NCL_proj_1.py

This script illustrates the following concepts:
  • Drawing filled contours over a Mollweide map

  • Setting the spacing for latitude/longitude grid lines

  • Changing the font size of the colorbar’s labels

  • Spanning part of a color map for contour fill

  • Turning off the map perimeter (boundary)

See following URLs to see the reproduced NCL plot & script:
import cartopy.crs as ccrs
import geocat.datafiles as gdf
import matplotlib.pyplot as plt

Import packages:

import numpy as np
import xarray as xr
from geocat.viz import cmaps as gvcmaps
from geocat.viz import util as gvutil

Read in data:

# Open a netCDF data file using xarray default engine and load the data into xarrays
ds = xr.open_dataset(gdf.get("netcdf_files/atmos.nc"), decode_times=False)
t = ds.TS.isel(time=0)

# Fix the artifact of not-shown-data around 0 and 360-degree longitudes
wrap_t = gvutil.xr_add_cyclic_longitudes(t, "lon")

Plot:

# Generate figure (set its size (width, height) in inches)
fig = plt.figure(figsize=(10, 10))

# Generate axes using Cartopy and draw coastlines
ax = plt.axes(projection=ccrs.Mollweide())
ax.coastlines(linewidths=0.5)

# Draw gridlines
gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=1, color='black', alpha=0.5)

# Import an NCL colormap
newcmp = gvcmaps.gui_default

# Contourf-plot data (for filled contours)
temp = wrap_t.plot.contourf(ax=ax,
                            transform=ccrs.PlateCarree(),
                            levels=11,
                            cmap=newcmp,
                            add_colorbar=False)

# Add color bar
cbar_ticks = np.arange(220, 310, 10)
cbar = plt.colorbar(temp,
                    orientation='horizontal',
                    shrink=0.8,
                    pad=0.05,
                    extendrect=True,
                    ticks=cbar_ticks)

cbar.ax.tick_params(labelsize=10)

# Contour-plot data (for borderlines)
wrap_t.plot.contour(ax=ax,
                    transform=ccrs.PlateCarree(),
                    levels=11,
                    linewidths=0.5,
                    cmap='black')

# Use geocat.viz.util convenience function to add titles to left and right of the plot axis.
gvutil.set_titles_and_labels(ax,
                             maintitle="Example of Mollweide Projection",
                             lefttitle="Surface Temperature",
                             righttitle="K")

# Show the plot
plt.show()
Surface Temperature, Example of Mollweide Projection, K

Total running time of the script: ( 0 minutes 0.853 seconds)

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