Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes
Author
Switanek, Matthew B.Troch, Peter A.
Castro, Christopher L.
Leuprecht, Armin
Chang, Hsin-I
Mukherjee, Rajarshi

Demaria, Eleonora M. C.

Affiliation
Univ Arizona, Dept Hydrol & Atmospher SciIssue Date
2017-06-06
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COPERNICUS GESELLSCHAFT MBHCitation
Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes 2017, 21 (6):2649 Hydrology and Earth System SciencesRights
© Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Commonly used bias correction methods such as quantile mapping (QM) assume the function of error correction values between modeled and observed distributions are stationary or time invariant. This article finds that this function of the error correction values cannot be assumed to be stationary. As a result, QM lacks justification to inflate/deflate various moments of the climate change signal. Previous adaptations of QM, most notably quantile delta mapping (QDM), have been developed that do not rely on this assumption of stationarity. Here, we outline a methodology called scaled distribution mapping (SDM), which is conceptually similar to QDM, but more explicitly accounts for the frequency of rain days and the likelihood of individual events. The SDM method is found to outperform QM, QDM, and detrended QM in its ability to better preserve raw climate model projected changes to meteorological variables such as temperature and precipitation.Note
open access journalISSN
1607-7938Version
Final published versionSponsors
Austrian Federal Ministry of Agriculture, Forestry, Environment and Water Management [OKS15]; Austrian Klima- und Energiefonds through the Austrian Climate Research Program (ACRP) [B368584, B464795]Additional Links
http://www.hydrol-earth-syst-sci.net/21/2649/2017/ae974a485f413a2113503eed53cd6c53
10.5194/hess-21-2649-2017
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Except where otherwise noted, this item's license is described as © Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License.