Nander Wever

We monitored the formation and seasonal evolution of suncup roughness over three snow ablation seasons at Weissfluhjoch in the Swiss Alps using a terrestrial LiDAR scanner. From high-temporal-resolution digital surface models, we find that suncup onset required three concurrent conditions: sustained daytime surface melting, above-freezing wet-bulb temperatures, and reduced wind speeds. Suncups formed in all three years, but their planar arrangement and geometry varied substantially, controlled by whether radiative or turbulent conditions dominated ablation. Comparing measured broadband albedo to flat-surface TARTES simulations forced by SNOWPACK-modelled snow properties, we find that suncup roughness and surface impurity loading together reduce albedo by 0.03–0.1, depending on illumination geometry and impurity load, consistent with previous work. Isolating the two contributions is complicated by their co-evolution: the same melt processes that deepen suncups also drive surface enrichment and the spatial redistribution of impurities, which are uniformly distributed during early suncup formation but concentrate into the hollows as melt progresses. As a practical alternative, we identify a robust logarithmic relationship between broadband albedo and the aerodynamic roughness length z ₀ that captures the combined radiative effect of roughness and impurities regardless of their relative contribution. Because broadband albedo decays fastest at the onset of suncup formation, we infer that a uniform early impurity distribution is particularly effective at accelerating albedo loss. Because z ₀ evolves by one order of magnitude through ablation, yet is kept constant in most snow models, our results call for its explicit, time-varying representation in physics-based snow models, which would improve both the turbulent fluxes z ₀ governs directly and, through its link to albedo, the roughness–impurity darkening.

Glacier mass balance measurements and models are key tools for understanding the glacier response to climate change and specific processes occurring at the glacier surface. Snow accumulation and wind-driven erosion are among the most difficult processes to measure and model in high-altitude alpine terrain and on glaciers, due to their high variability in space and time, and to the scarcity of in situ observations. In addition, snow accumulation and erosion are key processes in the formation and preservation of ice core archives located on high-altitude accumulation areas of mountain glaciers, yet their impact on these paleoclimatic archives is still unquantified. In this study we used a rare dataset of nivo-meteorological and mass balance observations collected between 2011 and 2015 at 3830 m a.s.l. (meter above sea level) on Mt. Ortles (Eastern Alps) to investigate snow accumulation and erosion processes in close proximity to an ice core drilling site located in the upper accumulation area of Alto dell'Ortles Glacier. We applied the physics-based snow cover model SNOWPACK, constrained by field data, to reproduce the local mass balance and to explicitly simulate snow erosion by wind. The model reproduced the observed seasonal and annual mass balance variability with good accuracy over the four-year study period. Results indicate that wind erosion was the dominant ablation process at the study site, removing 21 % of the snowfall, whereas melt played a minor role removing only 3 %. Erosion was most effective in winter, during or shortly after snowfall events, and its efficiency was controlled by air temperature, with dry snow being much more susceptible to erosion (91 % of total erosion) than wetted snow (9 % of total erosion). Sensitivity experiments to air temperature perturbations demonstrated that wind erosion provides a negative feedback to the mass balance, because increasing temperature accelerates snow metamorphism and makes the snow surface less erodible. However, a further 1 °C warming would promote a transition from an erosion-dominated to a melt-dominated mass balance regime. Our findings emphasize the importance of accounting for wind erosion in projections of glacier mass balance on high-elevation wind exposed glacierized areas. They also highlight the relevance of snow erosion for the interpretation of ice core records, because long-term variations in snow erosion may have affected the formation of the seasonal paleoclimatic signal and its preservation.

We monitored the formation and seasonal evolution of suncup roughness over three snow ablation seasons at Weissfluhjoch, Swiss Alps, using a terrestrial LiDAR scanner. Suncup onset required two concurrent conditions, identified from high-temporal-resolution digital surface models of surface roughness: sustained surface melting through most of the day and reduced wind speeds. Suncups formed in all three years, but their planar arrangement and geometric properties varied substantially across seasons, controlled by whether radiative or turbulent heat exchange dominated ablation. Comparing measured broadband albedo to flat-surface simulations from TARTES forced by SNOWPACK-modelled snow properties, we find that the combined effect of suncup roughness and surface impurity loading reduces albedo by 0.02–0.15, depending on illumination geometry and impurity load, consistent with previous literature. Isolating the two contributions is complicated by their co-evolution during the ablation season: the same melt processes that progressively deepen suncups also drive surface enrichment and spatial redistribution of impurities. Resolving the two effects independently would in principle require equally fine-scale measurements of both roughness and impurity distribution. We identify a robust logarithmic correlation between broadband albedo and aerodynamic roughness length that simultaneously captures the radiative effects of roughness and impurities, regardless of their relative contributions. During early suncup formation, impurities remained uniformly distributed. At later stages, meltwater scavenging concentrated impurities to the suncup hollows. As the rate of broadband albedo decay is strongest at the beginning of suncup formation and relaxes thereafter, we infer that the interaction between the multiple-reflection mechanism and the more uniform distribution of impurities is particularly effective in accelerating albedo decay, beyond the effect of either factor alone. Given that C-band SAR backscatter is sensitive to the early development of surface roughness on wet snow, these findings encourage future work on the assimilation of surface roughness into snow energy balance models.

