Pervasive glacier retreats across Svalbard from 1985 to 2023.

A major uncertainty in predicting the behaviour of marine-terminating glaciers is ice dynamics driven by non-linear calving front retreat, which is poorly understood and modelled. Using 124919 calving front positions for 149 marine-terminating glaciers in Svalbard from 1985 to 2023, generated with deep learning, we identify pervasive calving front retreats for non-surging glaciers over the past 38 years. We observe widespread seasonal cycles in calving front position for over half of the glaciers.

Large-scale flood modeling and forecasting with FloodCast.

Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model parameters as well as incurring a high computational cost. This limits their ability to accurately forecast flood crests and issue time-critical hazard warnings. In this work, we build a fast, stable, accurate, resolution-invariant, and geometry-adaptive flood modeling and forecasting framework that can perform at large scales, namely FloodCast.