Knowledge of how glaciations formed landscapes is particularly important as receding glaciers currently uncover subglacial landscapes that are prone to a series of natural hazards, but that also bring opportunities for hydropower or water resources. We present high-resolution (1 × 1 m) swath bathymetric data of a proglacial lake in front of the Rhonegletscher (Swiss Alps) that started to form in the early 2000s allowing a look into a freshly uncovered glacier bed and its characterized morphology in an overdeepened setting. The comparison of two surveys from 2015 and 2021 allows an unprecedented quantification of the accumulation and erosion processes in the central lake basin. This highly dynamic environment is characterized by iceberg calving, fluctuating outflow conduits, rapid sedimentation due to particle-laden meltwaters and dumped glacial debris. Assuming constant sediment yield, the Rhone Lake would persist for ~300 years. However, as intense glacier retreat continues in the coming decades, a chain of overdeepened lakes will be revealed that will act as long persisting sediment traps.

This study investigates the impacts of the timing of an extreme cyclone that occurred in August 2012 on the sea-ice volume evolution based on the Arctic Ice Ocean Prediction System (ArcIOPS). By applying a novel cyclone removal algorithm to the atmospheric forcing during 4–12 August 2012, we superimpose the derived cyclone component onto the atmospheric forcing one month later or earlier. This study finds that although the extreme cyclone leads to strong sea-ice volume loss in all runs, large divergence occurs in sea-ice melting mechanism in response to various timing of the cyclone. The extreme cyclone occurred in August, when enhanced ice volume loss is attributed to ice bottom melt primarily and ice surface melt secondarily. If the cyclone occurs one month earlier, ice surface melt dominates ice volume loss, and earlier appearance of open water within the ice zone initiates positive ice-albedo feedback, leading to a long lasting of the cyclone-induced impacts for approximately one month, and eventually a lower September ice volume. In contrast, if the cyclone occurs one month later, ice bottom melt entirely dominates ice volume loss, and the air-open water heat flux in the ice zone tends to offset ice volume loss.

Avalanche modeling is an essential tool to assess snow avalanche hazard. Today, most popular numerical approaches adopt depth-averaged equations. These methods are computationally efficient but limited in capturing processes occurring in the flow depth direction, e.g. erosion or deposition, which are often considered using ad hoc parameterizations or neglected completely. However, processes such as snow erosion, can crucially influence flow dynamics and run-out and are often not negligible. We address these issues by using a new three-dimensional (3-D) model, based on the material point method and finite strain elastoplasticity. To assess the possibilities and challenges associated with these highly detailed but computationally expensive calculations, we simulated the ‘Salezer’ snow avalanche that released in Davos, Switzerland in 2019. To reproduce the event in our simulations, we use the release areas mapped in a photogrammetric drone survey and estimate the snow conditions on the day of the event. We compare macroscopic features, such as flow outline and snow deposition of the simulated avalanche to field observations. An in-depth analysis of transient 3-D flow structures at the avalanche head not only demonstrates the degree of physical detail in the model, but also highlights challenges which still need to be addressed.

We review successes and challenges from five recent subglacial bedrock drilling campaigns intended to find evidence for Antarctic Ice Sheet retreat during warm periods in the geologic past. Insights into times when the polar ice sheets were smaller than present serve as guiding information for modeling efforts that aim to predict the rate and magnitude of future sea level rise that would accompany major retreat of the Antarctic Ice Sheet. One method to provide direct evidence for the timing of deglaciations and minimum extent of prior ice sheets is to extract subglacial bedrock cores for cosmogenic nuclide analysis from beneath the modern ice sheet surface. Here we summarize the lessons learned from five field seasons tasked with obtaining bedrock cores from shallow depths (<120 m beneath ice surface) across West Antarctica since 2016. We focus our findings on drilling efforts and technology and geophysical surveys with ground-penetrating radar. Shallow subglacial drilling provides a high risk, high reward means to test for past instabilities of the Antarctic Ice Sheet, and we highlight key challenges and solutions to increase the likelihood of success for future subglacial drilling efforts in polar regions.

