Southern Patagonia hosts the largest accumulation of ice in South America. The Patagonian Icefields (PI), situated just north of 52° S, with a highly fragmented glacier outline and a N-S orientation represent the largest glacial system in the region with surface areas of 4,000 and 12,000 km², respectively. A smaller ice cap covers the Cordillera Darwin (CD, 2600 km²) in the south-western part of the Tierra del Fuego main island. The Gran Campo Nevado (GCN, 200 km²) is situated halfway between the Southern Patagonian Icefield and CD. The area of the PI is subject to intense glacial isostatic adjustment (GIA) effects due to its particular rheological setting as response to relatively recent ice-mass loss. These effects include observed bedrock uplift and gravity field changes. Continuous monitoring of the ice loss in Patagonia is key to understanding the impact of ongoing climate change in the southern mid-latitudes and the southeastern Pacific. Previously published mass-balance estimates for the PI agree in an intense ice-mass loss, but indicate a dependence on the analyzed period and the applied method. The GRACE (2002-2017) and GRACE-Follow On (GRACE-FO, since 2018) missions provide an efficient tool for quantifying mass redistribution on Earth from satellite gravimetry data. Richter et al. (2019) developed a method to determine a mass change time series of the PI over the 15-years period of the GRACE mission. By applying a series of corrections, the gravimetric effects of simultaneous mass redistribution processes are removed from the pseudo-observables in order to isolate the target mass-change signal prior to the inversion. We present a new ice-mass change time series extending our estimation of the PI over CD and GCN, and including the GRACE-FO data record over a time span of 22 years. It benefits from improved models used to correct for the gravity effects of GIA, ocean mass redistribution, continental water storage variations, and ice-mass changes of the polar ice sheets and mountain glaciers outside Patagonia. In addition, the effects of major earthquakes in the study region are corrected, and recent InSAR remote-sensing results are incorporated as a priori information on the spatial distribution of ice-mass changes in Southern Patagonia. Our results confirm a steady ice-mass loss with a mean rate of -30 Gt/a and reveal an increase in the mass-loss rate during most recent years, reaching values of about −43 Gt/a.

How to cite: Romero, A., Richter, A., Döhne, T., Horwath, M., Mardewald, E., and Suad Corbetta, F.:  Accelerated ice-mass loss in southern Patagonia observed by satellite gravimetry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19130, https://doi.org/10.5194/egusphere-egu26-19130, 2026.

Digital elevation models (DEMs) from optical stereo satellite imagery are widely used to quantify glacier elevation change through DEM differencing. However, incomplete spatial coverage and irregular temporal sampling limit the applicability of standard pair-wise DEM differencing over large glaciers, requiring the analysis of multi-temporal DEM time series.

Here, we compare methodological approaches for interpolating optical DEM time series to derive mean glacier elevation change rates using freely available datasets. We exploit SPOT-5 and ArcticDEM as high-resolution complements to the ASTER DEM record. Using the Hofsjökull ice cap (Iceland) as a pilot study, we assess the performance and transferability of a pixel-based Gaussian interpolation approach (Hugonnet et al., 2021) and introduce a computationally efficient elevation-band-based method. Validation is performed against independent elevation datasets, such as LiDAR and Pléiades, and through pairwise DEM differencing. 

Our results show that the elevation-band approach provides reliable estimates of glacier-elevation change under sparse, irregular sampling conditions. Furthermore, with its low computational cost and flexibility, the method is well-suited for regional applications and for extending geodetic glacier mass-balance assessments beyond the ASTER era.

Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L., Farinotti, D., Huss, M., Dussaillant, I., Brun, F. and Kääb, A., 2021. Accelerated global glacier mass loss in the early twenty-first century. Nature, 592(7856), pp.726-731.

How to cite: Webster, C., Ioli, F., Belart, J. M. C., Jóhannesson, T., Berthier, E., Mattea, E., McNabb, R., Treichler, D., Girod, L., Zemp, M., and Piermattei, L.: Comparing approaches for glacier elevation change estimation using optical DEM time series, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11729, https://doi.org/10.5194/egusphere-egu26-11729, 2026.

