Refreezing is a critical component of the mass balance of glaciers in Svalbard, yet the processes and changes under a warming climate are not fully understood. Here, we investigate changes in firn properties of the Austfonna ice cap, Svalbard, using a combination of observations and model simulations. We analyze firn stratigraphy and density from five newly retrieved and 11 previously retrieved firn cores, collected at elevations ranging from 506 m a.s.l. to 791 m a.s.l. between 1958 and 2022. All cores exhibit frequent ice layers that indicate persistent refreezing of meltwater; however, no ice slabs (layers exceeding 1 m) were observed. A 13-year-long firn temperature time series from a site near the summit (773 m a.s.l.) shows that annual water percolation reaches depths of 7 m to over 13 m. A notable transition in the firn thermal regime occurred in 2013, transitioning from cold to temperate conditions above the firn-ice interface despite the seasonal cooling occurring in the upper firn layers. Simulations using the CryoGrid community model from 2009 to 2022 corroborate this thermal shift and suggest the development of a firn aquifer multiple times since 2013, with increasing duration and thickness over time.

Accelerated glacier mass loss across the Antarctic Peninsula has consequences for sea level rise and local ecology. However, there are few direct glaciological observations available from this region. Here, we reveal glacier changes on the James Ross Archipelago between 2010 and 2023. The median rate of glacier area loss (remote-sensing derived) increased over the study period, with the most significant changes observed in smaller glaciers. In situ measurements show that ablation has prevailed since 2019/20 with the most negative point surface mass balance change measured as −1.39 ± 0.12 m water equivalent at Davies Dome and Lookalike Glacier in 2022/23 (200–300 m a.s.l.). We identified a tripling of the frontal velocity of Kotick Glacier in 2015, which, combined with terminus surface elevation gains (bulging), suggests that this is the first surge-type glacier identified in Antarctica from velocity and surface elevation change observations. We contend that the glacier recession rate has increased due to increased air temperatures (0.24 ± 0.08°C yr−1, 2010–23), decreased albedo and glacier elevation change feedbacks. These processes could decrease glacier longevity on the archipelago. Future research should prioritise monitoring albedo and rising equilibrium-line altitudes and identify glaciers most vulnerable to rapid future mass loss.

The climatic conditions, particularly the sources of precipitation that enabled extensive glacial growth during the Last Glacial Maximum (LGM) in the European Alps, remain poorly constrained. Here, we apply an inversion method to reconstruct equilibrium line altitude (ELA) fields using glacier footprints, such as the moraines deposited by Alpine glaciers during the LGM. By employing a machine-learning emulator trained on outputs from a glacier-evolution model, we predict glacier maximal thickness. The emulator is integrated into a gradient-based inversion scheme to derive ELA fields consistent with LGM footprints. The results show that the reconstructed ELA fields align with those from previous studies, validating the robustness of our approach. Unlike existing inversion methods, our approach is more general and avoids restrictive assumptions. Notably, by incorporating the transient response of glaciers to climate variability (we do not assume steady state), we show that the cold spell period is crucial for interpreting the reconstructed climate patterns—an aspect previously overlooked. Our findings provide new insights into climatic variability during the LGM, particularly concerning the interaction between precipitation patterns and the cold spell period. Furthermore, the computational efficiency of our method makes it applicable to large-scale paleoclimate reconstructions based on glacier footprints.

We conduct an ensemble of simulations of the englacial temperature field of the Antarctic ice sheet to gauge the sensitivity to uncertainties in geothermal heat flow, surface climatic conditions, ice thermodynamics and dynamics. We compare the modeled temperature fields with observational constraints, including deep-borehole temperature measurements, englacial temperatures retrieved from the Soil Moisture and Ocean Salinity satellite observations, and the distribution of subglacial lakes to determine the most likely boundary conditions. Results show that temperate basal conditions prevail over 60% of the Antarctic ice sheet, with a mean basal melt rate of 6.9 mm a−1. The ensemble mean subglacial meltwater production over the grounded ice sheet is 69 Gt a−1, with a contribution of 51% from geothermal heat and 49% from frictional heat. While geothermal heat flow remains the largest source of uncertainty, heat flow datasets leading to colder conditions tend to fit englacial temperature measurements better. However, ice thermomechanical approximations influence the shape of temperature profiles and may, in some cases, be more important than the geothermal heat flow. Furthermore, since frictional heat contributes significantly to basal melt in regions hosting fast-flowing glaciers, uncertainties in basal slipperiness affect the basal melt estimates as much as the geothermal heat flow.

