Accurate knowledge of the ice thickness distribution and glacier bed topography is essential for predicting dynamic glacier changes and the future developments of downstream hydrology, which are impacting the energy sector, tourism industry and natural hazard management. Using AIR-ETH, a new helicopter-borne ground-penetrating radar (GPR) platform, we measured the ice thickness of all large and most medium-sized glaciers in the Swiss Alps during the years 2016–20. Most of these had either never or only partially been surveyed before. With this new dataset, 251 glaciers – making up 81% of the glacierized area – are now covered by GPR surveys. For obtaining a comprehensive estimate of the overall glacier ice volume, ice thickness distribution and glacier bed topography, we combined this large amount of data with two independent modeling algorithms. This resulted in new maps of the glacier bed topography with unprecedented accuracy. The total glacier volume in the Swiss Alps was determined to be 58.7 ± 2.5 km3 in the year 2016. By projecting these results based on mass-balance data, we estimated a total ice volume of 52.9 ± 2.7 km3 for the year 2020. Data and modeling results are accessible in the form of the SwissGlacierThickness-R2020 data package.
Abstract. Our changing climate is expected to affect ice core records as cold firn progressively transitions to a temperate state. Thus, there is a need to improve our understanding and to further develop quantitative process modeling, to better predict cold firn evolution under a range of climate scenarios. Here we present the application of a distributed, fully coupled energy balance model, to simulate cold firn at the high-alpine glaciated saddle of Colle Gnifetti (Swiss–Italian Alps) over the period 2003–2018. We force the model with high-resolution, long-term, and extensively quality-checked meteorological data measured in the closest vicinity of the firn site, at the highest automatic weather station in Europe (Capanna Margherita, 4560 m a.s.l.). The model incorporates the spatial variability of snow accumulation rates and is calibrated using several partly unpublished high-altitude measurements from the Monte Rosa area. The simulation reveals a very good overall agreement in the comparison with a large archive of firn temperature profiles. Our results show that surface melt over the glaciated saddle is increasing by 3–4 mm w.e. yr−2 depending on the location (29 %–36 % in 16 years), although with large inter-annual variability. Analysis of modeled melt indicates the frequent occurrence of small melt events (<4 mm w.e.), which collectively represent a significant fraction of the melt totals. Modeled firn warming rates at 20 m depth are relatively uniform above 4450 m a.s.l. (0.4–0.5 ∘C per decade). They become highly variable at lower elevations, with a marked dependence on surface aspect and absolute values up to 2.5 times the local rate of atmospheric warming. Our distributed simulation contributes to the understanding of the thermal regime and evolution of a prominent site for alpine ice cores and may support the planning of future core drilling efforts. Moreover, thanks to an extensive archive of measurements available for comparison, we also highlight the possibilities of model improvement most relevant to the investigation of future scenarios, such as the fixed-depth parametrized routine of deep preferential percolation.
The marginal areas of the Greenland ice sheet develop streams and lakes each summer, documenting that surface runoff of meltwater is a major component of ice-sheet mass balance. Here we map the slush limit, a proxy for the extent of surface runoff, using daily MODIS data for the years 2000–2021. We develop an automated algorithm capable of detecting daily slush limits, provided sufficient image quality. The algorithm is applied to the ice sheet's western flank (61.7 $^{\circ }$ N to 76.5 $^{\circ }$ N). We find significant increasing trends in maximum slush limits until the year 2012, but not thereafter. We show that the slush limit typically rises quickly early in the ablation season but stabilizes before melting ceases. The data provide evidence that upward migration of surface runoff in summer 2012 stopped early at the upper margin of the ice slabs. These thick and continuous ice layers are located close to the surface, in the firn, and impede percolation of melt into deeper pore space. Had the ice slabs extended higher, the summer 2012 provided sufficient energy to raise the slush limit by another $\sim$ 300 m in elevation.
Abstract. Our changing climate is expected to affect ice core records as cold firn progressively transitions to a temperate state. Thus there is a need to improve understanding and further develop quantitative process modeling, to better predict cold firn evolution under a range of climate scenarios. Here we present the application of a distributed, fully coupled energy balance model, to simulate high-alpine cold firn at Colle Gnifetti over the period 2003–2018. For the first time, we force such a model with high-resolution, long-term and extensively quality-checked meteorological data measured in closest vicinity of the firn site, at the Capanna Margherita (4560 m a.s.l.). The model incorporates the spatial variability of snow accumulation rates, and is calibrated using several, partly unpublished high-altitude measurements from the Monte Rosa area. The simulation reveals a very good overall agreement in the comparison with a large archive of firn temperature profiles. The rate of firn warming at 20 m depth is estimated at 0.44 °C per decade. Our results show that surface melt over the glaciated saddle is increasing by 3–4 mm w.e. yr−2 depending on the location (29–36 % in 16 years), although with large inter-annual variability. Analysis of modeled melt indicates a marked tendency towards small melt events (
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.