Formulating and testing a method for perturbing precipitation time series to reflect anticipated climatic changes

Sørup, Hjalte Jomo Danielsen; Georgiadis, Stylianos; Gregersen, Ida Bülow; Arnbjerg-Nielsen, Karsten

doi:https://doi.org/10.5194/hess-21-345-2017

Articles | Volume 21, issue 1

https://doi.org/10.5194/hess-21-345-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Rainfall and urban hydrology

https://doi.org/10.5194/hess-21-345-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 21, issue 1

Research article

|

20 Jan 2017

Research article |

| 20 Jan 2017

Formulating and testing a method for perturbing precipitation time series to reflect anticipated climatic changes

Hjalte Jomo Danielsen Sørup, Stylianos Georgiadis, Ida Bülow Gregersen, and Karsten Arnbjerg-Nielsen

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Final revised paper (published on 20 Jan 2017)
Preprint (discussion started on 06 Oct 2016)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'referee comments', Anonymous Referee #1, 07 Nov 2016
- AC1: 'Reply to Anonymous Referee #1', Hjalte Jomo Danielsen Sørup, 07 Dec 2016
RC2: 'Reviewer 2 Comments', Anonymous Referee #2, 01 Dec 2016
- AC2: 'Reply to Anonymous Referee #2', Hjalte Jomo Danielsen Sørup, 07 Dec 2016

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to minor revisions (further review by Editor) (21 Dec 2016) by Chris Onof

AR by Hjalte Jomo Danielsen Sørup on behalf of the Authors (03 Jan 2017) Author's response Manuscript

ED: Publish subject to technical corrections (04 Jan 2017) by Chris Onof

AR by Hjalte Jomo Danielsen Sørup on behalf of the Authors (04 Jan 2017) Manuscript

Short summary

In this study we propose a methodology changing present-day precipitation time series to reflect future changed climate. Present-day time series have a much finer resolution than what is provided by climate models and thus have a much broader application range. The proposed methodology is able to replicate most expectations of climate change precipitation. These time series can be used to run fine-scale hydrological and hydraulic models and thereby assess the influence of climate change on them.