气候变化领域集成服务门户(CCPortal): A nonlinear least squares four-dimensional variational data assimilation system for PM2.5 forecasts (NASM): Description and preliminary evaluation

CCPortal

DOI	10.1016/j.apr.2021.03.003
	A nonlinear least squares four-dimensional variational data assimilation system for PM2.5 forecasts (NASM): Description and preliminary evaluation
	Zhang, Shan; Tian, Xiangjun; Zhang, Hongqin; Han, Xiao; Zhang, Meigen
通讯作者	Tian, XJ (通讯作者)
发表日期	2021
ISSN	1309-1042
起始页码	122
结束页码	132
卷号	12 期号:4
英文摘要	Air quality is a vital concern globally, especially in China. To improve fine particulate matter (PM2.5) forecasts, a nonlinear least squares four-dimensional variational (NLS-4DVar) data assimilation system was established and applied into the Weather Research and Forecasting model coupled with the offline Community Multiscale Air Quality (WRF-CMAQ) model. By assimilating hourly surface PM2.5 observations, the optimal initial conditions (ICs) of the state variable were solved iteratively with the NLS-4DVar method, which uses a Gauss-Newton iterative scheme to handle nonlinearity without a tangent linear or adjoint model, thereby rendering the aerosol assimilation process fast and simple. Observing system simulation experiments (OSSEs) were designed from 10 to 16 November 2018 to evaluate the effectiveness of the NLS-4DVar data assimilation system for PM2.5 forecasts (NASM) assimilation system. The results derived from the OSSEs indicated that the NASM system could effectively assimilate multi-time PM2.5 observations, reduce uncertainty in surface initial PM2.5 concentrations, and thus improve the accuracy of predictions.
关键词	ENSEMBLE DATA ASSIMILATION WEATHER RESEARCH KALMAN FILTER MODEL CMAQ IMPLEMENTATION CHEMISTRY OZONE CHINA SIMULATION
英文关键词	Data assimilation system; NLS-4DVar method; PM2.5 forecast; WRF-CMAQ model
语种	英语
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Environmental Sciences
WOS记录号	WOS:000635603000004
来源期刊	ATMOSPHERIC POLLUTION RESEARCH
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/260351
推荐引用方式 GB/T 7714	Zhang, Shan,Tian, Xiangjun,Zhang, Hongqin,et al. A nonlinear least squares four-dimensional variational data assimilation system for PM2.5 forecasts (NASM): Description and preliminary evaluation[J]. 中国科学院青藏高原研究所,2021,12(4).
APA	Zhang, Shan,Tian, Xiangjun,Zhang, Hongqin,Han, Xiao,&Zhang, Meigen.(2021).A nonlinear least squares four-dimensional variational data assimilation system for PM2.5 forecasts (NASM): Description and preliminary evaluation.ATMOSPHERIC POLLUTION RESEARCH,12(4).
MLA	Zhang, Shan,et al."A nonlinear least squares four-dimensional variational data assimilation system for PM2.5 forecasts (NASM): Description and preliminary evaluation".ATMOSPHERIC POLLUTION RESEARCH 12.4(2021).