干旱区生态环境知识资源中心(Arid): Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods

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DOI	10.1029/2019MS001890
	Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods
	Choi, Yonghan 1,2; Chen, Shu-Hua 1; Huang, Chu-Chun 1; Earl, Kenneth 1; Chen, Chih-Ying 3; Schwartz, Craig S.4; Matsui, Toshihisa 5
通讯作者	Chen, Shu-Hua
来源期刊	JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
EISSN	1942-2466
出版年	2020
卷号	12 期号:4
英文摘要	This study evaluates the impact of assimilating moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data using different data assimilation (DA) methods on dust analyses and forecasts over North Africa and tropical North Atlantic. To do so, seven experiments are conducted using the Weather Research and Forecasting dust model and the Gridpoint Statistical Interpolation analysis system. Six of these experiments differ in whether or not AOD observations are assimilated and the DA method used, the latter of which includes the three-dimensional variational (3D-Var), ensemble square root filter (EnSRF), and hybrid methods. The seventh experiment, which allows us to assess the impact of assimilating deep blue AOD data, assimilates only dark target AOD data using the hybrid method. The assimilation of MODIS AOD data clearly improves AOD analyses and forecasts up to 48 hr in length. Results also show that assimilating deep blue data has a primarily positive effect on AOD analyses and forecasts over and downstream of the major North African source regions. Without assimilating deep blue data (assimilating dark target only), AOD assimilation only improves AOD forecasts for up to 30 hr. Of the three DA methods examined, the hybrid and EnSRF methods produce better AOD analyses and forecasts than the 3D-Var method does. Despite the clear benefit of AOD assimilation for AOD analyses and forecasts, the lack of information regarding the vertical distribution of aerosols in AOD data means that AOD assimilation has very little positive effect on analyzed or forecasted vertical profiles of backscatter.
类型	Article
语种	英语
国家	USA ; South Korea ; Taiwan
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000538038300008
WOS关键词	ENSEMBLE KALMAN FILTER ; VARIATIONAL DATA ASSIMILATION ; PARTICULATE MATTER ; DAILY MORTALITY ; BIAS CORRECTION ; ICE NUCLEATION ; SATELLITE DATA ; SAHARAN DUST ; DESERT DUST ; PART I
WOS类目	Meteorology & Atmospheric Sciences
WOS研究方向	Meteorology & Atmospheric Sciences
来源机构	University of California, Davis
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/319624
作者单位	1.Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA; 2.Korea Polar Res Inst, Incheon, South Korea; 3.Acad Sinica, Res Ctr Environm Changes, Taipei, Taiwan; 4.Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA; 5.NASA, Goddard Space Flight Ctr, Greenbelt, MD USA
推荐引用方式 GB/T 7714	Choi, Yonghan,Chen, Shu-Hua,Huang, Chu-Chun,et al. Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods[J]. University of California, Davis,2020,12(4).
APA	Choi, Yonghan.,Chen, Shu-Hua.,Huang, Chu-Chun.,Earl, Kenneth.,Chen, Chih-Ying.,...&Matsui, Toshihisa.(2020).Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods.JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS,12(4).
MLA	Choi, Yonghan,et al."Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods".JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 12.4(2020).