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The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER)version 1 algorithm was developed to retrieve hourly aerosol optical depth at550 nm (AOD) and other subsidiary aerosol optical properties over East Asia.The GOCI YAER AOD had accuracy comparable to ground-based and othersatellite-based observations but still had errors because of uncertaintiesin surface reflectance and simple cloud masking. In addition, near-real-time(NRT) processing was not possible because a monthly database for each yearencompassing the day of retrieval was required for the determination ofsurface reflectance. This study describes the improved GOCI YAER algorithmversion 2 (V2) for NRT processing with improved accuracy based on updates tothe cloud-masking and surface-reflectance calculations using a multi-yearRayleigh-corrected reflectance and wind speed database, and inversion channels for surface conditions. The improved GOCI AOD τG is closer to that of the Moderate Resolution ImagingSpectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD than was the case for AOD from the YAER V1 algorithm. The V2τG has a lower median bias and higher ratio withinthe MODIS expected error range (0.60 for land and 0.71 for ocean) compared withV1 (0.49 for land and 0.62 for ocean) in a validation test against AerosolRobotic Network (AERONET) AOD τA from 2011 to2016. A validation using the Sun-Sky Radiometer Observation Network (SONET)over China shows similar results. The bias of error (τG − τA) is within −0.1 and 0.1, and it isa function of AERONET AOD and Ångström exponent (AE), scattering angle, normalized difference vegetation index (NDVI), cloud fraction andhomogeneity of retrieved AOD, and observation time, month, and year. Inaddition, the diagnostic and prognostic expected error (PEE) of τG are estimated. The estimated PEE of GOCI V2 AOD is wellcorrelated with the actual error over East Asia, and the GOCI V2 AOD overSouth Korea has a higher ratio within PEE than that over China and Japan

atmospheric measurement techniques

GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia