Articles | Volume 24, issue 6
Hydrol. Earth Syst. Sci., 24, 2963–2979, 2020
https://doi.org/10.5194/hess-24-2963-2020
Hydrol. Earth Syst. Sci., 24, 2963–2979, 2020
https://doi.org/10.5194/hess-24-2963-2020

Research article 08 Jun 2020

Research article | 08 Jun 2020

Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections

Nicholas J. Potter et al.

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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 (further review by editor and referees) (14 Jul 2019) by Nadav Peleg
AR by Potter Nick on behalf of the Authors (30 Aug 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (02 Sep 2019) by Nadav Peleg
RR by Anonymous Referee #3 (03 Oct 2019)
RR by Anonymous Referee #2 (09 Oct 2019)
ED: Reconsider after major revisions (further review by editor and referees) (14 Oct 2019) by Nadav Peleg
AR by Potter Nick on behalf of the Authors (13 Jan 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (22 Jan 2020) by Nadav Peleg
RR by Anonymous Referee #2 (06 Feb 2020)
ED: Publish subject to minor revisions (review by editor) (14 Feb 2020) by Nadav Peleg
AR by Potter Nick on behalf of the Authors (24 Feb 2020)  Author's response    Manuscript
ED: Publish subject to technical corrections (26 Feb 2020) by Nadav Peleg
AR by Potter Nick on behalf of the Authors (02 Apr 2020)  Author's response    Manuscript
Short summary
There is a growing need for information about possible changes to water resource availability in the future due to climate change. Large-scale outputs from global climate models need to be translated to finer-resolution spatial scales before hydrological modelling. Biases in this downscaled data often need to be corrected. We show that usual bias correction methods can retain residual biases in multi-day occurrences of rainfall, which can result in biases in modelled runoff.