Spatially variable basal conditions are thought to govern how ice sheets behave at glacial time scales (>1000 years) and responsible for changes in dynamics between the core and peripheral regions of the Laurentide and Fennoscandian ice sheets. Basal motion is accomplished via the deformation of unconsolidated sediments, or via sliding of the ice over an undeformable bed. We present an ice sheet sliding module for the Parallel Ice Sheet Model (PISM) that takes into account changes in sediment cover and incorporates surface meltwater. This model routes meltwater, produced at the surface and base of the ice sheet, toward the margin of the ice sheet. Basal sliding is accomplished through the deformation of water saturated sediments, or sliding at the ice-bed interface. In areas with continuous, water saturated sediments, sliding is almost always accomplished through sediment deformation. In areas with incomplete cover, sliding has a stronger dependence on the supply of water. We find that the addition of surface meltwater to the base is a more important factor for ice sheet evolution than the style of sliding. In a glacial cycle simulation, our model causes a more rapid buildup of the Laurentide Ice Sheet.

Rifts are full-thickness fractures that propagate laterally across an ice shelf. They cause ice-shelf weakening and calving of tabular icebergs, and control the initial size of calved icebergs. Here, we present a joint inverse and forward computational modeling framework to capture rifting by combining the vertically integrated momentum balance and anisotropic continuum damage mechanics formulations. We incorporate rift–flank boundary processes to investigate how the rift path is influenced by the pressure on rift–flank walls from seawater, contact between flanks, and ice mélange that may also transmit stress between flanks. To illustrate the viability of the framework, we simulate the final 2 years of rift propagation associated with the calving of tabular iceberg A68 in 2017. We find that the rift path can change with varying ice mélange conditions and the extent of contact between rift flanks. Combinations of parameters associated with slower rift widening rates yield simulated rift paths that best match observations. Our modeling framework lays the foundation for robust simulation of rifting and tabular calving processes, which can enable future studies on ice-sheet–climate interactions, and the effects of ice-shelf buttressing on land ice flow.

Using global Sentinel-1 radar backscatter data, we systematically map the locations of glaciers with surge-type activity during 2017–22. Patterns of pronounced increases or decreases in the strongest backscatter between two winter seasons often indicate large changes in glacier crevassing, which we treat here as a sign of surge-type activity. Validations against velocity time series, terminus advances and crevassing found in optical satellite images confirm the robustness of this approach. We find 115 surge-type events globally between 2017 and 2022, around 100 of which on glaciers already know as surge-type. Our data reveal a pronounced spatial clustering in three regions, (i) Karakoram, Pamirs and Western Kunlun Shan (~50 surges), (ii) Svalbard (~25) and (iii) Yukon/Alaska (~9), with only a few other scattered surges elsewhere. This spatial clustering is significantly more pronounced than the overall global clustering of known surge-type glaciers. The 2017–22 clustering may point to climatic forcing of surge initiation.

Glacial quarrying stems from the fracturing of subglacial bedrock. Much evidence shows that subcritical crack propagation of bedrock is closely related to subglacial water pressure fluctuations. Here we employ a model that assesses the impact of subglacial water pressure fluctuation on cavity length and subcritical crack propagation, while analyzing the effect of a pre-existing crack location using a phase-field model (PFM). Our results indicate that the cavity length is reduced during diurnal fluctuations in water pressure. There are two patterns of subcritical crack propagation on the corner of the step. The first stems from a rapid drop in water pressure. The second occurs after the water pressure recovers from the fluctuation to the initial steady state. This pattern is a consequence of enhanced stress concentration on the step since the modeled cavity length exceeds its steady value and has higher efficiency in promoting subcritical crack propagation. Additionally, based on the PFM results, we speculate that the subcritical crack initiation and propagation happen on a broader scale, including the ice-bed contact region and its adjacent region. Our findings imply that the duration of subcritical crack propagation is short and typically ceases once the cavity length adjusts to reduced water pressure levels.

We recently reported on the radio-frequency attenuation length of cold polar ice at Summit Station, Greenland, based on bi-static radar measurements of radio-frequency bedrock echo strengths taken during the summer of 2021. Those data also allow studies of (a) the relative contributions of coherent (such as discrete internal conducting layers with sub-centimeter transverse scale) vs incoherent (e.g. bulk volumetric) scattering, (b) the magnitude of internal layer reflection coefficients, (c) limits on signal propagation velocity asymmetries (‘birefringence’) and (d) limits on signal dispersion in-ice over a bandwidth of ~100 MHz. We find that (1) attenuation lengths approach 1 km in our band, (2) after averaging 10 000 echo triggers, reflected signals observable over the thermal floor (to depths of ~1500 m) are consistent with being entirely coherent, (3) internal layer reflectivities are ≈–60$\to$–70 dB, (4) birefringent effects for vertically propagating signals are smaller by an order of magnitude relative to South Pole and (5) within our experimental limits, glacial ice is non-dispersive over the frequency band relevant for neutrino detection experiments.

