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DOI	10.1109/JSTARS.2021.3108669
	Aerosol Absorption Over Land Derived From the Ultra-Violet Aerosol Index by Deep Learning
	Sun, Jiyunting; Veefkind, Pepijn; van Velthoven, Peter; Levelt, Pieternel F.
通讯作者	Sun, JYT (corresponding author), Royal Netherlands Meteorol Inst, Dept R&D Satellite Observat, NL-3731 De Bilt, Netherlands.
来源期刊	IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN	1939-1404
EISSN	2151-1535
出版年	2021
卷号	14 页码:9692-9710
英文摘要	Quantitative measurements of aerosol absorptive properties, e.g., the absorbing aerosol optical depth (AAOD) and the single scattering albedo (SSA), are important to reduce uncertainties of aerosol climate radiative forcing assessments. Currently, global retrievals of AAOD and SSA are mainly provided by the ground-based aerosol robotic network (AERONET), whereas it is still challenging to retrieve them from space. However, we found the AERONET AAOD has a relatively strong correlation with the satellite retrieved ultra-violet aerosol index (UVAI). Based on this, a numerical relation is built by a deep neural network (DNN) to predict global AAOD and SSA over land from the long-term UVAI record (2006-2019) provided by the ozone monitoring instrument (OMI) onboard Aura. The DNN predicted aerosol absorption is satisfying for samples with AOD at 550 nm larger than 0.1, and the DNN model performance is better for smaller absorbing aerosols (e.g., smoke) than larger ones (e.g., mineral dust). The comparison of the DNN predictions with AERONET shows a high correlation coefficient of 0.90 and a root mean square of 0.005 for the AAOD, and over 80% of samples are within the expected uncertainty of AERONET SSA (+/- 0.03).
英文关键词	Absorbing aerosol optical depth (AAOD) deep neural network (DDN) machine learning ozone monitoring instrument (OMI) single scattering albedo (SSA) ultra-violet aerosol index (UVAI)
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SCI-E
WOS记录号	WOS:000704824700004
WOS关键词	IMAGING SPECTRORADIOMETER MISR ; SINGLE-SCATTERING ALBEDO ; OPTICAL DEPTH PRODUCTS ; LONG-TERM RECORD ; NEURAL-NETWORK ; DESERT DUST ; VERTICAL-DISTRIBUTION ; TROPOSPHERIC AEROSOL ; INVERSION ALGORITHM ; HEIGHT RETRIEVAL
WOS类目	Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/363565
作者单位	[Sun, Jiyunting; Veefkind, Pepijn] Royal Netherlands Meteorol Inst, Dept R&D Satellite Observat, NL-3731 De Bilt, Netherlands; [Sun, Jiyunting; Veefkind, Pepijn; Levelt, Pieternel F.] Delft Univ Technol, Dept Geosci & Remote Sensing GRS Civil Engn & Ge, NL-2628 Delft, Netherlands; [van Velthoven, Peter] Royal Netherlands Meteorol Inst, Dept R&D Weather & Climate Modeling, NL-3731 De Bilt, Netherlands; [Levelt, Pieternel F.] Natl Ctr Atmospher Res NCAR, Atmospher Chem Observat & Modeling Lab ACOM, Boulder, CO 80301 USA
推荐引用方式 GB/T 7714	Sun, Jiyunting,Veefkind, Pepijn,van Velthoven, Peter,et al. Aerosol Absorption Over Land Derived From the Ultra-Violet Aerosol Index by Deep Learning[J],2021,14:9692-9710.
APA	Sun, Jiyunting,Veefkind, Pepijn,van Velthoven, Peter,&Levelt, Pieternel F..(2021).Aerosol Absorption Over Land Derived From the Ultra-Violet Aerosol Index by Deep Learning.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,14,9692-9710.
MLA	Sun, Jiyunting,et al."Aerosol Absorption Over Land Derived From the Ultra-Violet Aerosol Index by Deep Learning".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 14(2021):9692-9710.