DynamicalGEFS

class earth2studio.data.DynamicalGEFS(cache=True, verbose=True)

Global

NOAA GEFS analysis from the dynamical.org catalog.

Best-estimate analysis (dimensions [time, lat, lon]) built from the first hours of successive NOAA Global Ensemble Forecast System runs, on a global 0.25 degree regular latitude/longitude grid.

Parameters:

• cache (bool, optional) – Retained for API parity; Icechunk reads chunks lazily on demand rather than caching whole files locally, by default True

• verbose (bool, optional) – Print download progress, by default True

Examples

>>> source = DynamicalGEFS()
>>> source.variables  # variables are determined dynamically

Warning

This is a remote data source and can potentially download a large amount of data to your local machine for large requests.

Note

The dynamical.org dataset documentation and STAC metadata are available at:

• https://dynamical.org/catalog/noaa-gefs-analysis/

• https://stac.dynamical.org/noaa-gefs-analysis/collection.json

__call__(time, variable)

Retrieve analysis data.

Parameters:

• time (datetime | list[datetime] | TimeArray) – Timestamps to return data for (UTC).

• variable (str | list[str] | VariableArray) – Variable(s) to return, in the dynamical.org lexicon or native to the collection.

Returns:

Data array with dimensions [time, variable, lat, lon].

Return type:

xr.DataArray

async fetch(time, variable)

Async function to retrieve analysis data.

Parameters:

• time (datetime | list[datetime] | TimeArray) – Timestamps to return data for (UTC).

• variable (str | list[str] | VariableArray) – Variable(s) to return, in the dynamical.org lexicon or native to the collection.

Returns:

Data array with dimensions [time, variable, lat, lon].

Return type:

xr.DataArray

available(time)

Check if a given time is available in this dynamical.org collection.

Unlike most Earth2Studio sources, availability is collection-dependent (each collection advertises its own temporal extent in its STAC metadata), so this is an instance method rather than a classmethod: it opens the collection and checks the requested time against the extent of the collection’s temporal dimension (time for analysis, init_time for forecast collections).

Parameters:

time (datetime | np.datetime64) – Time to check. For forecast collections this is the forecast initialization time.

Returns:

Whether the time falls within the collection’s temporal extent.

Return type:

bool