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Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Asahi, Yuichi; Inagaki, Atsushi*; Shimose, Kenichi*; Hirano, Kohin*
Keisan Kogaku Koenkai Rombunshu (CD-ROM), 28, 4 Pages, 2023/05
We have developed a multi-scale wind simulation code named CityLBM that can resolve entire cities to detailed streets. CityLBM enables a real time ensemble simulation for several km square area by applying the locally mesh-refined lattice Boltzmann method on GPU supercomputers. On the other hand, real-world wind simulations contain complex boundary conditions that cannot be modeled, so data assimilation techniques are needed to reflect observed data in the simulation. This study proposes an optimization method for ground surface temperature bias based on an ensemble Kalman filter to reproduce wind conditions within urban city blocks. As a verification of CityLBM, an Observing System Simulation Experiment (OSSE) is conducted for the central Tokyo area to estimate boundary conditions from observed near-surface temperature values.
Onodera, Naoyuki; Idomura, Yasuhiro; Hasegawa, Yuta; Asahi, Yuichi; Inagaki, Atsushi*; Shimose, Kenichi*; Hirano, Kohin*
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Our research group has been developing a multi-scale wind simulation code, CityLBM, which covers a wide area including the entire city as well as small alleys. CityLBM can perform real-time simulations by applying the AMR method and GPU acceleration to the lattice Boltzmann method. This study performed a meter-resolution simulation of the area around the Tokyo Institute of Technology. The simulation results were compared with the Doppler lidar observations, and it was confirmed that the simulation reproduced the wind conditions well, even under the conditions of large changes in the main wind direction during the day.
Onodera, Naoyuki; Hasegawa, Yuta; Idomura, Yasuhiro; Asahi, Yuichi; Kawamura, Takuma; Ina, Takuya; Shimomura, Kazuya; Inagaki, Atsushi*; Suzuki, Shinichi*; Hirano, Kohin*; et al.
no journal, ,
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.
Onodera, Naoyuki; Shimokawabe, Takashi*; Idomura, Yasuhiro; Kawamura, Takuma; Hasegawa, Yuta; Ina, Takuya; Inagaki, Atsushi*; Hirano, Kohin*; Shimose, Kenichi*; Oda, Ryoko*; et al.
no journal, ,
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 FY2023, a data assimilation method based on the Local Ensemble Transform Kalman Filter (LETKF) was applied to CityLBM in order to reproduce local wind conditions with high accuracy. We validated the data assimilation method for two-dimensional forced isotropic turbulence. It was confirmed that the LETKF with 64 ensembles provides the same levels of accuracy with 1/16th of the coarse observation points compared to the nudging method. In addition, it was confirmed that the application of LETKF can reproduce the phase of the Kalman vortex with high accuracy in the verification of the flow around a three-dimensional square cylinder.