The Pamir Mountains are a key focus of research on the response of glaciers to climate change in High Mountain Asia. They constitute an important mountain water tower that is highly vulnerable to future climatic and environmental change, and they host glaciers that experienced limited but increasing mass loss during 2000-2019. Few studies have constrained mass balance in detail within the region, and these have highlighted strong spatio-temporal variability. Quantification of glacier mass changes and their drivers is challenged by sparse in situ data, strong East-West gradients of temperature and precipitation, and complex glacier processes including debris cover, surging behavior, and collapse features. In this study, we focus on 41 glaciers in the Sangvor region of the western Pamir for 2003-2025 to: i) evaluate the robustness of previous estimates of mass losses for 2000-2019, ii) identify glacier trajectories beyond 2019, and iii) understand the influence of surging glaciers on the observed mass changes. We adopted a stereo image-processing workflow from the Ames Stereo Pipeline and generated DEMs from SPOT5, SPOT6, and Pléiades stereo satellite imagery. Glacier mass balance for each time series was derived using current best practices for DEM co-registration, bias correction, and uncertainty propagation. Additionally, we applied new algorithms for jitter correction, seasonal snow correction based on in-situ data, and a duration-dependent correction scheme for volume-to-mass conversion uncertainties.

Our results provide a time series of high-resolution geodetic surface height changes and glacier mass balance over seven sub-periods spanning 2003 to 2025: -0.19 ± 0.04 m w.e. a^-1 for 2003-2019, -0.63 ± 0.05 m w.e. a^-1 for 2019-2025, and -0.28 ± 0.02 m w.e. a^-1 for the entire period of 2003-2025 for three key intervals. Our 2003-2019 results agree with the mean mass balance measured by ASTER for 2000-2019 (-0.21 m w.e. a^-1) and with the temporal trend. We highlight a sharp mass gain (0.16 ± 0.03 m w.e. a^-1) between 2014 and 2019, followed by a pronounced progressive shift toward negative mass balances. During 2019-2025, characterized by exceptionally warm and dry conditions, the mass balance has been increasingly negative despite higher uncertainty in our annual estimates, reaching its maximum loss of -1.45 (+0.51/-0.19) m w.e. a^-1 in 2024-2025. We also find no statistically significant difference between the mass balance of surging glaciers and the regional mean for the periods of our study. Overall, our results reveal strong temporal variability in glacier mass balance in the region. While long-term mean mass balances agree with previous ASTER-based estimates, our high-resolution geodetic time series resolves their short-term variability, illuminating a complex evolution that includes a marked mass gain for 2014-2019 and a rapid shift toward strongly negative balances thereafter. Comparison with reanalysis data suggests that this variability is more closely linked to precipitation anomalies than to temperature, suggesting a dominant role of mass accumulation and snowfall variability. These results demonstrate the value of high-resolution stereo imagery and motivate extension to the wider Pamir region and can form a new, high-resolution baseline for modelling projections of future glacier changes in the region.

How to cite: Hagiwara, H., Miles, E., Jouberton, A., Muñoz Hermosilla, J., Ren, S., E. Shaw, T., Fiddes, J., Dehecq, A., Hugonnet, R., and Pellicciotti, F.: Glacier mass changes in the Western Pamirs during 2003-2025 from high-resolution stereo satellite images, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17768, https://doi.org/10.5194/egusphere-egu26-17768, 2026.

Field-based seasonal and annual mass-balance observations collected over the past one decade from four benchmark glaciers in the Ladakh region of the western Himalaya, Viz., Pensilungpa, Drang-Drung, Kangrez, and Machoi, indicate a consistent and significant loss of glacier mass across all elevation bands. Mass-balance estimates, obtained from stake networks and snow-pit observations exhibit persistently negative annual values, with enhanced ablation in lower and mid-elevation zones and limited accumulation at higher elevations. The average annual glacier mass balance ranges from −0.4 to −1.4 m w.e. yr⁻¹, with glacier-specific mass balance ranges of −0.8 to −1.4 m w.e. (Pensilungpa), −0.6 to −1.2 m w.e. (Drang-Drung), −0.5 to −1.1 m w.e. (Kangrez), and −0.4 to −0.9 m w.e. (Machoi). Winter accumulation across these four benchmark glaciers ranges from +0.3 to +1.1 m w.e., while summer ablation varies between −0.8 and −2.0 m w.e., reflecting strong altitude-dependent glacier-melt. All glaciers show steep mass-balance gradients, with a pronounced melt in lower ablation zones, and limited but persistent accumulation at higher elevations in the accumulation zones. Drang-Drung and Kangrez exhibit relatively stronger winter mass gains at higher elevations, while Pensilungpa and Machoi display the most intense summer ablation. Although the accumulation zones still gain seasonal mass, but it is not enough to offset the significant ablation as the ablation zones dominate glacier area, causing cumulative negative mass balances. The upward-shifted equilibrium-line altitudes and the dominance of ablation over accumulation indicate the increasing glacier sensitivity to regional warming in the cold desert Ladakh region.

