Retrieval of aerosol optical properties from GOCI-II observations: Continuation of long-term geostationary aerosol monitoring over East Asia
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Title
- Retrieval of aerosol optical properties from GOCI-II observations: Continuation of long-term geostationary aerosol monitoring over East Asia
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Author(s)
- Lee, Seoyoung; Choi, Myungje; Kim, Jhoon; Park, Young Je; Choi, Jong Kuk; Lim, Hyunkwang; Lee, Jeewoo; Kim, Minseok; Cho, Yeseul
- KIOST Author(s)
- Park, Young Je(박영제); Choi, Jong Kuk(최종국)
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Alternative Author(s)
- 박영제; 최종국
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Publication Year
- 2023-12
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Abstract
- Since the Geostationary Ocean Color Imager (GOCI) was successfully launched in 2010, the GOCI Yonsei aerosol retrieval (YAER) algorithm has been continuously updated to retrieve hourly aerosol optical properties. GOCI-II has 4 more channels including UV, finer spatial resolution (250 m), and daily full disk coverage as compared to GOCI, and was launched in February 2020, onboard the GEO-KOMPSAT-2B (GK-2B) satellite. In this study, we extended the YAER algorithm to GOCI-II data based on its improved performance in many aspects and present the first results of aerosol optical properties retrieved from GOCI-II data. Utilizing the overlapping period between the GOCI-II and GOCI in geostationary Earth orbit, we present GOCI-II aerosol retrievals for high aerosol-loading cases over East Asia and show that these have a consistent spatial distribution with those from GOCI. Furthermore, GOCI-II provides AOD at an even higher spatial resolution, revealing finer changes in aerosol concentrations. Validation results for one year data show that the GOCI-II AOD has a correlation coefficient of 0.83 and a ratio within the expected error (EE) of 59.4 % when compared with the aerosol robotic network (AERONET) data. We compared statistical metrics for the GOCI and GOCI-II AODs to assess the consistency between the two datasets. In addition, it was found that there is a strong correlation between the two datasets from the comparison of gridded GOCI and GOCI-II AOD products. It is expected that data from GOCI-II will continue long-term aerosol records with high accuracy that can be used to address air-quality issues over East Asia.
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ISSN
- 0048-9697
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/44680
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DOI
- 10.1016/j.scitotenv.2023.166504
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Bibliographic Citation
- Science of the Total Environment, v.903, 2023
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Publisher
- Elsevier BV
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Keywords
- Aerosol; Geostationary satellite; AOD; GOCI; GOCI-II
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Type
- Article
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Language
- English
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Document Type
- Article
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