Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

Thorndahl, Søren; Andersen, Aske Korup; Larsen, Anders Badsberg

doi:https://doi.org/10.5194/hess-21-4433-2017

Articles | Volume 21, issue 9

https://doi.org/10.5194/hess-21-4433-2017

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

https://doi.org/10.5194/hess-21-4433-2017

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

Articles | Volume 21, issue 9

Research article

|

07 Sep 2017

Research article |

| 07 Sep 2017

Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

Søren Thorndahl, Aske Korup Andersen, and Anders Badsberg Larsen

Download

Final revised paper (published on 07 Sep 2017)
Preprint (discussion started on 01 Mar 2017)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Referee comments', Patrick Willems, 26 May 2017
- AC1: 'Reply to review by Patrick Willems', Søren Thorndahl, 01 Jul 2017
RC2: 'HESS-urban hydrology', Lars Bengtsson, 22 Jun 2017
- AC2: 'Reply to review by Lars Bengtsson', Søren Thorndahl, 01 Jul 2017

Peer-review completion

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

ED: Publish subject to revisions (further review by Editor and Referees) (03 Jul 2017) by Nadia Ursino

AR by Søren Thorndahl on behalf of the Authors (31 Jul 2017) Author's response Manuscript

ED: Publish as is (01 Aug 2017) by Nadia Ursino

Short summary

Time series of rainfall are developed in order to represent future climate conditions. These series can be used in design of, for example, drainage systems where future rainfall loads are important to account for. The climate projections are evaluated on a number of key statistical parameters of rainfall such as yearly and seasonal precipitation amounts, number of extreme events and rainfall intensities, specific duration, and return periods.