climpred.prediction.compute_hindcast

climpred.prediction.compute_hindcast(initialized, verif, metric='pearson_r', comparison='e2o', dim='init', alignment='same_verifs', **metric_kwargs)[source]

Verify hindcast predictions against verification data.

Parameters

  • initialized (xr.Dataset) – Initialized hindcast ensemble. Expected to follow package conventions: * init : dim of initialization dates * lead : dim of lead time from those initializations Additional dims can be member, lat, lon, depth, …

  • verif (xr.Dataset) – Verification data with some temporal overlap with the hindcast.

  • metric (str) – Metric used in comparing the decadal prediction ensemble with the verification data. (see get_metric_class() and Metrics).

  • comparison (str) –

    How to compare the decadal prediction ensemble to the verification data:

    • e2o : ensemble mean to verification data (Default)

    • m2o : each member to the verification data

    (see Comparisons)

  • dim (str or list) – dimension to apply metric over. default: ‘init’

  • alignment (str) – which inits or verification times should be aligned? - maximize: maximize the degrees of freedom by slicing initialized and verif to a common time frame at each lead. - same_inits: slice to a common init frame prior to computing metric. This philosophy follows the thought that each lead should be based on the same set of initializations. - same_verif: slice to a common/consistent verification time frame prior to computing metric. This philosophy follows the thought that each lead should be based on the same set of verification dates.

  • **metric_kwargs (dict) – additional keywords to be passed to metric (see the arguments required for a given metric in Metrics).

Returns

result (xr.Dataset) – Verification metric over lead reduced by dimension(s) dim.

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