climpred.prediction.compute_perfect_model(ds, control, metric='pearson_r', comparison='m2e', dim=None, add_attrs=True, **metric_kwargs)[source]

Compute a predictability skill score for a perfect-model framework simulation dataset.

  • ds (xarray object) – ensemble with dims lead, init, member.
  • control (xarray object) – control with dimension time.
  • metric (str) – metric name, see climpred.utils.get_metric_class() and (see Metrics).
  • comparison (str) – comparison name defines what to take as forecast and verification (see climpred.utils.get_comparison_class() and Comparisons).
  • dim (str or list) – dimension to apply metric over. default: [‘member’, ‘init’]
  • add_attrs (bool) – write climpred compute args to attrs. default: True
  • metric_kwargs (**) – additional keywords to be passed to metric. (see the arguments required for a given metric in

skill score with dimensions as input ds

without dim.

Return type:

skill (xarray object)