Continued deglaciation in the Bolivian Andes threatens regional water security and may result in increased exposure to geohazards. We analyse high spatial resolution (∼3–5 m) satellite imagery to constrain annual glacier and glacial lake evolution across the Bolivian Andes between 2016 and 2022. The total glaciated area of the region decreased by 9.1%, from 316.6 ± 3.2 km2 to 287.8 ± 2.9 km2; a rate of loss of 4.8 km2 a−1. Concurrently, the number (total surface area) of glacial lakes increased by 2.6% (1.9%), from 704 (37.1 ± 0.7 km2) to 770 (37.8 ± 0.8 km2). A comprehensive glacial lake outburst flood susceptibility analysis was undertaken for the 2022 lake inventory, with eleven lakes identified as ‘high susceptibility’. Subglacial topographic analysis was undertaken to predict potential future sites for lake formation. We identified 55 such sites given continued deglaciation. The model was tested by applying it to areas where glaciers retreated between 2000 and 2022. Of the 22 potentially susceptible lakes which formed during this period, 14 (64%) did so in overdeepenings identified by the model. This is the first time that an inventory of potential future lake sites has been produced for the region.

Englacial layers are a product of historic accumulation and are reshaped by ice deformation. Hence, radio-echo sounding (RES), which can resolve englacial layering, has been adopted as an observational tool to infer ice age and ice dynamics from ice stratigraphy. However, the commonly applied synthetic aperture radar focusing algorithms, used to improve image resolution, are either i) incoherent or ii) optimized for the ice-bed interface. Dipping specular reflectors, such as englacial layers, are then lost during focusing. Instead, we focus the RES measurements using subapertures, synthetically squinting the radar beam toward orthogonal incidence for every dipping layer. We then either recombine all subapertures or reject those with low signal to generate an image that resolves all englacial targets together. We apply these methods to both along- and across-flow RES images at Academy Glacier, East Antarctica, which has significant englacial layer relief, especially perpendicular to the ice-flow direction. Our method significantly elevates signal power for dipping englacial layers ($ \gt $15 dB), and quantifiably improves layer continuity compared to other processed data products. This squinted focusing approach enables novel studies of ice deformation (as recorded in englacial layering) in the presence of complex basal topography and heterogeneous substrate properties.

We have been conducting mass-balance monitoring on Aldegondabreen since the early 21st century. Over the most recent five year period (2019/20–2023/24), the glacier has experienced its most negative mass balance, averaging −2.0 m w.e. a−1. This dramatic loss is linked to rising air temperatures, with several of the warmest years on record for the Arctic land occurring during this interval. In 2024, for the first time, the critical threshold of 1.5°C above pre-industrial levels was exceeded globally, and this resulted in the lowest annual balance observed since the beginning of our monitoring program (−2.48 m w.e. a−1). Archival evidence indicates that such intense melting is unprecedented since at least 1911, which marked the end of the Little Ice Age in the region. As of 2025, the glacier’s mean ice thickness has been estimated at 39 m (33 m w.e.) meaning that the loss of 10 m w.e. in just the last five years is an enormous change.

The difference between the ice and water pressures, or the effective pressure, influences water flow and sliding at the ice-bed interface. Effective pressure is typically quantified with subglacial hydrology models because direct measurements of the subglacial environment are sparse. Active subglacial lakes provide an opportunity to constrain effective pressures with altimetry because subglacial water-volume changes manifest at the ice-sheet surface as elevation-change anomalies. Here, we develop a method for estimating effective pressures from altimetry data above active subglacial lakes. We synthesise a previous theory of subglacial lake effective pressure with an altimetry-based inverse method that relates elevation-change data to water-volume changes. We apply the method to elevation-change data from NASA’s ICESat-2 satellite altimetry mission over several active lakes in Antarctica. We find that deviations from flotation (zero effective pressure) are typically a negligible fraction of the overburden (e.g., $\sim$10 kPa), although larger deviations can arise when the ice viscosity is large. For example, effective pressures over subglacial lake Byrds10 in East Antarctica locally reached magnitudes on the order of the tensile strength of glacier ice (e.g., over 100 kPa). These effective pressure estimates can constrain subglacial hydrology models in regions with active subglacial lakes and provide new insights into glacier-bed dynamics.

