气候变化领域集成服务门户(CCPortal): The impact of optimal selected historical forecasting samples on hybrid ensemble-variational data assimilation

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DOI	10.1016/j.atmosres.2020.104980
	The impact of optimal selected historical forecasting samples on hybrid ensemble-variational data assimilation
	Chen Y.; Guo S.; Meng D.; Wang H.; Xu D.; Wang Y.; Wang J.
发表日期	2020
ISSN	0169-8095
卷号	242
英文摘要	A resampling method that selects historical forecasting samples as supplementary samples is proposed for the hybrid ensemble-variational data assimilation system to alleviate the computational burden of ensemble forecasting samples. To select reasonable samples from all historical forecasting samples, the first modes of absolute vorticity are abstracted by the empirical orthogonal function (EOF) as indicators of atmospheric dynamic features from the background and each of historical forecasting sample, then they are matched at the analysis time. A series of single observation tests and 19-day cycling data assimilation and forecasting experiments for a Mei-yu period are carried out to evaluate the impact of the selected historical forecasting samples. The single observation tests indicate that the use of selected historical forecasting samples is able to provide reasonable flow-dependent background error covariance for the data assimilation system. The cycling data assimilation and forecasting experiments demonstrate that the analyses and forecasts as well as precipitation forecast skills are improved by using the combination of selected historical forecasting samples and ensemble forecasting samples. The sample-combined experiment performs close to the experiment with full-size ensemble forecasting samples, but it spends fewer computational resources. The diagnosis of a heavy rainfall case is presented to further illustrate the role of the selected historical forecasting samples. It is found that the simulation of vertical velocity and relative humidity are improved for the case in the experiment of the combined samples, leading to better intensity and position forecasts of the precipitation. © 2020 Elsevier B.V.
关键词	Atmospheric humidity Orthogonal functions Background-error covariances Computational costs Data assimilation Empirical Orthogonal Function Hybrid Numerical weather prediction Variational data assimilation Variational data assimilation system Weather forecasting climate prediction cost analysis data assimilation empirical orthogonal function analysis ensemble forecasting forecasting method weather forecasting Citrus maxima
语种	英语
来源机构	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/132456
推荐引用方式 GB/T 7714	Chen Y.,Guo S.,Meng D.,et al. The impact of optimal selected historical forecasting samples on hybrid ensemble-variational data assimilation[J]. Atmospheric Research,2020,242.
APA	Chen Y..,Guo S..,Meng D..,Wang H..,Xu D..,...&Wang J..(2020).The impact of optimal selected historical forecasting samples on hybrid ensemble-variational data assimilation.,242.
MLA	Chen Y.,et al."The impact of optimal selected historical forecasting samples on hybrid ensemble-variational data assimilation".242(2020).