Abstract:Output from numerical models at high spatial and temporal resolutions is critical for modeling applications in a variety of disciplines. Prior to its use in modeling, output from climate models must be brought to a finer spatial resolution and calibrated with respect to observations. The calibration of model output, referred to as bias‐correction, poses many statistical challenges. Here, we develop a bias‐correction method in which systematic biases in the mean and standard deviation of model output are correc… Show more
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