Simultaneous data assimilation of wind velocities and tracer concentrations for plume advection simulation

2021 Fiscal Year Final Research Report

• Project/Area Number: 17K00533
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Environmental dynamic analysis
• Research Institution: Japan, Meteorological Research Institute
• Principal Investigator: SEKIYAMA Tsuyoshi 気象庁気象研究所, 全球大気海洋研究部, 主任研究官 (90354498)
• Project Period (FY): 2017-04-01 – 2022-03-31
• Keywords: データ同化 / 数値シミュレーション / 気象学 / 大気化学

Outline of Final Research Achievements

We aimed to develop a technique called "variable-localized data assimilation" for inverse estimation of the wind velocity distribution, which caused the radiocesium dispersion, from the distribution of radiocesium concentration. Although the inverse estimation of the wind velocity distribution was not successful, we found that the accuracy of concentration distribution analyses was significantly improved by simultaneously assimilating wind velocity and concentration observation data using variable localization. In addition, since it was urgently needed to improve the accuracy of advection-diffusion simulations for the data assimilation calculations in this study, we obtained a side benefit, in which the development of an advection-diffusion model was unexpectedly progressed.

Free Research Field

気象学

Academic Significance and Societal Importance of the Research Achievements

大気汚染物質の濃度情報によって風速分布の推定精度を上げる技術は開発半ばとなったが、データ同化における変数局所化技術の有用性を示すことはできた。この変数局所化技術は気象庁などでの天気予報の基盤技術開発にも有用であろう。また、本研究では変数局所化データ同化によって大気汚染濃度分布の推定精度を大きく上げることに成功した。これは放射性セシウム以外の大気汚染予測サービス（黄砂や光化学スモッグなどの予報）の品質向上にも繋がる貴重な知見である。