Subglacial seismicity presents the opportunity to monitor inaccessible glacial beds at the epicentral location and time. Glaciers can be underlain by rock or till, a first order control on bed mechanics. Velocity-weakening, necessary for unstable slip, has been shown for each bed type, but is much stronger and evolves over more than an order of magnitude longer distances for till beds. Utilizing a de-stiffened double direct shear apparatus, we found conditions for instability at freezing temperatures and high slip rates for both bed types. During stick–slip stress-drops, we recorded acoustic emissions with piezoelectric transducers frozen into the ice. The two populations of event waveforms appear visually similar and overlap in their statistical features. We implemented a suite of supervised machine learning algorithms to classify the bed type of recorded waveforms and spectra, with prediction accuracy between 65–80%. The Random Forest Classifier is interpretable, showing the importance of initial oscillation peaks and higher frequency energy. Till beds have generally higher friction and resulting stress-drops, with more impulsive first arrivals and more high frequency content compared to rock emissions, but rock beds can produce many till-like events. Seismic signatures could enhance interpretation of bed conditions and mechanics from subglacial seismicity.

For snow-avalanche hazard mapping, one needs efficient tools that nevertheless capture the essential physical processes. The code MoT-PSA (Method of Transport – Powder Snow Avalanche) described here is based on the two-layer depth-averaged formulation for mixed snow avalanches developed by Eglit and co-workers in the 1980s but is extended to 3-D terrain and uses a fast numerical scheme based on the method of transport. Compared to previous works, we introduce novel formulations for the suspension and deposition of snow from the dense core. Snow cover and air entrainment are quantified with physics-based models. A sensitivity study of the model parameters on an idealized topography shows that both the dense core and the parameters of the powder snow cloud (PSC) governing particle suspension and settling significantly affect the dynamics. As expected, we observe that snow cover entrainment favours the formation of large PSCs with long runout. The powder-snow avalanche that occurred in Lom (Norway) on 27 February 2020 is back-calculated using MoT-PSA. With plausible parameter values, the model reproduces the dense core stopping at the gully's base and the dilute PSC travelling across the frozen lake for almost 1 km.

Interferometric synthetic aperture radar (InSAR) data suffer from an elevation bias due to signal penetration into the firn and ice surface, rendering the height information unusable for elevation and mass-change detection. This study estimates the penetration bias in X-band InSAR data to quantify its impact on elevation and mass-change detection and to demonstrate the applicability of TanDEM-X digital elevation models (DEMs) for cryosphere research. To achieve this, a multiple linear regression model is applied to a time series of four TanDEM-X DEMs acquired between 2010 and 2018 over the Sverdrup Glacier basin (SGB), Devon Ice Cap, Canada. The resulting penetration corrected TanDEM-X DEMs agreed to within ±14 cm of spatially and temporally coincident precise in situ kinematic dGPS data (±10 cm RMSE). Additionally, multi-year estimations of mass change for the SGB derived from differencing TanDEM-X DEMs over multi-year periods between 2010 and 2018, showed good agreement with mean deviation of 338 ± 166 mm w.e. with independent measurements of mass change derived from annual in situ surface mass balance over the same time periods. The results show that the penetration bias can vary significantly, leading to random under- and overestimations in the detection of elevation and mass changes.

Passive-microwave sea ice concentration (SIC) algorithms employ different frequencies and polarisations in their operational implementations. Commonly, these algorithms utilise combinations such as 19/37 GHz, yielding reduced measurement uncertainties but at a coarse spatial resolution. Alternatively, these algorithms can solely use 89 GHz, producing a higher spatial resolution but with increased measurement uncertainties. This study evaluates the application of a resolution-enhancing SIC algorithm (reSICCI3LF), initially developed for the coarser Special Sensor Microwave Imager / Sounder, on the Advanced Microwave Scanning Radiometer. By applying reSICCI3LF, we aim to produce a 5 km SIC for 2013–2020 in the Fram Strait and the Barents and Kara Sea region that gains the benefits of both types of algorithms, high spatial resolution and low measurement uncertainty.

