DOI: 10.5194/hess-23-773-2019
论文题名: Multivariate stochastic bias corrections with optimal transport
作者: Robin Y. ; Vrac M. ; Naveau P. ; Yiou P.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2019
卷: 23, 期: 2 起始页码: 773
结束页码: 786
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
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). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/163054
Appears in Collections: 气候变化与战略
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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
Recommended Citation:
Robin Y.,Vrac M.,Naveau P.,et al. Multivariate stochastic bias corrections with optimal transport[J]. Hydrology and Earth System Sciences,2019-01-01,23(2)