Articles | Volume 10, issue 4
Research article
25 Apr 2017
Research article |  | 25 Apr 2017

Data-driven clustering of rain events: microphysics information derived from macro-scale observations

Mohamed Djallel Dilmi, Cécile Mallet, Laurent Barthes, and Aymeric Chazottes


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
AR by Anna Wenzel on behalf of the Authors (22 Mar 2017)  Author's response
ED: Referee Nomination & Report Request started (22 Mar 2017) by Gianfranco Vulpiani
ED: Publish as is (29 Mar 2017) by Gianfranco Vulpiani
Short summary
The concept of a rain event is used to obtain a parsimonious characterisation of rain events using a minimal subset of variables at macrophysical scale. A classification in five classes is obtained in a unsupervised way from this subset. Relationships between these classes of microphysical parameters of precipitation are highlighted. There are several implications especially for remote sensing in the context of weather radar applications and quantitative precipitation estimation.