suptitle != '':
suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label
else:
suptitle = rootGroup.title + ' ' + cmdLineArgs.label
imgbufs = []
# Global Heat Transport
HTplot = heatTrans(advective, diffusive)
yy = y[1:, :].max(axis=-1)
plotHeatTrans(yy, HTplot, title='Global Y-Direction Heat Transport [PW]')
plt.plot(yobs, NCEP['Global'], 'k--', linewidth=0.5, label='NCEP')
plt.plot(yobs, ECMWF['Global'], 'k.', linewidth=0.5, label='ECMWF')
plotGandW(GandW['Global']['lat'], GandW['Global']['trans'],
GandW['Global']['err'])
plt.xlabel(r'Latitude [$\degree$N]')
plt.suptitle(suptitle)
plt.legend(loc=0, fontsize=10)
annotateObs()
if diffusive is None:
annotatePlot('Warning: Diffusive component of transport is missing.')
if stream is True: objOut = io.BytesIO()
else: objOut = cmdLineArgs.outdir + '/HeatTransport_global.png'
plt.savefig(objOut)
if stream is True: imgbufs.append(objOut)
# Atlantic Heat Transport
plt.clf()
m = 0 * basin_code
m[(basin_code == 2) | (basin_code == 4) | (basin_code == 6) |
(basin_code == 7) | (basin_code == 8)] = 1
HTplot = heatTrans(advective,
diffusive,
vmask=m * numpy.roll(m, -1, axis=-2))
yy = y[1:, :].max(axis=-1)
HTplot[yy < -34] = numpy.nan
plotHeatTrans(yy, HTplot, title='Atlantic Y-Direction Heat Transport [PW]')
plt.plot(yobs, NCEP['Atlantic'], 'k--', linewidth=0.5, label='NCEP')
plt.plot(yobs, ECMWF['Atlantic'], 'k.', linewidth=0.5, label='ECMWF')
plotGandW(GandW['Atlantic']['lat'], GandW['Atlantic']['trans'],
GandW['Atlantic']['err'])
plt.xlabel(r'Latitude [$\degree$N]')
plt.suptitle(suptitle)
plt.legend(loc=0, fontsize=10)
annotateObs()
if diffusive is None:
annotatePlot('Warning: Diffusive component of transport is missing.')
if stream is True: objOut = io.BytesIO()
else: objOut = cmdLineArgs.outdir + '/HeatTransport_Atlantic.png'
plt.savefig(objOut)
if stream is True: imgbufs.append(objOut)
# Indo-Pacific Heat Transport
plt.clf()
m = 0 * basin_code
m[(basin_code == 3) | (basin_code == 5)] = 1
HTplot = heatTrans(advective,
diffusive,
vmask=m * numpy.roll(m, -1, axis=-2))
yy = y[1:, :].max(axis=-1)
HTplot[yy < -34] = numpy.nan
plotHeatTrans(yy,
HTplot,
title='Indo-Pacific Y-Direction Heat Transport [PW]')
plt.plot(yobs, NCEP['IndoPac'], 'k--', linewidth=0.5, label='NCEP')
plt.plot(yobs, ECMWF['IndoPac'], 'k.', linewidth=0.5, label='ECMWF')
plotGandW(GandW['IndoPac']['lat'], GandW['IndoPac']['trans'],
GandW['IndoPac']['err'])
plt.xlabel(r'Latitude [$\degree$N]')
annotateObs()
if diffusive is None:
annotatePlot('Warning: Diffusive component of transport is missing.')
