Articles | Volume 22, issue 6
https://doi.org/10.5194/hess-22-3175-2018
https://doi.org/10.5194/hess-22-3175-2018
Research article
 | 
07 Jun 2018
Research article |  | 07 Jun 2018

Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2D2) bias correction

Mathieu Vrac

Related authors

Attributing the occurrence and intensity of extreme events with the flow analogues method
Robin Noyelle, Davide Faranda, Yoann Robin, Mathieu Vrac, and Pascal Yiou
EGUsphere, https://doi.org/10.5194/egusphere-2024-3167,https://doi.org/10.5194/egusphere-2024-3167, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
A causality-based method for multi-model comparison: Application to relationships between atmospheric and marine biogeochemical variables
Germain Bénard, Marion Gehlen, and Mathieu Vrac
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2024-31,https://doi.org/10.5194/esd-2024-31, 2024
Preprint under review for ESD
Short summary
Long vs. Short: Understanding the dynamics of persistent summer hot spells in Europe
Duncan Pappert, Alexandre Tuel, Dim Coumou, Mathieu Vrac, and Olivia Martius
EGUsphere, https://doi.org/10.5194/egusphere-2024-2980,https://doi.org/10.5194/egusphere-2024-2980, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Assessing multivariate bias corrections of climate simulations on various impact models under climate change
Denis Allard, Mathieu Vrac, Bastien François, and Iñaki García de Cortázar-Atauri
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-102,https://doi.org/10.5194/hess-2024-102, 2024
Preprint under review for HESS
Short summary
ClimaMeter: contextualizing extreme weather in a changing climate
Davide Faranda, Gabriele Messori, Erika Coppola, Tommaso Alberti, Mathieu Vrac, Flavio Pons, Pascal Yiou, Marion Saint Lu, Andreia N. S. Hisi, Patrick Brockmann, Stavros Dafis, Gianmarco Mengaldo, and Robert Vautard
Weather Clim. Dynam., 5, 959–983, https://doi.org/10.5194/wcd-5-959-2024,https://doi.org/10.5194/wcd-5-959-2024, 2024
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Downscaling precipitation over High-mountain Asia using multi-fidelity Gaussian processes: improved estimates from ERA5
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024,https://doi.org/10.5194/hess-28-4903-2024, 2024
Short summary
Mapping soil moisture across the UK: assimilating cosmic-ray neutron sensors, remotely sensed indices, rainfall radar and catchment water balance data in a Bayesian hierarchical model
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024,https://doi.org/10.5194/hess-28-4819-2024, 2024
Short summary
Assessing rainfall radar errors with an inverse stochastic modelling framework
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024,https://doi.org/10.5194/hess-28-4539-2024, 2024
Short summary
Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024,https://doi.org/10.5194/hess-28-4455-2024, 2024
Short summary
Spatiotemporal responses of runoff to climate change in the southern Tibetan Plateau
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024,https://doi.org/10.5194/hess-28-4361-2024, 2024
Short summary

Cited articles

Araújo, M. and Rahbek, C.: How Does Climate Change Affect Biodiversity?, Science, 313, 1396–1397, https://doi.org/10.1126/science.1131758, 2006.
Bardossy, A. and Pegram, G.: Multiscale spatial recorrelation of RCM precipitation to produce unbiased climate change scenarios over large areas and small, Water Resour. Res., https://doi.org/10.1029/2011WR011524, 2012.
Berg, P., Feldmann, H., and Panitz, H.-J.: Bias correction of high resolution regional climate model data, J. Hydrol., 448–449, 80–92, https://doi.org/10.1016/j.jhydrol.2012.04.026, 2012.
Bevacqua, E., Maraun, D., Hobæk Haff, I., Widmann, M., and Vrac, M.: Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy), Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, 2017.
Cannon, A.: 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, 2017.
Download
Short summary
This study presents a multivariate bias correction method named R2D2 to adjust both the 1d-distributions and inter-variable/site dependence structures of climate simulations in a high-dimensional context, while providing some stochasticity. R2D2 is tested on temperature and precipitation reanalyses and illustrated on future simulations. In both cases, R2D2 is able to correct the spatial and physical dependence, opening proper use of climate simulations for impact (e.g. hydrological) models.