14.2. Color-filled Contouring

This notebook creates an example of overlaying color-filled contours and regular contours over the CONUS.

Import Packages

from datetime import datetime, timedelta

from metpy.plots import declarative
from metpy.units import units
import xarray as xr

Get Data

Here we use data available from the NCAR Research Data Archive (RDA) from the quarter degree GFS.

You can find other data available at this resource: https://rda.ucar.edu/thredds

# Set the date/time of the model run
date = datetime(2017, 2, 24, 12)

# Remote access to the dataset from the NCEI Archive
ds = xr.open_dataset('https://www.ncei.noaa.gov/thredds/dodsC/model-gfs-g3-anl-files-old'
                     f'/{date:%Y%m}/{date:%Y%m%d}/gfsanl_3_{date:%Y%m%d_%H}00_000.grb')

# Subset data to be just over the U.S. for plotting purposes
ds = ds.sel(lat=slice(70,10), lon=slice(360-140, 360-60)).metpy.parse_cf()

Plot Data

Here we demonstrate the use of FilledContourPlot() for having the computer draw color-filled contours of a variable. Many of the attributes are the same as ContourPlot(), but there are also other specific attributes for setting things like colorbars and a colormap. Only a small subset of atttributes are used in this example, but your plot can be further customized using a host of different attributes, which you can read about in the MetPy documentation.

MetPy FilledContourPlot() Documentation

# Set attributes for plotting contours
cntr = declarative.ContourPlot()
cntr.data = ds
cntr.field = 'Pressure_reduced_to_MSL_msl'
cntr.level = None
cntr.time = date
cntr.contours = range(0, 2000, 4)
cntr.clabels = True
cntr.plot_units = 'hPa'
cntr.smooth_field = 4 # Smooth the contours

# Set attributes for plotting filled contours
cfill = declarative.FilledContourPlot()
cfill.data = ds
cfill.field = 'Temperature_height_above_ground'
cfill.level = 2 * units.m
cfill.time = date
cfill.contours = range(-38, 103, 2)
cfill.colormap = 'coolwarm'
cfill.colorbar = 'horizontal'
cfill.plot_units = 'degF'

# Set attributes for plotting wind barbs
barbs = declarative.BarbPlot()
barbs.data = ds
barbs.time = date
barbs.field = ['u-component_of_wind_height_above_ground',
               'v-component_of_wind_height_above_ground']
barbs.level = 10 * units.m
barbs.skip = (2, 2)
barbs.plot_units = 'knot'

# Set the attributes for the map
# and put the contours on the map
panel = declarative.MapPanel()
panel.area = [-125, -74, 22, 52]
panel.projection = 'lcc'
panel.layers = ['states', 'coastline', 'borders']
panel.left_title = f'MSLP (hPa), 2-m TMPF, 10-m Wind Barbs (kts)'
panel.right_title = f'Valid Time: {date:%d %B %Y %H UTC}'
panel.plots = [cntr, cfill, barbs]

# Set the attributes for the panel
# and put the panel in the figure
pc = declarative.PanelContainer()
pc.size = (15, 15)
pc.panels = [panel]

# Show the figure
pc.show()