plt.suptitle(suptitle)
plt.legend(loc=0, fontsize=10)
if stream is True: objOut = io.BytesIO()
else: objOut = cmdLineArgs.outdir + '/HeatTransport_IndoPac.png'
plt.savefig(objOut)
if stream is True: imgbufs.append(objOut)
if stream is True:
return imgbufs
import matplotlib.colors
import matplotlib.patches as mpatches
import os
import sys
gridspec = '/archive/gold/datasets/OM4_025/mosaic.v20140610.unpacked'
x = netCDF4.Dataset(gridspec+'/ocean_hgrid.nc').variables['x'][::2,::2]
xcenter = netCDF4.Dataset(gridspec+'/ocean_hgrid.nc').variables['x'][1::2,1::2]
y = netCDF4.Dataset(gridspec+'/ocean_hgrid.nc').variables['y'][::2,::2]
ycenter = netCDF4.Dataset(gridspec+'/ocean_hgrid.nc').variables['y'][1::2,1::2]
msk = netCDF4.Dataset(gridspec+'/ocean_mask.nc').variables['mask'][:]
area = msk*netCDF4.Dataset(gridspec+'/ocean_hgrid.nc').variables['area'][:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(gridspec+'/ocean_topog.nc').variables['depth'][:]
code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
cmap = matplotlib.colors.ListedColormap(['#a1a1a1','#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99',
'#e31a1c','#fdbf6f','#ff7f00','#cab2d6','#6a3d9a'])
colors = ['#a1a1a1','#a6cee3','#1f78b4','#b2df8a','#33a02c','#fb9a99',
'#e31a1c','#fdbf6f','#ff7f00','#cab2d6','#6a3d9a']
cmap = matplotlib.colors.ListedColormap(colors)
plt.figure()
plt.pcolormesh(code,cmap=cmap)
plt.title('Basin Mask')
ax = plt.gca()
gridspec = '/archive/gold/datasets/OM4_025/mosaic.v20140610.unpacked'
x = netCDF4.Dataset(gridspec + '/ocean_hgrid.nc').variables['x'][::2, ::2]
xcenter = netCDF4.Dataset(gridspec + '/ocean_hgrid.nc').variables['x'][1::2,
1::2]
y = netCDF4.Dataset(gridspec + '/ocean_hgrid.nc').variables['y'][::2, ::2]
ycenter = netCDF4.Dataset(gridspec + '/ocean_hgrid.nc').variables['y'][1::2,
1::2]
msk = netCDF4.Dataset(gridspec + '/ocean_mask.nc').variables['mask'][:]
area = msk * netCDF4.Dataset(
gridspec + '/ocean_hgrid.nc').variables['area'][:, :].reshape(
[msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(gridspec + '/ocean_topog.nc').variables['depth'][:]
code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
cmap = matplotlib.colors.ListedColormap([
'#a1a1a1', '#a6cee3', '#1f78b4', '#b2df8a', '#33a02c', '#fb9a99',
'#e31a1c', '#fdbf6f', '#ff7f00', '#cab2d6', '#6a3d9a'
])
colors = [
'#a1a1a1', '#a6cee3', '#1f78b4', '#b2df8a', '#33a02c', '#fb9a99',
'#e31a1c', '#fdbf6f', '#ff7f00', '#cab2d6', '#6a3d9a'
]
cmap = matplotlib.colors.ListedColormap(colors)
plt.figure()
plt.pcolormesh(code, cmap=cmap)
def main(cmdLineArgs, stream=False):
if not os.path.exists(cmdLineArgs.gridspec):
raise ValueError(
'Specified gridspec directory/tar file does not exist.')
if os.path.isdir(cmdLineArgs.gridspec):
xcenter = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['x'][1::2, 1::2]
y = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['y'][1::2, 1::2].max(
axis=-1)
ycenter = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['y'][1::2, 1::2]
msk = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_mask.nc').variables['mask'][:]
area = msk * netCDF4.Dataset(
cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['area'][:, :].reshape(
[msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_topog.nc').variables['depth'][:]
try:
basin = netCDF4.Dataset(cmdLineArgs.gridspec +
'/basin_codes.nc').variables['basin'][:]
except:
basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
elif os.path.isfile(cmdLineArgs.gridspec):
xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'ocean_hgrid.nc', 'x')[1::2, 1::2]
y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc',
'y')[1::2, 1::2].max(axis=-1)
ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'ocean_hgrid.nc', 'y')[1::2, 1::2]
msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_mask.nc',
'mask')[:]
area = msk * m6toolbox.readNCFromTar(
cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'area')[:, :].reshape(
[msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_topog.nc',
'depth')[:]
try:
basin = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'basin_codes.nc', 'basin')[:]
except:
basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
else:
raise ValueError(
'Unable to extract grid information from gridspec directory/tar file.'
