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DOI	10.1029/2021EA001767
	i4DVar: An Integral Correcting Four-Dimensional Variational Data Assimilation Method
	Tian, Xiangjun; Zhang, Hongqin; Feng, Xiaobing; Li, Xin
通讯作者	Tian, XJ (通讯作者)
发表日期	2021
EISSN	2333-5084
卷号	8 期号:9
英文摘要	Four-dimensional variational data assimilation (4DVar) has become an increasingly important tool in data science with wide applications in many engineering and scientific fields. The current state-of-the-art 4DVar offers only two choices in incorporating the forecast model which lead to the strongly and weakly constrained 4DVar approaches. The former ignores the model error and only corrects the initial condition error at the expense of reduced accuracy; while the latter accounts for both the initial and model errors but corrects them separately, which increases computational costs and uncertainty. To overcome these limitations, in this study we develop an integral correcting 4DVar (i4DVar) approach by treating all errors together as a whole and correcting them simultaneously and indiscriminately. Our main idea is to introduce an averaged penalization term in the cost functional to correct the error evolution at selected time steps with same interval, which is amount to dividing the assimilation window into several sub-windows. As a result, i4DVar greatly enhances the capability of the strongly constrained 4DVar for correcting the model error while also overcomes the limitation of the weakly constrained 4DVar for being prohibitively expensive with added uncertainty. The new i4DVar approach has the potential to be applicable to various scientific and engineering fields as well as industrial sectors which involve big observation data because of its ease of implementation and superior performance.
关键词	MODEL-ERROR ESTIMATION WEAK-CONSTRAINT METEOROLOGICAL OBSERVATIONS OPERATIONAL IMPLEMENTATION SYSTEM IMPACT FILTER
英文关键词	data assimilation; 4DVar; model error; initial error
语种	英语
WOS研究方向	Astronomy & Astrophysics ; Geology
WOS类目	Astronomy & Astrophysics ; Geosciences, Multidisciplinary
WOS记录号	WOS:000702253100011
来源期刊	EARTH AND SPACE SCIENCE
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/260430
推荐引用方式 GB/T 7714	Tian, Xiangjun,Zhang, Hongqin,Feng, Xiaobing,et al. i4DVar: An Integral Correcting Four-Dimensional Variational Data Assimilation Method[J]. 中国科学院青藏高原研究所,2021,8(9).
APA	Tian, Xiangjun,Zhang, Hongqin,Feng, Xiaobing,&Li, Xin.(2021).i4DVar: An Integral Correcting Four-Dimensional Variational Data Assimilation Method.EARTH AND SPACE SCIENCE,8(9).
MLA	Tian, Xiangjun,et al."i4DVar: An Integral Correcting Four-Dimensional Variational Data Assimilation Method".EARTH AND SPACE SCIENCE 8.9(2021).