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Plotting wind direction using quiverΒΆ

This example demonstrates using quiver to plot wind speed contours and wind direction arrows from wind vector component input data. The vector components are co-located in space in this case.

For the second plot, the data used for the arrows is normalised to produce arrows with a uniform size on the plot.

"""
Plotting wind direction using quiver
===========================================================

This example demonstrates using quiver to plot wind speed contours and wind
direction arrows from wind vector component input data. The vector components
are co-located in space in this case.

For the second plot, the data used for the arrows is normalised to produce
arrows with a uniform size on the plot.

"""

import matplotlib.pyplot as plt
import numpy as np

import iris
import iris.coord_categorisation
import iris.quickplot as qplt

import cartopy
import cartopy.feature as cfeat
import cartopy.crs as ccrs


def main():
    # Load the u and v components of wind from a pp file
    infile = iris.sample_data_path('wind_speed_lake_victoria.pp')

    uwind = iris.load_cube(infile, 'x_wind')
    vwind = iris.load_cube(infile, 'y_wind')

    ulon = uwind.coord('longitude')
    vlon = vwind.coord('longitude')

    # The longitude points go from 180 to 540, so subtract 360 from them
    ulon.points = ulon.points - 360.0
    vlon.points = vlon.points - 360.0

    # Create a cube containing the wind speed
    windspeed = (uwind ** 2 + vwind ** 2) ** 0.5
    windspeed.rename('windspeed')

    x = ulon.points
    y = uwind.coord('latitude').points
    u = uwind.data
    v = vwind.data

    # Set up axes to show the lake
    lakes = cfeat.NaturalEarthFeature('physical', 'lakes', '50m',
                                      facecolor='none')

    plt.figure()
    ax = plt.axes(projection=ccrs.PlateCarree())
    ax.add_feature(lakes)

    # Get the coordinate reference system used by the data
    transform = ulon.coord_system.as_cartopy_projection()

    # Plot the wind speed as a contour plot
    qplt.contourf(windspeed, 20)

    # Add arrows to show the wind vectors
    plt.quiver(x, y, u, v, pivot='middle', transform=transform)

    plt.title("Wind speed over Lake Victoria")
    qplt.show()

    # Normalise the data for uniform arrow size
    u_norm = u / np.sqrt(u ** 2.0 + v ** 2.0)
    v_norm = v / np.sqrt(u ** 2.0 + v ** 2.0)

    plt.figure()
    ax = plt.axes(projection=ccrs.PlateCarree())
    ax.add_feature(lakes)

    qplt.contourf(windspeed, 20)

    plt.quiver(x, y, u_norm, v_norm, pivot='middle', transform=transform)

    plt.title("Wind speed over Lake Victoria")
    qplt.show()

if __name__ == '__main__':
    main()

(Source code)

../../_images/wind_speed_00.png

(png)

../../_images/wind_speed_01.png

(png)