Environmental Science and Engineering Seminar

One of the biggest uncertainties in sea-level rise projections arises from our incomplete understanding of the dynamics of the ice sheet in a warming climate. In this talk, I will discuss two poorly understood aspects of ice dynamics. The first concerns how the melting of ice surfaces triggers ice-shelf collapse through "hydrofracture", which led to the catastrophic disintegration of the Larsen B Ice Shelf. I will discuss how combining physics-based models and deep learning can yield physical insights into the stability of ice shelves and the vulnerability of mass loss of Antarctic ice sheets to atmospheric warming. In the second part of the talk, I will discuss the inversion of the poorly-constrained flow law of glacial ice using physics-informed deep learning and remote-sensing observations. The flow law of ice, i.e., ice rheology, directly governs the dynamics of ice shelves but is challenging, if not impossible, to directly measure in the field. Here, with a data-driven approach, we identify flow laws that differ from those previously assumed in ice-sheet models. Our results suggest the need to reassess the impact of ice flow law on the future projection of sea-level rise.