.. 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
====================================

.. how-to:: Plotting Wind Direction Using Quiver
   :tags: topic_plotting

   How to use Iris to plot wind quivers.

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 18-68



.. 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 0.503 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>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_wind_speed.zip <plot_wind_speed.zip>`


.. only:: html

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

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