Integration of Goci and AHI Yonsei Aerosol Optical Depth Products during Two Field Campaigns: 2016 KORUS-AQ and 2018 EMeRGe

Northeast Asian region is known as one of the regions where many aerosols loading all over the world, and there are various types. In general, aerosols are known to have negative radiative forcing and have the cooling effect the Earth- atmosphere climate system, but the radiative forcing depends on the aerosol type. For example, sulfate aerosols mainly scatter, and their radiative forcing shows cooling effect, while black carbon has strong absorption thus positive radiative forcing. Geostationary Ocean Color Imager (GOCI) and Advanced Himawari Imager (AHI) retrieve aerosol optical properties with high accuracy in East Asia.

However, errors in two GOCI aerosol optical depth (AOD) products and two AHI AOD products are different depending on the uncertainty of surface reflectance estimation and calibration status. Therefore, this study attempts to estimate the optimal AOD for East Asia in consideration of the characteristics of these errors. The first step of the fusion is to analyze the AERONET instrument and the error characteristics of each retrieved results and perform the bias correction according to the normalized vegetation indexes. The bias correction is based on the assumption that the different AOD characteristics have normal distributions, and bias was corrected through Gaussian fitting. After the bias was corrected, the fused product was estimated using an ensemble average and maximum likelihood estimation (MLE) method. These fused results were a combination of retrieved AODs, all of which have a higher % within Expected Error (EE) than the retrieved result for each satellite.