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.
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.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Jun 2020
Research article |
| 15 Jun 2020
| 15 Jun 2020
Multivariate bias corrections of climate simulations: which benefits for which losses?
Bastien François
CORRESPONDING AUTHOR
Laboratoire des Sciences du Climat et l’Environnement (LSCE-IPSL) CNRS/CEA/UVSQ, UMR8212, Université Paris-Saclay, Gif-sur-Yvette, France
Mathieu Vrac
Laboratoire des Sciences du Climat et l’Environnement (LSCE-IPSL) CNRS/CEA/UVSQ, UMR8212, Université Paris-Saclay, Gif-sur-Yvette, France
Alex J. Cannon
Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada
Yoann Robin
Centre National de Recherches Météorologiques, Université de Toulouse, CNRS, Météo-France, Toulouse, France
Denis Allard
INRAE, BioSP, 84914, Avignon, France
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Latest update: 29 Jun 2024
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.
Recently, multivariate bias correction (MBC) methods designed to adjust climate simulations have...
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