Special Session 113: Recent Advances in Uncertainty Quantification and Scientific Machine Learning with Applications to Complex Dynamical Systems

Multiscale Modelling and Data Assimilation for Sea Ice Dynamics
Quanling Deng
Yau Mathematical Sciences Center
Peoples Rep of China
Co-Author(s):    
Abstract:
Sea ice dynamics involve complex interactions across a wide range of scales, from individual floe collisions to large-scale coupled behaviour with the ocean and atmosphere. This talk presents a multiscale perspective on sea ice modelling and data assimilation, with an emphasis on connecting discrete floe-level dynamics to continuum descriptions suitable for larger-scale prediction and the corresponding sea ice rheology. After a brief introduction to the main features of sea ice and a short overview of major continuum approaches, I will introduce a multiscale modelling framework for sea ice floes and discuss how it captures essential physical mechanisms across scales. Building on this framework, I will then present a multiscale data assimilation approach designed to combine Lagrangian and Eulerian observational data in a coherent and flexible way. The talk will conclude with a brief discussion of ongoing efforts to incorporate machine learning tools into the assimilation pipeline, with the goal of improving predictive accuracy, robustness, and computational efficiency in sea ice modelling.