Abstract A stochastic representation based on a physical transport principle is proposed to account for mesoscale eddy effects on the evolution of the large-scale flow. This framework arises from a decomposition of the Lagrangian velocity into a smooth (in time) component and a highly oscillating term. One important characteristic of this random model is that it conserves the energy of any transported scalar. Such an energy-preserving representation is tested for the coarse simulation of a barotropic circulation in a shallow ocean basin, driven by a symmetric double-gyres wind forcing. The empirical spatial correlation of the random small-scale velocity is estimated from data of an eddy-resolving simulation. After reaching a turbulent equilibrium state, a statistical analysis of tracers shows that the proposed random model enables us to reproduce accurately, on a coarse mesh, the local structures of the first four statistical moments (mean, variance, skewness and kurtosis) of the high-resolution eddy-resolved data.

中文翻译：

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粗分辨率正压模型中尺度涡效应的随机表示

摘要 提出了一种基于物理传输原理的随机表示来解释中尺度涡流对大尺度流动演化的影响。该框架源于将拉格朗日速度分解为平滑（时间）分量和高度振荡项。这种随机模型的一个重要特征是它保存了任何传输的标量的能量。在由对称双环流风力驱动的浅海盆地正压环流的粗略模拟中，对这种节能表示进行了测试。随机小尺度速度的经验空间相关性是从涡解析模拟的数据中估计出来的。达到湍流平衡状态后，