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Koshimizu, Masanori*; Onodera, Kazuya*; Nishikido, Fumihiko*; Haruki, Rie; Shibuya, Kengo*; Kishimoto, Shunji*; Asai, Keisuke*
Journal of Applied Physics, 111(2), p.024906_1 - 024906_5, 2012/01
Times Cited Count:29 Percentile:74.79(Physics, Applied)Onodera, Osamu*; Iguchi, Masahide*; Saito, Masakatsu*; Hamada, Kazuya; Nakajima, Hideo; Okuno, Kiyoshi; Sugimoto, Makoto; Nakahira, Masataka; Kitamura, Kazunori; Takayanagi, Tadatoshi*; et al.
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no abstracts in English
Onodera, Naoyuki; Hasegawa, Yuta; Idomura, Yasuhiro; Asahi, Yuichi; Kawamura, Takuma; Ina, Takuya; Shimomura, Kazuya; Inagaki, Atsushi*; Suzuki, Shinichi*; Hirano, Kohin*; et al.
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Wind prediction based on digital twin is a promising technology that can contribute to the construction of new social infrastructures, including applications to smart city design and operation. In this poster presentation, we will introduce wind simulations based on data assimilation with observations and mesoscale meteorological data for the realization of a digital twin of wind conditions in urban areas.
Onodera, Naoyuki; Shimokawabe, Takashi*; Idomura, Yasuhiro; Kawamura, Takuma; Asahi, Yuichi; Hasegawa, Yuta; Ina, Takuya; Shimomura, Kazuya; Inagaki, Atsushi*; Hirano, Kohin*; et al.
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The project goal is to realize real-time wind prediction in urban areas by assimilating observed data into real-time wind simulations on GPU supercomputers. In FY2022, the first year of the project, we developed a dynamic optimization method for model variables by applying a particle filter (PF) based data assimilation method to reproduce wind conditions in the atmospheric boundary layer with high accuracy. The numerical simulations for the field experiment in Oklahoma City showed improvements of about 10 % for the standard deviation error of the all-day velocity compared to the results without the application of PF. In addition, a multi-scale analysis based on boundary conditions given by a geographic information system (GIS) and a cloud-resolving numerical model (CReSS) was realized for the Tokyo metropolitan area.