:py:mod:`mlair.reference_models.reference_model_intellio3_v1`
=============================================================

.. py:module:: mlair.reference_models.reference_model_intellio3_v1

.. autoapi-nested-parse::

   Extract forecasts from intelliO3 and store them for MLAir



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

Classes
~~~~~~~

.. autoapisummary::

   mlair.reference_models.reference_model_intellio3_v1.IntelliO3_ts_v1




Attributes
~~~~~~~~~~

.. autoapisummary::

   mlair.reference_models.reference_model_intellio3_v1.__author__
   mlair.reference_models.reference_model_intellio3_v1.__date__
   mlair.reference_models.reference_model_intellio3_v1.io3


.. py:data:: __author__
   :annotation: = Felix Kleinert

   

.. py:data:: __date__
   :annotation: = 2021-01-29

   

.. py:class:: IntelliO3_ts_v1(ref_name: str, ref_store_path: str = None)

   Bases: :py:obj:`mlair.reference_models.abstract_reference_model.AbstractReferenceB2share`

   Reference handler that extracts IntelliO3-ts v1.0 forecasts (Kleinert, 2021).

   IntelliO3 forecasts can be used as a competitive model within MLAir. Downloads the IntelliO3 tar-ball and extracts
   the forecasts.

   Kleinert, F., Leufen, L. H., and Schultz, M. G.: IntelliO3-ts v1.0: a neural network approach to predict
   near-surface ozone concentrations in Germany, Geosci. Model Dev., 14, 1–25,
   https://doi.org/10.5194/gmd-14-1-2021, 2021.

   .. py:method:: untar_forecasts(self)

      Extracts IntelliO3 forecasts from tar-ball.


   .. py:method:: file_list(self)

      :return: base dir of tmp path and list of forecast files
      :rtype: tuple(str, list(str))


   .. py:method:: read_and_drop(self, sel_coords: dict = None)

      Reads original forecast files, renames coord type and store forecasts as NetCdf4 files
      :param sel_coords:


   .. py:method:: make_reference_available_locally(self, remove_tmp_dir: bool = True)

      :return:
      :rtype:



.. py:data:: io3