Articles | Volume 22, issue 11
https://doi.org/10.5194/hess-22-5919-2018
https://doi.org/10.5194/hess-22-5919-2018
Research article
 | 
19 Nov 2018
Research article |  | 19 Nov 2018

Dealing with non-stationarity in sub-daily stochastic rainfall models

Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz

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Interactive discussion

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: Reconsider after major revisions (further review by editor and referees) (07 Aug 2018) by Carlo De Michele
AR by Anna Wenzel on behalf of the Authors (18 Sep 2018)  Author's response
ED: Referee Nomination & Report Request started (02 Oct 2018) by Carlo De Michele
RR by Nadav Peleg (09 Oct 2018)
RR by Anonymous Referee #2 (17 Oct 2018)
ED: Publish as is (08 Nov 2018) by Carlo De Michele
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Short summary
We propose a method for unsupervised classification of the space–time–intensity structure of weather radar images. The resulting classes are interpreted as rain types, i.e. pools of rain fields with homogeneous statistical properties. Rain types can in turn be used to define stationary periods for further stochastic rainfall modelling. The application of rain typing to real data indicates that non-stationarity can be significant within meteorological seasons, and even within a single storm.