Steady crevasse location in Pâkitsoq, Greenland over one decade: Results from MimiNet, a new deep-learning model for crevasse detection

Naureen Khan , Kristin Poinar , Jason P. Briner, Sophie Nowicki, Jessica Mejia , Mary Verne

If crevasse fields deliver meltwater to the bed of the Greenland Ice Sheet, it would affect seasonal ice flow speeds and total mass balance. The best current automated tool to map crevasse fields extends only a few dozen kilometers inland. To address this gap, we develop MimiNet, a neural-network-based tool that identifies surface crevasse fields. We train MimiNet on Sentinel-1 scenes across a 629 km² area in Pâkitsoq, central-western Greenland, and use it to locate crevasse fields annually over 2015–2024. We find that the crevassed area varied from a minimum of 106±5 km² in 2019 to a maximum of 144±6 km² in 2016, with no overall trend over the ten-year study period. We find some evidence that seasonal ice velocity anomalies in crevasse fields are higher than those in moulin-drained areas in the late melt season. This may suggest that the subglacial drainage system under crevasse fields remains inefficient all summer, and thus that at least some Pâkitsoq crevasse fields deliver meltwater to the bed. Interannual variability in ice dynamics may drive the observed variability in crevassed areas; we expect crevasse extent to become more variable in time as ice flow speeds, and their variations, amplify under climate change