Future projections of sea-level rise under strong warming scenarios are dominated by mass loss in the marine-grounded sectors of West Antarctica, where thinning shelves as a result of warming oceans can lead to reduced buttressing. This consequently leads to accelerated flow from the upstream grounded ice. However, the relation between warming oceans and increased melt rates under the shelves is very uncertain, especially when interactions with the changing shelf geometry are considered. Here, we compare six widely used, highly parameterised formulations relating sub-shelf melt to thermal forcing. We implemented them in an ice-sheet model, and applied the resulting set-up to an idealised-geometry setting, as well as to the Antarctic ice sheet. In our simulations, the differences in modelled ice-sheet evolution resulting from the choice of parameterisation, as well as the choice of numerical scheme used to apply sub-shelf melt near the grounding line, generally are larger than differences from ice-dynamical processes such as basal sliding, as well as uncertainties from the forcing scenario of the model providing the ocean forcing. This holds for the idealised-geometry experiments as well as for the experiments using a realistic Antarctic topography.

Crevasses pose severe risks for mountaineers and field glaciologists. Smaller cracks between 0.5 and 2 m are still dangerous, but often not visible in medium resolution satellite imagery. If they are snow covered, they are completely undetectable by optical sensors. We set out to develop an approach to detect potentially crevassed areas by a minimum of geometric data, and to make the method generally applicable to glacier regions. On Vernagtferner, we compared a reference dataset of crevasses observed in high-resolution optical imagery with the curvature of the ice surface and the spatial gradients in driving stress. Both parameters can be derived from a digital surface model and a bedrock model, derived from ice thickness measurements. The correlation patterns show that crevasses preferably form in convex areas and in areas where the driving stress rapidly increases. This corresponds with the theory of crevasse formation. Although the method still misclassifies larger parts, the approach has the potential to define probable non-crevassed areas as well as to aid the planning of safe routes.

The density structure of firn has implications for hydrological and climate modelling, and ice-shelf stability. The structure of firn can be evaluated from depth models of seismic velocity, widely obtained with Herglotz–Wiechert inversion (HWI), an approach that considers the slowness of refracted seismic arrivals. However, HWI is strictly appropriate only for steady-state firn profiles and the inversion accuracy can be compromised where firn contains ice layers. In these cases, full waveform inversion (FWI) may yield more success than HWI. FWI extends HWI capabilities by considering the full seismic waveform and incorporates reflected arrivals. Using synthetic firn density profiles, assuming both steady- and non-steady-state accumulation, we show that FWI outperforms HWI for detecting ice slab boundaries (5–80 m thick, 5–80 m deep) and velocity anomalies within firn. FWI can detect slabs thicker than one wavelength (here, 20 m, assuming a maximum frequency of 60 Hz) but requires the starting velocity model to be accurate to ±2.5%. We recommend for field practice that the shallowest layers of velocity models are constrained with ground-truth data. Nonetheless, FWI shows advantages over established methods, and should be considered when the characterisation of firn ice slabs is the goal of the seismic survey.

Wet-snow avalanches are triggered by the infiltration of liquid water which weakens the snowpack. Wet-snow avalanches are among the most destructive avalanches, yet their release mechanism is not sufficiently understood for a process-based prediction model. Therefore, we followed a data-driven approach and developed a random forest model, depending on slope aspect, to predict the local wet-snow avalanche activity at the locations of 124 automated weather stations distributed throughout the Swiss Alps. The input variables were the snow and weather data recorded by the stations over the past 20 years. The target variable was based on manual observations over the same 20-year period. To filter out erroneous reports, we defined the days with wet-snow avalanches in a stringent manner, selecting only the most extreme active or inactive days, which reduced the size of the dataset but increased the reliability of the target variable. The model was trained with weather variables and variables computed from simulated snow stratigraphy in 38$^\circ$ slopes facing the 4 cardinal directions. While model development and validation were done in nowcast mode, we also studied model performance in 24-hour forecast mode by using input variables computed from a numerical weather prediction (NWP) model. Overall, the performance was good in both nowcast and forecast mode (f1-score around 0.8). To assess model performance beyond the stringent definition of wet-snow avalanche days, we compared model predictions to wet-snow avalanche activity over the entire Swiss Alps, based on the raw data over 8 winters. We obtained a Spearman correlation coefficient of 0.71. Hence, our model represents a step toward the application of support tools in operational wet-snow avalanche forecasting.