We present the algorithm tuning, spectral analysis of spatial resolutions, and validation against the Round Robin Data Package of 0% and 100% SIC points and SIC derived from Landsat-8. The findings demonstrate that the reSICCI3LF algorithm produces a SIC field with fine details, achieving a balance between high spatial resolution and lower measurement uncertainties compared to a 89 GHz based SIC. Consequently, this resolution-enhanced SIC technique can potentially initialise higher-resolution coupled ocean and sea ice forecasting systems through data assimilation.

In the course of an artificially triggered avalanche, a particle tracking procedure is combined with supplementary measurements, including Global Navigation Satellite System (GNSS) positioning, terrestrial laser scanning and Doppler radar measurements. Specifically, an intertial measurement unit is mounted inside a rigid sphere, which is placed in the avalanche track. The sphere is entrained by the moving snow, recording translational accelerations, angular velocities and the flux density of Earth's magnetic field. Based on the recorded data, we present a threefold analysis: (i) a qualitative data interpretation, identifying different particle motion phases which are associated with corresponding flow regimes, (ii) a quantitative time integration algorithm, determining the corresponding particle trajectory and associated velocities on the basis of standard sensor calibration, and (iii) an improved quantitative evaluation relying on a novel in situ sensor calibration technique, which is motivated by the limitations of the given dataset. The final results, i.e. the evolution of the angular orientation of the sensor unit, translational and rotational velocities and estimates of the sensor trajectory, are assessed with respect to their reliability and relevance for avalanche dynamics as well as for future design of experiments.

Spatial variability of snowpack properties adds uncertainty in the evaluation of avalanche hazard. We propose a combined mechanical–statistical approach to study how spatial variation of slab depth affects the skier-triggering probability and possible release size. First, we generate multiple slab depth maps on a plane fictional slope based on Gaussian Random Fields (GRF) for a specific set of mean, variance and correlation length. For each GRF, we derive analytically the Skier Propagation Index (SPI). We then simulate multiple skier tracks and computed the probability based on the number of skier hits where SPI is below 1. Finally, we use a depth-averaged material point method to evaluate the possible avalanche size for given slab depth variations. The results of this analysis show that large correlation lengths and small variances lead to a lower probability of skier-triggering as it reduces the size and the number of areas with low slab depth. Then, we show the effect of skiing style and skier group size on skier-triggering probability. Spatial variability also affects the possible avalanche size by adding stress fluctuation causing early or late tensile failure. Finally, we demonstrate with our models the well-known relationship between the probability and the size in avalanche forecasting.

In the Himalaya, ice thickness data are limited, and field measurements are even scarcer. In this study, we employed the GlabTop model to estimate ice reserves in the Jhelum (1.9 ± 0.6 km3) and Drass (2.9 ± 0.9 km3) sub-basins of the Upper Indus Basin. Glacier ice thickness in the Jhelum ranged up to 187 ± 56 m with a mean of ~24 ± 7 m, while the Drass showed ice thickness up to 202 ± 60 m, with a mean of ~17 ± 5 m. Model results were validated using Ground Penetrating Radar measurements across four profiles in the ablation zone of the Kolahoi glacier in the Jhelum and nine profiles across the Machoi glacier in the Drass sub-basin. Despite underestimating ice-thickness by ~10%, the GlabTop model effectively captured glacier ice-thickness and spatial patterns in most of the profile locations where GPR measurements were taken. The validation showed high correlation coefficient of 0.98 and 0.87, low relative bias of ~ −13% and ~ −3% and a high Nash–Sutcliffe coefficient of 0.94 and 0.93 for the Kolahoi and Machoi glaciers, respectively, demonstrating the model's effectiveness. These ice-thickness estimates improve our understanding of glacio-hydrological, and glacial hazard processes over the Upper Indus Basin.

