Von Mises Stress a Robust Predictor of Ice Slab Fracture in Greenland

Fractures in Greenland’s ice slabs provide englacial drainage pathways that initially reduce surface runoff but may eventually form surface-to-bed connections that cause high-elevation hydrodynamic coupling. As a result, characterizing the large-scale spatial patterns of surface fracture in ice slabs is important for assessing the current and future mass balance of the Greenland Ice Sheet. Unfortunately, these crevasses are mostly too narrow to be directly observed with remote sensing systems that provide consistent pan-Greenland coverage. Here, we integrate the respective strengths of remote sensing and fracture mechanics with statistical methods to overcome this challenge. We use ice sheet surface velocities derived from satellite remote sensing to calculate the stresses at the ice sheet surface. We then use sparse but high-fidelity observations of ice slab fractures from WorldView imagery to train a logistic regression model to predict fracture likelihood based the von Mises stress. We use a model ensemble approach to both optimize our calculation of the surface stresses and to account for uncertainty in the stress state due to velocity measurement error and ice viscosity uncertainty. Our regionally cross-validated model achieves an F1 score of 0.83+/-0.05, demonstrating that the von Mises stress can robustly predict spatial patterns of crevassing in Greenland's ice slabs. Across the Greenland Ice Sheet, we predict that 41% of the ice slab area is fractured, with most crevasses fields forming in marine-terminating sectors. This result suggests that (1) englacial storage is likely a significant component of mass balance in many ice slab regions and (2) that the interplay between melt-modulated basal sliding and oceanic terminus forcing may be key to the future evolution of Greenland's marine-terminating outlet glaciers as englacial drainage expands to higher elevations.