ufs2arco.targets.Anemoi.__init__#
- Anemoi.__init__(source: Source, chunks: dict, store_path: str, rename: dict | None = None, forcings: list | tuple | None = None, statistics_period: dict | None = None, compute_temporal_residual_statistics: bool | None = False, sort_channels_by_levels: bool | None = False, variables_with_nans: list | None = None, transformed_dims: dict | None = None) None#
- Parameters:
... (... the rest of the docs)
transformed_dims (dict, optional) – if your dataset gets regridded to have new dimension names, e.g. from latitude/longitude to a curvilinear grid with y/x coordinates (in the case of GFS -> HRRR grid), we need to explicitly tell the target class about this transformation, so it knows how to handle horizontal dimensions, since horizontal dimensions are always different. So this would be based on dimension order e.g. {‘latitude’: ‘y’, ‘longitude’: ‘x’}