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

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (27 Mar 2018) by András Bárdossy
AR by Edmund Meredith on behalf of the Authors (03 May 2018)  Author's response   Manuscript 
ED: Publish as is (12 Jul 2018) by András Bárdossy
AR by Edmund Meredith on behalf of the Authors (17 Jul 2018)
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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.