Avalanches result from an interaction of weather and terrain, where past weather and internal snow cover processes play important roles. So far, climatology was mainly based on weather data, as regional snow instability information, such as avalanche activity, is scarce on climatological time scales. We present a new approach to create a snow avalanche climatology from simulations of avalanche problem types based on snow cover simulations of reanalysis data and a cluster analysis. Analyzing the winters between 1958 and 2020 in the French Alps, wet-snow situations dominated natural release. Dry-snow situations with non-persistent and persistent weak layers occurred each on at least one third of the days. Four typical patterns of avalanche problem types were identified. They follow the main orography with more new snow situations in the northern regions and more cases of persistent weak layers in inner-Alpine regions. In the front-ranges and in southern regions wet-snow situations occurred early in winter – typical for coastal snow climates. Agreement with the standard snow climate classification and the geography of the French Alps suggests that mountain regions with similar conditions can now be outlined. This method for snow avalanche climatology will inform avalanche forecasting and facilitate climate change impact studies.

We present new data from the debris-rich basal ice layers of the NEEM ice core (NW Greenland). Using mineralogical observations, SEM imagery, geochemical data from silicates (meteoric 10Be, εNd, 87Sr/86Sr) and organic material (C/N, δ13C), we characterize the source material, succession of previous glaciations and deglaciations and the paleoecological conditions during ice-free episodes. Meteoric 10Be data and grain features indicate that the ice sheet interacted with paleosols and eroded fresh bedrock, leading to mixing in these debris-rich ice layers. Our analysis also identifies four successive stages in NW Greenland: (1) initial preglacial conditions, (2) glacial advance 1, (3) glacial retreat and interglacial conditions and (4) glacial advance 2 (current ice-sheet development). C/N and δ13C data suggest that deglacial environments favored the development of tundra and taiga ecosystems. These two successive glacial fluctuations observed at NEEM are consistent with those identified from the Camp Century core basal sediments over the last 3 Ma. Further inland, GRIP and GISP2 summit sites have remained glaciated more continuously than the western margin, with less intense ice-substratum interactions than those observed at NEEM.

In Southeast Greenland, summer melt and high winter snowfall rates give rise to firn aquifers: vast stores of meltwater buried beneath the ice-sheet surface. Previous detailed studies of a single Greenland firn aquifer site suggest that the water drains into crevasses, but this is not known at a regional scale. We develop and use a tool in Ghub, an online gateway of shared datasets, tools and supercomputing resources for glaciology, to identify crevasses from elevation data collected by NASA's Airborne Topographic Mapper across 29000 km2 of Southeast Greenland. We find crevasses within 3 km of the previously mapped downglacier boundary of the firn aquifer at 20 of 25 flightline crossings. Our data suggest that crevasses widen until they reach the downglacier boundary of the firn aquifer, implying that crevasses collect firn-aquifer water, but we did not find this trend with statistical significance. The median crevasse width, 27 meters, implies an aspect ratio consistent with the crevasses reaching the bed. Our results support the idea that most water in Southeast Greenland firn aquifers drains through crevasses. Less common fates are discharge at the ice-sheet surface (3 of 25 sites) and refreezing at the aquifer bottom (1 of 25 sites).

Most theoretical descriptions of stresses induced by freezing are rooted in the (generalized) Clapeyron equation, which predicts the pressure that a solid can exert as it cools below its melting temperature. This equation is central for topics ranging beyond glaciology to geomorphology, civil engineering, food storage and cryopreservation. However, it has inherent limitations, requiring isotropic solid stresses and conditions near bulk equilibrium. Here, we examine when the Clapeyron equation is applicable by providing a rigorous derivation that details all assumptions. We demonstrate the natural extension for anisotropic stress states, and we show how the temperature and pressure ranges for validity depend on well-defined material properties. Finally, we demonstrate how the range of applicability of the (linear) Clapeyron equation can be extended by adding higher-order terms, yielding results that are in good agreement with experimental data for the pressure melting of ice.

