Multi-Year Glaciological and Meteorological Observations on Debris-Covered Kennicott Glacier, Alaska, 2016–2023

Abstract

Despite increasing availability of satellite-derived products, in situ glacier observations are pivotal to accurately monitor glacier change and to calibrate and validate glacier models. However, comprehensive multi-variable field observations are especially rare on large glaciers and on debris-covered glaciers. Here we present extensive field observations from Kennicott Glacier, a heavily debris-covered glacier in central Alaska covering more than 400 km². The multi-year data set includes point glacier mass balances, meteorological data from several weather stations on and off the glacier, debris thickness and temperature, ice cliff back wasting derived from time-lapse photography of horizontal stakes drilled into several cliffs, and bathymetry, water temperature, and water level of proglacial and supraglacial lakes. Cumulated summer melt of more than 8 m was observed at the lowest clean-ice sites. Melt rates over clean ice correlate well with elevation, while the rates over debris-covered ice lack any strong elevation dependence. Melt rates drop exponentially with increasing debris thickness and tend to be much lower than for clean ice at similar elevations. Melt rates determined for ice cliffs in areas of otherwise continuous debris cover were up to 10× those for debris-covered ice, and even exceeded standard clean ice melt rates. Debris-cover thickness measurements at 150 sites vary from < 1 to 69 cm with an average of 17 ± 11 cm (±standard deviation). Debris thickens down-glacier, but with high spatial variability–thickness was observed to vary by tens of cm within a ~15 m radius. Depth-averaged thermal heat conductivity derived from supraglacial debris temperature profiles at 12 sites ranges from 0.53 to 1.86 W m⁻¹ K⁻¹. Interconnected proglacial lakes covered 1.61 km² in 2018 with observed water depths of more than 60 m in the two largest lakes. The dataset can be downloaded at https://doi.org/10.5281/zenodo.14625691 (Petersen, Hock, Loso, Guo, et al., 2024) and will be useful for glaciological and glacier meteorological studies.