Basic Usage

xsdba performs a training on a source dataset hist to reproduce a target ref. “ref” is short for reference, and “hist” for historical: In climate services, it is common to refer to the training data as historical, a period of time where observations are available. The training is then applied to a dataset sim to obtain an adjusted dataset. This may simply be the training data hist which is not adjusted in the first training part. An example with a basic Quantile Mapping is given below.

import xsdba

# Example: Using a Quantile Mapping method
# Instantiate a TrainAdjust class with the training, with the source `hist` mapped to a target `ref`
ADJ = xsdba.EmpiricalQuantileMapping.train(ref=ref, hist=hist)
# Perform adjust for data outside the training period, `sim`
adj = ADJ.adjust(sim=sim)