climpred.metrics._conditional_bias¶

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

Conditional bias between forecast and verification data.

$\text{conditional bias} = r_{fo} - \frac{\sigma_f}{\sigma_o},$

where $\sigma_{f}$ and $\sigma_{o}$ are the standard deviations of the forecast and verification data over the experimental period, respectively.

Parameters

forecast (xarray object) – Forecast.
verif (xarray object) – Verification data.
dim (str) – Dimension(s) to perform metric over.
metric_kwargs (dict) – see pearson_r()

:param and Datasetstd():

Details:

minimum	-∞
maximum	1.0
perfect	0.0
orientation	negative

Reference:

https://www-miklip.dkrz.de/about/murcss/

Example

>>> HindcastEnsemble.verify(metric='conditional_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 0.1705 0.03435 -0.05988 ... -0.1436 -0.175 -0.1434