climpred.classes.HindcastEnsemble.verify

HindcastEnsemble.verify(reference=None, metric=None, comparison=None, dim=None, alignment=None, **metric_kwargs)[source]

Verifies the initialized ensemble against observations.

Note

This will automatically verify against all shared variables between the initialized ensemble and observations/verification data.

Parameters

  • reference (str) – Type of reference forecasts to also verify against the observations. Choose one or more of [‘uninitialized’, ‘persistence’]. Defaults to None.

  • metric (str, Metric) – Metric to apply for verification. see metrics.

  • comparison (str, Comparison) – How to compare to the observations/verification data. See comparisons.

  • dim (str, list of str) – Dimension(s) to apply metric over. dim is passed on to xskillscore.{metric} and includes xskillscore’s member_dim. dim should contain member when comparison is probabilistic but should not contain member when comparison=e2o. Defaults to None meaning that all dimensions other than lead are reduced.

  • alignment (str) –

    which inits or verification times should be aligned?

    • ’maximize’: 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.

  • **metric_kwargs (optional) – arguments passed to metric.

Returns

Dataset with dimension skill containing initialized and reference skill(s).