.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "generated/gallery/meteorology/plot_wind_speed.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_generated_gallery_meteorology_plot_wind_speed.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_generated_gallery_meteorology_plot_wind_speed.py:


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.

.. GENERATED FROM PYTHON SOURCE LINES 13-63



.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /generated/gallery/meteorology/images/sphx_glr_plot_wind_speed_001.png
         :alt: Wind speed over Lake Victoria
         :srcset: /generated/gallery/meteorology/images/sphx_glr_plot_wind_speed_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /generated/gallery/meteorology/images/sphx_glr_plot_wind_speed_002.png
         :alt: Wind speed over Lake Victoria
         :srcset: /generated/gallery/meteorology/images/sphx_glr_plot_wind_speed_002.png
         :class: sphx-glr-multi-img





.. code-block:: Python


    import cartopy.feature as cfeat
    import matplotlib.pyplot as plt

    import iris
    import iris.plot as iplt
    import iris.quickplot as qplt


    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")

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

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

        # Show the lake on the current axes.
        lakes = cfeat.NaturalEarthFeature("physical", "lakes", "50m", facecolor="none")
        plt.gca().add_feature(lakes)

        # Add arrows to show the wind vectors.
        iplt.quiver(uwind, vwind, pivot="middle")

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

        # Normalise the data for uniform arrow size.
        u_norm = uwind / windspeed
        v_norm = vwind / windspeed

        # Make a new figure for the normalised plot.
        plt.figure()

        qplt.contourf(windspeed, 20)
        plt.gca().add_feature(lakes)
        iplt.quiver(u_norm, v_norm, pivot="middle")

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


    if __name__ == "__main__":
        main()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.663 seconds)


.. _sphx_glr_download_generated_gallery_meteorology_plot_wind_speed.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_wind_speed.ipynb <plot_wind_speed.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_wind_speed.py <plot_wind_speed.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_