Recent ice cores from the Allan Hills, a blue ice area in Antarctica, are nearly 3 million years old. These cores extend ice core chronologies, enabling new insight into key climate periods such as the Mid-Pleistocene Transition. The interpretation of these climate records is complex because of the disturbed stratigraphy in this ice. Here, we present a new three-dimensional multitrack electrical conductivity measurement method (3D ECM) to resolve layer structure. We demonstrate this technique on a cumulative 60 m of two large-diameter (241 mm) ice cores, ALHIC2201 and ALHIC2302. Measurements were taken on the upper section of both cores due to better ice core quality in this shallow ice. We find well-defined and dipping layering in both cores, averaging 29° in ALHIC2201 and 69° in ALHIC2302 from horizontal. We observe a slight decrease in dip with depth in both cores, although it only achieves statistical significance in ALHIC2302. We discuss how this new method can be applied to enable accurate, high-resolution multi-proxy record development even in ice cores with steeply dipping layers. 3D ECM improves interpretation of blue ice area cores by providing accurate, non-destructive constraints on stratigraphy.

Using ICESat-2 and ArcticDEM strips we track height change in a glacial basin in northern Ellesmere Island Canada. The surface topography dips towards the middle of the basin and ArcticDEM differences show a 1–3 m increase in 2020 summer surface height over an area of 8–10 km2. ICESat-2 heights confirm that each melt season (2019–2024), the height change of melt water at the basin edge matches that over ice in the basin middle. The summer height increase happens at the same time as an upstream drop in surface elevation suggesting yearly episodic subglacial water movement from upstream to a downstream subglacial lake. Melt water drainage occurs in the fall to a particular elevation and apparently follows a path at the northern edge of the basin. These data illustrate subglacial melt water movement both spatially and temporally in rarely obtained detail and are consistent with data from two NASA IceBridge passes.

The mixture of icebergs and sea ice in tidewater glacier fjords, known as ice mélange, is postulated to impact iceberg calving directly through physical buttressing and indirectly through freshwater fluxes altering fjord circulation. In this contribution, we assess the textural characteristics of ice mélange in summer and winter at the terminus of Helheim Glacier, Greenland, using high resolution (1-3 m) X-band Synthetic Aperture Radar (SAR) imagery from the ICEYE small satellite constellation. The Grey Level Co-occurrence Matrix (GLCM) and statistical variations in pixel intensity downfjord reveal structural zoning within the mélange matrix in both summer and winter. The boundary between these zones represents the transition between ice concentrations, demonstrating structural weaknesses in the mélange that may persist throughout the year. Furthermore, we compare two iceberg segmentation methods, texture-based vs the Segment Anything Model (SAM). Both techniques detect large (> 0. 1 km2) icebergs in summer when pixel variations are larger, but SAM has high iceberg detection accuracy in both seasons. The detected icebergs stabilise near concentration boundaries in the mélange, suggesting they act as the nucleus of mélange zones and control matrix stability. Our study demonstrates the potential for using high-resolution ICEYE SAR imagery for studying dynamic processes in glaciology and beyond.

Submarine glacier melt rates of the Greenland Ice Sheet remain a major uncertainty in climate model projections of future sea level rise. Development of submarine melt parameterizations has to a high degree relied on ocean circulation modelling of glacial fjords, designed to quantify effects such as ocean thermal forcing and fjord–glacier geometry. Greenlandic fjords are relatively narrow, and it is frequently assumed that across-fjord flow variations are small enough to allow marine melt to be quantified with two-dimensional ocean-circulation models. Here, we present three-dimensional model simulations showing that the interplay between fjord–glacier geometry, side wall friction, and Earth’s rotation makes the circulation in ice-shelf cavities three-dimensional even in narrow fjords. Remarkably, we find that Earth’s rotation changes the flow pattern in the cavity below the ice shelf, leading to a decrease in the marine melt on a 10 km wide ice shelf by a factor of five compared to a non-rotating simulation. Our study prompts using three-dimensional model configurations of Greenlandic fjords.

