climpred.metrics._me#
- climpred.metrics._me(forecast: Dataset, verif: Dataset, dim: str | List[str] | None = None, **metric_kwargs: Any) Dataset [source]#
Mean Error (ME).
- Parameters:
forecast – Forecast.
verif – Verification data.
dim – Dimension(s) to perform metric over.
metric_kwargs – see
xskillscore.me()
Notes
minimum
0.0
maximum
-/+∞
perfect
0.0
orientation
negative
See also
References
Jolliffe and Stephenson [2011]
Example
>>> HindcastEnsemble.verify( ... metric="me", comparison="e2o", alignment="same_verifs", dim="init" ... ) <xarray.Dataset> Dimensions: (lead: 10) Coordinates: * lead (lead) int32 1 2 3 4 5 6 7 8 9 10 skill <U11 'initialized' Data variables: SST (lead) float64 -0.01158 -0.02512 -0.0408 ... -0.1322 -0.1445 Attributes: prediction_skill_software: climpred https://climpred.readthedocs.io/ skill_calculated_by_function: HindcastEnsemble.verify() number_of_initializations: 64 number_of_members: 10 alignment: same_verifs metric: me comparison: e2o dim: init reference: []