Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue.

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Maraun, Douglas (2013) Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue. Journal of Climate, 26 (6). pp. 2137-2143. DOI 10.1175/JCLI-D-12-00821.1.

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Abstract

Quantile mapping is routinely applied to correct biases of regional climate model simulations compared to observational data. If the observations are of similar resolution as the regional climate model, quantile mapping is a feasible approach. However, if the observations are of much higher resolution, quantile mapping also attempts to bridge this scale mismatch. Here, it is shown for daily precipitation that such quantile mapping-based downscaling is not feasible but introduces similar problems as inflation of perfect prognosis ("prog") downscaling: the spatial and temporal structure of the corrected time series is misrepresented, the drizzle effect for area means is overcorrected, area-mean extremes are overestimated, and trends are affected. To overcome these problems, stochastic bias correction is required.

Document Type: Article
Additional Information: WOS:000316620500017
Keywords: Climate change, Regional effects, Bias, Statistical techniques, Model output statistics, Regional models
Research affiliation: OceanRep > GEOMAR > FB1 Ocean Circulation and Climate Dynamics > FB1-ME Maritime Meteorology
Refereed: Yes
Open Access Journal?: No
Publisher: AMS (American Meteorological Society)
Related URLs:
Date Deposited: 25 Apr 2013 12:57
Last Modified: 04 Aug 2020 09:28
URI: https://oceanrep.geomar.de/id/eprint/21175

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