emc2.core.model.CESM2¶

class emc2.core.model.CESM2(file_path, time_range=None, load_processed=False, time_dim='time', appended_str=False)[source]¶

This loads a CESM2 simulation output with all of the necessary parameters for EMC^2 to run.

Parameters:

file_path: str: Path to an E3SMv1 simulation.
time_range: tuple, list, or array, typically in datetime64 format: Two-element array with starting and ending of time range.
load_processed: bool: If True, treating the ‘file_path’ variable as an EMC2-processed dataset; thus skipping appended string removal and dimension stacking, which are typically part of pre-processing.
time_dim: str: Name of the time dimension. Typically “time” or “ncol”.
appended_str: bool: If True, removing appended strings added to fieldnames and coordinates during post-processing (e.g., in cropped regions from global simualtions).

__init__(file_path, time_range=None, load_processed=False, time_dim='time', appended_str=False)[source]¶

This loads a CESM2 simulation output with all of the necessary parameters for EMC^2 to run.

Parameters:

file_path: str: Path to an E3SMv1 simulation.
time_range: tuple, list, or array, typically in datetime64 format: Two-element array with starting and ending of time range.
load_processed: bool: If True, treating the ‘file_path’ variable as an EMC2-processed dataset; thus skipping appended string removal and dimension stacking, which are typically part of pre-processing.
time_dim: str: Name of the time dimension. Typically “time” or “ncol”.
appended_str: bool: If True, removing appended strings added to fieldnames and coordinates during post-processing (e.g., in cropped regions from global simualtions).

Methods

`__init__`(file_path[, time_range, ...])	This loads a CESM2 simulation output with all of the necessary parameters for EMC^2 to run.
`check_and_stack_time_lat_lon`([...])	Stack the time dim together with the lat and lon dims (if the lat and/or lon dims are longer than 1) to enable EMC^2 processing of regional model output.
`finalize_subcol_fields`([more_fieldnames])	Remove all zero values from subcolumn output fields enabling better visualization.
`load_subcolumns_from_netcdf`(file_name)	Load all of the subcolumn data from a previously saved netCDF file.
`permute_dims_for_processing`([base_order, ...])	Reorder dims for consistent processing such that the order is: subcolumn x time x height.
`remove_appended_str`([all_appended_in_lat])	Remove appended strings from xr.Dataset coords and fieldnames based on lat/lon coord names (typically required when using post-processed output data files).
`remove_subcol_fields`([cloud_class])	Remove all subcolumn output fields for the given cloud class to save memory (mainly releveant for CESM and E3SM).
`set_hyd_types`(hyd_types)
`subcolumns_to_netcdf`(file_name)	Saves all of the simulated subcolumn parameters to a netCDF file.
`unstack_time_lat_lon`([order_dim, ...])	Unstack the time, lat, and lon dims if they were previously stacked together (self.stacked_time_dim is not None).

Attributes

`hydrometeor_classes`	The list of hydrometeor classes.
`num_hydrometeor_classes`	The number of hydrometeor classes used
`num_subcolumns`	Gets the number of subcolumns in the model.