.. _extinction:

Extinction
^^^^^^^^^^

Time Series
"""""""""""

Plot the monthly mean 750 nm extinction ratio in the tropics for altitudes above the tropopause.

.. code-block:: python

    import os
    import xarray as xr
    import matplotlib.pyplot as plt

    # load all of the version 7 data and set time as the dimension
    v7_folder = r'path\to\v7_data'
    data = xr.open_mfdataset([os.path.join(v7_folder, f) for f in os.listdir(v7_folder)])
    data = data.swap_dims({'profile_id': 'time'})

    rayleigh_xs = 1.278155e-22  # rayleigh cross section at 750 nm
    air_density = data.pressure / ((1.380648e-23 * data.temperature) * 1e6)
    ext_ratio = data.extinction / (air_density * rayleigh_xs)
    ext_ratio.where((data.latitude < 10) & (data.latitude > -10))\
             .where(data.altitude > data.tropopause_altitude)\
             .resample(time='MS').mean(dim='time') \
             .plot.contourf(x='time', vmin=0, vmax=3, levels=20, ylim=[17.5, 35], figsize=[9, 4])

.. image:: ../images/ex_time_series.png
   :align: center

Zonal Mean
""""""""""

Plot the zonal mean of the 750 nm aerosol extinction in October 2011.

.. code-block:: python

    import os
    import xarray as xr
    import numpy as np

    # load all of the version 7 data and set time as the dimension
    v7_folder = r'path\to\v7_data'
    data = xr.open_mfdataset([os.path.join(v7_folder, f) for f in os.listdir(v7_folder)])
    data = data.swap_dims({'profile_id': 'time'})

    lat_res = 5
    lat_bins = np.arange(-90, 91, lat_res)
    groups = data.extinction.sel(time='2011-10') \
                 .groupby_bins(data.latitude.sel(time='2011-10'),
                               bins=lat_bins, labels=lat_bins[1:] - lat_res / 2)

    groups.mean(dim='time').plot(x='latitude_bins', figsize=[7, 4])

.. image:: ../images/ex_zonal_mean.png
   :align: center