climpred.metrics._unconditional_bias

climpred.metrics._unconditional_bias(forecast, verif, dim=None, **metric_kwargs)[source]

Unconditional additive bias.

bias = f - o

Parameters
  • forecast (xarray object) – Forecast.

  • verif (xarray object) – Verification data.

  • dim (str) – Dimension(s) to perform metric over

  • metric_kwargs (dict) – see xarray.mean

Details:

minimum

-∞

maximum

perfect

0.0

orientation

negative

Reference:

Example

>>> HindcastEnsemble.verify(metric='unconditional_bias', 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

Conditional bias is removed by remove_bias().

>>> HindcastEnsemble = HindcastEnsemble.remove_bias(alignment='same_verifs')
>>> HindcastEnsemble.verify(metric='unconditional_bias', 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 3.203e-18 -1.068e-18 ... 2.882e-17 -2.776e-17