Journal of the Meteorological Society of Japan. Ser. II
Online ISSN : 2186-9057
Print ISSN : 0026-1165
Common Retrieval of Aerosol Properties for Imaging Satellite Sensors
Mayumi YOSHIDAMaki KIKUCHITakashi M. NAGAOHiroshi MURAKAMITomoyuki NOMAKIAkiko HIGURASHI
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JOURNALS FREE ACCESS Advance online publication

Article ID: 2018-039

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Abstract

 We develop a common retrieval algorithm of aerosol properties such as aerosol optical thickness, single-scattering albedo, and Ångström exponent for various satellite sensors over both land and ocean. The three main features of this algorithm are as follows: (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) preparation of lookup tables for every 1 nm in the range from 300 to 2500 nm of 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 an approximately continuous estimate of aerosol optical thickness over land and ocean. Further, the aerosol optical thickness estimated using our algorithm was generally consistent with the products from Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET). Additionally, we applied our algorithm to MODIS on board the Aqua satellite and then compared the retrieval results to those that were obtained using AHI. The comparisons of the aerosol optical thickness retrieved from different sensors with different viewing angles on board 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 us to identify a weakness in the algorithm, which includes the assumptions in the aerosol model (e.g. sphericity or size distiribution).

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