A 198.8 m deep borehole was drilled through ice to subglacial bedrock in the northwestern marginal part of Princess Elizabeth Land, ~12 km south of Zhongshan Station, in January–February 2019. Three years later, in February 2022, the borehole temperature profile was measured, and the geothermal heat flow (GHF) was estimated using a 1-D time-dependent energy-balance equation. For a depth corresponding to the base of the ice sheet, the GHF was calculated as 72.6 ± 2.3 mW m−2 and temperature −4.53 ± 0.27°C. The regional averages estimated for this area based, generally, on tectonic setting vary from 55 to 66 mW m−2. A higher GHF is interpreted to originate mostly from the occurrence of metamorphic complexes intruded by heat-producing elements in the subglacial bedrock below the drill site.

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.

Convolutional neural networks (CNN) trained from high-order ice-flow model realisations have proven to be outstanding emulators in terms of fidelity and computational performance. However, the dependence on an ensemble of realisations of an instructor model renders this strategy difficult to generalise to a variety of ice-flow regimes found in the nature. To overcome this issue, we adopt the approach of physics-informed deep learning, which fuses traditional numerical solutions by finite differences/elements and deep-learning approaches. Here, we train a CNN to minimise the energy associated with high-order ice-flow equations within the time iterations of a glacier evolution model. As a result, our emulator is a promising alternative to traditional solvers thanks to its high computational efficiency (especially on GPU), its high fidelity to the original model, its simplified training (without requiring any data), its capability to handle a variety of ice-flow regimes and memorise previous solutions, and its relatively simple implementation. Embedded into the ‘Instructed Glacier Model’ (IGM) framework, the potential of the emulator is illustrated with three applications including a large-scale high-resolution (2400x4000) forward glacier evolution model, an inverse modelling case for data assimilation, and an ice shelf.

We present a Simple Lake Ice Model to calculate the growth rate of lake ice in a cold and relatively dry climate. The focus is on Lake St. Moritz, Switzerland, which has an area of 0.78 km2 and is about 45 m deep. In winter the lake is extensively used for recreational purposes, including horse racing with thousands of spectators. Safety on the ice cover is essential, and there is a great need to have a simple tool with which the growth rate of the ice layer can be calculated for given meteorological conditions. The approach is based on a simple formulation of the upper temperature of the ice layer, which depends on air temperature and snow cover. Input data are the date on which the lake freezes over, daily mean air temperatures and snow depth. For the winter 2021/22 calculated ice growth compares well with ice thickness measurements. We demonstrate that grooming of the snow has a significant positive effect on the ice thickening rate. We also evaluate the sensitivity of the simulated ice thickness to increasing mean temperature.

Our limited knowledge of the climate prevailing over Europe during former glaciations is the main obstacle to reconstruct the past evolution of the ice coverage over the Alps by numerical modelling. To address this challenge, we perform a two-step modelling approach: First, a regional climate model is used to downscale the time slice simulations of a global earth system model in high resolution, leading to climate snapshots during the Last Glacial Maximum (LGM) and the Marine Isotope Stage 4 (MIS4). Second, we combine these snapshots and a climate signal proxy to build a transient climate over the last glacial period and force the Parallel Ice Sheet Model to simulate the dynamical evolution of glaciers in the Alps. The results show that the extent of modelled glaciers during the LGM agrees with several independent key geological imprints, including moraine-based maximal reconstructed glacial extents, known ice transfluences and trajectories of erratic boulders of known origin and deposition. Our results highlight the benefit of multiphysical coupled climate and glacier transient modelling over simpler approaches to help reconstruct paleo glacier fluctuations in agreement with traces they have left on the landscape.

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.

The hypothesis that ice-sheet evolution is only controlled by the long-term non-Newtonian viscous behavior of ice has been challenged by observations indicating that effects like brittle failure, stick-slip sliding, tides and wave action may affect ice-sheet evolution on sub-daily timescales. Over these timescales, the quasi-static-creep approximation is no longer appropriate and elastic effects become important. Simulating elastic effects in ice-sheet models over relevant timescales, however, remains challenging. Here, we show that by including a visco-elastic rheology and reintroducing the oft neglected acceleration term back into the ice-sheet stress balance, we can create a visco-elastic system where the velocity is locally determined and information propagates at the elastic wave speed. Crucially, the elastic wave speed can be treated like an adjustable parameter and set to any value to reproduce a range of phenomena, provided the wave speed is large compared to the viscous velocity. We illustrate the system using three examples. The first two examples demonstrate that the system converges to the steady-state viscous and elastic limits. The third example examines ice-shelf rifting and iceberg calving. This final example hints at the utility of the visco-elastic formulation in treating both long-term evolution and short-term environmental effects.