Ice crystal fabrics can exert significant rheological control on ice sheets and ice shelves, potentially softening or hardening anisotropic ice by several orders of magnitude compared to isotropic ice. We introduce an anisotropic extension of the Shallow Shelf Approximation (SSA), allowing for fabric-induced viscous anisotropy to affect the flow of ice shelves in coupled, transient simulations. We show that the viscous anisotropy of synthetic ice shelves can be parameterized using an isotropic flow enhancement factor, suggesting that existing SSA flow models could, with little effort, approximate the effect of fabric on flow. Next, we propose a new way to directly solve for SSA fabric fields using satellite-derived velocities, assuming velocities are approximately steady and that fabric evolution is dominated by lattice rotation with or without discontinuous dynamic recrystallization. We apply our method to the Ross and Pine Island ice shelves, Antarctica, suggesting that these regions might experience significant fabric-induced hardening and softening depending on the relative strength of lattice rotation and recrystallization. Our results emphasize the ice-dynamical relevance of needing to better constrain the strength of fabric processes. This calls for more widespread fabric and temperature measurements from the field, since measurements are currently too sparse for model validation.

Assessing glacier surface mass balance (SMB) is essential for evaluating glacier response to climate change. However, traditional in situ measurement methods are labour intensive and often lack the temporal and spatial resolutions required to fully constrain SMB models. Here, we explore the potential of the Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique which exploits reflected satellite signals to track surface height changes for continuous SMB estimation. Using data from 13 GNSS stations operating between 2019 and 2021 on Glacier d’Argentière (French Alps), we compare GNSS-IR-derived SMB with estimates from snow pits, wooden stakes, continuous ice-melt measurements using a SmartStake device, and a degree-day model. We demonstrate that the GNSS-IR technique can reliably estimate SMB values that closely match independent in situ measurements, while also offering the advantages of spatial integration and long-term time series that capture both snowfall events and snow/ice melt. We show that glacier surface roughness and antenna height, when the glacier is snow-free, strongly influence uncertainties, which can be reduced to as little as 2 cm d−1 using a smoothing filter. Finally, we demonstrate that the GNSS-IR technique can further constrain the degree-day factor, particularly its temporal evolution throughout the ablation season.

Ice shelves regulate ice sheet dynamics, with their stability influenced by horizontal flow and vertical flexure. MacAyeal and others (2021) developed the theoretical foundation for a coupled flow-flexure model (the “M21 model”), combining the Shallow Shelf Approximation with thin-beam flexure, providing a computationally efficient tool for studying phenomena like ice shelf rumpling and lake drainage. However, the M21 model relies on proprietary software, is unstable under compressive flow conditions, and does not incorporate fracture processes critical for capturing ice-shelf damage evolution. We present an open-source version of the M21 model addressing these limitations. Using the free Python libraries Firedrake and icepack, we introduce a plastic failure mechanism, effectively limiting bending stresses and thereby stabilizing the model. This enhancement expands the viscous M21 model into a viscoplastic flow-flexure-fracture (3F) framework. We validate the 3F model through test cases replicating key ice shelf phenomena, including marginal rumpling and periodic surface meltwater drainage. By offering this tool as open-source software, we aim to enable broader adoption, with the ultimate aim of representing surface meltwater induced flow-flexure-fracture processes in large-scale ice sheet models.

