NCL_lb_1.py

This script illustrates the following concepts:

• Making a horizontal colorbar

• Changing the colorbar labels

• Setting color maps using the new standard

See following URLs to see the reproduced NCL plot & script:

• Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/lb_1.ncl

• Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/lb_1_lg.png

Import packages

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

import geocat.datafiles as gdf
import geocat.viz as gv

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)
# Extract variable
v = ds.V.isel(time=0, lev=3)

# Fix the artifact of not-shown-data around 0 and 360-degree longitudes
wrap_v = gv.xr_add_cyclic_longitudes(v, "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.PlateCarree())
ax.coastlines(linewidths=0.5)

# Import an NCL colormap
newcmp = cmaps.wgne15

# Contourf-plot data (for filled contours)
a = wrap_v.plot.contourf(levels=np.arange(-24, 32, 4),
                         cmap=newcmp,
                         add_colorbar=False,
                         add_labels=False)
# Contour-plot data (for borderlines)
wrap_v.plot.contour(levels=np.arange(-24, 32, 4),
                    linewidths=0.5,
                    cmap='black',
                    add_labels=False)

# Add vertical colorbar
cbar = fig.colorbar(a,
                    label='',
                    ticks=np.arange(-20, 28, 4),
                    shrink=0.8,
                    orientation="horizontal",
                    extendrect=True,
                    pad=0.11,
                    drawedges=True)

# Use geocat.viz.util convenience function to set axes limits & tick values without calling several matplotlib functions
gv.set_axes_limits_and_ticks(ax,
                             ylim=(-90, 90),
                             xticks=np.linspace(-180, 180, 13),
                             yticks=np.linspace(-90, 90, 7))

# Use geocat.viz.util convenience function to add minor and major tick lines
gv.add_major_minor_ticks(ax, labelsize=10)

# Use geocat.viz.util convenience function to make plots look like NCL plots by using latitude, longitude tick labels
gv.add_lat_lon_ticklabels(ax)

# Use geocat.viz.util convenience function to add titles to left and right of the plot axis.
gv.set_titles_and_labels(ax,
                         lefttitle="meridional wind component",
                         lefttitlefontsize=14,
                         righttitle="m/s",
                         righttitlefontsize=14,
                         xlabel="",
                         ylabel="")

# Show the plot
plt.show()