Articles | Volume 21, issue 3
https://doi.org/10.5194/hess-21-1693-2017
https://doi.org/10.5194/hess-21-1693-2017
Research article
 | 
22 Mar 2017
Research article |  | 22 Mar 2017

A combined statistical bias correction and stochastic downscaling method for precipitation

Claudia Volosciuk, Douglas Maraun, Mathieu Vrac, and Martin Widmann

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Cited articles

Ahmed, K. F., Wang, G., Silander, J., Wilson, A. M., Allen, J. M., Horton, R., and Anyah, R.: Statistical downscaling and bias correction of climate model outputs for climate change impact assessment in the U.S. northeast, Global Planet. Change, 100, 320–332, https://doi.org/10.1016/j.gloplacha.2012.11.003, 2013.
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Bárdossy, A. and Pegram, G. G. S.: Copula based multisite model for daily precipitation simulation, Hydrol. Earth Syst. Sci., 13, 2299–2314, https://doi.org/10.5194/hess-13-2299-2009, 2009.
Bjornstad, O. N.: ncf: Spatial nonparametric covariance functions, r package version 1.1-6, http://CRAN.R-project.org/package=ncf (last access: 17 March 2017), 2015.
Chan, S. C., Kendon, E. J., Fowler, H. J., Blenkinsop, S., and Roberts, N. M.: Projected increases in summer and winter UK sub-daily precipitation extremes from high-resolution regional climate models, Environ. Res. Lett., 9, 084019, https://doi.org/10.1088/1748-9326/9/8/084019, 2014.
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Short summary
For impact modeling, infrastructure design, or adaptation strategy planning, high-quality climate data on the point scale are often demanded. Due to the scale gap between gridbox and point scale and biases in climate models, we combine a statistical bias correction and a stochastic downscaling model and apply it to climate model-simulated precipitation. The method performs better in summer than in winter and in winter best for mild winter climate (Mediterranean) and worst for continental winter.