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The Ising model for melt ponds: new features and applications

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SIPW05 - SIP Follow on: Mathematics of sea ice in the twenty-first century

In order to help develop a predictive theoretical approach to studying melting sea ice, Ma et al., 2019 introduced a two-dimensional random field Ising model which accounts for only the most basic physics in the system. The ponds are identified as metastable states in the model, where the binary spin variable corresponds to the presence of meltwater or ice on the sea ice surface. In this talk, I will discuss the new dynamic features of such an Ising-type model and their possible applications. I will also present a new machine learning architecture (MeltPondNet) for sea ice image segmentation that might be useful for the parametrization of melt pond models. 

This talk is part of the Isaac Newton Institute Seminar Series series.

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