We present an initial assessment of all-season Arctic sea ice thickness estimates from ICESat-2 by combining freeboard retrievals with all-season SnowModel-LG snow loading. ICESat-2 captures the key regional and seasonal patterns of Arctic sea ice variability and shows good agreement with CryoSat-2 all-season estimates, including regional patterns of inter-annual variability in summer ice thickness. ICESat-2 shows consistently thicker ice compared to CryoSat-2 across the western coastal Arctic, while CryoSat-2 shows some periods of thicker ice across the Central Arctic, largely consistent with winter thickness biases. Validation against upward-looking sonar moorings, IceBird-2019 airborne observations and MOSAiC buoy data highlights generally strong performance across a range of conditions, although seasonal biases linked to snow loading, freeboard differences and ice density assumptions persist. The SnowModel-LG and NESOSIM snow accumulation models perform well across the validation datasets, but do not consistently add skill beyond the modified Warren climatology. Experimental ICESat-2/CryoSat-2 dual altimetry winter snow depths show strong performance relative to existing products and future work should extend these into summer for further assessments. Overall, our analysis supports the viability of an all-season ICESat-2-derived thickness record.

Ground-based time-lapse cameras are often used to monitor glacier recession, which is primarily driven by the falling of ice from the glacier front, known as iceberg calving or, more commonly, calving events. Glaciologists can utilise these images by manually identifying calving events, a laborious task that requires the analysis of thousands of images in order to identify image pairs that represent the glacier front before, during and after calving. We present a computer vision based method to filter out images rendered unusable due to weather effects such as fog and precipitation by calculating the number of salient key-points detected in the image using the SIFT (Scale-Invariant Feature Transform) algorithm as an indicator of the visibility of the glacier front and discarding any image with fewer key-points than a defined threshold. We propose the use of SNN (Siamese neural network) and show that it is useful in detecting calving events since it allows to separately calculate features on two images and then merges them together in order to track differences between them thus detecting calving areas. The trained model achieved an overall accuracy of 92%, with 79% of calving events and 93% of non-calving being correctly classified on an unseen test set formed from imagery in the same time period as the training data. The model was able to generalise to new time periods (and therefore small changes in viewpoint and alignment) to some extent with an overall accuracy of 82%, with 27% of calving events and 90% of non-calving being correctly classified.

Polarimetric multi-offset radio-echo sounding offers improved constraints on englacial thermal conditions, basal properties and ice crystal orientation compared to standard monostatic observations. Nevertheless, such surveys are uncommon in glaciology and are typically limited in offset due to cable losses. In the 2023–24 austral summer, we deployed two radar systems on Eastwind Glacier and the McMurdo Ice Shelf in Antarctica, collecting five polarimetric common-midpoint (CMP) surveys. Using an Autonomous phase-sensitive Radio-Echo Sounder (ApRES), modified with off-the-shelf radio frequency-over-fiber (RFoF) hardware and a low-loss fiber optic link, we detect bed reflections at offsets up to the equivalent of four ice thicknesses, well beyond the theoretical point of total internal reflection. A second, cable-less system built around a software-defined radio (SDR) was deployed simultaneously as an unsynchronized receiver recording the same ApRES transmitter. These co-located datasets demonstrate the potential for cabled radar systems with integrated RFoF technology for extending maximum offsets by overcoming attenuation losses inherent to coaxial cables. Furthermore, we perform polarimetric amplitude-vs-offset analysis to probe glacier dielectric structure. Finally, we present data from deployment of the fiber optic system on Thwaites Glacier, where we detect bed reflections at an offset of 4 km, demonstrating operation on thick ice (~2.2 km).

