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:

• Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/proj_1.ncl

• Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/proj_1_lg.png

Import packages:

import numpy as np
import xarray as xr
import cartopy.crs as ccrs
import matplotlib.pyplot as plt

import geocat.datafiles as gdf
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()