An example interactive python session to plot SST from MOM6 post-processed files, using just matplotlib and netCDF4

demo_plot_MOM6_SST.py

# Import necessary modules
import netCDF4
import matplotlib.pyplot as plt

tFiles = netCDF4.MFDataset('/archive/bls/tikal_201406_mom6_2014.07.01/OM4_SIS_baseline/gfdl.ncrc2-intel-prod/pp/ocean_monthly/ts/monthly/10yr/ocean_monthly.*.temp.nc')
print tFiles
 
tType = tFiles.variables['temp']
print tType
print tType.shape
 
# These all give the same results
sst = tType[0,0]
sst = tType[0,0,:]
sst = tType[0,0,:,:]
print sst.shape
 
# Quickly check data
plt.pcolormesh( sst ); plt.show(block=False)
# Add a colorbar. Note different usages of plt.show() - I prefer block=False for instant results
plt.colorbar()
plt.show()
 
# Now read the grid from the super-grid. Note the various one-line equivalents of the multiple steps used above.
superGridFile = netCDF4.Dataset('/archive/gold/datasets/OM4_025/mosaic.v20140610.unpacked/ocean_hgrid.nc')
lon = superGridFile.variables['x'][::2,::2]
lat = superGridFile.variables['y'][::2,::2]
lat = netCDF4.Dataset('/archive/gold/datasets/OM4_025/mosaic.v20140610.unpacked/ocean_hgrid.nc').variables['y'][::2,0::2]
# lon,lat are the corner positions of T-cells (nodes of mesh where SST will be cell-cnetered) and thus 1 row/col wider than SST

# Plot with proper coordinates
plt.pcolormesh(lon, lat, sst); plt.colorbar(); plt.show(block=False)

# Now animate
plt.clf(); plt.show(block=False)
for n in range(tType.shape[0]):
    plt.clf(); plt.pcolormesh(lon, lat, tType[n,0,:,:]); plt.colorbar(); plt.draw()