MLD_obs = netCDF4.Dataset(cmdLineArgs.obsdata).variables['MLD'][:]
x_obs = netCDF4.Dataset(cmdLineArgs.obsdata).variables['LONGITUDE'][:]
y_obs = netCDF4.Dataset(cmdLineArgs.obsdata).variables['LATITUDE'][:]
ciMin = m6plot.linCI(0,95,5)
ciMax = m6plot.linCI(0,680,20)
# Plot of shallowest model MLD (summer)
m6plot.xyplot( MLD.min(axis=0), x, y, area=area,
suptitle=rootGroup.title+' '+cmdLineArgs.label, title='Annual-minimum MLD$_{0.03}$ [m]',
clim=ciMin, extend='max', colormap='dunneRainbow',
save=cmdLineArgs.outdir+'/MLD_003_minimum.png')
# 2-panel plot of shallowest model MLD + obs (summer)
m6plot.setFigureSize(aspect=[3,3], verticalresolution=976, npanels=0)
ax1 = plt.subplot(2,1,1)
m6plot.xyplot( numpy.roll(MLD_obs.min(axis=0),300,axis=-1), x_obs-300, y_obs,
suptitle=rootGroup.title+' '+cmdLineArgs.label, title='Hosoda et al., 2010, annual-minimum MLD$_{0.03}$ [m]',
clim=ciMin, extend='max', colormap='dunneRainbow',
axis=ax1)
ax2 = plt.subplot(2,1,2)
m6plot.xyplot( MLD.min(axis=0), x, y, area=area,
suptitle=rootGroup.title+' '+cmdLineArgs.label, title='Annual-minimum MLD$_{0.03}$ [m]',
clim=ciMin, extend='max', colormap='dunneRainbow',
axis=ax2,
save=cmdLineArgs.outdir+'/MLD_003_minimum.2_panel.png')
# Plot of deepest model MLD (winter)
m6plot.xyplot( MLD.max(axis=0), x, y, area=area,
suptitle=rootGroup.title+' '+cmdLineArgs.label, title='Annual-maximum MLD$_{0.03}$ [m]',
def main(cmdLineArgs, stream=False):
rootGroup = netCDF4.MFDataset(cmdLineArgs.infile)
if 'MLD_003' not in rootGroup.variables:
raise Exception('Could not find "MLD_003" in file "%s"' %
(cmdLineArgs.infile))
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]
y = netCDF4.Dataset(cmdLineArgs.gridspec +
'/ocean_hgrid.nc').variables['y'][::2, ::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)
elif os.path.isfile(cmdLineArgs.gridspec):
x = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc',
'x')[::2, ::2]
y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc',
'y')[::2, ::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)
else:
raise ValueError(
'Unable to extract grid information from gridspec directory/tar file.'
)
variable = rootGroup.variables['MLD_003']
shape = variable.shape
MLD = variable[:].reshape(shape[0] / 12, 12, shape[1],
shape[2]).mean(axis=0)
if not hasattr(cmdLineArgs, 'obsdata') or cmdLineArgs.obsdata == '':
cmdLineArgs.obsdata = '/archive/gold/datasets/obs/Hosada2010_MLD_climatology.v20140515.nc'
MLD_obs = netCDF4.Dataset(cmdLineArgs.obsdata).variables['MLD'][:]
x_obs = netCDF4.Dataset(cmdLineArgs.obsdata).variables['LONGITUDE'][:]
y_obs = netCDF4.Dataset(cmdLineArgs.obsdata).variables['LATITUDE'][:]
ciMin = m6plot.linCI(0, 95, 5)
ciMax = m6plot.linCI(0, 680, 20)
imgbufs = []
# Plot of shallowest model MLD (summer)
m6plot.xyplot(MLD.min(axis=0),
x,
y,
area=area,
suptitle=rootGroup.title + ' ' + cmdLineArgs.label,
title='Annual-minimum MLD$_{0.03}$ [m]',
clim=ciMin,
extend='max',
colormap='dunneRainbow',
save=cmdLineArgs.outdir + '/MLD_003_minimum.png')
# 2-panel plot of shallowest model MLD + obs (summer)
if stream is True: img = io.BytesIO()
else: img = cmdLineArgs.outdir + '/MLD_003_minimum.2_panel.png'
m6plot.setFigureSize(aspect=[3, 3], verticalresolution=976, npanels=0)
ax1 = plt.subplot(2, 1, 1)
m6plot.xyplot(numpy.roll(MLD_obs.min(axis=0), 300, axis=-1),
x_obs - 300,
y_obs,
suptitle=rootGroup.title + ' ' + cmdLineArgs.label,
title='Hosoda et al., 2010, annual-minimum MLD$_{0.03}$ [m]',
clim=ciMin,
extend='max',
colormap='dunneRainbow',
axis=ax1)
ax2 = plt.subplot(2, 1, 2)
m6plot.xyplot(MLD.min(axis=0),
x,
y,
area=area,
suptitle=rootGroup.title + ' ' + cmdLineArgs.label,
title='Annual-minimum MLD$_{0.03}$ [m]',
clim=ciMin,
extend='max',
colormap='dunneRainbow',
axis=ax2,
save=img)
if stream is True: imgbufs.append(img)
# Plot of deepest model MLD (winter)
m6plot.xyplot(MLD.max(axis=0),
x,
y,
area=area,
suptitle=rootGroup.title + ' ' + cmdLineArgs.label,
title='Annual-maximum MLD$_{0.03}$ [m]',
clim=ciMax,
extend='max',
colormap='dunneRainbow',
save=cmdLineArgs.outdir + '/MLD_003_maximum.png')
