Mesoscale-to-microscale coupling (MMC) aims to address the limited scope of traditional large-eddy simulations by driving the microscale flow with information concerning large-scale weather patterns provided by mesoscale models. We present a new offline MMC technique for horizontally homogeneous microscale flow conditions, in which internal forcing terms are computed based on mesoscale time–height profiles of mean-flow quantities. The advantage of such an approach is that it can be used to drive a microscale simulation with either mesoscale or observational data, and that it does not rely on specific terms in the mesoscale budget equations, which are typically not part of the default output of a mesoscale solver. The performance of the proposed profile assimilation technique is assessed based on the simulation of a typical diurnal cycle over the Scaled Wind Farm Technology site in west Texas. Results indicate that simple data assimilation techniques lead to unphysically high levels of shear and turbulence caused by the algorithm’s inability to cope with inaccuracies in the mesoscale time–height profiles. Modifying the algorithm to account for vertical coherence in the mesoscale source terms gives the microscale solver a greater ability to correct the provided mesoscale time–height profiles, leading to improved predictions of shear and turbulence statistics. The resulting turbulence statistics are in good agreement with meteorological tower observations and simulation results obtained with state-of-the-art coupling techniques using mesoscale budget components.

中文翻译：

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大涡模拟时高剖面同化技术的发展

中尺度到微尺度耦合 (MMC) 旨在通过利用中尺度模型提供的有关大尺度天气模式的信息驱动微尺度流来解决传统大涡模拟的范围有限的问题。我们提出了一种新的离线 MMC 技术，用于水平均匀的微尺度流动条件，其中内部强迫项是根据平均流量的中尺度时间-高度剖面计算的。这种方法的优点是它可以用来驱动具有中尺度或观测数据的微尺度模拟，并且它不依赖中尺度预算方程中的特定项，这些项通常不是默认输出的一部分中尺度求解器。所提出的剖面同化技术的性能是根据德克萨斯州西部 Scaled Wind Farm Technology 站点上典型昼夜循环的模拟来评估的。结果表明，简单的数据同化技术会导致由于算法无法处理中尺度时间-高度剖面的不准确性而导致非物理高水平的剪切和湍流。修改算法以考虑中尺度源项中的垂直相干性，使微尺度求解器具有更大的能力来校正所提供的中尺度时间-高度剖面，从而改进对剪切和湍流统计的预测。