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Large-Eddy Simulation of Stratified Turbulence. Part II: Application of the Stretched-Vortex Model to the Atmospheric Boundary Layer

机译:分层湍流的大涡模拟。第二部分:伸展涡模型在大气边界层的应用

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摘要

The buoyancy-adjusted stretched-vortex subgrid-scale (SGS) model is assessed for a number of large-eddy simulations (LESs) corresponding to diverse atmospheric boundary layer conditions. The cases considered are free convection, a moderately stable boundary layer [first Global Energy and Water Exchanges (GEWEX) Atmospheric Boundary Layer Study (GABLS)] case, shallow cumulus [Barbados Oceanographic and Meteorological Experiment (BOMEX)], shallow precipitating cumulus [Rain in Cumulus over the Ocean (RICO)] and nocturnal stratocumulus [Second Dynamics and Chemistry of the Marine Stratocumulus (DYCOMS-II) field study RF01]. An identical LES setup, including advection discretization and SGS model parameters, is used for all cases, which is a stringent test on the ability of LES to accurately capture diverse conditions without any flow-adjustable parameters. The LES predictions agree well with observations and previously reported model results. A grid-resolution convergence study is carried out, and for all cases the mean profiles exhibit good grid-resolution independence, even for resolutions that are typically considered coarse. Second-order statistics, for example, variances, converge at finer resolutions compared to domain means. The simulations show that 90% of the turbulent kinetic energy (at each level) must be resolved to obtain sufficiently converged mean profiles. This empirical convergence criterion can be used as a guide in designing future LES runs.
机译:评估了浮力调整后的拉伸涡流子网格规模(SGS)模型,以获取与各种大气边界层条件相对应的许多大涡模拟(LES)。所考虑的案例是自由对流,边界层中等稳定的[第一次全球能源和水交换(GEWEX)大气边界层研究(GABLS)]案例,浅积云[巴巴多斯海洋和气象实验(BOMEX)],浅降水积云[雨在海洋积云(RICO)]和夜间平积云中[海洋层积云的第二动力学和化学(DYCOMS-II)现场研究RF01]。所有情况下均使用相同的LES设置,包括对流离散化和SGS模型参数,这是对LES准确捕获各种条件而无需任何流量可调参数的能力的严格测试。 LES的预测与观测值和先前报告的模型结果非常吻合。进行了网格分辨率收敛研究,并且在所有情况下,即使对于通常认为较粗糙的分辨率,均值剖面也显示出良好的网格分辨率独立性。相较于域均值,二阶统计量(例如方差)以更高的分辨率收敛。仿真表明,必须解析90%的湍动能(在每个水平上)以获得足够收敛的平均轮廓。此经验收敛准则可作为设计未来LES运行的指南。

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