)
Sobs = netCDF4.Dataset(cmdLineArgs.woa).variables['salt']
if len(Sobs.shape) == 3: Sobs = Sobs[:]
else: Sobs = Sobs[:].mean(axis=0)
Zobs = netCDF4.Dataset(cmdLineArgs.woa).variables['eta'][:]
rootGroup = netCDF4.MFDataset(cmdLineArgs.infile)
if 'salt' in rootGroup.variables: varName = 'salt'
elif 'so' in rootGroup.variables: varName = 'so'
else:
raise Exception('Could not find "salt" or "so" in file "%s"' %
(cmdLineArgs.infile))
if len(rootGroup.variables[varName].shape) == 4:
Smod = rootGroup.variables[varName][:].mean(axis=0)
else:
Smod = rootGroup.variables[varName][:]
if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0]
else: Zmod = Zobs # Using model z-output
def zonalAverage(S, eta, area, mask=1.):
vols = (mask * area) * (eta[:-1] - eta[1:]
) # mask * area * level thicknesses
return numpy.sum(vols * S, axis=-1) / numpy.sum(vols, axis=-1), (
mask * eta).min(axis=-1)
ci = m6plot.pmCI(0.125, 2.25, .25)
if cmdLineArgs.suptitle != '':
suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label
else:
suptitle = rootGroup.title + ' ' + cmdLineArgs.label
imgbufs = []
# Global
sPlot, z = zonalAverage(Smod, Zmod, area)
sObsPlot, _ = zonalAverage(Sobs, Zobs, area)
if stream is True: objOut = io.BytesIO()
else: objOut = cmdLineArgs.outdir + '/S_global_xave_bias_WOA05.png'
m6plot.yzplot(
sPlot - sObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title='''Global zonal-average salinity bias (w.r.t. WOA'05) [ppt]''',
clim=ci,
colormap='dunnePM',
centerlabels=True,
extend='both',
save=objOut)
if stream is True: imgbufs.append(objOut)
if stream is None:
m6plot.yzcompare(sPlot,
sObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1='Global zonal-average salinity [ppt]',
title2='''WOA'05 salinity [ppt]''',
clim=m6plot.linCI(20, 30, 10, 31, 39, .5),
colormap='dunneRainbow',
extend='both',
dlim=ci,
dcolormap='dunnePM',
dextend='both',
centerdlabels=True,
save=cmdLineArgs.outdir +
'/S_global_xave_bias_WOA05.3_panel.png')
# Atlantic + Arctic
newMask = 1. * msk
newMask[(basin != 2) & (basin != 4)] = 0.
sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask)
sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask)
if stream is True: objOut = io.BytesIO()
else: objOut = cmdLineArgs.outdir + '/S_Atlantic_xave_bias_WOA05.png'
m6plot.yzplot(
sPlot - sObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title='''Atlantic zonal-average salinity bias (w.r.t. WOA'05) [ppt]''',
clim=ci,
colormap='dunnePM',
centerlabels=True,
extend='both',
save=objOut)
if stream is True: imgbufs.append(objOut)
if stream is None:
m6plot.yzcompare(sPlot,
sObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1='Atlantic zonal-average salinity [ppt]',
title2='''WOA'05 salinity [ppt]''',
clim=m6plot.linCI(20, 30, 10, 31, 39, .5),
colormap='dunneRainbow',
extend='both',
dlim=ci,
dcolormap='dunnePM',
dextend='both',
centerdlabels=True,
save=cmdLineArgs.outdir +
'/S_Atlantic_xave_bias_WOA05.3_panel.png')
# Pacific
newMask = 1. * msk
newMask[(basin != 3)] = 0.
sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask)
sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask)
if stream is True: objOut = io.BytesIO()
else: objOut = cmdLineArgs.outdir + '/S_Pacific_xave_bias_WOA05.png'
m6plot.yzplot(
sPlot - sObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title='''Pacific zonal-average salinity bias (w.r.t. WOA'05) [ppt]''',
clim=ci,
colormap='dunnePM',
centerlabels=True,
extend='both',
save=objOut)
if stream is True: imgbufs.append(objOut)
if stream is None:
m6plot.yzcompare(sPlot,
sObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1='Pacific zonal-average salinity [ppt]',
title2='''WOA'05 salinity [ppt]''',
clim=m6plot.linCI(20, 30, 10, 31, 39, .5),
colormap='dunneRainbow',
extend='both',
dlim=ci,
dcolormap='dunnePM',
dextend='both',
centerdlabels=True,
save=cmdLineArgs.outdir +
'/S_Pacific_xave_bias_WOA05.3_panel.png')
# Indian
newMask = 1. * msk
newMask[(basin != 5)] = 0.
sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask)
sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask)
if stream is True: objOut = io.BytesIO()
else: objOut = cmdLineArgs.outdir + '/S_Indian_xave_bias_WOA05.png'
m6plot.yzplot(
sPlot - sObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title='''Indian zonal-average salinity bias (w.r.t. WOA'05) [ppt]''',
clim=ci,
colormap='dunnePM',
centerlabels=True,
extend='both',
save=objOut)
if stream is True: imgbufs.append(objOut)
if stream is None:
m6plot.yzcompare(sPlot,
sObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1='Indian zonal-average salinity [ppt]',
title2='''WOA'05 salinity [ppt]''',
clim=m6plot.linCI(20, 30, 10, 31, 39, .5),
colormap='dunneRainbow',
extend='both',
dlim=ci,
dcolormap='dunnePM',
dextend='both',
centerdlabels=True,
save=cmdLineArgs.outdir +
'/S_Indian_xave_bias_WOA05.3_panel.png')
if stream is True:
return imgbufs
def main(cmdLineArgs,stream=None):
if not os.path.exists(cmdLineArgs.gridspec): raise ValueError('Specified gridspec directory/tar file does not exist.')
if os.path.isdir(cmdLineArgs.gridspec):
x = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['x'][::2,::2]
xcenter = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['x'][1::2,1::2]
y = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['y'][::2,::2]
ycenter = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['y'][1::2,1::2]
msk = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_mask.nc').variables['mask'][:]
area = msk*netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['area'][:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_topog.nc').variables['depth'][:]
try: basin_code = netCDF4.Dataset(cmdLineArgs.gridspec+'/basin_codes.nc').variables['basin'][:]
except: basin_code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
elif os.path.isfile(cmdLineArgs.gridspec):
x = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','x')[::2,::2]
xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','x')[1::2,1::2]
y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[::2,::2]
ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[1::2,1::2]
msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_mask.nc','mask')[:]
area = msk*m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','area')[:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_topog.nc','depth')[:]
try: basin_code = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'basin_codes.nc','basin')[:]
except: basin_code = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
else:
raise ValueError('Unable to extract grid information from gridspec directory/tar file.')
if stream != None:
if len(stream) != 3:
raise ValueError('If specifying output streams, exactly three streams are needed for this analysis')
rootGroup = netCDF4.MFDataset( cmdLineArgs.annual_file )
if 'T_ady_2d' in rootGroup.variables:
varName = 'T_ady_2d'
if len(rootGroup.variables[varName].shape)==3: advective = rootGroup.variables[varName][:].mean(axis=0).filled(0.)
