Articles | Volume 26, issue 3
https://doi.org/10.5194/npg-26-339-2019
https://doi.org/10.5194/npg-26-339-2019
Research article
 | 
26 Sep 2019
Research article |  | 26 Sep 2019

Statistical post-processing of ensemble forecasts of the height of new snow

Jari-Pekka Nousu, Matthieu Lafaysse, Matthieu Vernay, Joseph Bellier, Guillaume Evin, and Bruno Joly

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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Matthieu Lafaysse on behalf of the Authors (06 Aug 2019)  Author's response    Manuscript
ED: Publish subject to minor revisions (review by editor) (28 Aug 2019) by Stephan Hemri
AR by Matthieu Lafaysse on behalf of the Authors (29 Aug 2019)  Author's response    Manuscript
ED: Publish subject to technical corrections (02 Sep 2019) by Stephan Hemri
AR by Matthieu Lafaysse on behalf of the Authors (02 Sep 2019)  Author's response    Manuscript
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Short summary
Forecasting the height of new snow is crucial for avalanche hazard, road viability, ski resorts and tourism. The numerical models suffer from systematic and significant errors which are misleading for the final users. Here, we applied for the first time a state-of-the-art statistical method to correct ensemble numerical forecasts of the height of new snow from their statistical link with measurements in French Alps and Pyrenees. Thus the realism of automatic forecasts can be quickly improved.