Abstract Glaciers in Alaska contribute greatly to sea-level rise and are losing mass at a faster rate than any other region. Yet, our understanding of ongoing changes and ability to model them are hindered by a lack of observations, particularly at high spatiotemporal resolution. Here, we leverage Sentinel-1 synthetic aperture radar (SAR) data to produce temporally-varying glacier melt extents and snowlines from mid-2016 to 2024 for 99% of glaciers in Alaska greater than 2 km 2 . The melt extents are strongly correlated with temperatures, revealing that each 1°C increase in summer temperature causes up to 3 additional weeks of glacier melt. The high spatiotemporal resolution also captures subseasonal changes such as the 2019 heat wave, which caused subregional snowlines to retreat up to 105 m higher and exposed up to 28% more of the underlying glacier compared to typical years. Our snowlines agree well with optical datasets (r 2 up to 0.94), thus providing unprecedented reliable data unencumbered by clouds or lighting conditions. Moving forward, our automated, open-source workflow can easily be applied to other regions. These data also present unique opportunities to calibrate and validate large-scale glacier evolution models, a critical step for improving projections of glacier changes and their impacts.
Wells et al. (Wed,) studied this question.