Articles | Volume 12, issue 4
Earth Syst. Dynam., 12, 1253–1273, 2021
Earth Syst. Dynam., 12, 1253–1273, 2021
Research article
25 Nov 2021
Research article | 25 Nov 2021

Is time a variable like the others in multivariate statistical downscaling and bias correction?

Yoann Robin and Mathieu Vrac

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Cited articles

Bárdossy, A. and Pegram, G.: Multiscale spatial recorrelation of RCM precipitation to produce unbiased climate change scenarios over large areas and small, Water Resour. Res., 48, 9502,, 2012. a, b
Bartók, B., Tobin, I., Vautard, R., Vrac, M., Jin, X., Levavasseur, G., Denvil, S., Dubus, L., Parey, S., Michelangeli, P.-A., Troccoli, A., and Saint-Drenan, Y.-M.: A climate projection dataset tailored for the European energy sector, Clim. Serv., 16, 100138,, 2019. a
Bevacqua, E., Maraun, D., Vousdoukas, M. I., 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,, 2019. a
Bhuiyan, M. A. E., Nikolopoulos, E. I., Anagnostou, E. N., Quintana-Seguí, P., and Barella-Ortiz, A.: A nonparametric statistical technique for combining global precipitation datasets: development and hydrological evaluation over the Iberian Peninsula, Hydrol. Earth Syst. Sci., 22, 1371–1389,, 2018. 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,, 2007. a
Short summary
We propose a new multivariate downscaling and bias correction approach called time-shifted multivariate bias correction, which aims to correct temporal dependencies in addition to inter-variable and spatial ones. Our method is evaluated in a perfect model experiment context where simulations are used as pseudo-observations. The results show a large reduction of the biases in the temporal properties, while inter-variable and spatial dependence structures are still correctly adjusted.
Final-revised paper