climpred.prediction.compute_persistence¶
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climpred.prediction.
compute_persistence
(hind, reference, metric='pearson_r', max_dof=False, **metric_kwargs)[source]¶ Computes the skill of a persistence forecast from a simulation.
Parameters: - hind (xarray object) – The initialized ensemble.
- reference (xarray object) – The reference time series.
- metric (str) – Metric name to apply at each lag for the persistence computation. Default: ‘pearson_r’
- max_dof (bool) –
If True, maximize the degrees of freedom by slicing hind and reference to a common time frame at each lead.
If False (default), then slice to a common time frame prior to computing metric. This philosophy follows the thought that each lead should be based on the same set of initializations.
- 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.