climpred.metrics._smape¶

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

Symmetric Mean Absolute Percentage Error (sMAPE).

Similar to the Mean Absolute Percentage Error (mape), but sums the forecast and observation mean in the denominator.

$sMAPE = \frac{1}{n} \sum \frac{|f-o|}{|f|+|o|}$

Parameters

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

Details:

minimum	0.0
maximum	1.0
perfect	0.0
orientation	negative

See also

smape()

Example

>>> HindcastEnsemble.verify(metric='smape', 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 0.3801 0.3906 0.4044 0.3819 ... 0.4822 0.5054 0.5295