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

Model code and software

Rain typing utilities L. Benoit https://github.com/ LionelBenoit/Rain_typing.git

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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.