Melt on Antarctic ice shelves: observing surface melt duration from microwave remote sensing and modeling the dynamical impacts of subshelf melting

Abstract

Melt on the surface and underside of Antarctic ice shelves are important to the mass balance and stability of the ice sheet, and therefore pose significance to global sea levels. Satellite-based passive microwave observations provide daily or near-daily coarse resolution surface observations from 1978 on, and we use this record to identify days in which melt water is present on the ice sheet and ice shelf surfaces, called melt days. There are significant differences in the results of melt detection methods however, and we evaluate four different passive microwave melt detection algorithms. There is a lack of sufficient ground truth observations, so we use Google Earth Engine to build time series of Sentinel-1 Synthetic Aperture Radar images from which we can also detect melt to serve as a comparison dataset. A melt detection method using a Kmeans clustering algorithm developed here is shown to be the most effective on ice shelves, so we further apply this method to quantify melt days across all Antarctica ice shelves for every year from 1979/80 to 2019/20. The highest sums of melt days occur on the Antarctic Peninsula at 89 melt days per year, and we find few linear trends in the annual melt days on ice shelves around the continent. The primary mode of spatial variability in the melt day dataset is closely related to the Southern Annular Mode, a climate index for the southward migration of Southern Westerly Winds, which has been increasing in recent decades. Positive Southern Annular Mode index values are associated with decreased melt days in some regions of Antarctica. We also present a novel application of passive microwave analysis to detect changes in firn structure due to unusually large melt events in some regions and we show how this method detects ice lens formation and grain growth on specific ice shelves. To study the impacts of subshelf melt we focus on the Filchner-Ronne region of Antarctica, which contains the second largest ice shelf on the continent. We performed an ensemble of ice sheet model runs for a set of ocean warming scenarios. Each ensemble used a realistic range of physical parameters to control ice dynamics and sliding, generated by a Bayesian analysis of a surrogate model and observed velocities. Increased ocean temperatures were associated with increased mass loss, and by the year 2100 this region contributed 14 mm to sea level per degree of ocean warming at depth between +0°C and +4°C of ocean potential temperature. Beyond +4°C, the rate mass loss increased substantially. This mass loss corresponded to grounding line retreat across the region.