isofit.utils.add_HRRR_profiles_to_modtran_config
================================================

.. py:module:: isofit.utils.add_HRRR_profiles_to_modtran_config


Attributes
----------

.. autoapisummary::

   isofit.utils.add_HRRR_profiles_to_modtran_config.pygrib


Classes
-------

.. autoapisummary::

   isofit.utils.add_HRRR_profiles_to_modtran_config.HRRR_to_MODTRAN_profiles


Functions
---------

.. autoapisummary::

   isofit.utils.add_HRRR_profiles_to_modtran_config.reporthook
   isofit.utils.add_HRRR_profiles_to_modtran_config.download_HRRR
   isofit.utils.add_HRRR_profiles_to_modtran_config.get_HRRR_data
   isofit.utils.add_HRRR_profiles_to_modtran_config.cli


Module Contents
---------------

.. py:data:: pygrib
   :value: None


.. py:class:: HRRR_to_MODTRAN_profiles(config_file)

   This class assumes that the MODTRAN config file has already been
   filled with the correct run data, including time, lat/lon, etc.


   .. py:attribute:: config


   .. py:attribute:: modtran_config_filenames


   .. py:attribute:: output_modtran_config_filenames


   .. py:attribute:: year_for_HRRR_profiles_in_modtran


   .. py:attribute:: HRRR_data_library_path


   .. py:method:: create_profiles(template)

      Create MODTRAN profile strings from HRRR data. For example:

      print(self.prof_altitude)

      yields:

      {
      "TYPE": "PROF_ALTITUDE",
      "UNITS": "UNT_KILOMETERS",
      "PROFILE": [1.224, 2.000, 3.000, 4.000, 5.000, 6.000, 7.000, 8.000, 9.000, 10.000, 11.000, 12.000, 13.000, 14.000, 15.000, 16.000, 17.000, 18.000, 19.000]
      }



.. py:function:: reporthook(a, b, c)

   Report download progress in megabytes


.. py:function:: download_HRRR(DATE, model='hrrr', field='sfc', hour=range(0, 24), fxx=range(0, 1), OUTDIR='./')

   # Brian Blaylock
   # February 13, 2018

   # Updated December 10, 2018 for Python 3

   # Modified from original by Jay Fahlen to not download the file if it already exists.
   # March 4, 2020

   Download archived HRRR files from MesoWest Pando S3 archive system.

   Please register before downloading from our HRRR archive:
   http://hrrr.chpc.utah.edu/hrrr_download_register.html

   For info on the University of Utah HRRR archive and to see what dates are
   available, look here:
   http://hrrr.chpc.utah.edu/

   Contact:
   brian.blaylock@utah.edu

   Downloads from the University of Utah MesoWest HRRR archive
   Input:
       DATE   - A date object for the model run you are downloading from.
       model  - The model type you want to download. Default is 'hrrr'
                Model Options are ['hrrr', 'hrrrX','hrrrak']
       field  - Variable fields you wish to download. Default is sfc, surface.
                Options are fields ['prs', 'sfc','subh', 'nat']
       hour   - Range of model run hours. Default grabs all hours of day.
       fxx    - Range of forecast hours. Default grabs analysis hour (f00).
       OUTDIR - Directory to save the files.

   Outcome:
       Downloads the desired HRRR file and renames with date info preceeding
       the original file name (i.e. 20170101_hrrr.t00z.wrfsfcf00.grib2)


.. py:function:: get_HRRR_data(filename)

.. py:function:: cli(**kwargs)