298 AHI/Himawari-8 Yonsei Aerosol Retrieval (YAER): Algorithm, Validation and Merged Products

Wednesday, 11 July 2018
Regency A/B/C (Hyatt Regency Vancouver)
Hyunkwang Lim, Yonsei Univ., Seoul, Korea, Republic of (South); and J. Kim, M. Choi, S. Go, P. W. Chan, and Y. Kasai

Himawari-8, a next-generation geostationary meteorological satellite, was successfully launched by the Japanese Meteorological Agency (JMA) on 7 October 2014 and has been in official operation since 7 July 2015. The Advanced Himawari Imager (AHI) onboard Himawari-8 has 16 channels from 0.47 to 13.3 μm and performs full-disk observations every 10-minute. This study describes AHI aerosol optical property (AOP) retrieval based on a multi-channel algorithm using three visible and one near-infrared channels (470, 510, 640, and 860 nm). AOPs were retrieved by obtaining the visible surface reflectance using shortwave infrared (SWIR) data along with normalized difference vegetation index shortwave infrared (NDVISWIR) categories and the minimum reflectance method (MRM). Estimated surface reflectance from SWIR (ESR) tends to be overestimated in urban and cropland areas. Thus the visible surface reflectance was improved by considering urbanization effects. Ocean surface reflectance is obtained using MRM and the new Cox and Munk method, which uses the ocean bidirectional reflectance distribution function (BRDF) and requires input parameters that include wind speed, chlorophyll and salinity, among others. Based on validation with ground-based sun-photometer measurements from the Aerosol Robotic Network (AERONET) data, the error pattern tends to the opposition between MRMver AOD and ESRver AOD. To estimate optimal AOD products, two methods were used to merge the data. The final aerosol products and the two surface reflectances were merged, which resulted in higher accuracy AOD values than those retrieved by either individual method. All four AODs shown in this study show accurate diurnal variation compared with AERONET, but the optimum AOD changes depending on observation time.
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