研究目的
To present improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validate the results during the DRAGON-NE Asia 2012 campaign, focusing on the retrieval of aerosol optical properties over East Asia.
研究成果
The GOCI YAER algorithm shows good agreement with AERONET and MODIS for AOD retrieval, with a Pearson correlation coefficient of 0.881. The algorithm performs better over ocean than land and shows better agreement with MODIS DB than DT. Other products like AE, FMF, and SSA have lower correlation but are useful for qualitative analysis. Improvements in surface reflectance determination and aerosol model selection are recommended for future versions.
研究不足
The study is limited to the spring season over East Asia, and the validation is based on data from the DRAGON-NE Asia 2012 campaign. The algorithm's performance may vary under different atmospheric and surface conditions. The lack of IR channels in GOCI limits cloud masking capabilities.
1：Experimental Design and Method Selection
The study uses the GOCI YAER algorithm for retrieving aerosol optical properties from GOCI TOA radiance. The algorithm includes cloud masking, surface reflectance determination over land and ocean, turbid water detection, aerosol model creation based on AERONET inversion data, and LUT calculation for inversion.
2：Sample Selection and Data Sources
Data from the DRAGON-NE Asia 2012 campaign, including AERONET observations and MODIS Collection 6 aerosol products, are used for validation. GOCI Level 1B radiance data are the primary input for the algorithm.
3：List of Experimental Equipment and Materials
GOCI onboard COMS, AERONET sun photometers, MODIS onboard Aqua and Terra.
4：Experimental Procedures and Operational Workflow
The algorithm processes include cloud masking, surface reflectance determination, turbid water detection, aerosol model selection, and inversion to retrieve aerosol properties. Validation is performed by comparing GOCI products with AERONET and MODIS data.
5：Data Analysis Methods
Statistical metrics such as Pearson correlation coefficient, RMSE, MAE, MBE, and the ratio within expected error are used for validation. Intercomparison between GOCI and MODIS products is also conducted.
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