From 2017 to 2020, three significant calving events took place on Pine Island Glacier, West Antarctica. Ice-shelf velocities changed over this period and the calving events have been suggested as possible drivers. However, satellite observations also show significant changes in the areal extent of fracture zones, especially in the marginal areas responsible for providing lateral support to the ice shelf. Here, we conduct a model study to identify and quantify drivers of recent ice-flow changes of the Pine Island Ice Shelf. In agreement with recent studies, we find that the calving events caused significant velocity changes over the ice shelf. However, calving alone cannot explain observed velocity changes. Changes in the structural rigidity, i.e. ice damage, further significantly impacted ice flow. We suggest that ice damage evolution of the ice-shelf margins may have influenced recent calving events, and these two processes are linked.

We present a method for tracking radio-tagged pebbles and cobbles through subglacial meltwater channels under shallow temperate glaciers. Natural particles tagged with active radio transmitters were injected directly into a large subglacial channel 300 m up-glacier from the terminus of the Glacier d'Otemma, Switzerland. A roving antenna was developed to localise tagged particles planimetrically in subglacial and proglacial channel reaches (350 and 150 m long, respectively) using a probabilistic technique, delivering records of the change in particle location and transport distance over time with uncertainty. The roving antenna had a ±5−15 m planimetric precision, a 75% particle localisation rate and operated at a maximum ice depth of 47 m. Additionally, stationary supraglacial and proglacial antennas continuously monitored the passage of tagged particles through consecutive reaches of the channel, constraining the timing of particle transport events. The proglacial antenna system had a 98.1% detection rate and was operational to 0.89 m water depth during testing. Roving and stationary antenna records were combined to create a transport distance model for each particle, which may be used in conjunction with hydraulic data to investigate the kinematics of particle motion. When applied at scale in future studies, this method may be used to reveal the mechanisms and timescales of coarse sediment export from Alpine glaciers.

Ice-crystal fabric can induce mechanical anisotropy that significantly affects flow, but ice-flow models generally do not include fabric development or its effect upon flow. Here, we incorporate a new spectral expansion of fabric, and more complete description of its evolution, into the ice-flow model Elmer/Ice. This approach allows us to model the effect of both lattice rotation and migration recrystallization on large-scale ice flow. The fabric evolution is coupled to flow using an unapproximated non-linear orthotropic rheology that better describes deformation when the stress and fabric states are misaligned. These improvements are most relevant for simulating dynamically interesting areas, where recrystallization can be important, tuning data are scarce and rapid flow can lead to misalignment between stress and fabric. We validate the model by comparing simulated fabric to ice-core and phase-sensitive radar measurements on a transect across Dome C, East Antarctica. With appropriately tuned rates for recrystallization, the model is able to reproduce observations of fabric. However, these tuned rates differ from those previously derived from laboratory experiments, suggesting a need to better understand how recrystallization acts differently in the laboratory compared to natural settings.

Stable water isotope records of six firn cores retrieved from two adjacent plateaus on the northern Antarctic Peninsula between 2014 and 2016 are presented and investigated for their connections with firn-core glacio-chemical data, meteorological records and modelling results. Average annual accumulation rates of 2500 kg m−2 a−1 largely reduce the modification of isotopic signals in the snowpack by post-depositional processes, allowing excellent signal preservation in space and time. Comparison of firn-core and ECHAM6-wiso modelled δ18O and d-excess records reveals a large agreement on annual and sub-annual scales, suggesting firn-core stable water isotopes to be representative of specific synoptic situations. The six firn cores exhibit highly similar isotopic patterns in the overlapping period (2013), which seem to be related to temporal changes in moisture sources rather than local near-surface air temperatures. Backward trajectories calculated with the HYSPLIT model suggest that prominent δ18O minima in 2013 associated with elevated sea salt concentrations are related to long-range moisture transport dominated by westerly winds during positive SAM phases. In contrast, a broad δ18O maximum in the same year accompanied by increased concentrations of black carbon and mineral dust corresponds to the advection of more locally derived moisture with northerly flow components (South America) when the SAM is negative.