Articles | Volume 27, issue 2
Nonlin. Processes Geophys., 27, 329–347, 2020
https://doi.org/10.5194/npg-27-329-2020

Special issue: Advances in post-processing and blending of deterministic...

Nonlin. Processes Geophys., 27, 329–347, 2020
https://doi.org/10.5194/npg-27-329-2020

Research article 29 May 2020

Research article | 29 May 2020

From research to applications – examples of operational ensemble post-processing in France using machine learning

Maxime Taillardat and Olivier Mestre

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Status: closed
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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 (08 Apr 2020)  Author's response
ED: Referee Nomination & Report Request started (15 Apr 2020) by Sebastian Lerch
RR by Anonymous Referee #2 (24 Apr 2020)
ED: Publish subject to technical corrections (24 Apr 2020) by Sebastian Lerch
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Short summary
Statistical post-processing of ensemble forecasts is now a well-known procedure in order to correct biased and misdispersed ensemble weather predictions. But practical application in European national weather services is in its infancy. Different applications of ensemble post-processing using machine learning at an industrial scale are presented. Forecast quality and value are improved compared to the raw ensemble, but several facilities have to be made to adjust to operational constraints.