Based on typical uncertainties associated with stake measurements, density sampling, and spatial interpolation of point observation, the uncertainty in annual mass-balance is estimated at ±0.25–0.40 m w.e. yr⁻¹. Despite this uncertainty, the results robustly demonstrate significant glacier mass loss in the  Ladakh region, underscoring enhanced cryospheric vulnerability to climate change and potential impacts on hydrological regimes in the upper Indus basin. These findings are consistent with regional trends in the Himalaya showing accelerated ice loss and rising ELAs, underscoring the growing sensitivity of cold-arid glaciers to climate warming, once considered relatively resilient. Continued mass loss has significant implications for water security, climate adaptation, and glacier hazard risk management across the upper Indus basin.

How to cite: Romshoo, S. A., Lone, B. N., Shah, U. A., Bhat, M., Shah, W., Bhat, M., Shah, W., Yousuf, A., Abdullah, T., Murtaza, K. O., Lone, G., Mir, A., Shah, U., Paul, O., and Romshoo, S.:  Melting Glaciers in the Western Himalaya: Evidence from In-Situ Seasonal and Annual Mass Balance Observations from the Ladakh Himalaya , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-791, https://doi.org/10.5194/egusphere-egu26-791, 2026.

Continuous observations of glaciers are critical for measuring climate variability and understanding its consequences for regional water supplies. This study presents a comprehensive assessment of glacier changes in terms of dimension, mass balance and surface velocity in the Gyama Massif, Karzok Range, Ladakh, from 1980 to 2025. In 1980, the Gyama contained 100 glaciers characterized by a mean area of ~0.50 km² (range 0.02–4.77 km²), steep mean surface slopes of ~26° (13–41°), and high mean elevations of ~5,797 m a.s.l. (5,590–6,140 m a.s.l.), indicating predominantly small, steep, high-altitude glacier systems. The glaciers in this region experienced a total deglaciation of ~41% between 1980 and 2025. Mass-balance measurements for 100 glaciers indicate a moderately negative mean mass balance of −0.18 ± 0.10 m w.e. y^-¹ for 2000–2018. Glacier flow velocities (1990–2022) exhibit a statistically significant decreasing trend of −0.13 m y^-¹, corresponding to a ~75% reduction in mean velocity over the 32-year period. The average velocity of all glaciers across the study period was 4.16 m y^-¹. The most pronounced areal losses occurred among the smallest glaciers: those <0.1 km² in 2000 experienced >80–100% area loss, and several glaciers disappeared completely. Glacier fragmentation increased substantially, with the number of discrete glaciers rising from 9 in 2015 to 14 in 2020 and 28 in 2025, reflecting progressive morphological disintegration associated with sustained mass loss.The substantial loss of glacier area across the Gyama Massif, together with progressive mass loss, has led to a marked slowdown in surface ice velocity, highlighting the strong coupling between glacier geometry, mass balance, and ice flow. The consistent glacier decline at very high elevations (mean ~5797 m a.s.l.) further points to the influence of elevation-dependent warming in this Trans-Himalayan region. We recommend sustained high spatio-temporal resolution remote sensing, complemented by targeted field observations, to improve glacier monitoring in this data-sparse high-altitude region. Such integrated approaches are essential for detecting glacier instability and evaluating impacts on regional hydrology and downstream water resources in the Trans-Himalaya.

Keywords: Remote sensing; Mass balance; Glacier velocity; Deglaciation; Glacier fragmentation; Ladakh Himalaya

How to cite: Prajapati, M., Garg, P. K., Mukherjee, S., Guha, S., Tiwari, A., and Taloor, A. K.: Remote sensing insights into fragmentation and decline of glaciers in the Gyama Massif of Karzok, Ladakh (1980-2025), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7945, https://doi.org/10.5194/egusphere-egu26-7945, 2026.