Understanding ice flexural behavior is essential for assessing interactions with structures in cold environments. The mechanical response of ice depends on microstructural properties, such as grain size and porosity, which vary widely in natural ice. Existing bending test data often lack detailed microstructural characterization, making it difficult to interpret or generalize the results. In brittle materials such as concrete or rock, pores commonly act as failure-initiating defects. Therefore, porosity (pore size, shape and density) should be considered a key parameter when studying ice fracture. Here, we provide a robust set of bending experiments on well-controlled isotropic polycrystalline ice microstructures and investigate the role of porosity in ice failure. Two porosity levels were studied, characterized at high resolution by micro-computed X-ray tomography. Analyzing the bending failure by means of the Weibull model reveals that the sample failure is initiated by different defect populations, in relation to the porosity. Providing that the Griffith/Irwin failure criterion can be applied, the measured pore distribution allows the prediction of a critical stress for defect activation. Compared with measured failure stress, this prediction enables discriminating the defect population responsible for failure and offers a mechanistic interpretation of the volume effect observed in porous ice flexural strength.

To address the scarcity of data on compacted snow shear damage under complex conditions, unconfined shear tests were conducted in Northeast China. This study examined apparent shear strength variations with density (300–550 kg·m−3), temperature (−17.4°C to 0°C) and strain rate (1.3 × 10−5–3.8 × 10−2 s−1), complemented by discrete element method simulations of particle rearrangement and crack extension. The key findings include the following. (1) The apparent shear strength first increases but then decreases with increasing strain rate, increasing by 56% during ductile failure and decreasing by 97% during brittle failure. The form of damage transitions from ductile to brittle as deformation and crack expansion occur, with a critical strain rate of ∼10−4 s−1. (2) An increase in compacted snow density significantly enhances shear capacity and inhibits crack propagation; a density increase of 200 kg·m−3 can reduce transverse and longitudinal snow cracks by 10–20%. (3) Snow temperature influences bond strength, thereby affecting both the strength value and the size of deformation cracks. Snow temperature exhibits a negative correlation with apparent shear strength. This study is significant for understanding alpine snow layer shear damage mechanisms and useful for compacted snow pavement design.

Patagonia Icefields are large ice masses with a significant contribution to sea level rise among mountain glaciers in the Southern Hemisphere. In order to improve the estimation of the Northern Patagonia Icefield (NPI) surface mass balance and to better understand its relationship with climate variables and modes, we simulated the surface mass balance over the icefield during the period 1980–2014 with the MAR model. Model reliability was assessed against: weather stations, albedo from MODIS data and previous estimates of the San Rafael glacier’s surface mass balance. We obtain a surface mass balance of –2.48 ± 1.86 Gta–1 and a non-significant trend. Temperature (a physically downscaled variable) was a key variable through its direct impact on melting, but also on solid precipitation. We found that the annual, spring and autumn icefield mean surface mass balance had a significant negative correlation with the Southern Annular Mode (SAM) through air temperature. Over the next century, the impacts of greenhouse gas emissions are projected to keep the SAM in a positive phase and accelerate atmospheric warming. Thus, the NPI is expected to increase its mass loss and its contribution to future sea level rise. However, more in-situ data (precipitation, temperature and accumulation/ablation on the icefield) are needed to improve the projection’s uncertainty.

