Geology topics
Publications and source records attributed to Louis Sass.
Glaciers lost 408 ± 132 Gt of mass during the hydrological year 2025, equivalent to 1.1 ± 0.4 mm sea-level rise. Since 1975, glacier mass loss has totalled 9,583 ± 1,211 Gt, equivalent to 26.4 ± 3.3 mm of sea-level rise, with six of the highest mass-loss years on record occurring in the past seven years.
Glacier energy-balance models offer mechanistic insights into glacier mass balance under a changing climate, yet their considerable data requirements hinder large-scale applications. Here we present the open-source Python Energy Balance model for Snow and Ice (PEBSI), which includes physically based albedo evolution using the Snow, Ice and Aerosol Radiative (SNICAR) model. PEBSI is calibrated and validated using robust in situ data from Gulkana Glacier, Alaska from 2000 to 2024. Simulations forced with original and bias-corrected climate reanalysis data show that statistically downscaling reanalysis data with in situ observations is necessary to reproduce summer mass balance (mean absolute error [MAE] = 0.75 m w.e. vs 0.22 m w.e., respectively). A grid search across two parameters, a precipitation factor and a densification parameter, reveals tradeoffs in performance compared to seasonal mass balance and end-of-winter snow density and depth. No single combination of parameters minimizes all errors, underscoring the inherent overparameterization of energy-balance models and challenges with translating coarse climate data to the glacier scale. The calibrated model successfully simulates the 2024 melt season, agreeing with surface-height change (MAE = 0.48 m) and albedo (MAE = 0.066) observations. Moving forward, PEBSI provides unique opportunities to quantify albedo feedbacks and their impact on present and future glacier mass loss.
Alaska's glaciers are losing mass at the fastest rate of any region globally, significantly affecting both the volume and distribution of water across the landscape. Though glaciers in the Alaska region (as defined by glaciologists this includes both Alaska and portions of adjacent Canada) range from sea level to nearly 6200 m (20,320 ft), the majority of glacier area in the Alaska region is concentrated between 900 and 2100 m (2950 to 6890 ft). Long term glacier monitoring in Alaska by the U.S. Geological Survey (USGS) Benchmark Glacier Project is on moderate-sized glaciers with distributions of glacier area in this elevation range. These are some of the longest in-situ records of glacier mass change in the world. The process-based understanding of glacier change on those “Benchmark Glaciers” is robust, but it is limited to the range of conditions present on those particular glaciers—at moderate elevations—where large amounts of melt water and rain pass through the glacier and into the downstream ecosystem on an annual basis.
There is significant uncertainty regarding the spatiotemporal distribution of seasonal snow on glaciers, despite being a fundamental component of glacier mass balance. To address this knowledge gap, we collected repeat, spatially extensive high-frequency ground-penetrating radar (GPR) observations on two glaciers in Alaska for five consecutive years. GPR measurements showed steep snow water equivalent (SWE) elevation gradients at both sites; continental Gulkana Glacier’s SWE gradient averaged 115 mm 100 m–1 and maritime Wolverine Glacier’s gradient averaged 440 mm 100 m–1 (over >1000 m). We extrapolated GPR point observations across the glacier surface using terrain parameters derived from digital elevation models as predictor variables in two statistical models (stepwise multivariable linear regression and regression trees). Elevation and proxies for wind redistribution had the greatest explanatory power, and exhibited relatively time-constant coefficients over the study period. Both statistical models yielded comparable estimates of glacier-wide average SWE (1 % average difference at Gulkana, 4 % average difference at Wolverine), although the spatial distributions produced by the models diverged in unsampled regions of the glacier, particularly at Wolverine. In total, six different methods for estimating the glacier-wide average agreed within ± 11 %. We assessed interannual variability in the spatial pattern of snow accumulation predicted by the statistical models using two quantitative metrics. Both glaciers exhibited a high degree of temporal stability, with ~85 % of the glacier area experiencing less than 25 % normalized absolute variability over this five-year interval. We found SWE at a sparse network (3 stakes per glacier) of long-term glaciological stake sites to be highly correlated with the GPR-derived glacier-wide average. We estimate that interannual variability in the spatial pattern of SWE is only a small component (4–10 % of glacier-wide average) of the total mass balance uncertainty and thus, our findings support the concept that sparse stake networks effectively measure interannual variability in winter balance on glaciers, rather than some spatially varying pattern of snow accumulation.