日本地球惑星科学連合2025年大会

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[J] 口頭発表

セッション記号 M (領域外・複数領域) » M-IS ジョイント

[M-IS16] 地球流体力学:地球惑星現象への分野横断的アプローチ

2025年5月25日(日) 13:45 〜 15:15 101 (幕張メッセ国際会議場)

コンビーナ:伊賀 啓太(東京大学大気海洋研究所)、吉田 茂生(九州大学大学院理学研究院地球惑星科学部門)、柳澤 孝寿(国立研究開発法人海洋研究開発機構 海域地震火山部門)、相木 秀則(名古屋大学)、座長:伊賀 啓太(東京大学大気海洋研究所)

13:45 〜 14:00

[MIS16-01] ラグランジュ粒子のデータ同化に基づく熱対流の再構成と予測

*中尾 篤史1,2能登 大輔3柳澤 孝寿2,4田坂 裕司2,4桑谷 立2 (1.秋田大学大学院理工学研究科、2.海洋研究開発機構海域地震火山部門、3.ペンシルベニア大学地球環境科学専攻、4.北海道大学大学院工学研究院)

キーワード:アジョイント法、マーカインセル法、レイリーべナール対流、逆問題

Lagrangian particles passively following fluid motions often record information about the surrounding flow, e.g. volcanic ash distributions reflect eruption intensity and wind speed, and metamorphic rocks contain flow processes of the surrounding mantle. In this study, we demonstrate the effectiveness of data assimilation in exploiting such particle-recorded information by applying it to particle images obtained from a laboratory experiment. Long-term particle trajectories were obtained from video recordings of Rayleigh-Bénard convection in a high-viscosity fluid containing tracer particles in a thin rectangular water tank. We developed four-dimensional variational data assimilation (4D-Var) for a marker and cell system and applied it to the particle trajectory data to reconstruct the thermal convection. As a result, we successfully estimated the temperature, velocity, particle trajectories, and Rayleigh number with high accuracy. Furthermore, the obtained solution was able to predict the fluid behavior beyond the assimilation time window. These results suggest that 4D-Var data assimilation can be used not only to reconstruct past processes and estimate system parameters, but also to predict future states in the absence of direct observational data.