Monitoring snow distribution in alpine terrain is critical for hydrology, avalanche safety, and climate research, yet traditional surveys are costly, hazardous, and spatially sparse. We assess a gondola-mounted, low-cost Light Detection and Ranging (lidar) system (MOLISENS) for repeated snow monitoring in Real-Time Kinematics (RTK)-denied mountain environments. The system fuses lidar, Inertial Measurement Unit (IMU), and standalone Global Navigation Satellite System (GNSS) using a Simultaneous Localization And Mapping (SLAM) algorithm to generate 3D point clouds along a fixed aerial-lift transect at Hoher Sonnblick, Austria. Six winter runs (March 2023) were processed and compared with summer Unmanned Aircraft System (UAS)-photogrammetry. Intra-system repeatability between same-day scans reached centimetre precision (weighted standard deviation 0.010 m; 95% within $\pm$0.006 m), supporting detection of daily to seasonal changes in snow thickness along the route. Absolute agreement with the UAS reference was limited to decimetre scale, primarily due to registration and standalone GNSS uncertainties rather than sensor range noise. Performance degraded over feature-poor snowfields, and manual segment merging was labor-intensive; consequently, quantitative analyses were restricted to well-constrained segments. Despite these limitations, the results demonstrate the feasibility of gondola-mounted lidar for cost-effective, repeatable snow-thickness mapping.

The meltwater-driven disintegration of the Larsen B ice shelf has raised concerns that other ice shelves may face similar vulnerabilities as global temperatures rise. Climate projections show increased ice shelf vulnerability to surface melt in the coming century, yet the ability of large-scale climate models to simulate temperatures over ice shelves—a key factor in these projections—has rarely been assessed. We address this gap by using ERA5 reanalysis data to evaluate 31 CMIP6 models’ performance in simulating near-surface air temperatures over 46 Antarctic ice shelves from 1979 to 2014. We find that CMIP6 models exhibit annual and summer warm biases over most ice shelves. There is also inter-model variability of up to 13°C between model temperatures over the Amery and Riiser-Larsen shelves for both annual and summer periods. Significant regional differences are present: shelves in the Amundsen Sea Embayment show cold biases, while those in the Weddell Sea show warm biases. While topography corrections can reduce some biases, we find notable seasonal differences, including biases with opposite signs between annual and summer means. Our results underscore the importance of careful model selection by shelf and region to improve the reliability of future climate projections and assessments of Antarctic ice shelf vulnerability.

Patagonia and Tierra del Fuego (Austral Andes) are the most glacierised regions in the Southern Hemisphere, where glaciers have experienced significant mass changes in recent decades. Understanding glacier–climate–water interactions is crucial for addressing future climate challenges. Open-access data play a key role in advancing geoscience research, improving models and assessing the impacts of hazards and sea-level rise impacts. Here, we present QFuego-Patagonia, a free glacier-related GIS dataset and web portal covering Patagonia and Tierra del Fuego, which provides essential geospatial information across four scientific topics: Glaciology, Atmosphere, Terrain Models, and Glacial Geology and Geomorphology. This initiative aims to foster interdisciplinary research and collaboration, synthesise current knowledge and establish an advanced glacier data repository that will be continuously updated as new data and insights become available.

Glacial lakes in the Kashmir Himalaya have remained understudied despite their destructive potential for outburst floods. This study presents a comprehensive, manually delineated glacial lake inventory of 155 glacial lakes and a baseline for glacial lake outburst flood (GLOF) hazard across the region. Lakes are characterized by type and assessed for long-term spatio-temporal dynamics using a multi-temporal Landsat series in a GIS environment from 1992 to 2024. The area of ice-contact proglacial lakes increased by 26% during the 32-year observation period. A multi-criteria analysis-based framework validated by historical GLOFs in the Himalayan region is employed to evaluate the lake outburst susceptibility. Key factors such as dam material, slope gradient, upstream cascades, seismic activity and permafrost occurrence, are integrated in the susceptibility framework. Potential outburst events from five lakes categorised as having very high GLOF susceptibility threaten several thousand buildings, 15 major bridges, roads and a hydroelectric power project. The study also highlights the potential for GLOF process chains in the region, where upstream lake outbursts could trigger secondary events downstream. The five most susceptible lakes identified here may require intensive monitoring and risk management initiatives to protect vulnerable downstream communities and infrastructure.