We monitored the formation and seasonal evolution of suncup roughness over three snow ablation seasons at Weissfluhjoch, Swiss Alps, using a terrestrial LiDAR scanner. Suncup onset required two concurrent conditions, identified from high-temporal-resolution digital surface models of surface roughness: sustained surface melting through most of the day and reduced wind speeds. Suncups formed in all three years, but their planar arrangement and geometric properties varied substantially across seasons, controlled by whether radiative or turbulent heat exchange dominated ablation. Comparing measured broadband albedo to flat-surface simulations from TARTES forced by SNOWPACK-modelled snow properties, we find that the combined effect of suncup roughness and surface impurity loading reduces albedo by 0.02–0.15, depending on illumination geometry and impurity load, consistent with previous literature. Isolating the two contributions is complicated by their co-evolution during the ablation season: the same melt processes that progressively deepen suncups also drive surface enrichment and spatial redistribution of impurities. Resolving the two effects independently would in principle require equally fine-scale measurements of both roughness and impurity distribution. We identify a robust logarithmic correlation between broadband albedo and aerodynamic roughness length that simultaneously captures the radiative effects of roughness and impurities, regardless of their relative contributions. During early suncup formation, impurities remained uniformly distributed. At later stages, meltwater scavenging concentrated impurities to the suncup hollows. As the rate of broadband albedo decay is strongest at the beginning of suncup formation and relaxes thereafter, we infer that the interaction between the multiple-reflection mechanism and the more uniform distribution of impurities is particularly effective in accelerating albedo decay, beyond the effect of either factor alone. Given that C-band SAR backscatter is sensitive to the early development of surface roughness on wet snow, these findings encourage future work on the assimilation of surface roughness into snow energy balance models.

We monitored the formation and seasonal evolution of suncup roughness over three snow ablation seasons at Weissfluhjoch, Swiss Alps, using a terrestrial LiDAR scanner. Suncup onset required two concurrent conditions, identified from high-temporal-resolution digital surface models of surface roughness: sustained surface melting through most of the day and reduced wind speeds. Suncups formed in all three years, but their planar arrangement and geometric properties varied substantially across seasons, controlled by whether radiative or turbulent heat exchange dominated ablation. Comparing measured broadband albedo to flat-surface simulations from TARTES forced by SNOWPACK-modelled snow properties, we find that the combined effect of suncup roughness and surface impurity loading reduces albedo by 0.02–0.15, depending on illumination geometry and impurity load, consistent with previous literature. Isolating the two contributions is complicated by their co-evolution during the ablation season: the same melt processes that progressively deepen suncups also drive surface enrichment and spatial redistribution of impurities. Resolving the two effects independently would in principle require equally fine-scale measurements of both roughness and impurity distribution. We identify a robust logarithmic correlation between broadband albedo and aerodynamic roughness length that simultaneously captures the radiative effects of roughness and impurities, regardless of their relative contributions. During early suncup formation, impurities remained uniformly distributed. At later stages, meltwater scavenging concentrated impurities to the suncup hollows. As the rate of broadband albedo decay is strongest at the beginning of suncup formation and relaxes thereafter, we infer that the interaction between the multiple-reflection mechanism and the more uniform distribution of impurities is particularly effective in accelerating albedo decay, beyond the effect of either factor alone. Given that C-band SAR backscatter is sensitive to the early development of surface roughness on wet snow, these findings encourage future work on the assimilation of surface roughness into snow energy balance models.

We monitored the formation and seasonal evolution of suncup roughness over three snow ablation seasons at Weissfluhjoch, Swiss Alps, using a terrestrial LiDAR scanner. Suncup onset required two concurrent conditions, identified from high-temporal-resolution digital surface models of surface roughness: sustained surface melting through most of the day and reduced wind speeds. Suncups formed in all three years, but their planar arrangement and geometric properties varied substantially across seasons, controlled by whether radiative or turbulent heat exchange dominated ablation. Comparing measured broadband albedo to flat-surface simulations from TARTES forced by SNOWPACK-modelled snow properties, we find that the combined effect of suncup roughness and surface impurity loading reduces albedo by 0.02–0.15, depending on illumination geometry and impurity load, consistent with previous literature. Isolating the two contributions is complicated by their co-evolution during the ablation season: the same melt processes that progressively deepen suncups also drive surface enrichment and spatial redistribution of impurities. Resolving the two effects independently would in principle require equally fine-scale measurements of both roughness and impurity distribution. We identify a robust logarithmic correlation between broadband albedo and aerodynamic roughness length that simultaneously captures the radiative effects of roughness and impurities, regardless of their relative contributions. During early suncup formation, impurities remained uniformly distributed. At later stages, meltwater scavenging concentrated impurities to the suncup hollows. As the rate of broadband albedo decay is strongest at the beginning of suncup formation and relaxes thereafter, we infer that the interaction between the multiple-reflection mechanism and the more uniform distribution of impurities is particularly effective in accelerating albedo decay, beyond the effect of either factor alone. Given that C-band SAR backscatter is sensitive to the early development of surface roughness on wet snow, these findings encourage future work on the assimilation of surface roughness into snow energy balance models.

