Retrieval of aerosol optical properties from GOCI-II observations: Continuation of long-term geostationary aerosol monitoring over East Asia SCIE SCOPUS

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Title
Retrieval of aerosol optical properties from GOCI-II observations: Continuation of long-term geostationary aerosol monitoring over East Asia
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)
Alternative Author(s)
박영제; 최종국
Publication Year
2023-12
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.
ISSN
0048-9697
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/44680
DOI
10.1016/j.scitotenv.2023.166504
Bibliographic Citation
Science of the Total Environment, v.903, 2023
Publisher
Elsevier BV
Keywords
Aerosol; Geostationary satellite; AOD; GOCI; GOCI-II
Type
Article
Language
English
Document Type
Article
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