In order to improve the simulation accuracy, it is effective to use a data assimilation technique which is capable of reproducing more realistic simulated states by incorporating observational data into simulation models. One of the simplest ones among data assimilation techniques is a Newtonian relaxation‐type nudging method which has been widely used in mesoscale meteorological models. In this study, we proposed a data assimilation method using a vibration equation which can incorporate turbulence winds toward target mean winds while maintaining small‐scale turbulent fluctuations as a different approach from the conventional nudging method. First, we conducted test simulations in which nudging is applied in a basic turbulent boundary layer (TBL) flow toward a target one. It is shown that the basic TBL flow can be reasonably nudged toward the target one while maintaining the turbulent fluctuations well when prescribing the natural frequency in the vibration equation smaller than the spectral peak frequency in the TBL flow. Then, we applied the proposed nudging method by incorporating data obtained from meteorological observations located in the actual city of Kyoto. The mean wind velocity profiles were reasonably nudged toward the target observed profile and the turbulence statistics were also favorably maintained. It is concluded that the data assimilation method using the vibration equation successfully nudges toward the target mean winds while maintaining small‐scale turbulent fluctuations well. Plain Language Summary In order to improve the simulation accuracy, it is effective to use a data assimilation technique which is capable of reproducing more realistic simulated states by incorporating observational data into simulation models. Since the observational data assimilated are normally averaged in time and/or in space by filtering out small‐scale turbulent fluctuations, the conventional data assimilation method is not suitable for large‐eddy simulations of unsteady turbulent flows. In this study, we proposed a data assimilation method using a vibration equation which can nudge turbulence winds toward target mean winds while maintaining small‐scale turbulent fluctuations. It was shown that our proposed method is capable of both nudging the flow fields toward a target state and retaining the fluctuating nature of turbulent flows. The data assimilation method using a vibration equation is suitable for LES models and has a high potential to practically reproduce more realistic atmospheric state.
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