Antarctic heatwaves driven by atmospheric rivers are emerging as high-impact extremes, yet the role of climate change in amplifying such events remains uncertain. Here we investigate the climate change contribution to the March 2022 East Antarctic heatwave using pseudo-global warming experiments with the snow-atmospheric coupled model CRYOWRF. By comparing present-day and preindustrial storylines, we identify that under current climate, cloud and water-vapor radiation feedbacks non-linearly amplify near-surface warming by up to 10 °C (equivalent to 25% of the amplification) relative to preindustrial conditions. These feedbacks are likely underrepresented in global climate models due to their use of hydrostatic dynamics, and poor cloud representation over coarse resolutions. Future warming further intensifies this amplification, particularly along the coast, where firn air content is depleted, meltwater percolates, and ice lenses thicken. Such melting conditions threaten to accelerate surface mass loss and destabilize the fringing ice shelves. Our results reveal a key amplification pathway for Antarctic extremes, with potentially far-reaching implications for ice-sheet stability.

Mass and energy exchanges between the cryosphere and the atmosphere affect the state of both systems, motivating the development of two-way coupled cryosphere-atmosphere models. For snow-atmosphere models, traditional atmospheric models are coupled to multilayer physics-based snow models and run in a large-eddy mode when simulating horizontal resolutions approaching 100m. For the CRYOWRF model in particular, the atmospheric model WRF was coupled to the snow model SNOWPACK. This approach has enabled detailed studies of snow-atmosphere feedbacks such as sublimation of drifting and blowing snow. However, the high computational cost of CRYOWRF limits its application to short spatio-temporal domains at scales relevant to drifting and blowing snow (

Understanding snow processes in the sea-ice system is essential to improving Arctic sea-ice predictions and climate modeling. We show that the winter snow cover on Arctic sea ice is strongly enriched in heavy isotopes near the snow-sea ice interface, unexplainable by snow metamorphism alone. During the MOSAiC expedition, stratigraphic investigations revealed that large temperature gradients drive water vapor transport and mass transfer from sea ice into the snowpack. We estimate the contributed snow depth equivalent as 39 ± 7 mm (cumulative mass redistribution) and 63 ± 21 mm (isotope two-source model). Despite uncertainties, both highlight the need for detailed snowpack vapor flux modeling. Recognizing this recrystallization process improves understanding of snow stratigraphy, gas exchange, atmospheric chemistry through snow impurity distributions (e.g., sea salt aerosol), and reduces uncertainties in snow mass balance and heat conductivity. With continued Arctic change, evolving snowpack temperature gradients and recrystallized sea-ice snow contributions will further shape these processes.

Glacier mass balance measurements and models are key tools for understanding the glacier response to climate change and specific processes occurring at the glacier surface. Snow accumulation and wind-driven erosion are among the most difficult processes to measure and model in high-altitude alpine terrain and on glaciers, due to their high variability in space and time, and to the scarcity of in situ observations. Here we use a unique dataset of nivo-meteorological and mass balance observations collected between 2011 and 2015 at 3830 m a.s.l. on Mt. Ortles (Eastern Alps) to investigate snow accumulation and erosion processes. We applied the physics-based snow cover model SNOWPACK, constrained by field data, to reproduce the local mass balance and to explicitly simulate snow erosion by wind. The model reproduces the observed seasonal and annual mass balance variability with good accuracy over the four-year study period. Results indicate that wind erosion is the dominant ablation process at the study site, removing 21 % of the snowfall, whereas melt plays a minor role. Erosion is most effective in winter, during or shortly after snowfall events, and its efficiency is controlled by air temperature, with dry snow being much more susceptible to erosion than wet snow. Sensitivity experiments to air temperature perturbations demonstrate that wind erosion provides a negative feedback to the mass balance, because increasing temperature accelerates snow metamorphism and makes the snow surface less erodible. However, a further 1 °C warming would promote a transition from an erosion-dominated to a melt-dominated mass balance regime. Our findings emphasize the importance of accounting for wind erosion in projections of glacier mass balance under climate change. They also highlight the relevance of snow erosion for the interpretation of ice core records, because long-term variations in snow erosion may have affected the formation and preservation of the seasonal paleoclimatic signal.