Particle filter for Large-eddy Simulations of turbulent boundary-layer flow generation based on observations

Onodera, Naoyuki   ; Idomura, Yasuhiro   ; Hasegawa, Yuta   ; Nakayama, Hiromasa   ; Shimokawabe, Takashi*; Aoki, Takayuki*

This paper presents a novel data assimilation method in realistic turbulent boundary layer simulations for the realization of a wind digital twin. We have developed a plume dispersion simulation code named CityLBM based on a lattice Boltzmann method. CityLBM enables a real time ensemble simulation for several km square area by applying locally mesh-refinement method on GPU supercomputers. Mesoscale wind boundary conditions produced by a Weather Research and Forecasting Model are given as boundary conditions in CityLBM by using a nudging data assimilation method. In this study, we propose a dynamic nudging data assimilation method, where a particle filter optimizes the nudging coefficient based on the observation data. This approach gave reasonable agreements in vertical profiles of the wind speed, the wind direction, and the turbulent intensity compared to the observation data throughout the day, and enabled all-day simulations, where atmospheric conditions change significantly.