Physics-Informed Machine Learning On Polar Ice: A Survey

arXiv:2404.19536v1 Announce Type: new
Abstract: The mass loss of the polar ice sheets contributes considerably to ongoing sea-level rise and changing ocean circulation, leading to coastal flooding and risking the homes and livelihoods of tens of millions of people globally. To address the complex problem of ice behavior, physical models and data-driven models have been proposed in the literature. Although traditional physical models can guarantee physically meaningful results, they have limitations in producing high-resolution results. On the other hand, data-driven …

abstract arxiv behavior cs.lg data data-driven flooding homes ice loss machine machine learning ocean people physics physics-informed polar survey type