Sea ice profoundly influences the polar environment and the global climate. Traditionally, Sea ice has been modeled as a continuum under Eulerian coordinates to describe its large-scale features, using, for instance, viscous-plastic rheology. Recently, Lagrangian particle models, also known as the discrete element method (DEM) models, have been utilized for characterizing the motion of individual sea ice fragments (called floes) at scales of 10 km and smaller, especially in marginal ice zones. This paper develops a multiscale model that couples the particle and the continuum systems to facilitate an effective representation of the dynamical and statistical features of sea ice across different scales. The multiscale model exploits a Boltzmann-type system that links the particle movement with the continuum equations. For the small-scale dynamics, it describes the motion of each sea ice floe. Then, as the large-scale continuum component, it treats the statistical moments of mass density and linear and angular velocities. The evolution of these statistics affects the motion of individual floes, which in turn provides bulk feedback that adjusts the large-scale dynamics. Notably, the particle model characterizing the sea ice floes is localized and fully parallelized, in a framework that is sometimes called superparameterization, which significantly improves computation efficiency. Numerical examples demonstrate the effective performance of the multiscale model. Additionally, the study demonstrates that the multiscale model has a linear-order approximation to the truth model.
翻译:海冰深刻地影响着极地环境和全球气候。传统上,海冰被建模为连续介质,使用粘塑性流变学等欧拉坐标描述其大尺度特征。最近,拉格朗日粒子模型,也称为离散元素法(DEM)模型,已被用于在小于10公里的尺度范围内表征单个海冰碎片(称为块)的运动,特别是在边缘冰区。本文开发了一种多尺度模型,将粒子和连续介质系统相结合,以有效地表示海冰在不同尺度下的动态和统计特征。多尺度模型利用类似玻尔兹曼的系统,将粒子运动与连续介质方程联系在一起。对于小尺度动力学,它描述了每个海冰块的运动。然后,作为大尺度连续介质部分,它处理了质量密度、线性和角速度的统计矩。这些统计量的演化影响了单个块的运动,从而提供了调整大尺度动力学的群体反馈。值得注意的是,描述海冰块的粒子模型是本地化和完全并行化的,在一个被称为超参数化的框架中,这显著提高了计算效率。数值例子证明了多尺度模型的有效性。此外,研究证明了多尺度模型对真实模型具有线性级别的近似。