A Frontal Ablation Dataset for 49 Tidewater Glaciers in Greenland.

Frontal ablation at tidewater glaciers, which comprises iceberg calving, submarine and subaerial melting, is a key boundary condition for numerical ice sheet models but remains difficult to measure directly in-situ. Many previous studies have quantified frontal ablation over varying spatio-temporal scales, however most use ice discharge as an approximation for frontal ablation, thereby neglecting the influence of terminus location change. Frontal ablation estimates that do account for terminus location change are spatio-temporally limited by the availability of observational data. Here, we present a processing chain to quantify frontal ablation using open-source observational data. We apply the processing chain to 49 tidewater glaciers in Greenland with reliable near-terminus bathymetry data in the BedMachine V4 dataset. Nearterminus volume change over the time period 1987 - 2020 is determined using a previously published dataset of terminus positions (TermPicks), ice thicknesses from ArcticDEM and AeroDEM, adjusted for surface elevation change over time, and bathymetry data from BedMachine v4. Assuming a vertical terminus geometry and uniform ice density, we estimate frontal ablation as the difference between mass flux towards the terminus (Mankoff et al., 2020) and mass change between consecutive observation. The frontal ablation dataset offers exciting opportunities for developing new insights into ice dynamics, including helping to improve numerical model hindcasting and projections. Lastly, we provide a processing chain that may serve as a community standard for determining frontal ablation from observational data for any tidewater glacier. [ABSTRACT FROM AUTHOR]