Journal of the Meteorological Society of Japan. Ser. II
Online ISSN : 2186-9057
Print ISSN : 0026-1165
Articles
Common Retrieval of Aerosol Properties for Imaging Satellite Sensors
Mayumi YOSHIDAMaki KIKUCHITakashi M. NAGAOHiroshi MURAKAMITomoyuki NOMAKIAkiko HIGURASHI
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2018 Volume 96B Pages 193-209

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Abstract

 We developed a common algorithm to retrieve aerosol properties, such as aerosol optical thickness, single-scattering albedo, and Ångström exponent for various satellite sensors over land and ocean. The three main features of this algorithm are: (1) automatic selection of the optimum channels for aerosol retrieval by introducing a weight for each channel to the object function, (2) setting common candidate aerosol models over land and ocean, and (3) preparing lookup tables for every 1 nm in the range of 300 to 2500 nm in the wavelength and weighting the radiance using the response function for each sensor. This method was applied to the Advanced Himawari Imager (AHI) on board the Japan Meteorological Agency's geostationary satellite Himawari-8, and the results depicted a continuous estimate of aerosol optical thickness over land and ocean. Furthermore, the aerosol optical thickness estimated using our algorithm was generally consistent with the products of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET). In addition, we applied our algorithm to MODIS on board the Aqua satellite and compared the retrieval results to the results obtained from AHI. The comparisons of the aerosol optical thickness, retrieved from different sensors with the different viewing angles onboard the geostationary and polar-orbiting satellites, suggest an underestimation of aerosol optical thickness at the backscattering direction (or overestimated in other directions). The retrieval of aerosol properties using a common algorithm allows in identifying a weakness in the algorithm, such as the assumptions in the aerosol model (e.g., sphericity or size distribution).

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© 2018 The Author(s) CC-BY 4.0 (Before 2018: Copyright © Meteorological Society of Japan)
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