Articles | Volume 21, issue 6
https://doi.org/10.5194/hess-21-2649-2017
https://doi.org/10.5194/hess-21-2649-2017
Research article
 | 
06 Jun 2017
Research article |  | 06 Jun 2017

Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes

Matthew B. Switanek, Peter A. Troch, Christopher L. Castro, Armin Leuprecht, Hsin-I Chang, Rajarshi Mukherjee, and Eleonora M. C. Demaria

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Latest update: 19 Jun 2024
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Short summary
The commonly used bias correction method called quantile mapping assumes a constant function of error correction values between modeled and observed distributions. Our article finds that this function cannot be assumed to be constant. We propose a new bias correction method, called scaled distribution mapping, that does not rely on this assumption. Furthermore, the proposed method more explicitly accounts for the frequency of rain days and the likelihood of individual events.