else: advective = rootGroup.variables[varName][:].filled(0.)
else: raise Exception('Could not find "T_ady_2d" in file "%s"'%(cmdLineArgs.annual_file))
if 'T_diffy_2d' in rootGroup.variables:
varName = 'T_diffy_2d'
if len(rootGroup.variables[varName].shape)==3: diffusive = rootGroup.variables[varName][:].mean(axis=0).filled(0.)
else: diffusive = rootGroup.variables[varName][:].filled(0.)
else:
diffusive = None
warnings.warn('Diffusive temperature term not found. This will result in an underestimation of the heat transport.')
def heatTrans(advective, diffusive=None, vmask=None):
"""Converts vertically integrated temperature advection into heat transport"""
rho0 = 1.035e3; Cp = 3989.
if diffusive != None: HT = advective + diffusive
else: HT = advective
HT = HT * (rho0 * Cp); HT = HT * 1.e-15 # convert to PW
if vmask != None: HT = HT*vmask
HT = HT.sum(axis=-1); HT = HT.squeeze() # sum in x-direction
return HT
def plotHeatTrans(y, HT, title, xlim=(-80,90)):
plt.plot(y, y*0., 'k', linewidth=0.5)
plt.plot(y, HT, 'r', linewidth=1.5,label='Model')
plt.xlim(xlim); plt.ylim(-2.5,3.0)
plt.title(title)
plt.grid(True)
def annotatePlot(label):
fig = plt.gcf()
#fig.text(0.1,0.85,label)
fig.text(0.535,0.12,label)
def annotateObs():
fig = plt.gcf()
fig.text(0.1,0.85,r"Trenberth, K. E. and J. M. Caron, 2001: Estimates of Meridional Atmosphere and Ocean Heat Transports. J.Climate, 14, 3433-3443.", fontsize=8)
fig.text(0.1,0.825,r"Ganachaud, A. and C. Wunsch, 2000: Improved estimates of global ocean circulation, heat transport and mixing from hydrographic data.", fontsize=8)
fig.text(0.13,0.8,r"Nature, 408, 453-457", fontsize=8)
m6plot.setFigureSize(npanels=1)
# Load Observations
fObs = netCDF4.Dataset('/archive/John.Krasting/obs/TC2001/Trenberth_and_Caron_Heat_Transport.nc') #Trenberth and Caron
yobs = fObs.variables['ylat'][:]
NCEP = {}; NCEP['Global'] = fObs.variables['OTn']
NCEP['Atlantic'] = fObs.variables['ATLn'][:]; NCEP['IndoPac'] = fObs.variables['INDPACn'][:]
ECMWF = {}; ECMWF['Global'] = fObs.variables['OTe'][:]
ECMWF['Atlantic'] = fObs.variables['ATLe'][:]; ECMWF['IndoPac'] = fObs.variables['INDPACe'][:]
#G and W
Global = {}
Global['lat'] = numpy.array([-30., -19., 24., 47.])
Global['trans'] = numpy.array([-0.6, -0.8, 1.8, 0.6])
Global['err'] = numpy.array([0.3, 0.6, 0.3, 0.1])
Atlantic = {}
Atlantic['lat'] = numpy.array([-45., -30., -19., -11., -4.5, 7.5, 24., 47.])
Atlantic['trans'] = numpy.array([0.66, 0.35, 0.77, 0.9, 1., 1.26, 1.27, 0.6])
Atlantic['err'] = numpy.array([0.12, 0.15, 0.2, 0.4, 0.55, 0.31, 0.15, 0.09])
IndoPac = {}
IndoPac['lat'] = numpy.array([-30., -18., 24., 47.])
IndoPac['trans'] = numpy.array([-0.9, -1.6, 0.52, 0.])
