Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 13, issue 11
Articles | Volume 13, issue 11
https://doi.org/10.5194/gmd-13-5367-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-5367-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 11
Model description paper
 | 
06 Nov 2020
Model description paper |  | 06 Nov 2020

R2D2 v2.0: accounting for temporal dependences in multivariate bias correction via analogue rank resampling

Mathieu Vrac and Soulivanh Thao

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Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W., and Courchamp, F.: Impacts of climate change on the future of biodiversity, Ecol. Lett., 15, 365–377, https://doi.org/10.1111/j.1461-0248.2011.01736.x, 2012. a
Ben-Ari, T., Boé, J., Ciais, P., Lecerf, R., Van der Velde, M., and Makowski, D.: Causes and implications of the unforeseen 2016 extreme yield loss in the breadbasket of France, Nat. Commun., 9, 1627, https://doi.org/10.1038/s41467-018-04087-x , 2018. a
Bevacqua, E., Maraun, D., Vousdoukas, M., Voukouvalas, E., Vrac, M., Mentaschi, L., and Widmann, M.: Higher probability of compound flooding from precipitation and storm surge in Europe under anthropogenic climate change, Sci. Adv., 5, eaaw5531, https://doi.org/10.1126/sciadv.aaw5531, 2019. a
Boé, J., Terray, L., Habets, F., and Martin, E.: Statistical and dynamical downscaling of the Seine basin climate for hydro‐meteorological studies, Int. J. Climatol., 27, 1643–1655, https://doi.org/10.1002/joc.1602, 2007. a
Brown, C. J., Schoeman, D. S., Sydeman, W. J., Brander, K., Buckley, L. B., Burrows, M., Duarte, C. M., Moore, P. J., Pandolfi, J. M., Poloczanska, E., Venables, W., and Richardson, A. J.: Quantitative approaches in climate change ecology, Glob. Change Biol., 17, 3697–3713, https://doi.org/10.1111/j.1365-2486.2011.02531.x, 2011. a
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We propose a multivariate bias correction (MBC) method to adjust the spatial and/or inter-variable properties of climate simulations, while also accounting for their temporal dependences (e.g., autocorrelations). It consists on a method reordering the ranks of the time series according to their multivariate distance to a reference time series. Results show that temporal correlations are improved while spatial and inter-variable correlations are still satisfactorily corrected.
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