Lake-terminating glaciers retreat and thin faster than land-terminating glaciers, yet their long-term dynamics remain underexplored. Using multi source–remote sensing data combined with glacier velocity and elevation change datasets, we investigated their distribution and evolution in the Himalaya and Southeastern Tibet from 1990 to 2020. By 2020, 577 lake-terminating glaciers (2561.5 ± 11.8 km2) had been identified, representing ∼2% of all glaciers by number and ∼10% by area. Of these, 246 glaciers maintained contact with proglacial lakes (Type 1 change), while 331 developed new lakes (Type 2 change). Additionally, 173 glaciers detached from lakes (Type 3 change). Variations in glacier–lake contact strongly modulate glacier dynamics. Type 1 change glaciers experienced the largest area loss (73.8 ± 13.1 km2), whereas Type 2 change glaciers showed the greatest average retreat distance (1.06 ± 0.05 km). Among Type 1 change glaciers (>5 km2) with significant velocity trends, 22% accelerated and 78% decelerated, while all Type 3 change glaciers with significant velocity trends consistently decelerated. These findings underscore the pivotal influence of proglacial lake evolution on glacier dynamics, advancing our understanding of glacier–lake interactions on the Tibetan Plateau and beyond.

Glacier algae are relevant factors in the darkening phenomenon of glaciers, especially at the margins of the ice sheets. This study focuses on glacier algae variation during summer seasons in the 2016–2023 period at Qaanaaq Ice Cap, NW Greenland. Based on ice samples and field spectroscopy measurements, an empirical model is proposed to estimate glacier algae abundance from a reflectance ratio (695/687 or 695/681 nm). By applying this method to Sentinel-2 data at high resolution (10 m), through a phenology approach, algae abundance variation was estimated in relation to glaciological parameters and a marked spatial and temporal heterogeneity was found. High algae concentrations were found in the 2019, 2020 and 2023 summer seasons (∼1 × 106 cells mL−1 on average) especially at low elevations (<800 m a.s.l.). At the scale of an outlet glacier, strong algal blooms were observed with more than one month of continuous positive air temperature and hiatus of snowfalls. The present research represents one of the first estimations of glacier algae phenology for the high latitudes at this high spatial resolution. These results could set the stage for future research focused on understanding the role of glacier algae at the scale of the Greenland Ice Sheet.

Accurate knowledge of basal topography is required for numerical modelling efforts to predict how Earth’s ice sheets will respond to continued warming. The widely used BedMachine v3 dataset has limitations with respect to its use in modelling studies, particularly in estimating uncertainties. Machine learning approaches offer promise in addressing this gap, with quantile regression forests (QRFs) especially suited to geospatial data. Here, we apply a novel QRF approach to map the basal topography of Greenland’s ice sheet using airborne radio echo sounding (RES) data. Compared to BedMachine, our model reduces the root-mean-squared-error of ice depth predictions by 18%, from 232 to 190 m. It also significantly improves uncertainty calibration: 89.8% of new observations fall within our 90% prediction interval, versus 68% for BedMachine. The QRF model achieves a lower continuous ranked probability score (92 m vs. 130 m), indicating improved balance between accuracy and uncertainty. Our volume estimate for the Greenland ice sheet is 0.7% higher than BedMachine’s, though we emphasise differences in the predicted shape of subglacial features like outlet glacier troughs. This approach offers a computationally efficient, accessible method for deriving subglacial topography from RES data, while providing better-calibrated uncertainty estimates than existing models.

Since the 1990s, Pine Island Glacier (PIG) has been a focal point of research due to its vulnerability within the West Antarctic Ice Sheet. Decades of research have interrogated this dynamic glacier system with a focus on its main trunk and the ice shelf section bordering and stabilizing PIG to the south (the ‘south shelf’), receiving comparatively less attention. Using satellite-derived observations from 2017 to 2023, we document marked dynamic changes on the south shelf, particularly following PIG’s 2018 calving event, which removed >60 km2 of ice from this section. Measurements of surface deformation, ice velocity and strain rates from synthetic aperture radar and optical imagery show localized acceleration and structural weakening of the south shelf near-coincident with this loss. Our findings, highlighting the role of peripheral ice shelves in glacier-system stability, suggest that PIG’s new configuration—characterized by weakening margins and a compromised south shelf—may result in a geometry that grows progressively unstable.

