日本地球惑星科学連合2021年大会

講演情報

[E] ポスター発表

セッション記号 A (大気水圏科学) » A-CG 大気海洋・環境科学複合領域・一般

[A-CG36] 衛星による地球環境観測

2021年6月3日(木) 17:15 〜 18:30 Ch.06

コンビーナ:沖 理子(宇宙航空研究開発機構)、本多 嘉明(千葉大学環境リモートセンシング研究センター)、高薮 縁(東京大学 大気海洋研究所)、松永 恒雄(国立環境研究所地球環境研究センター/衛星観測センター)

17:15 〜 18:30

[ACG36-P11] Simultaneous retrieval of aerosols and ocean color parameters using GCOM-C/SGLI data

*関口 美保1、橋本 真喜子2、竹中 栄晶3、Shi Chong4、中島 映至4 (1.国立大学法人東京海洋大学学術研究院、2.JAXA/EORC、3.国立大学法人千葉大学、4.国立環境研究所)

キーワード:衛星観測、エアロゾル、海色

Atmospheric aerosols have a significant impact on the global climate through direct and indirect climate effects. Emissions of anthropogenic aerosols are said to be increasing year by year, and more accurate estimates are needed to suppress them. In remote sensing of land and ocean, aerosols are contaminants that cause serious errors, and it is important to remove them for better satellite analysis.

In this study, we performed an analysis of atmospheric aerosol by the new satellite analysis algorithm, the multi-wavelength multi-pixel method (MWP method)(Hashimoto and Nakajima, 2017), and an analysis of atmospheric aerosol and chlorophyll concentrations by the simultaneous method (Shi and Nakajima, 2017). The MWP method is a solution method in which observation values of multiple channels are used for multiple pixels at once, and the aerosol distribution is limited and derived to be smooth. The spatial distribution of the AOT obtained even in an urban area that is complicated in the horizontal direction, which is a superiority of this method. The simultaneous method is that enables simultaneous estimation by considering the radiative transfer process in the ocean under the conflicting situations where the effect of ocean color needs to be considered when analyzing aerosols, and aerosols need to be considered when analyzing ocean color. Both methods can estimate more parameters at once by using a large number of observation data at once. The problem of high computational cost has been overcome by using the Neural Network method (Takenaka et al., 2011) as the radiative transfer model.

In this presentation, we apply GCOM-C / SGLI observation data to these methods and show the results of atmospheric aerosols and ocean color analysis in the Ariake and Yellow Sea areas. Also, the validation results are shown with AERONET.