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’smember_dim
.dim
should containmember
whencomparison
is probabilistic but should not containmember
whencomparison=e2o
. Defaults toNone
meaning that all dimensions other thanlead
are reduced.alignment (str) –
which inits or verification times should be aligned?
’maximize’: maximize the degrees of freedom by slicing
hind
andverif
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).