Initialising model glaciers such that they match well with their real counterparts and are thus able to make more accurate predictions is an ongoing challenge in glacier modelling. We set out a data-assimilation approach using an ensemble Kalman filter in a 2D flowline example that provides one possible solution to this problem. We show that our approach is valid across a range of parameters and scenarios, including deliberately data-deficient or inaccurate ones, and leads to robust retrieval of the glacier bed. We also provide some suggestions for how best to use data assimilation within a mountain-glacier context.

Melting glacier surfaces are unique ecosystems for specialized microbes, frequently harbouring blooms of microalgae with pigments contributing to the darkening of ice surfaces, reducing albedo and enhancing melt rates. The main cause of this phenomenon is algae of the genus Ancylonema. Prior investigation depended on field-collected material because these algae resisted cultivation. To enhance research on how these algae dominate melting ice, we established a strain of Ancylonema alaskanum from an alpine glacier and exposed to temperatures around the freezing point at irradiations of ~10% of full sunlight. The morphology of the culture changed, with the cells becoming longer and turning green by losing their brownish pigmentation, indicating that these dark phenols are crucial for survival in the cryosphere. Photophysiological comparisons of strain and glacial material showed adaptation of the photosynthetic apparatus to prevailing conditions. This laboratorial strain opens possibilities for a wide range of comparative ‘omics’ research.

Climate change has had a significant impact on glacier recession, particularly in the Arctic, where glacier meltwater is an important contributor to global sea-level rise. Therefore, it is important to accurately quantify glacier recession within this sensitive region, using multiple observations of glacier extent. In this study, we mapped 480 glaciers in Novaya Zemlya, Russian Arctic, using object-based image analysis applied to multispectral Landsat satellite imagery in Google Earth Engine and quantify the area changes between 1986–89 and 2019–21. The results show that in 1986–89, the total glacierized area was 22 990 ± 301 km2, in 2000–01 the area was 22 525 ± 308 km2 and by 2019–21 the glacier area reduced to 21 670 ± 292 km2, representing a total of 5.8% reduction in glacier area between 1986–89 and 2019–21. Higher glacier area loss was observed on the Barents Sea coast (7.3%) compared to the Kara (4.2%), reflecting previously observed differences in warming trends. The accuracy of the automatically generated outlines of each layer (1986–89, 2000–01 and 2019–21) was evaluated by comparing with manually corrected outlines (reference data) using random sampling, resulting in an overall accuracy estimate of between 96 and 97% compared to the reference data. This automated approach in Google Earth Engine is a promising tool for rapidly mapping glacier change that reduces the amount of time required to generate accurate glacier outlines.

Ice aprons are defined as very small ice bodies covering steep rock slopes. They have only been the subject of increased scientific interest for a few years, despite the fact that they are a condition for mountaineering and obvious elements in the high-alpine landscapes. However, very little is known about their distribution, evolution and physical characteristics. In this paper, we review the existing knowledge on ice aprons, which have almost exclusively been investigated in the Mont-Blanc massif, Western Alps. We supplement this review with novel results from recent surveys of ice aprons. We used a wide array of methodologies, from remote sensing (multi-source imagery) to in situ (stakes and thermal monitoring) and laboratory (radiocarbon dating and texture analysis) glaciological investigations. In the Mont-Blanc massif, ice aprons occupy 4.2 km2 within the alpine permafrost zone. Temperature measured at the ice–rock interface is indeed largely negative. Thinness of ice aprons coupled with the cold context implies a quasi-stationary shear regime without basal Sliding. Only ice at the surface can possibly melt in warm periods. After a shrinking period from the end of the Little Ice Age to the mid-to-late-1960s, ice aprons experienced a short period of expansion, followed by an accelerated shrinkage since the beginning of the 21st century. This shrinkage now favours rockfall triggering and poses a serious threat to a glaciological heritage since ice aprons host several-thousand-year-old ice. Finally, we synthesize this information to assess the existing definition of ice aprons, and propose some future research directions.

