scripts.regridding.regrid_and_vert_interp
=========================================

.. py:module:: scripts.regridding.regrid_and_vert_interp


Functions
---------

.. autoapisummary::

   scripts.regridding.regrid_and_vert_interp.regrid_and_vert_interp
   scripts.regridding.regrid_and_vert_interp._regrid_and_interpolate_levs
   scripts.regridding.regrid_and_vert_interp.save_to_nc
   scripts.regridding.regrid_and_vert_interp.regrid_data


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

.. py:function:: regrid_and_vert_interp(adf)

   This funtion regrids the test cases to the same horizontal
   grid as the observations or baseline climatology.  It then
   vertically interpolates the test case (and baseline case
   if need be) to match a default set of pressure levels, which
   are (in hPa):

   1000, 925, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50,
   30, 20, 10, 7, 5, 3, 2, 1

   Currently any 3-D observations file needs to have equivalent pressure
   levels in order to work properly, although in the future it is hoped
   to enable the vertical interpolation of observations as well.

   Description of needed inputs from ADF:

   case_name        -> Name of CAM case provided by "cam_case_name"
   input_climo_loc  -> Location of CAM climo files provided by "cam_climo_loc"
   output_loc       -> Location to write re-gridded CAM files, specified by "cam_regrid_loc"
   var_list         -> List of CAM output variables provided by "diag_var_list"
   var_defaults     -> Dict that has keys that are variable names and values that are plotting preferences/defaults.
   target_list      -> List of target data sets CAM could be regridded to
   taget_loc        -> Location of target files that CAM will be regridded to
   overwrite_regrid -> Logical to determine if already existing re-gridded
                       files will be overwritten. Specified by "cam_overwrite_regrid"


.. py:function:: _regrid_and_interpolate_levs(model_dataset, var_name, regrid_dataset=None, regrid_ofrac=False, **kwargs)

   Function that takes a variable from a model xarray
   dataset, regrids it to another dataset's lat/lon
   coordinates (if applicable), and then interpolates
   it vertically to a set of pre-defined pressure levels.
   ----------
   model_dataset -> The xarray dataset which contains the model variable data
   var_name      -> The name of the variable to be regridded/interpolated.

   Optional inputs:

   ps_file        -> A NetCDF file containing already re-gridded surface pressure
   regrid_dataset -> The xarray dataset that contains the lat/lon grid that
                     "var_name" will be regridded to.  If not present then
                     only the vertical interpolation will be done.

   kwargs         -> Keyword arguments that contain paths to surface pressure
                     and mid-level pressure files, which are necessary for
                     certain types of vertical interpolation.

   This function returns a new xarray dataset that contains the regridded
   and/or vertically-interpolated model variable.


.. py:function:: save_to_nc(tosave, outname, attrs=None, proc=None)

   Saves xarray variable to new netCDF file


.. py:function:: regrid_data(fromthis, tothis, method=1)

   Regrid data using various different methods