气候变化领域集成服务门户(CCPortal): 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 Y.; Chen S.-H.; Huang C.-C.; Earl K.; Chen C.-Y.; Schwartz C.S.; Matsui T.
发表日期	2020
ISSN	19422466
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. © 2020. The Authors.
英文关键词	aerosol assimilation; aerosol optical depth (AOD); deep blue AOD; dust model; GSI; Sahara Desert
语种	英语
scopus关键词	Aerosols; Dust; Optical properties; Radiometers; Supercomputers; Value engineering; Aerosol optical depths; Data assimilation; Data assimilation methods; Ensemble square root filter; Moderate resolution imaging spectroradiometer; Statistical interpolation; Vertical distributions; Weather research and forecasting; Weather forecasting; aerosol; data assimilation; dust; MODIS; observational method; optical depth; satellite data; vertical distribution; Atlantic Ocean; Atlantic Ocean (East); Atlantic Ocean (North); North Africa
来源期刊	Journal of Advances in Modeling Earth Systems
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156729
作者单位	Department of Land, Air, and Water Resources, University of California, Davis, CA, United States; Korea Polar Research Institute, Incheon, South Korea; Research Center of Environmental Changes, Academia Sinica, Taipei, Taiwan; National Center for Atmospheric Research, Boulder, CO, United States; NASA Goddard Space Flight Center, Greenbelt, MD, United States
推荐引用方式 GB/T 7714	Choi Y.,Chen S.-H.,Huang C.-C.,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],2020,12(4).
APA	Choi Y..,Chen S.-H..,Huang C.-C..,Earl K..,Chen C.-Y..,...&Matsui T..(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 Y.,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).