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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Cited articles

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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.