Articles | Volume 27, issue 2
Nonlin. Processes Geophys., 27, 307–327, 2020
https://doi.org/10.5194/npg-27-307-2020

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

Nonlin. Processes Geophys., 27, 307–327, 2020
https://doi.org/10.5194/npg-27-307-2020

Research article 27 May 2020

Research article | 27 May 2020

Correcting for model changes in statistical postprocessing – an approach based on response theory

Jonathan Demaeyer and Stéphane Vannitsem

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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
AR by Jonathan Demaeyer on behalf of the Authors (22 Mar 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (25 Mar 2020) by Maxime Taillardat
RR by Michael Zamo (11 Apr 2020)
ED: Publish subject to minor revisions (review by editor) (12 Apr 2020) by Maxime Taillardat
AR by Jonathan Demaeyer on behalf of the Authors (17 Apr 2020)  Author's response    Manuscript
ED: Publish as is (22 Apr 2020) by Maxime Taillardat
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Short summary
Postprocessing schemes used to correct weather forecasts are no longer efficient when the model generating the forecasts changes. An approach based on response theory to take the change into account without having to recompute the parameters based on past forecasts is presented. It is tested on an analytical model and a simple model of atmospheric variability. We show that this approach is effective and discuss its potential application for an operational environment.