Mass balance models are typically evaluated using a sparse collection of point measurements on one or more glaciers. Discrete measurements of mass or elevation loss often reflect surface elevation/mass change along centreline ablation stakes. More recent approaches use geodetic data to help constrain these mass balance models, but the infrequent nature of these distributed datasets often precludes an evaluation of how well these models capture important physical properties such as albedo evolution, short-term events such as impurity deposition following wildfire or dust loading, or the importance of heat waves. Here we describe the unique observational dataset for Place Glacier, a small (2 km2) benchmark glacier monitored since 1965. Our dataset includes 62 airborne laser altimetic and 30 hyperspectral surveys from which we derive monthly surface elevation change and optical retrievals (e.g. grain size, albedo and radiative forcing caused by light-absorbing particles-LAPs) during the ablation seasons (2020-2025). These 2-m data are currently being used to assess the performance of distributed surface mass balance models such as COSIPY, GEMB, CROCUS. The dense observational record allows us to perform suitable calibration and validation exercises for each model but also for spaceborne-derived datasets of surface elevation and albedo change. Surface mass balance model performance during the validation period is typically excellent, but significantly degrades when attempting to simulate mass change prior to 2020. Factors which account for this poor pre-2020 performance includes major changes in the extent of firn, late-lying snow and impurity deposition. In addition to elevated flux of LAPs from dry and wet deposition, thinning of firn has elevated surface concentration of LAPs and surface debris thereby darkening the glacier and accelerating mass loss. Work is underway to physically model these important physical processes leading to albedo reduction and attendant glacier mass loss.  

How to cite: Menounos, B. and Viner, N.: Surface elevation change and optical retrieval products to benchmark the next generation of surface mass balance models, Place Glacier, Canada, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11825, https://doi.org/10.5194/egusphere-egu26-11825, 2026.

The equilibrium-line altitude (ELA) is a key indicator of the climatic limit for glacier sustainability. Monitoring ELA is therefore essential for understanding and projecting glacier change. In practice, however, direct ELA measurements from field surveys (the glaciological method) are available for only a limited number of glaciers because sustained observations require substantial time and labor.

Here, we observe multi-decadal variations in firn-line altitude (FLA) over an Alaskan icefield located near a well-monitored reference glacier with a long-term in situ ELA record, using a time series of L-band SAR imagery from JERS-1, ALOS, ALOS-2, and ALOS-4. We validate the SAR-derived FLA against the in situ ELA record and find that FLA variations closely track the observed ELA changes. This agreement indicates that L-band SAR-based FLA retrieval can serve as a proxy for long-term ELA trends.

To clarify how winter observations differ between frequencies, we compare winter backscatter behavior at C-band and L-band. Winter C-band backscatter is strongly influenced by scattering from seasonal snow cover. By contrast, wintertime dry snow is largely transparent at L-band, and winter L-band SAR therefore primarily reflects surface conditions established at the end of the preceding summer. These results suggest that FLA can be monitored with a single winter L-band SAR acquisition.

How to cite: Arie, K. and Tadono, T.: Firn-Line Monitoring over the Juneau Icefield in Alaska Using SAR Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2645, https://doi.org/10.5194/egusphere-egu26-2645, 2026.

Glacier surface albedo is an important factor affecting glacier ablation, and it plays a crucial role in understanding glacier health and the surface energy balance. However, its temporal and spatial distribution on glaciers is frequently ignored, entailing the use of constant values in melt models, which can cause inaccurate melt estimates. Glacier albedo changes in the 21^st century remain poorly understood.

Past studies highlight a decrease in glacier albedo between 2001 and 2021 in most regions of the Third Pole. However, the glacier response to climate change in the Karakoram region is not fully understood. A large portion of the glacierized area has shown unusual behavior with respect to global glacier shrinkage, commonly known as the “Karakoram Anomaly”.

In this study, we analyzed, both temporally and spatially, the long-term trend of summer glacier albedo from 1993 to 2025, using Landsat 4/5 TM, 7 EMT+, and 8/9 OLI data from Google Earth Engine database. Our study focuses on the Central Hunza basin, a large basin (2383 km²) in Karakoram (Pakistan), hosting around 280 glaciers. This basin has already shown, on average, an almost balanced mass budget in the period 1973-2009. To ensure focusing only on snow free glacier surface albedo, we masked out snow covered areas by means of the OTSU algorithm and also assessed the Snow Line Altitude, in order to investigate also its variations at the glacier and basin scale. To assure data continuity across sensors with different spectral resolution, we performed a harmonization of the Landsat data.

