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DOI	10.1002/wcc.535
	Data assimilation in the geosciences: An overview of methods, issues, and perspectives
	Carrassi A.; Bocquet M.; Bertino L.; Evensen G.
发表日期	2018
ISSN	1757-7780
EISSN	1757-7779
卷号	9 期号:5
英文摘要	We commonly refer to state estimation theory in geosciences as data assimilation (DA). This term encompasses the entire sequence of operations that, starting from the observations of a system, and from additional statistical and dynamical information (such as a dynamical evolution model), provides an estimate of its state. DA is standard practice in numerical weather prediction, but its application is becoming widespread in many other areas of climate, atmosphere, ocean, and environment modeling; in all circumstances where one intends to estimate the state of a large dynamical system based on limited information. While the complexity of DA, and of the methods thereof, stands on its interdisciplinary nature across statistics, dynamical systems, and numerical optimization, when applied to geosciences, an additional difficulty arises by the continually increasing sophistication of the environmental models. Thus, in spite of DA being nowadays ubiquitous in geosciences, it has so far remained a topic mostly reserved to experts. We aim this overview article at geoscientists with a background in mathematical and physical modeling, who are interested in the rapid development of DA and its growing domains of application in environmental science, but so far have not delved into its conceptual and methodological complexities. This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models. © 2018 Wiley Periodicals, Inc.
英文关键词	Bayesian methods; data assimilation; ensemble methods; environmental prediction
语种	英语
scopus关键词	Bayesian networks; Climate models; Estimation; Numerical methods; Optimization; Weather forecasting; Bayesian methods; Data assimilation; Ensemble methods; Environmental prediction; Knowledge generations; Large dynamical Systems; Numerical optimizations; Numerical weather prediction; Dynamical systems; Bayesian analysis; climate change; data assimilation; ensemble forecasting; environmental modeling; numerical model; weather forecasting
来源期刊	Wiley Interdisciplinary Reviews: Climate Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/129943
作者单位	Nansen Environmental and Remote Sensing Center, Bergen, Norway; CEREA, Joint Laboratory École des Ponts ParisTech and EDF R&D, Université Paris-Est, Champs-sur-Marne, France; International Research Institute of Stavanger (IRIS), Bergen, Norway
推荐引用方式 GB/T 7714	Carrassi A.,Bocquet M.,Bertino L.,et al. Data assimilation in the geosciences: An overview of methods, issues, and perspectives[J],2018,9(5).
APA	Carrassi A.,Bocquet M.,Bertino L.,&Evensen G..(2018).Data assimilation in the geosciences: An overview of methods, issues, and perspectives.Wiley Interdisciplinary Reviews: Climate Change,9(5).
MLA	Carrassi A.,et al."Data assimilation in the geosciences: An overview of methods, issues, and perspectives".Wiley Interdisciplinary Reviews: Climate Change 9.5(2018).