气候变化领域集成服务门户(CCPortal): Multivariate stochastic bias corrections with optimal transport

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DOI	10.5194/hess-23-773-2019
	Multivariate stochastic bias corrections with optimal transport
	Robin Y.; Vrac M.; Naveau P.; Yiou P.
发表日期	2019
ISSN	1027-5606
起始页码	773
结束页码	786
卷号	23 期号:2
英文摘要	Bias correction methods are used to calibrate climate model outputs with respect to observational records. The goal is to ensure that statistical features (such as means and variances) of climate simulations are coherent with observations. In this article, a multivariate stochastic bias correction method is developed based on optimal transport. Bias correction methods are usually defined as transfer functions between random variables. We show that such transfer functions induce a joint probability distribution between the biased random variable and its correction. The optimal transport theory allows us to construct a joint distribution that minimizes an energy spent in bias correction. This extends the classical univariate quantile mapping techniques in the multivariate case. We also propose a definition of non-stationary bias correction as a transfer of the model to the observational world, and we extend our method in this context. Those methodologies are first tested on an idealized chaotic system with three variables. In those controlled experiments, the correlations between variables appear almost perfectly corrected by our method, as opposed to a univariate correction. Our methodology is also tested on daily precipitation and temperatures over 12 locations in southern France. The correction of the inter-variable and inter-site structures of temperatures and precipitation appears in agreement with the multi-dimensional evolution of the model, hence satisfying our suggested definition of non-stationarity. © 2019 Author(s).
语种	英语
scopus关键词	Chaotic systems; Probability distributions; Random variables; Statistical mechanics; Stochastic systems; Transfer functions; Bias-correction methods; Climate simulation; Controlled experiment; Daily precipitations; Joint distributions; Joint probability distributions; Non-stationarities; Statistical features; Climate models; calibration; climate modeling; correction; experimental study; methodology; multivariate analysis; precipitation (climatology); statistical analysis; stochasticity; transfer function; France
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159764
作者单位	Robin, Y., Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212, CEA-CNRS-UVSQ, IPSL and U Paris-Saclay, Gif-sur-Yvette, France; Vrac, M., Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212, CEA-CNRS-UVSQ, IPSL and U Paris-Saclay, Gif-sur-Yvette, France; Naveau, P., Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212, CEA-CNRS-UVSQ, IPSL and U Paris-Saclay, Gif-sur-Yvette, France; Yiou, P., Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212, CEA-CNRS-UVSQ, IPSL and U Paris-Saclay, Gif-sur-Yvette, France
推荐引用方式 GB/T 7714	Robin Y.,Vrac M.,Naveau P.,et al. Multivariate stochastic bias corrections with optimal transport[J],2019,23(2).
APA	Robin Y.,Vrac M.,Naveau P.,&Yiou P..(2019).Multivariate stochastic bias corrections with optimal transport.Hydrology and Earth System Sciences,23(2).
MLA	Robin Y.,et al."Multivariate stochastic bias corrections with optimal transport".Hydrology and Earth System Sciences 23.2(2019).