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

.. only:: html

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

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

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

.. _sphx_glr_examples_retrieve_plot_vad.py:


=========================================
Calculate and Plot VAD profile
=========================================

Calculates a VAD and plots a vertical profile of wind

.. GENERATED FROM PYTHON SOURCE LINES 8-49



.. image-sg:: /examples/retrieve/images/sphx_glr_plot_vad_001.png
   :alt: Wind profile obtained from VAD
   :srcset: /examples/retrieve/images/sphx_glr_plot_vad_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

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    min height 160.68632691167295  meters

    Text(0.5, 0.98, 'Wind profile obtained from VAD')





|

.. code-block:: Python


    # Author: Daniel Wolfensberger (daniel.wolfensberger@meteoswiss.ch)
    # License: BSD 3 clause

    import matplotlib.pyplot as plt
    import numpy as np
    from open_radar_data import DATASETS

    import pyart

    # Read in a sample file
    filename = DATASETS.fetch("MLA2119412050U.nc")
    radar = pyart.io.read_cfradial(filename)

    # Loop on all sweeps and compute VAD
    zlevels = np.arange(100, 5000, 100)  # height above radar
    u_allsweeps = []
    v_allsweeps = []

    for idx in range(radar.nsweeps):
        radar_1sweep = radar.extract_sweeps([idx])
        vad = pyart.retrieve.vad_browning(
            radar_1sweep, "corrected_velocity", z_want=zlevels
        )
        u_allsweeps.append(vad.u_wind)
        v_allsweeps.append(vad.v_wind)

    # Average U and V over all sweeps and compute magnitude and angle
    u_avg = np.nanmean(np.array(u_allsweeps), axis=0)
    v_avg = np.nanmean(np.array(v_allsweeps), axis=0)
    orientation = np.rad2deg(np.arctan2(-u_avg, -v_avg)) % 360
    speed = np.sqrt(u_avg**2 + v_avg**2)

    # Display vertical profile of wind
    fig, ax = plt.subplots(1, 2, sharey=True)
    ax[0].plot(speed * 2, zlevels + radar.altitude["data"])
    ax[1].plot(orientation, zlevels + radar.altitude["data"])
    ax[0].set_xlabel("Wind speed [m/s]")
    ax[1].set_xlabel("Wind direction [deg]")
    ax[0].set_ylabel("Altitude [m]")
    fig.suptitle("Wind profile obtained from VAD")


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

   **Total running time of the script:** (0 minutes 8.406 seconds)


.. _sphx_glr_download_examples_retrieve_plot_vad.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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