Looking at your code trying to replicate the GOES-16 thermal map tutorial, here are the key issues causing unexpected output, along with straightforward fixes:

• Empty Title Rendering
  Your plt.title call uses a placeholder-free format string, so it won't display any text. The current line:

  plt.title(' on '.format(data_long_name, data_time_grab))
  

  Should be updated to include placeholders for your variables:

  plt.title('{0} on {1}'.format(data_long_name, data_time_grab))
  

  This will properly show the data's long name and timestamp in the plot title.

• Incorrect Missing Data Handling
  You're using np.where(data.data != 65535) to find valid data bounds, but GOES NetCDF data is often stored as masked arrays. Leveraging the built-in mask attribute is more reliable and avoids accidentally including invalid values:

  data_bounds = np.where(~data.mask)  # Invert the mask to select valid points
  

  If your data isn't masked, double-check that 65535 is indeed the correct fill value for your specific variable (verify from the NetCDF metadata—some GOES products use different values).

• Shading Parameter Mismatch
  The shading='gouraud' parameter in m.pcolormesh is designed for irregular triangular grids, but GOES-16 data uses regular gridded data. This can cause rendering artifacts or incorrect color interpolation. Switch to the appropriate setting for regular grids:

  m.pcolormesh(lon.data, lat.data, data, latlon=True, zorder=999, shading='flat')
  

• TeX Setup Placement
  Your plt.rc('text', usetex=True) line comes after creating the figure and colorbar, so it won't affect the colorbar label or title. Move this line to the top of your script, before initializing the figure:

  plt.rc('text', usetex=True)
  fig = plt.figure(figsize=(9, 4), dpi=200)
  

• Fragile Unit String Manipulation
  Your manual string replacement for units is error-prone. Use raw strings and proper TeX syntax directly instead:

  # Replace your current unit processing line with this
  cb.set_label(r'{} {}'.format(var_name, data_units))
  

  The r prefix ensures TeX commands are interpreted correctly without needing messy manual fixes.

• Minor: Simplified Savefig Color
  Your facecolor value can be rewritten as a hex string for better readability:

  plt.savefig('goes_16_data_demo.png', dpi=200, facecolor='#fcfcfc')
  

Fixed Full Code Snippet #

plt.rc('text', usetex=True)  # Move to top for proper TeX rendering
nc_folder = data_path # define folder where .nc files are located
lon, lat = lat_lon_reproj(nc_folder)
data, data_units, data_time_grab, data_long_name, var_name = data_grab(nc_folder, file_indx) # main data grab from function above

# Handle masked or fill-value based invalid data
data_bounds = np.where(~data.mask) if hasattr(data, 'mask') else np.where(data.data != 65535)
bbox = [np.min(lon[data_bounds]), np.min(lat[data_bounds]), np.max(lon[data_bounds]), np.max(lat[data_bounds])] # set bounds for plotting

# figure routine for visualization
fig = plt.figure(figsize=(9, 4), dpi=200)
n_add = 0 # for zooming in and out
m = Basemap(llcrnrlon=bbox[0] - n_add, llcrnrlat=bbox[1] - n_add, urcrnrlon=bbox[2] + n_add, urcrnrlat=bbox[3] + n_add, resolution='i', projection='cyl')
m.fillcontinents(color='#d9b38c', lake_color='#bdd5d5', zorder=1) # continent colors
m.drawmapboundary(fill_color='#bdd5d5', zorder=0) # ocean color
m.drawcoastlines(linewidth=0.5)
m.drawcountries(linewidth=0.25)
m.drawstates(zorder=2)

# Plot data with correct shading for regular grids
m.pcolormesh(lon.data, lat.data, data, latlon=True, zorder=999, shading='flat') # plotting actual LST data

parallels = np.linspace(bbox[1], bbox[3], 5)
m.drawparallels(parallels, labels=[True, False, False, False], zorder=2, fontsize=8)
meridians = np.linspace(bbox[0], bbox[2], 5)
m.drawmeridians(meridians, labels=[False, False, False, True], zorder=1, fontsize=8)

cb = m.colorbar()
# Clean unit label with raw TeX string
cb.set_label(r'{} {}'.format(var_name, data_units))
# Fixed title with proper variable insertion
plt.title('{0} on {1}'.format(data_long_name, data_time_grab))
plt.tight_layout()
# Simplified facecolor hex code
plt.savefig('goes_16_data_demo.png', dpi=200, facecolor='#fcfcfc') # uncomment to save figure
plt.show()

内容的提问来源于stack exchange，提问作者Hasham Ghuffary