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GOCI Yonsei Aerosol Retrieval (YAER) Algorithm and Validation During the DRAGON-NE Asia 2012 CampaignThe Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGONNE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 x AERONET AOD - 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.
Document ID
20170003266
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Choi, Myungje
(Yonsei Univ. Seoul, Korea, Republic of)
Kim, Jhoon
(Yonsei Univ. Seoul, Korea, Republic of)
Lee, Jaehwa
(Maryland Univ. College Park, MD, United States)
Kim, Mijin
(Yonsei Univ. Seoul, Korea, Republic of)
Park, Young-Je
(Korea Ocean Research and Development Inst. Seoul, Korea, Republic of)
Jeong, Ukkyo
(Yonsei Univ. Seoul, Korea, Republic of)
Kim, Woogyung
(Yonsei Univ. Seoul, Korea, Republic of)
Hong, Hyunkee
(Pukyong National Univ. Busan, Korea, Republic of)
Holben, Brent
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Eck, Thomas F.
(Universities Space Research Association Columbia, MD, United States)
Song, Chul H.
(Gwangju Inst. of Science and Technology South Korea)
Lim, Jae-Hyun
(National Institute of Environmental Research Incheon, Korea, Republic of)
Song, Chang-Keun
(National Institute of Environmental Research Incheon, Korea, Republic of)
Date Acquired
April 7, 2017
Publication Date
April 1, 2016
Publication Information
Publication: Atmospheric Measurement Techniques
Publisher: Copernicus Publications
Volume: 9
Issue: 3
ISSN: 1867-1381
e-ISSN: 1867-8548
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN41279
Funding Number(s)
CONTRACT_GRANT: NNG11HP16A
Distribution Limits
Public
Copyright
Other

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