IndoPac['err'] = numpy.array([0.3, 0.6, 0.2, 0.05,])
GandW = {}
GandW['Global'] = Global
GandW['Atlantic'] = Atlantic
GandW['IndoPac'] = IndoPac
def plotGandW(lat,trans,err):
low = trans - err
high = trans + err
for n in range(0,len(low)):
if n == 0:
plt.plot([lat[n],lat[n]], [low[n],high[n]], 'c', linewidth=2.0, label='G&W')
else:
plt.plot([lat[n],lat[n]], [low[n],high[n]], 'c', linewidth=2.0)
plt.scatter(lat,trans,marker='s',facecolor='cyan')
if cmdLineArgs.suptitle != '': suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label
else: suptitle = rootGroup.title + ' ' + cmdLineArgs.label
# Global Heat Transport
HTplot = heatTrans(advective,diffusive)
yy = y[1:,:].max(axis=-1)
plotHeatTrans(yy,HTplot,title='Global Y-Direction Heat Transport [PW]')
plt.plot(yobs,NCEP['Global'],'k--',linewidth=0.5,label='NCEP')
plt.plot(yobs,ECMWF['Global'],'k.',linewidth=0.5,label='ECMWF')
plotGandW(GandW['Global']['lat'],GandW['Global']['trans'],GandW['Global']['err'])
plt.xlabel(r'Latitude [$\degree$N]')
plt.suptitle(suptitle)
plt.legend(loc=0,fontsize=10)
annotateObs()
if diffusive is None: annotatePlot('Warning: Diffusive component of transport is missing.')
if stream != None:
plt.savefig(stream[0])
else:
plt.savefig(cmdLineArgs.outdir+'/HeatTransport_global.png')
# Atlantic Heat Transport
plt.clf()
m = 0*basin_code; m[(basin_code==2) | (basin_code==4) | (basin_code==6) | (basin_code==7) | (basin_code==8)] = 1
HTplot = heatTrans(advective, diffusive, vmask=m*numpy.roll(m,-1,axis=-2))
yy = y[1:,:].max(axis=-1)
HTplot[yy<-34] = numpy.nan
plotHeatTrans(yy,HTplot,title='Atlantic Y-Direction Heat Transport [PW]')
plt.plot(yobs,NCEP['Atlantic'],'k--',linewidth=0.5,label='NCEP')
plt.plot(yobs,ECMWF['Atlantic'],'k.',linewidth=0.5,label='ECMWF')
plotGandW(GandW['Atlantic']['lat'],GandW['Atlantic']['trans'],GandW['Atlantic']['err'])
plt.xlabel(r'Latitude [$\degree$N]')
plt.suptitle(suptitle)
plt.legend(loc=0,fontsize=10)
annotateObs()
if diffusive is None: annotatePlot('Warning: Diffusive component of transport is missing.')
if stream != None:
plt.savefig(stream[1])
else:
plt.savefig(cmdLineArgs.outdir+'/HeatTransport_Atlantic.png')
# Indo-Pacific Heat Transport
plt.clf()
m = 0*basin_code; m[(basin_code==3) | (basin_code==5)] = 1
HTplot = heatTrans(advective, diffusive, vmask=m*numpy.roll(m,-1,axis=-2))
yy = y[1:,:].max(axis=-1)
HTplot[yy<-34] = numpy.nan
plotHeatTrans(yy,HTplot,title='Indo-Pacific Y-Direction Heat Transport [PW]')
plt.plot(yobs,NCEP['IndoPac'],'k--',linewidth=0.5,label='NCEP')
plt.plot(yobs,ECMWF['IndoPac'],'k.',linewidth=0.5,label='ECMWF')
plotGandW(GandW['IndoPac']['lat'],GandW['IndoPac']['trans'],GandW['IndoPac']['err'])
plt.xlabel(r'Latitude [$\degree$N]')
annotateObs()
if diffusive is None: annotatePlot('Warning: Diffusive component of transport is missing.')
