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

Viewed

Total article views: 5,270 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,083 1,984 203 5,270 186 236
  • HTML: 3,083
  • PDF: 1,984
  • XML: 203
  • Total: 5,270
  • BibTeX: 186
  • EndNote: 236
Views and downloads (calculated since 01 Feb 2017)
Cumulative views and downloads (calculated since 01 Feb 2017)

Viewed (geographical distribution)

Total article views: 5,270 (including HTML, PDF, and XML) Thereof 5,062 with geography defined and 208 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 13 Aug 2026
Download
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.
Share