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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 4
Hydrol. Earth Syst. Sci., 20, 1483–1508, 2016
https://doi.org/10.5194/hess-20-1483-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 1483–1508, 2016
https://doi.org/10.5194/hess-20-1483-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 19 Apr 2016

Research article | 19 Apr 2016

Hydrologic extremes – an intercomparison of multiple gridded statistical downscaling methods

Arelia T. Werner and Alex J. Cannon

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (26 Oct 2015) by Remko Uijlenhoet
AR by A.T. Werner on behalf of the Authors (18 Nov 2015)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (18 Nov 2015) by Remko Uijlenhoet
RR by Anonymous Referee #2 (27 Jan 2016)
RR by Anonymous Referee #1 (10 Feb 2016)
ED: Publish subject to minor revisions (Editor review) (24 Feb 2016) by Remko Uijlenhoet
AR by Svenja Lange on behalf of the Authors (08 Mar 2016)  Author's response    Manuscript
ED: Publish as is (17 Mar 2016) by Remko Uijlenhoet
Publications Copernicus
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Short summary
Seven gridded statistical downscaling methods are tested for strength in simulating climate and hydrologic extremes. A recently developed technique, which is a post-processed version of bias corrected constructed analogues where the final bias correction is based on the bias corrected climate imprint method, is shown to be an especially strong method for hydrologic extremes versus other more commonly applied methods, including the popular bias corrected spatial disaggregation method.
Seven gridded statistical downscaling methods are tested for strength in simulating climate and...
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