AWSGEFSArchive

class ufs2arco.sources.AWSGEFSArchive(t0: dict, fhr: dict, member: dict, variables: list | tuple | None = None, levels: list | tuple | None = None, use_nearest_levels: bool | None = False, slices: dict | None = None, accum_hrs: dict | None = None)

Access NOAA’s forecast archive from the Global Ensemble Forecast System (GEFS) at s3://noaa-gefs-pds.

Methods

AWSGEFSArchive.__init__(t0, fhr, member[, ...])
AWSGEFSArchive.add_full_extra_coords(xds)	An optional routine that builds extra coordinates if needed, see example in ensemble_forecast.py.
AWSGEFSArchive.apply_slices(xds)	Apply any slices, for now just data selection via "sel" or "isel" Note that this is the first transformation, so slicing options relate to the standard dimensions:
AWSGEFSArchive.open_grib(dims, file_suffix, ...)	Open a single GRIB file.
AWSGEFSArchive.open_sample_dataset(dims, ...)

Attributes

AWSGEFSArchive.available_levels	Built-in immutable sequence.
AWSGEFSArchive.available_variables	Built-in immutable sequence.
AWSGEFSArchive.dynamic_vars
AWSGEFSArchive.file_suffixes
AWSGEFSArchive.horizontal_dims
AWSGEFSArchive.name
AWSGEFSArchive.rename	Use this to map whatever the original source is to the ufs2arco standards...which need to be documented
AWSGEFSArchive.sample_dims
AWSGEFSArchive.static_vars