Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2016-435
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
12 Sep 2016
Review status
A revision of this discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes
Matthew B. Switanek1, Peter A. Troch2, Christopher L. Castro2, Armin Leuprecht1, Hsin-I. Chang2, Rajarshi Mukherjee2, and Eleonora M. C. Demaria3 1Wegener Center for Climate and Global Change, University of Graz, Graz, 8010, Austria
2Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, 85721, USA
3Southwest Watershed Research Center, USDA – Agricultural Research Service, Tucson, 85719, USA
Abstract. Commonly used bias correction methods such as quantile mapping (QM) assume the function of error correction values between modelled 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.

Citation: Switanek, M. B., Troch, P. A., Castro, C. L., Leuprecht, A., Chang, H.-I., Mukherjee, R., and Demaria, E. M. C.: Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-435, in review, 2016.
Matthew B. Switanek et al.
Matthew B. Switanek et al.
Matthew B. Switanek et al.

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Short summary
The commonly used bias correction method called quantile mapping assumes a constant function of error correction values between modelled 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.
The commonly used bias correction method called quantile mapping assumes a constant function of...
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