climpred.metrics._less#
- climpred.metrics._less(forecast: Dataset, verif: Dataset, dim: Optional[Union[str, List[str]]] = None, **metric_kwargs: Any) Dataset [source]#
Logarithmic Ensemble Spread Score.
- Parameters:
forecast – Forecasts.
verif – Verification.
dim – The dimension(s) over which to aggregate. Defaults to None, meaning aggregation over all dims other than
lead
.
- Returns:
less – reduced by dimensions
dim
Notes
maximum
∞
positive
overdisperive / underconfident
perfect
0
negative
underdisperive / overconfident
minimum
-∞
orientation
None
Example
>>> # better detrend before >>> from climpred.stats import rm_poly >>> HindcastEnsemble.map(rm_poly, dim="init_or_time", deg=2).verify( ... metric="less", ... comparison="m2o", ... dim=["member", "init"], ... alignment="same_verifs", ... ).SST <xarray.DataArray 'SST' (lead: 10)> array([ 0.12633664, -0.12707636, -0.26143181, -0.25096537, -0.29267366, -0.2905725 , -0.43579508, -0.33774947, -0.46008438, -0.61010386]) Coordinates: * lead (lead) int32 1 2 3 4 5 6 7 8 9 10 skill <U11 'initialized' Attributes: units: None
References
Kadow et al. [2016]