Melting and calving of glaciers and ice caps in Antarctica and Greenland could potentially contribute significantly to global sea level rise. Updates to existing outlines that provide critical glacier baseline information in both regions could help in the analysis of particular changes in glacier parameters such as area and volume from time-series inventories. Here we synthesize previously established techniques and apply new multi-source datasets to update glacier outlines in selected test areas of Antarctica and Greenland, as well as to reduce uncertainties and errors during the mapping process. The workflow includes mapping glacier boundaries, subdividing glaciers by watersheds and assigning glacier attributes. Complicated glacier scenarios and updating challenges in polar regions are discussed and demonstrated by representative case studies. For the first time in Antarctica, we analyze the effect of terminus types on mapped glacier areas, and in Greenland we compare the differences with glacier mapping results using Landsat OLI and ETM+. With new data sources, the methods described in this study might help to create glacier outlines on a larger scale in Antarctica and Greenland. Although data sources can be substituted, the enormous amount of manual labor required to update glacier inventories remains a significant challenge.

The relationship between the behavior of water in snow and its microstructure is crucial to improve the prediction of wet snow disasters. X-ray computed tomography (X-ray CT) is frequently used to observe snow microscopically. However, distinguishing between ice and water in the X-ray images is difficult because ice exhibits an X-ray absorption coefficient similar to that of water. In contrast, magnetic resonance imaging (MRI) acquires nuclear magnetic resonance (NMR) signals of protons in a liquid and visualizes the NMR signal intensity, enabling discrimination between water and ice signals. However, snow grains and pore spaces cannot be distinguished in MRI images because they do not generate NMR signals.

To investigate the relationship between the microstructure of snow and the distribution of liquids in snow, we developed a novel method that combines X-ray CT and MRI images to compensate for the disadvantages associated with each method. Using this method, we successfully visualized where liquid (C12H24) occupied pore spaces. We also showed the possibility of using C12H24 instead of water to obtain water retention curve of snow cover, which is a fundamental aspect of hydraulic properties. Although there is room for improvement in the visualization of water in snow, such as shortening the imaging time to escape snow metamorphosis and image superimposition methods, this method is expected to effectively elucidate the behavior of water in snow and clarify the characteristics of wet snow.

Upernavik Isstrøm, the largest contributor to sea-level rise in northwest Greenland, has experienced complex and contrasting ice-flow-speed changes across its five outlets over the last two decades. In this study, we present a detailed remote-sensing analysis of the ice dynamics at Upernavik's outlets from 2000 to 2021 to evaluate the details of these changes. Previous research suggested that the presence or absence of floating ice tongues strongly influences Upernavik's ice dynamics. We use several lines of evidence to document the presence of floating ice tongues, and find that, while several outlets experienced ice-tongue formation and/or loss during the study period, these changes do not explain observed fluctuations in ice-flow velocity. Further exploration of ice-dynamic forcings using a flowline model suggests that changes in basal slipperiness near the terminus have a strong impact on upstream ice dynamics and can explain the velocity variations. Our results suggest that speed fluctuations at Upernavik's outlets may be seasonally and interannually controlled by bed conditions near the terminus, and highlight the need for further research on the influence of basal conditions on complex tidewater glacier dynamics.

We analyze the internal structure of two polythermal glaciers, Hurd and Johnsons, located on Livingston Island, Antarctica, using 200 and 750 MHz GPR data collected in 2003/04, 2008/09 and 2016/17 field campaigns. Based on the different permittivities of snow and ice, we determined the thickness distribution of the end-of winter snow cover and of the cold ice layer. Their knowledge is fundamental for mass balance and glacier dynamics studies due to the different densities and rheological properties of such media. The average measured thicknesses for the snow and cold ice layers (the latter including the snow layer) were of 1.44 ± 0.09 and 29.1 ± 1.5 m, and their corresponding maxima were of 2.45 ± 0.21 and 80.8 ± 2.5 m. GPR snow profiling allowed for extension of the coverage of the snow thickness survey, but added little information to that supplied by snow pits, stake readings and manual snow probing, because of the multiplicity of reflections within the seasonal snowpack caused by internal ice layers and lenses. The polythermal structure determined for Hurd Glacier fits into the so-called Scandinavian type, seldom reported for the Antarctic region.