plt.suptitle(suptitle)
plt.legend(loc=0,fontsize=10)
if stream != None:
plt.savefig(stream[2])
else:
plt.savefig(cmdLineArgs.outdir+'/HeatTransport_IndoPac.png')
def main(cmdLineArgs, stream=None):
if not os.path.exists(cmdLineArgs.gridspec):
raise ValueError(
'Specified gridspec directory/tar file does not exist.')
if os.path.isdir(cmdLineArgs.gridspec):
xcenter = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['x'][1::2, 1::2]
y = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['y'][1::2, 1::2].max(
axis=-1)
ycenter = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['y'][1::2, 1::2]
msk = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_mask.nc').variables['mask'][:]
area = msk * netCDF4.Dataset(
cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['area'][:, :].reshape(
[msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_topog.nc').variables['depth'][:]
try:
basin = netCDF4.Dataset(cmdLineArgs.gridspec +
'/basin_codes.nc').variables['basin'][:]
except:
basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
elif os.path.isfile(cmdLineArgs.gridspec):
xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'ocean_hgrid.nc', 'x')[1::2, 1::2]
y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc',
'y')[1::2, 1::2].max(axis=-1)
ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'ocean_hgrid.nc', 'y')[1::2, 1::2]
msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_mask.nc',
'mask')[:]
area = msk * m6toolbox.readNCFromTar(
cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'area')[:, :].reshape(
[msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1)
depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_topog.nc',
'depth')[:]
try:
basin = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,
'basin_codes.nc', 'basin')[:]
except:
basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth)
else:
raise ValueError(
'Unable to extract grid information from gridspec directory/tar file.'
)
if stream != None:
if len(stream) != 4:
raise ValueError(
'If specifying output streams, exactly four (4) streams are needed for this analysis'
)
Tobs = netCDF4.Dataset(cmdLineArgs.woa)
if 'temp' in Tobs.variables: Tobs = Tobs.variables['temp']
else: Tobs = Tobs.variables['ptemp']
if len(Tobs.shape) == 3: Tobs = Tobs[:]
else: Tobs = Tobs[:].mean(axis=0)
Zobs = netCDF4.Dataset(cmdLineArgs.woa).variables['eta'][:]
rootGroup = netCDF4.MFDataset(cmdLineArgs.annual_file)
if 'temp' in rootGroup.variables: varName = 'temp'
elif 'ptemp' in rootGroup.variables: varName = 'ptemp'
elif 'thetao' in rootGroup.variables: varName = 'thetao'
else:
raise Exception(
'Could not find "temp", "ptemp" or "thetao" in file "%s"' %
(cmdLineArgs.annual_file))
if len(rootGroup.variables[varName].shape) == 4:
Tmod = rootGroup.variables[varName][:].mean(axis=0)
else:
Tmod = rootGroup.variables[varName][:]
if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0]
else: Zmod = Zobs # Using model z-ou:put
def zonalAverage(T, eta, area, mask=1.):
vols = (mask * area) * (eta[:-1] - eta[1:]
) # mask * area * level thicknesses
return numpy.sum(vols * T, axis=-1) / numpy.sum(vols, axis=-1), (
mask * eta).min(axis=-1)
ci = m6plot.pmCI(0.25, 4.5, .5)
if cmdLineArgs.suptitle != '':
suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label
else:
suptitle = rootGroup.title + ' ' + cmdLineArgs.label
# Global
tPlot, z = zonalAverage(Tmod, Zmod, area)
tObsPlot, _ = zonalAverage(Tobs, Zobs, area)
if stream != None: objOut = stream[0]
else: objOut = cmdLineArgs.outdir + '/T_global_xave_bias_WOA05.png'
m6plot.yzplot(
tPlot - tObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title=
r'''Global zonal-average $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''',
clim=ci,
colormap='dunnePM',
centerlabels=True,
extend='both',
save=objOut)
if stream is None:
m6plot.yzcompare(tPlot,
tObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1=r'Global zonal-average $\theta$ [$\degree$C]',
title2=r'''WOA'05 $\theta$ [$\degree$C]''',
clim=m6plot.linCI(-2, 29, .5),
colormap='dunneRainbow',
extend='max',
dlim=ci,
dcolormap='dunnePM',
dextend='both',
centerdlabels=True,
save=cmdLineArgs.outdir +
'/T_global_xave_bias_WOA05.3_panel.png')
# Atlantic + Arctic
newMask = 1. * msk
newMask[(basin != 2) & (basin != 4)] = 0.
