Articles | Volume 11, issue 2
https://doi.org/10.5194/esd-11-537-2020
https://doi.org/10.5194/esd-11-537-2020
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

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Cited articles

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Cannon, A. J.: Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables, Clim. Dynam., 50, 31–49, https://doi.org/10.1007/s00382-017-3580-6, 2018a. a, b, c, d
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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.
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