Articles | Volume 23, issue 2
https://doi.org/10.5194/hess-23-773-2019
https://doi.org/10.5194/hess-23-773-2019
Research article
 | 
12 Feb 2019
Research article |  | 12 Feb 2019

Multivariate stochastic bias corrections with optimal transport

Yoann Robin, Mathieu Vrac, Philippe Naveau, and Pascal Yiou

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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
ED: Reconsider after major revisions (further review by editor and referees) (28 Nov 2018) by Uwe Ehret
AR by Yoann Robin on behalf of the Authors (29 Nov 2018)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (29 Nov 2018) by Uwe Ehret
RR by Anonymous Referee #1 (03 Dec 2018)
RR by Michael Muskulus (11 Jan 2019)
ED: Publish subject to minor revisions (review by editor) (11 Jan 2019) by Uwe Ehret
AR by Yoann Robin on behalf of the Authors (15 Jan 2019)  Author's response   Manuscript 
ED: Publish subject to technical corrections (16 Jan 2019) by Uwe Ehret
AR by Yoann Robin on behalf of the Authors (17 Jan 2019)  Author's response   Manuscript 
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Short summary
Bias correction methods are used to calibrate climate model outputs with respect to observations. In this article, a non-stationary, multivariate and stochastic bias correction method is developed based on optimal transport, accounting for inter-site and inter-variable correlations. Optimal transport allows us to construct a joint distribution that minimizes energy spent in bias correction. Our methodology is tested on precipitation and temperatures over 12 locations in southern France.