climpred.metrics._rank_histogram

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

Rank histogram or Talagrand diagram.

Parameters

  • forecast (xr.object) – Raw forecasts with member dimension.

  • verif (xr.object) – Verification data without member dim.

  • dim (list or str) – Dimensions to aggregate. Requires to contain member and at least one additional dimension.

Details:

perfect

flat distribution

See also

Example

>>> HindcastEnsemble.verify(metric='rank_histogram', comparison='m2o',
...     dim=['member', 'init'], alignment='same_verifs')
<xarray.Dataset>
Dimensions:  (lead: 10, rank: 11)
Coordinates:
  * lead     (lead) int32 1 2 3 4 5 6 7 8 9 10
  * rank     (rank) float64 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0
    skill    <U11 'initialized'
Data variables:
    SST      (lead, rank) int64 12 3 2 1 1 3 1 2 6 5 16 ... 0 1 0 0 3 0 2 6 6 34

>>> PerfectModelEnsemble.verify(metric='rank_histogram', comparison='m2c',
...     dim=['member', 'init'])
<xarray.Dataset>
Dimensions:  (lead: 20, rank: 10)
Coordinates:
  * lead     (lead) int64 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
  * rank     (rank) float64 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0
Data variables:
    tos      (lead, rank) int64 1 4 2 1 2 1 0 0 0 1 2 ... 0 2 0 1 2 1 0 3 1 2 0