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非平衡地球物理流的随机亚网格尺度建模。

Stochastic subgrid-scale modelling for non-equilibrium geophysical flows.

机构信息

Centre for Australian Weather and Climate Research, Bureau of Meteorology, Melbourne, Australia.

出版信息

Philos Trans A Math Phys Eng Sci. 2010 Jan 13;368(1910):145-60. doi: 10.1098/rsta.2009.0192.

Abstract

Methods motivated by non-equilibrium statistical mechanics of turbulence are applied to solve an important practical problem in geophysical fluid dynamics, namely the parametrization of subgrid-scale eddies needed in large-eddy simulations (LESs). A direct stochastic modelling scheme that is closely related to techniques based on statistical closure theories, but which is more generally applicable to complex models, is employed. Here, we parametrize the effects of baroclinically unstable subgrid-scale eddies in idealized flows with broad similarities to the Antarctic Circumpolar Current of the Southern Ocean. The subgrid model represents the effects of the unresolved eddies through a generalized Langevin equation. The subgrid dissipation and stochastic forcing covariance matrices as well as the mean subgrid forcing required by the LES model are obtained from the statistics of a high resolution direct numerical simulation (DNS). We show that employing these parametrizations leads to LES in close agreement with DNS.

摘要

基于非平衡统计力学的方法被应用于解决地球流体动力学中的一个重要实际问题,即大涡模拟(LES)中所需的次网格尺度涡旋的参数化。采用了一种与基于统计闭值理论的技术密切相关但更适用于复杂模型的直接随机建模方案。在这里,我们对具有与南大洋南极环极流广泛相似的理想流中的斜压不稳定次网格尺度涡旋的影响进行参数化。次网格模型通过广义朗之万方程来表示未解析的涡旋的影响。次网格耗散和随机强迫协方差矩阵以及 LES 模型所需的平均次网格强迫是从高分辨率直接数值模拟(DNS)的统计数据中得到的。我们表明,采用这些参数化方法可以得到与 DNS 非常吻合的 LES。

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