climpred.reference.compute_persistence

climpred.reference.compute_persistence(hind, verif, metric='pearson_r', alignment='same_verifs', add_attrs=True, **metric_kwargs)

Computes the skill of a persistence forecast from a simulation.

Parameters:

• hind (xarray object) – The initialized ensemble.
• verif (xarray object) – Verification data.
• metric (str) – Metric name to apply at each lag for the persistence computation. Default: ‘pearson_r’
• alignment (str) – which inits or verification times should be aligned? - maximize/None: maximize the degrees of freedom by slicing hind and verif to a common time frame at each lead. - same_inits: slice to a common init frame prior to computing metric. This philosophy follows the thought that each lead should be based on the same set of initializations. - same_verif: slice to a common/consistent verification time frame prior to computing metric. This philosophy follows the thought that each lead should be based on the same set of verification dates.
• add_attrs (bool) – write climpred compute_persistence args to attrs. default: True
• metric_kwargs (**) – additional keywords to be passed to metric (see the arguments required for a given metric in Metrics).

Returns:

Results of persistence forecast with the input metric

applied.

Return type:

pers (xarray object)

Reference:

• Chapter 8 (Short-Term Climate Prediction) in Van den Dool, Huug. Empirical methods in short-term climate prediction. Oxford University Press, 2007.