Thwaites Glacier (TG) plays an important role in future sea-level rise (SLR) contribution from the West Antarctic Ice Sheet. Recent observations show that TG is losing mass, and its grounding zone is retreating. Previous modeling has produced a wide range of results concerning whether, when, and how rapidly further retreat will occur under continued warming. These differences arise at least in part from ill-constrained processes, including friction from the bed, and future atmosphere and ocean forcing affecting ice-shelf and grounding-zone buttressing. Here, we apply the Ice Sheet and Sea-level System Model (ISSM) with a range of specifications of basal sliding behavior in response to varying ocean forcing. We find that basin-wide bed character strongly affects TG's response to sub-shelf melt by modulating how changes in driving stress are balanced by the bed as the glacier responds to external forcing. Resulting differences in dynamic thinning patterns alter modeled grounding-line retreat across Thwaites' catchment, affecting both modeled rates and magnitudes of SLR contribution from this critical sector of the ice sheet. Bed character introduces large uncertainties in projections of TG under equal external forcing, pointing to this as a crucial constraint needed in predictive models of West Antarctica.

Marine-terminating glaciers cover more than one-fourth of the total glacierized area in the Northern Hemisphere outside the Greenland ice sheet. It is therefore crucial to ensure an adequate representation of these glaciers when projecting large-scale glacier mass changes. We investigate how the introduction of marine frontal processes in the modeling chain influences the results of mass change projections, compared to projections neglecting such processes. We find that including frontal processes reduces the projected glacier mass loss, since incorporating frontal ablation in the model's mass-balance calibration results in a decrease in marine-terminating glaciers’ sensitivity to atmospheric temperatures. We also find that retrograde bed slopes lead to increased frontal ablation as the atmosphere warms, while frontal ablation decreases if bed slopes are prograde. These opposing effects have the potential to partly cancel each other when considering large glacier ensembles. Although we do not account for potential future changes in oceanic climate yet, any effect of these would be moderated by around half of today's marine-terminating glaciers becoming land-terminating in the course of the 21st century. While we find a significant influence of ice flow parameters on our results, boundary conditions remain the largest source of uncertainty in our projections.

This study presents the first dataset of physical and textural properties of sea ice collected in the South Atlantic and Indian Ocean sector of the Antarctic marginal ice zone (MIZ). Observations of sea ice from this region in the austral spring 2019, including sea-ice core temperature, salinity, crystal size, texture, oxygen isotopes and stratigraphy, were used in conjunction with a Lagrangian back-tracking algorithm and atmospheric reanalyses. This method relates the reconstructed synoptic conditions to sea-ice growth along the transect. A significant difference was found between the stratigraphy of consolidated pack ice samples collected at the same latitude and spanning over 550 km eastwards. The eastward group was found to have more disturbances in their stratigraphy which is attributed to the highly variable atmospheric and sea-ice conditions together with varying wave penetration through the sea-ice pack, notably during the passage of an intense polar cyclone, while the westward group showed no signs of disturbance or deformation. These results indicate that consolidated Antarctic sea-ice floes of similar thickness and from the same latitude in the MIZ have distinct stratigraphic properties, which will influence their physical and biogeochemical features.

This study provides the first comprehensive reconstruction of the dynamics of Iceberg Glacier, located on western Axel Heiberg Island, and reveals detailed observations of a complete surge for the first time in the Canadian Arctic. Historical aerial photographs, declassified intelligence satellite photographs, optical satellite imagery and synthetic aperture radar data were used to quantify changes in terminus position, ice velocity and glacier thickness since the 1950s. A surge initiated at the terminus in 1981 and terminated in 2003, suggesting a 22-year active phase. High surface velocities, reaching ~2300 m a−1 in 1991, were accompanied by a maximum terminus advance of >7 km and a large transfer of mass down-glacier, causing significant median trunk-wide surface elevation changes attaining >3 ± 1 m a−1. We suggest that the retreat from a pinning point, flotation of the terminus, the removal of sea-ice from the ice front, and an increase in subglacial meltwater availability from relatively high air temperatures in 1981 likely contributed to surge initiation. The ensuing quiescent period has seen a continual decrease in surface flow rates to an average centreline velocity of 11.5 m a−1 in 2020–21, a gradual steepening of the glacier surface and a > 2.5 km terminus retreat.

