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.

中文翻译：

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湍流边界层流动大涡模拟的振动方程数据同化方法开发

为了提高模拟精度，有效的是使用数据同化技术，该技术能够通过将观察数据合并到模拟模型中来再现更逼真的模拟状态。数据同化技术中最简单的一种是牛顿松弛型微调方法，该方法已广泛用于中尺度气象模型中。在这项研究中，我们提出了一种使用振动方程的数据同化方法，该方法可以将湍流向目标平均风合并，同时保持小范围的湍流波动，这是不同于常规微调方法的一种方法。首先，我们进行了测试模拟，其中在基本湍流边界层（TBL）流向目标层的过程中采用了裸结法。结果表明，当在振动方程中规定固有频率小于TBL流的频谱峰值频率时，基本的TBL流可以合理地向目标微移，同时保持湍流的波动。然后，我们通过结合从实际京都市内的气象观测获得的数据来应用所建议的微调方法。平均风速剖面被合理地推向目标观测剖面，并且湍流统计也得到有利地保持。结论是，使用振动方程的数据同化方法成功地向目标平均风微移，同时很好地保持了小范围的湍流波动。