Japan Geoscience Union Meeting 2021

Presentation information

[E] Poster

A (Atmospheric and Hydrospheric Sciences ) » A-CG Complex & General

[A-CG36] Satellite Earth Environment Observation

Thu. Jun 3, 2021 5:15 PM - 6:30 PM Ch.06

convener:Riko Oki(Japan Aerospace Exploration Agency), Yoshiaki HONDA(Center for Environmental Remote Sensing, Chiba University), Yukari Takayabu(Atmosphere and Ocean Research Institute, the University of Tokyo), Tsuneo Matsunaga(Center for Global Environmental Research and Satellite Observation Center, National Institute for Environmental Studies)

5:15 PM - 6:30 PM

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

*Miho Sekiguchi1, Makiko Hashimoto2, Hideaki Takenaka3, Chong Shi4, Teruyuki Nakajima4 (1.Tokyo University of Marine Science and Technology, 2.Japan Aerospace Exploration Agency/Earth Observation Research Center, 3.Chiba University, 4.National Institute for Environmental Studies)

Keywords:Satellite observation, aerosol, ocean color

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.