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

.. only:: html

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

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

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

.. _sphx_glr_examples_correct_plot_zdr_check.py:


ZDR Bias Calculation
---------------------

This example shows how to calculate the ZDR bias from VPT/Birdbath scans.
The technique here uses a vertically pointing scan in regions of light rain.
In these regions, raindrops should be approximately spherical and therefore their
ZDR near zero. Therefore, we want the average ZDR in these regions.
This code applies reflectivity and cross correlation ratio-based thresholds to the ZDR
bias calculation to ensure that we are taking the average ZDR in light rain.

.. GENERATED FROM PYTHON SOURCE LINES 13-51



.. image-sg:: /examples/correct/images/sphx_glr_plot_zdr_check_001.png
   :alt: plot zdr check
   :srcset: /examples/correct/images/sphx_glr_plot_zdr_check_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    Zdr Bias: 2.69






|

.. code-block:: Python


    import matplotlib.pyplot as plt
    from open_radar_data import DATASETS

    import pyart

    # Read in example data
    filename = DATASETS.fetch("sgpxsaprcfrvptI4.a1.20200205.100827.nc")
    ds = pyart.io.read(filename)

    # Set up a typical filter for ZDR bias calculation in birdbath scan
    # Light rain and RhoHV near 1 ensures that raindrops are close to spherical
    # Therefore ZDR should be zero in these regions
    gatefilter = pyart.filters.GateFilter(ds)
    gatefilter.exclude_below("cross_correlation_ratio_hv", 0.995)
    gatefilter.exclude_above("cross_correlation_ratio_hv", 1)
    gatefilter.exclude_below("reflectivity", 10)
    gatefilter.exclude_above("reflectivity", 30)

    results = pyart.correct.calc_zdr_offset(
        ds,
        zdr_var="differential_reflectivity",
        gatefilter=gatefilter,
        height_range=(1000, 3000),
    )

    print("Zdr Bias: " + "{:.2f}".format(results["bias"]))

    fig, ax = plt.subplots(1, 3, figsize=(8, 5))
    ax[0].plot(results["profile_zdr"], results["range"])
    ax[0].set_ylabel("Range (m)")
    ax[0].set_xlabel("Zdr (dB)")
    ax[1].plot(results["profile_reflectivity"], results["range"])
    ax[1].set_xlabel("Zh (dBZ)")
    ax[2].plot(results["profile_cross_correlation_ratio_hv"], results["range"])
    ax[2].set_xlabel("RhoHV ()")
    fig.tight_layout()
    plt.show()


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

   **Total running time of the script:** (0 minutes 0.540 seconds)


.. _sphx_glr_download_examples_correct_plot_zdr_check.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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