Articles | Volume 21, issue 6
https://doi.org/10.5194/hess-21-2777-2017
https://doi.org/10.5194/hess-21-2777-2017
Research article
 | 
09 Jun 2017
Research article |  | 09 Jun 2017

A non-stationary stochastic ensemble generator for radar rainfall fields based on the short-space Fourier transform

Daniele Nerini, Nikola Besic, Ioannis Sideris, Urs Germann, and Loris Foresti

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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: Publish subject to minor revisions (further review by Editor) (18 Apr 2017) by Remko Uijlenhoet
AR by Daniele Nerini on behalf of the Authors (27 Apr 2017)  Author's response    Manuscript
ED: Publish as is (29 Apr 2017) by Remko Uijlenhoet
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Short summary
Stochastic generators are effective tools for the quantification of uncertainty in a number of applications with weather radar data, including quantitative precipitation estimation and very short-term forecasting. However, most of the current stochastic rainfall field generators cannot handle spatial non-stationarity. We propose an approach based on the short-space Fourier transform, which aims to reproduce the local spatial structure of the observed rainfall fields.