tPlot, z = zonalAverage(Tmod, Zmod, area, mask=newMask)
tObsPlot, _ = zonalAverage(Tobs, Zobs, area, mask=newMask)
if stream != None: objOut = stream[1]
else: objOut = cmdLineArgs.outdir + '/T_Atlantic_xave_bias_WOA05.png'
m6plot.yzplot(
tPlot - tObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title=
r'''Atlantic zonal-average $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''',
clim=ci,
colormap='dunnePM',
centerlabels=True,
extend='both',
save=objOut)
if stream is None:
m6plot.yzcompare(
tPlot,
tObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1=r'Atlantic zonal-average $\theta$ [$\degree$C]',
title2=r'''WOA'05 $\theta$ [$\degree$C]''',
clim=m6plot.linCI(-2, 29, .5),
colormap='dunneRainbow',
extend='max',
dlim=ci,
dcolormap='dunnePM',
dextend='both',
centerdlabels=True,
save=cmdLineArgs.outdir +
'/T_Atlantic_xave_bias_WOA05.3_panel.png')
# Pacific
newMask = 1. * msk
newMask[(basin != 3)] = 0.
tPlot, z = zonalAverage(Tmod, Zmod, area, mask=newMask)
tObsPlot, _ = zonalAverage(Tobs, Zobs, area, mask=newMask)
if stream != None: objOut = stream[2]
else: objOut = cmdLineArgs.outdir + '/T_Pacific_xave_bias_WOA05.png'
m6plot.yzplot(
tPlot - tObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title=
r'''Pacific zonal-average $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''',
clim=ci,
colormap='dunnePM',
centerlabels=True,
extend='both',
save=objOut)
if stream is None:
m6plot.yzcompare(tPlot,
tObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1=r'Pacific zonal-average $\theta$ [$\degree$C]',
title2=r'''WOA'05 $\theta$ [$\degree$C]''',
clim=m6plot.linCI(-2, 29, .5),
colormap='dunneRainbow',
extend='max',
dlim=ci,
dcolormap='dunnePM',
dextend='both',
centerdlabels=True,
save=cmdLineArgs.outdir +
'/T_Pacific_xave_bias_WOA05.3_panel.png')
# Indian
newMask = 1. * msk
newMask[(basin != 5)] = 0.
tPlot, z = zonalAverage(Tmod, Zmod, area, mask=newMask)
tObsPlot, _ = zonalAverage(Tobs, Zobs, area, mask=newMask)
if stream != None: objOut = stream[3]
else: objOut = cmdLineArgs.outdir + '/T_Indian_xave_bias_WOA05.png'
m6plot.yzplot(
tPlot - tObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title=
r'''Indian zonal-average $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''',
clim=ci,
colormap='dunnePM',
centerlabels=True,
extend='both',
save=objOut)
if stream is None:
m6plot.yzcompare(tPlot,
tObsPlot,
y,
z,
splitscale=[0., -1000., -6500.],
suptitle=suptitle,
title1=r'Indian zonal-average $\theta$ [$\degree$C]',
title2=r'''WOA'05 $\theta$ [$\degree$C]''',
clim=m6plot.linCI(-2, 29, .5),
colormap='dunneRainbow',
extend='max',
dlim=ci,
dcolormap='dunnePM',
dextend='both',
centerdlabels=True,
save=cmdLineArgs.outdir +
'/T_Indian_xave_bias_WOA05.3_panel.png')