Understanding the behaviour of domes under both contemporary and historical environmental conditions is essential to facilitate the study of dome-divide dynamics and the interpretation of ice core records. This paper presents nearly 20 years of Global Navigation Satellite System observations at Dome C in East Antarctica, focusing on ice velocity and accumulation rates. The 38 measuring poles established in 1996 for the EPICA Dome C project were surveyed three times in 18 years. The data analysis indicates alterations in ice velocity patterns, including a horizontal velocity shift across the dome and a dynamic summit migration of about 100 m a−1. Specifically, increases in velocity on the southeastern slope were counterbalanced by a similar reduction in the northwestern sector. These changes are likely related to variations in accumulation distribution as indicated by snow radar measurements and shifts in the drainage basin of the Byrd Glacier. Furthermore, a 10% alteration in snow accumulation rates at Dome C over the past decade compared with previous centuries was observed, accompanied by an elevation increase of about 3.5 mm a−1. The recent findings of the Beyond EPICA – Oldest Ice (BE-OI) project highlight the minimal perturbations of the climate signal on the ice core, attributable to glaciological variability at the dome position.

Over the past two decades, the Canadian Arctic Archipelago has undergone significant glacier mass loss, driven primarily by surface melt. This study presents a detailed analysis of supraglacial drainage evolution along Ellesmere Island’s ∼830 km latitudinal extent using satellite imagery, historical aerial photographs and DEMs from 1959 to 2020. Analysis of five glaciers shows that drainage density (Dd) has increased over time, driven by the expansion of perennial rivers, especially at higher elevations. Far northern glaciers exhibit stable, well-developed drainage systems, while southern glaciers show a relatively greater increase in canyon development since 1959. Cold surface ice in the north supports higher Dd, while southern glaciers with extensive sinks (moulins and large crevasses) exhibit stronger surface-to-bed connectivity. Despite increased channelization, sinuosity changes remain statistically insignificant, reflecting dynamic canyon behavior governed by surface slope and meltwater discharge. Results align with modeled increases in melt, especially on southern glaciers where supraglacial systems have expanded most rapidly. Continued equilibrium line altitude rise under future warming is expected to intensify melt and result in the expansion of supraglacial drainage systems up-glacier, particularly for glaciers with large amounts of ice at mid-elevation.

Glide-snow avalanches release at the soil-snow interface and are currently difficult to predict. This is mostly due to a limited understanding of the release process and a lack of data, particularly of the snowpack and underlying soil conditions prior to release. Here, we synthesize the current process understanding on the source of interfacial water—a key factor in glide-snow avalanche release—in a simple explanatory model. The model classifies days with and without glide-snow avalanche activity using thresholds applied to proxies including snow liquid water content (LWC), soil temperature, soil LWC and meteorological parameters. These proxies were measured on Dorfberg (Davos, Switzerland) in the 2021/22 to 2023/24 seasons. The best-performing thresholds for the snow, soil and meteorological time series were determined through quasi-random sampling and were in line with previous field studies. Soil temperature and snow LWC were the most relevant variables to explain avalanche occurrence. These results demonstrate the importance of combining snow, soil and meteorological data for improving the forecasting of glide-snow avalanche activity.

Ice islands, massive tabular icebergs, are known to fracture as they drift. The footloose mechanism occurs when a large protuberance, known as a ram, develops along the submerged edge of the ice island and induces a buoyancy-driven bending stress. This study investigates the relationship between rams and footloose fracture using finite element models of ice islands with simulated underwater rams. Geospatial polygons of ice islands, derived from remote sensing imagery, were used to create three-dimensional shapes of ice islands at two thicknesses and with various ram sizes. Then, the location of maximum stress and fractures were predicted using finite element analysis (FEA) and the results were compared to remote sensing observations of the actual fractured pieces that calved from each of the 26 modelled ice islands. Accurate simulations of calving were achieved when a synthesized ram was placed along the ice island edge where the calving was observed. An empirical model was developed to predict the magnitude of stress from various ram sizes and shapes. The predictive ability of this empirical model suggests that ice island calving models can be improved and combined with drift forecasting models to help mitigate risks to offshore infrastructure and seafaring vessels.