We developed a Handheld Integrating Sphere Snow Grain Sizer (HISSGraS) for field use to measure the specific surface area (SSA) of snow. In addition to snow samples, HISSGraS can directly measure snow surfaces and snow pit walls. The basic measurement principle is the same as that of the IceCube SSA instrument. The retrieval algorithm for SSA from reflectance employs two conversion equations formulated using spherical and nonspherical grain shape models. We observed SSAs using HISSGraS, IceCube and the gas adsorption method in a snowfield in Hokkaido, Japan. Intercomparison of the results confirmed that with HISSGraS direct measurement, SSA profile observations can be completed in just ~1/10 the time required for measurement of snow samples. Our results also suggest that HISSGraS and IceCube have similar accuracy when the same snow samples are measured using the same grain shape model. However, SSAs of near-surface snow layers measured using the three techniques exhibited some biases, possibly due to rapid snow metamorphism or melting during measurement and some technical issues with optical techniques. When excluding SSA data for the surface layer, which metamorphosed remarkably during measurement, IceCube- and HISSGraS-derived SSAs correlated strongly with those obtained by gas adsorption and HISSGraS accuracy is 21–34%.

Glaciers of Baffin Island and nearby islands of Arctic Canada have experienced rapid mass losses over recent decades. However, projections of loss rates into the 21st century have so far been limited by the availability of model calibration and validation data. In this study, we model the surface mass balance of the largest ice cap on Baffin Island, Penny Ice Cap, since 1959, using an enhanced temperature index model calibrated with in situ data from 2006–2014. Subsequently, we project changes to 2099 based on the RCP4.5 climate scenario. Since the mid-1990s, the surface mass balance over Penny Ice Cap has become increasingly negative, particularly after 2005. Using volume–area scaling to account for glacier retreat, peak net mass loss is projected to occur between ~2040 and 2080, and the ice cap is expected to lose 22% (377.4 Gt or 60 m w.e.) of its 2014 ice mass by 2099, contributing 1.0 mm to sea level rise. Our 2015–2099 projections are approximately nine times more sensitive to changes in temperature than precipitation, with an absolute cumulative difference of 566 Gt (90 m w.e.) between +2 and −2°C scenarios, and 63 Gt (10 m w.e.) between +20% and −20% precipitation scenarios.

The geodetic mass balance of a glacier corresponds to glacier-wide volume changes, converted to mass changes using density assumptions. It is typically calculated by differencing multi-temporal digital elevation models. In this study, we show how the annual geodetic mass balance of a glacier can be derived from uncrewed aerial vehicle (UAV) data. The presented workflow is applied to two small- to medium-sized glaciers in the Kyrgyz Tien Shan (Central Asia): Bordu glacier and Sary-Tor glacier. The obtained geodetic mass balance is compared with the glaciological mass balance derived from a network of ablation stakes and snow pits. A previously calibrated mass-balance model is used to correct for the difference in acquisition dates. The results show that the determined geodetic mass balance matches closely with the glaciological mass balance. Besides, for both glaciers the geodetic mass balance does not seem to be particularly sensitive to the assumptions regarding volume-to-mass conversion. Therefore, our results demonstrate that UAVs can serve as a valuable instrument to quantify the annual geodetic mass balance and to validate the glaciological mass balance. The conventional glaciological mass-balance estimation often relies on interpolation and extrapolation methods, whereas UAVs offer the potential for direct data acquisition over the entire glacier surface.

Liquid water at the ground–snow interface is thought to play a crucial role in the release of glide-snow avalanches, which can be massive and threaten infrastructure in alpine regions. Several mechanisms have been postulated to explain the formation of this interfacial water. However, these mechanisms remain poorly understood, in part because suitable measurement techniques are lacking. Here, we demonstrate the use of neutron radiography for imaging water transport in soil–snow systems. Columns of sand, gravel and snow were used to simulate the capillary forces of the soil–vegetation–snow layering found in nature. The columns were connected to a water reservoir to maintain a constant-pressure boundary condition and placed in a climatic chamber within the neutron beam. We show that neutron radiography is capable of measuring changes in the optical density distribution (related to liquid water content) within all three layers of the model system. Results suggest that a porous interface between the sand and snow may induce the formation of a water layer in the basal snowpack. Improved understanding of the water transport in soil–snow systems should lead to better prediction of glide-snow avalanche release and could also benefit other fields such as snow hydrology.