Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4183-2018
https://doi.org/10.5194/hess-22-4183-2018
Research article
 | 
07 Aug 2018
Research article |  | 07 Aug 2018

A classification algorithm for selective dynamical downscaling of precipitation extremes

Edmund P. Meredith, Henning W. Rust, and Uwe Ulbrich

Data sets

The ERA-Interim reanalysis: configuration and performance of the data assimilation system D. P. Dee, S. M. Uppala, A. J. Simmons, P. Berrisford, P. Poli, S. Kobayashi, U. Andrae, M. A. Balmaseda, G. Balsamo, P. Bauer, P. Bechtold, A. C. M. Beljaars, L. van de Berg, J. Bidlot, N. Bormann, C. Delsol, R. Dragani, M. Fuentes, A. J. Geer, L. Haimberger, S. B. Healy, H. Hersbach, E. V. Hólm, L. Isaksen, P. Kållberg, M. Köhler, M. Matricardi, A. P. McNally, B. M. Monge-Sanz, J.-J. Morcrette, B.-K. Park, C. Peubey, P. de Rosnay, C. Tavolato, J.-N. Thépaut, and F. Vitart https://doi.org/10.1002/qj.828

Central European precipitation climatology - Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS) M. Rauthe, H. Steiner, U. Riediger, A. Mazurkiewicz, and A. Gratzki https://doi.org/10.1127/0941-2948/2013/0436

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Short summary
Kilometre-scale climate-model data are of great benefit to both hydrologists and end users studying extreme precipitation, though often unavailable due to the computational expense associated with such high-resolution simulations. We develop a method which identifies days with enhanced risk of extreme rainfall over a catchment, so that high-resolution simulations can be performed only when such a risk exists, reducing computational expense by over 90 % while still well capturing the extremes.