# 2-panel plot of deepest model MLD + obs (winter)
if stream is True: img = io.BytesIO()
else: img = cmdLineArgs.outdir + '/MLD_003_maximum.2_panel.png'
m6plot.setFigureSize(aspect=[3, 3], verticalresolution=976, npanels=0)
ax1 = plt.subplot(2, 1, 1)
m6plot.xyplot(numpy.roll(MLD_obs.max(axis=0), 300, axis=-1),
x_obs - 300,
y_obs,
suptitle=rootGroup.title + ' ' + cmdLineArgs.label,
title='Hosoda et al., 2010, annual-maximum MLD$_{0.03}$ [m]',
clim=ciMax,
extend='max',
colormap='dunneRainbow',
axis=ax1)
ax2 = plt.subplot(2, 1, 2)
m6plot.xyplot(MLD.max(axis=0),
x,
y,
area=area,
suptitle=rootGroup.title + ' ' + cmdLineArgs.label,
title='Annual-maximum MLD$_{0.03}$ [m]',
clim=ciMax,
extend='max',
colormap='dunneRainbow',
axis=ax2,
save=img)
if stream is True: imgbufs.append(img)
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) != 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=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
ciMax = m6plot.linCI(0, 680, 20)
# Plot of shallowest model MLD (summer)
m6plot.xyplot(MLD.min(axis=0),
x,
y,
area=area,
suptitle=rootGroup.title + ' ' + cmdLineArgs.label,
title='Annual-minimum MLD$_{0.03}$ [m]',
clim=ciMin,
extend='max',
colormap='dunneRainbow',
save=cmdLineArgs.outdir + '/MLD_003_minimum.png')
# 2-panel plot of shallowest model MLD + obs (summer)
m6plot.setFigureSize(aspect=[3, 3], verticalresolution=976, npanels=0)
ax1 = plt.subplot(2, 1, 1)
m6plot.xyplot(numpy.roll(MLD_obs.min(axis=0), 300, axis=-1),
x_obs - 300,
y_obs,
suptitle=rootGroup.title + ' ' + cmdLineArgs.label,
title='Hosoda et al., 2010, annual-minimum MLD$_{0.03}$ [m]',
clim=ciMin,
extend='max',
colormap='dunneRainbow',
axis=ax1)
ax2 = plt.subplot(2, 1, 2)
m6plot.xyplot(MLD.min(axis=0),
x,
y,
area=area,
suptitle=rootGroup.title+' '+cmdLineArgs.label, title=r'''170$\degree$W $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''',
clim=ci, colormap='dunnePM', centerlabels=True, extend='both')
cs1 = plt.contour( y[j0:j1,i][:] + 0*z, z, tObsPlot, levels=numpy.arange(0.,45,2.), colors='k' ); plt.clabel(cs1,fmt='%.0f')
cs2 = plt.contour( y[j0:j1,i][:] + 0*z, z, tPlot, levels=numpy.arange(0.,45,2.), colors='g' ); plt.clabel(cs2,fmt='%.0f')
plt.ylim(-1200,0)
plt.savefig(cmdLineArgs.outdir+'/T_170W_bias_WOA05.png')
m6plot.yzcompare( tPlot, tObsPlot , y[j0:j1,i], zi, splitscale=[0., -1000., -6500.],
suptitle=rootGroup.title+' '+cmdLineArgs.label,
title1=r'170$\degree$W $\theta$ [$\degree$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_170W_bias_WOA05.3_panel.png')
m6plot.setFigureSize(); axis=plt.gca()
uPlot = rootGroup.variables['uo'][0,:,j0:j1,i]
plt.contourf( y[j0:j1,i][:] + 0*z, z, uPlot, levels=m6plot.linCI(-0.5,1.3,0.1), cmap='spectral', extend='both')
plt.colorbar(extend='both')
cs1 = plt.contour( y[j0:j1,i][:] + 0*z, z, uPlot, levels=m6plot.linCI(-0.5,1.3,0.1), colors='k'); plt.clabel(cs1,cs1.levels[::2],fmt='%.1f',inline_spacing=1)
plt.ylim(-600,0); plt.suptitle(rootGroup.title+' '+cmdLineArgs.label);plt.title(r'170$\degree$W u [m/s]')
plt.xlabel(r'Latitude [$\degree$N]'); plt.ylabel('Elevation [m]')
plt.savefig(cmdLineArgs.outdir+'/U_170W_bias_WOA05.png')
# 140W, 20S-20N
j0 = numpy.abs( y[:,0] + 20. ).argmin()
j1 = numpy.abs( y[:,0] - 20. ).argmin()
i = numpy.abs( numpy.mod( x[j0,:] + 140. + 360., 360. ) ).argmin()
tPlot = rootGroup.variables[varName][0,:,j0:j1,i]
tObsPlot = obsRootGroup.variables[OTvar][0,:,j0:j1,i]
zi = Zobs[:,j0:j1,i]; z = 0.5 * ( zi[:-1] + zi[1:] )
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]')
#plt.xlabel(r'Latitude [$\degree$N]')
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=3)
if len(cmdLineArgs.label1): title1 = cmdLineArgs.label1
else: title1 = rootGroup.title
if len(cmdLineArgs.label2): title2 = cmdLineArgs.label2
else: title2 = rootGroupRef.title
# Global MOC
z = Zmod.min(axis=-1)
yy = y[1:,:].max(axis=-1)+0*z
psiPlotM = MOCpsi(VHmod)/1e6
psiPlotR = MOCpsi(VHref)/1e6
ci=m6plot.pmCI(0.,40.,5.)
di=m6plot.pmCI(0.,5.,0.5)
plt.subplot(311)
plotPsi(yy, z, psiPlotM, ci, title1)
findExtrema(yy, z, psiPlotM, max_lat=-30.)
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')