.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "generated/gallery/meteorology/plot_deriving_phenomena.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_deriving_phenomena.py>`
        to download the full example code

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

.. _sphx_glr_generated_gallery_meteorology_plot_deriving_phenomena.py:


Deriving Exner Pressure and Air Temperature
===========================================

This example shows some processing of cubes in order to derive further related
cubes; in this case the derived cubes are Exner pressure and air temperature
which are calculated by combining air pressure, air potential temperature and
specific humidity. Finally, the two new cubes are presented side-by-side in a
plot.

.. GENERATED FROM PYTHON SOURCE LINES 12-93



.. image-sg:: /generated/gallery/meteorology/images/sphx_glr_plot_deriving_phenomena_001.png
   :alt: Exner pressure, Air temperature
   :srcset: /generated/gallery/meteorology/images/sphx_glr_plot_deriving_phenomena_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import matplotlib.pyplot as plt
    import matplotlib.ticker

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


    def limit_colorbar_ticks(contour_object):
        """Limit colobar number of ticks.

        Take a contour object which has an associated colorbar and limits the
        number of ticks on the colorbar to 4.

        """
        colorbar = contour_object.colorbar
        colorbar.locator = matplotlib.ticker.MaxNLocator(4)
        colorbar.update_ticks()


    def main():
        fname = iris.sample_data_path("colpex.pp")

        # The list of phenomena of interest
        phenomena = ["air_potential_temperature", "air_pressure"]

        # Define the constraint on standard name and model level
        constraints = [
            iris.Constraint(phenom, model_level_number=1) for phenom in phenomena
        ]

        air_potential_temperature, air_pressure = iris.load_cubes(fname, constraints)

        # Define a coordinate which represents 1000 hPa
        p0 = coords.AuxCoord(1000, long_name="P0", units="hPa")
        # Convert reference pressure 'p0' into the same units as 'air_pressure'
        p0.convert_units(air_pressure.units)

        # Calculate Exner pressure
        exner_pressure = (air_pressure / p0) ** (287.05 / 1005.0)
        # Set the name (the unit is scalar)
        exner_pressure.rename("exner_pressure")

        # Calculate air_temp
        air_temperature = exner_pressure * air_potential_temperature
        # Set the name (the unit is K)
        air_temperature.rename("air_temperature")

        # Now create an iterator which will give us lat lon slices of
        # exner pressure and air temperature in the form
        # (exner_slice, air_temp_slice).
        lat_lon_slice_pairs = iris.iterate.izip(
            exner_pressure,
            air_temperature,
            coords=["grid_latitude", "grid_longitude"],
        )

        # For the purposes of this example, we only want to demonstrate the first
        # plot.
        lat_lon_slice_pairs = [next(lat_lon_slice_pairs)]

        plt.figure(figsize=(8, 4))
        for exner_slice, air_temp_slice in lat_lon_slice_pairs:
            plt.subplot(121)
            cont = qplt.contourf(exner_slice)

            # The default colorbar has a few too many ticks on it, causing text to
            # overlap. Therefore, limit the number of ticks.
            limit_colorbar_ticks(cont)

            plt.subplot(122)
            cont = qplt.contourf(air_temp_slice)
            limit_colorbar_ticks(cont)
            iplt.show()


    if __name__ == "__main__":
        main()


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

   **Total running time of the script:** (0 minutes 3.058 seconds)


.. _sphx_glr_download_generated_gallery_meteorology_plot_deriving_phenomena.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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