Multiscale eddy simulation for moist atmospheric convection: Preliminary investigation
Multiscale eddy simulation for moist atmospheric convection: Preliminary investigation
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湿大气对流的多尺度涡模拟：初步研究
DOI：
10.1016/j.jcp.2014.02.009
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
S. Stechmann
中科院分区：
文献类型：
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作者：
S. Stechmann
设计了一个模拟大气对流和云的多尺度计算框架。在这个多尺度框架中，大涡模拟（LES）用于模拟100 m及更大的粗尺度，随机一维湍流（ODT）模型用于代表100 m及更小的细尺度。这两个组件耦合在一起并共同发展，提供了多尺度涡模拟（MES）。通过其细尺度湍流和潮湿的热力学，MES允许粗网格单元是部分多云，并涵盖多云，清晰的空气混合的规模下降到1米，相反，在典型的LES这样的细尺度过程不表示或参数化使用批量确定性关闭。为了说明MES并研究其多尺度动力学，模拟了一个浅积云云场。细尺度的变化被认为是采取一个合理的形式，部分多云的网格细胞附近的云边缘和云顶突出。从早期的理论工作来看，这种多云和晴朗空气的混合被认为对浮力有重要影响。然而，相反的期望基于早期的理论研究，平均统计的散装云场基本上是相同的MES和LES，可能的原因进行了讨论，包括可能的局限性，在目前制定的MES。LES和MES之间的一个区别是在粗尺度湍流动能，这似乎是增长缓慢的时间，由于不连贯的随机波动的浮力。这一点和其他考虑表明，需要某种类型的空间和/或时间滤波，以衰减欠采样的随机精细尺度过程。
A multiscale computational framework is designed for simulating atmospheric convection and clouds. In this multiscale framework, large eddy simulation (LES) is used to model the coarse scales of 100 m and larger, and a stochastic, one-dimensional turbulence (ODT) model is used to represent the fine scales of 100 m and smaller. Coupled and evolving together, these two components provide a multiscale eddy simulation (MES). Through its fine-scale turbulence and moist thermodynamics, MES allows coarse grid cells to be partially cloudy and to encompass cloudy–clear air mixing on scales down to 1 m; in contrast, in typical LES such fine-scale processes are not represented or are parameterized using bulk deterministic closures. To illustrate MES and investigate its multiscale dynamics, a shallow cumulus cloud field is simulated. The fine-scale variability is seen to take a plausible form, with partially cloudy grid cells prominent near cloud edges and cloud top. From earlier theoretical work, this mixing of cloudy and clear air is believed to have an important impact on buoyancy. However, contrary to expectations based on earlier theoretical studies, the mean statistics of the bulk cloud field are essentially the same in MES and LES; possible reasons for this are discussed, including possible limitations in the present formulation of MES. One difference between LES and MES is seen in the coarse-scale turbulent kinetic energy, which appears to grow slowly in time due to incoherent stochastic fluctuations in the buoyancy. This and other considerations suggest the need for some type of spatial and/or temporal filtering to attenuate undersampling of the stochastic fine-scale processes.