climpred.metrics._spearman_r¶

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

Spearman’s rank correlation coefficient.

$corr = \mathrm{pearsonr}(ranked(f), ranked(o))$

This correlation coefficient is nonparametric and assesses how well the relationship between the forecast and verification data can be described using a monotonic function. It is computed by first ranking the forecasts and verification data, and then correlating those ranks using the pearson_r correlation.

This is also known as the anomaly correlation coefficient (ACC) when comparing anomalies, although the Pearson product-moment correlation coefficient (pearson_r) is typically used when computing the ACC.

Note

Use metric spearman_r_p_value or spearman_r_eff_p_value to get the corresponding p value.

Parameters

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

Details:

minimum	-1.0
maximum	1.0
perfect	1.0
orientation	positive