JpGU-AGU Joint Meeting 2020

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-AS 大気科学・気象学・大気環境

[A-AS11] Aerosol impacts on air quality, climate system, and our society

コンビーナ:安成 哲平(北海道大学 北極域研究センター)、Kyu-Myong Kim(NASA Goddard Space Flight Center)、Hongbin Yu(NASA Goddard Space Flight Center)、竹村 俊彦(九州大学応用力学研究所)

[AAS11-P11] GCOM-C SGLIエーロゾルプロダクトによるエーロゾルデータ同化実験

*田中 泰宙1弓本 桂也3,1吉田 真由美2村上 浩2永尾 隆4大方 めぐみ2 (1.気象庁気象研究所、2.宇宙航空研究開発機構、3.九州大学応用力学研究所、4.東京大学大気海洋研究所)

キーワード:エーロゾル、衛星観測、データ同化

The Global Change Observation Mission - Climate (GCOM-C) satellite was launched on 23 December 2017, for long-term environmental monitoring of the Earth. The GCOM-C satellite carries the second-generation global imager (SGLI), which is a multi-wavelength optical radiometer that has 19 observation wavelength bands from near-ultraviolet to thermal infrared and has characteristic functions such as polarization, multi-directional, and near-ultraviolet observation. SGLI observation data contributes to the improvement of the accuracy of the processes in climate models such as clouds, aerosols, sea colors, vegetation, and snow ice, and to be applied in various applications such as predictions of sand and dust storms, fishing ground, and understanding of red tide occurrence. JAXA Earth Observation Research Center (EORC) retrieves and provides quantitative information on atmospheric aerosols from SGLI data. The SGLI standard non-polarized aerosol product includes aerosol optical thickness (AOT), Angstrom exponent, and single scattered albedo on land are derived. JAXA EORC, Meteorological Research Institute of Japan Meteorological Agency (MRI/JMA), and Research Institute for Applied Mechanics (RIAM) of Kyushu University have been carrying joint research to utilize the geostationary and low-orbit satellites to monitor and predict the atmospheric aerosols, and to create an integrated aerosol product. MRI/JMA is currently developing a global aerosol prediction system that assimilates SGLI aerosol products using the global aerosol model MASINGAR. We will show the initial results of data assimilation experiments using two-dimensional variation (2D-Var) for the global aerosol model, and discuss the data verification, quality control, and the effects of the data assimilation.