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：海冰深刻影响着极地环境与全球气候。传统上，海冰在欧拉坐标下被建模为连续介质，以描述其大尺度特征（例如使用粘塑性流变学）。近年来，拉格朗日粒子模型（即离散元方法（DEM）模型）被用于表征尺度在10公里及以下的海冰碎片（称为浮冰）的运动，尤其是在边缘冰区。本文发展了一种耦合粒子系统与连续介质系统的多尺度模型，以有效表征海冰在不同尺度上的动力学和统计特征。该多尺度模型利用玻尔兹曼型系统将粒子运动与连续介质方程联系起来。对于小尺度动力学，它描述每个海冰浮冰的运动；作为大尺度连续介质分量，则处理质量密度、线速度与角速度的统计矩。这些统计量的演化影响单个浮冰的运动，同时浮冰运动提供整体反馈以调整大尺度动力学。值得注意的是，表征海冰浮冰的粒子模型采用局部化且完全并行化的框架（有时称为超参数化），显著提高了计算效率。数值算例验证了该多尺度模型的有效性能。此外，研究表明该多尺度模型对真实模型具有线性阶近似。