Despite their extreme elevation, glaciers on the Tibetan Plateau are losing mass in response to atmospheric warming, the pattern of which purportedly reflects regional contrasts in climate. Here we examine the evolution of glaciers along ~500 km of the Tanggula Shan, Central-Eastern Tibetan Plateau. Using remotely sensed datasets, we quantified changes in glacier mass, area and surface velocity, and compared these results to time series of meteorological observations, in order to disentangle drivers of glacier mass loss since the 1960s. Glacier mass loss has increased (from −0.21 ± 0.12 m w.e. a−1 in 1960s–2000s, to −0.52 ± 0.18 m w.e. a−1 in 2000s–2015/18) in association with pervasive positive temperature anomalies (up to 1.85°C), which are pronounced at the end of the now lengthened ablation season. However, glacier mass budget perturbations do not mirror the magnitude of temperature anomalies in sub-regions, thus additional factors have heightened glacier recession. We show how proglacial lake expansion and glacier surging have compounded glacier recession over decadal/multi-decadal time periods, and exert similar influence on glacier mass budgets as temperature changes. Our results demonstrate the importance of ice loss mechanisms not often incorporated into broad-scale glacier projections, which need to be better considered to refine future glacier runoff estimates.

Debris-covered ice is widespread in mountain regions with debris an important control on surface ice melt and glacier retreat. Quantifying debris cover extent and its evolution through time over large regions remains a challenge. This study develops two Normalized Difference Supraglacial Debris Indices for mapping debris-covered ice based on thermal and near Infrared Landsat 8 bands. They were calibrated with field data. Validation suggests that they have a high level of accuracy. They are then applied to Landsat data for 2016 to produce the first detailed glacier inventory of the Afghanistan Hindu Kush Himalaya that includes debris cover. 3408 glaciers were identified which, for those ⩾0.01 km2 in area, gives an ice cover of 2,222 ± 11 km2 and a debris cover of 619 ± 40 km2. Principal components analysis was used to identify the most influential drivers of debris-covered ice extent. Lower proportions of debris cover were associated with glaciers with a higher elevation range, that were larger, longer and wider. These relations were statistically clearer when the dataset was broken down into climate and geological zones. A glaciers continue to shrink, the proportion of debris cover will become higher, making it more important to map debris cover reliably.

Floating ice shelves that fringe the coast of Antarctica resist the flow of grounded ice into the ocean. One of the key factors governing the amount of flow resistance an ice shelf provides is the rigidity (related to viscosity) of the ice that constitutes it. Ice rigidity is highly heterogeneous and must be calibrated from spatially continuous surface observations assimilated into an ice-flow model. Realistic uncertainties in calibrated rigidity values are needed to quantify uncertainties in ice sheet and sea-level forecasts. Here, we present a physics-informed machine learning framework for inferring the full probability distribution of rigidity values for a given ice shelf, conditioned on ice surface velocity and thickness fields derived from remote-sensing data. We employ variational inference to jointly train neural networks and a variational Gaussian Process to reconstruct surface observations, rigidity values and uncertainties. Applying the framework to synthetic and large ice shelves in Antarctica demonstrates that rigidity is well-constrained where ice deformation is measurable within the noise level of the observations. Further reduction in uncertainties can be achieved by complementing variational inference with conventional inversion methods. Our results demonstrate a path forward for continuously updated calibrations of ice flow parameters from remote-sensing observations.

Mass loss from iceberg calving at marine-terminating glaciers is one of the largest and most poorly constrained contributors to sea-level rise. However, our understanding of the processes controlling ice fracturing and crevasse evolution is incomplete. Here, we use Gabor filter banks to automatically map crevasse density and orientation through time on a ~150 km2 terminus region of Narsap Sermia, an outlet glacier of the southwest Greenland ice sheet. We find that Narsap Sermia is dominated by transverse (flow-perpendicular) crevasses near the ice front and longitudinal (flow-aligned) crevasses across its central region. Measured crevasse orientation varies on sub-annual timescales by more than 45$^\circ$ in response to seasonal velocity changes, and also on multi-annual timescales in response to broader dynamic changes and glacier retreat. Our results show a gradual up-glacier propagation of the zone of flow-transverse crevassing coincident with frontal retreat and acceleration occurring in 2020/21, in addition to sub-annual crevasse changes primarily in transition zones between longitudinal to transverse crevasse orientation. This provides new insight into the dynamics of crevassing at large marine-terminating glaciers and a potential approach for the rapid identification of glacier dynamic change from a single pair of satellite images.