Multivariate bias corrections of climate simulations: which benefits for which losses?

François, Bastien; Vrac, Mathieu; Cannon, Alex J.; Robin, Yoann; Allard, Denis

doi:https://doi.org/10.5194/esd-11-537-2020

Articles | Volume 11, issue 2

https://doi.org/10.5194/esd-11-537-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esd-11-537-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 11, issue 2

Research article

|

15 Jun 2020

Research article |

| 15 Jun 2020

Multivariate bias corrections of climate simulations: which benefits for which losses?

Bastien François, Mathieu Vrac, Alex J. Cannon, Yoann Robin, and Denis Allard

Supplement

https://doi.org/10.5194/esd-11-537-2020-supplement

Data sets

SBCK (Statistical Bias Correction Kit) Y. Robin https://github.com/yrobink/SBCK

Model code and software

Multivariate Bias Correction of Climate Model Outputs A. J. Cannon https://CRAN.R-project.org/package=MBC

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Short summary

Recently, multivariate bias correction (MBC) methods designed to adjust climate simulations have been proposed. However, they use different approaches, leading potentially to different results. Therefore, this study intends to intercompare four existing MBC methods to provide end users with aid in choosing such methods for their applications. To do so, a wide range of evaluation criteria have been used to assess the ability of MBC methods to correct statistical properties of climate models.