干旱区生态环境知识资源中心(Arid): Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China

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DOI	10.5194/acp-20-15207-2020
	Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China
	Jin, Jianbing; Segers, Arjo; Liao, Hong; Heemink, Arnold; Kranenburg, Richard; Lin, Hai Xiang
通讯作者	Jin, JB ; Liao, H (corresponding author), Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Atmospher Environm & Equip, Sch Environm Sci & Engn, Jiangsu Key Lab Atmospher Environm Monitoring & P, Nanjing, Peoples R China. ; Jin, JB (corresponding author), Delft Univ Technol, Delft Inst Appl Math, Delft, Netherlands.
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
ISSN	1680-7316
EISSN	1680-7324
出版年	2020
卷号	20 期号:23 页码:15207-15225
英文摘要	Emission inversion using data assimilation fundamentally relies on having the correct assumptions about the emission background error covariance. A perfect covariance accounts for the uncertainty based on prior knowledge and is able to explain differences between model simulations and observations. In practice, emission uncertainties are constructed empirically; hence, a partially unrepresentative covariance is unavoidable. Concerning its complex parameterization, dust emissions are a typical example where the uncertainty could be induced from many underlying inputs, e.g., information on soil composition and moisture, land cover and erosive wind velocity, and these can hardly be taken into account together. This paper describes how an adjoint model can be used to detect errors in the emission uncertainty assumptions. This adjoint-based sensitivity method could serve as a supplement of a data assimilation inverse modeling system to trace back the error sources in case large observationminus-simulation residues remain after assimilation based on empirical background covariance. The method follows an application of a data assimilation emission inversion for an extreme severe dust storm over East Asia (Jin et al., 2019b). The assimilation system successfully resolved observation-minus-simulation errors using satellite AOD observations in most of the dust-affected regions. However, a large underestimation of dust in Northeast China remained despite the fact that the assimilated measurements indicated severe dust plumes there. An adjoint implementation of our dust simulation model is then used to detect the most likely source region for these unresolved dust loads. The backward modeling points to the Horqin desert as the source region, which was indicated as a non-source region by the existing emission scheme. The reference emission and uncertainty are then reconstructed over the Horqin desert by assuming higher surface erodibility. After the emission reconstruction, the emission inversion is performed again, and the posterior dust simulations and reality are now in much closer harmony. Based on our results, it is advised that emission sources in dust transport models include the Horqin desert as a more active source region.
类型	Article
语种	英语
开放获取类型	Green Submitted, gold
收录类别	SCI-E
WOS记录号	WOS:000599174200003
WOS关键词	DATA ASSIMILATION ; ASIAN DUST ; EAST-ASIA ; METEOROLOGICAL OBSERVATIONS ; FRICTION VELOCITY ; AEROSOL ; MODEL ; TRANSPORT ; HIMAWARI-8 ; PARAMETRIZATION
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
来源机构	南京信息工程大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/348739
作者单位	[Jin, Jianbing; Liao, Hong] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Atmospher Environm & Equip, Sch Environm Sci & Engn, Jiangsu Key Lab Atmospher Environm Monitoring & P, Nanjing, Peoples R China; [Jin, Jianbing; Heemink, Arnold; Lin, Hai Xiang] Delft Univ Technol, Delft Inst Appl Math, Delft, Netherlands; [Segers, Arjo; Kranenburg, Richard] TNO, Dept Climate Air & Sustainabil, Utrecht, Netherlands
推荐引用方式 GB/T 7714	Jin, Jianbing,Segers, Arjo,Liao, Hong,et al. Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China[J]. 南京信息工程大学,2020,20(23):15207-15225.
APA	Jin, Jianbing,Segers, Arjo,Liao, Hong,Heemink, Arnold,Kranenburg, Richard,&Lin, Hai Xiang.(2020).Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China.ATMOSPHERIC CHEMISTRY AND PHYSICS,20(23),15207-15225.
MLA	Jin, Jianbing,et al."Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China".ATMOSPHERIC CHEMISTRY AND PHYSICS 20.23(2020):15207-15225.