This study emphasizes the importance of not assuming albedo as a constant, since its long-term variability in the region may not follow global trends. This is particularly relevant as glaciers act as the main hydrological resource in this region.

How to cite: Barbagallo, B., Fugazza, D., and Diolaiuti, G. A.: Long-term variations of glacier albedo from 1993 to 2025 in the Central Hunza basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17333, https://doi.org/10.5194/egusphere-egu26-17333, 2026.

Knowledge of crevasse locations is essential for improving our understanding of glacier dynamics. In addition, accurate information on crevasses is crucial for mountaineering safety and enables reliable route planning. However, large-scale monitoring remains difficult because crevasses vary greatly in appearance and often show low contrast on snow-covered surfaces, limiting the effectiveness of traditional detection methods. Here, we present an automated crevasse-detection approach based on a multi-task neural network trained on high-resolution orthophotos of Austrian alpine glaciers.

The model was developed using 20 cm aerial imagery of glaciers in the Ötztal and Stubai Alps. Through systematic training and validation, the network achieved 86% detection accuracy across independent test sites, demonstrating robust performance in diverse glaciological settings. The multi-task architecture enables simultaneous feature extraction and classification, efficiently handling the complex spectral and textural characteristics of crevassed ice surfaces.

Following successful validation, we applied the method to all glaciated areas in Austria, producing a comprehensive, high-resolution dataset of crevasse locations. We analysed the spatial distribution of crevasses on Austrian glaciers in different mountain regions, including Hohe Tauern, Dachstein, Ötztal, Stubai, Silvretta and Zillertal.  Analysis of this dataset reveals spatial patterns of crevasse distribution and quantitative metrics on variations in crevasse density across slope, elevation, velocity, curvature and aspect.

The crevasse location dataset provides glacier modelers with detailed boundary conditions for glacier modelling and helps mountaineers plan safe routes. This dataset has already been incorporated into recently published hiking maps by the Austrian Alpine Club and demonstrates how machine learning and open data initiatives can bridge glaciological research and practical applications.

How to cite: Baumhoer, C. A., Straßburger, S., Leibrock, S., and Dietz, A.: Large-Scale Detection of Alpine Glacier Crevasses Using Remote Sensing and Deep Learning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1391, https://doi.org/10.5194/egusphere-egu26-1391, 2026.

The Karakoram mountain range is well-known for its numerous surge-type glaciers of which several have recently surged or are currently surging. Analysis of historic satellite images, topographic maps and reports revealed repeat surges for many of the glaciers, partly back to the 19^th century. The observed surges display a great variety of characteristics regarding surge durations, repeat cycles, flow velocities, advance rates and mass transfer patterns. However, surge mechanisms remain speculative, as the thermal and basal conditions of the glaciers are largely unknown.

Along with positive glacier mass balances and decreasing summer temperatures, the enhanced surge activity in this region is one part of the so-called Karakoram Anomaly. It has been speculated that the Karakoram Anomaly might come to an end, as its mass balance part is showing increasingly negative values, i.e. more similar to the glaciers in surrounding mountain ranges. However, dense time-series of freely available satellite images reveal that this is so far not reflected in a diminishing surge activity, which instead continues unabated.

For this study, animations of Sentinel-2 image quicklooks have been used for early detection of upcoming surges and an analysis of surge development over the past ten years in the central Karakoram. While tributary glaciers continued surging according to their surge cycles, also the much larger trunk glaciers (Panmah and Sarpo Laggo) are now surging again and deform or erase the surge marks of previous tributary surges. In 2024/25, at least 15 glaciers were surging in a small region of the Karakoram, two of which were not classified as of surge-type before. Apart from the animations revealing surge front migration and glacier interactions, time series of flow velocities and surface elevations reveal strong differences in surge dynamics among the glaciers. The 10 m resolution of Sentinel-2 is at the edge of providing meaningful velocity data for the 7 smallest glaciers in the sample.

How to cite: Paul, F.: Glacier surging in the Karakoram continues unabated, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12452, https://doi.org/10.5194/egusphere-egu26-12452, 2026.

Glacier thermal conditions directly influence ice mechanics, meltwater storage, and drainage, thereby governing glacier stability and hazard potential. Polythermal glaciers, in particular, can create conditions that promote ice break-offs, ice avalanches, water pocket outbursts, and even large-scale glacier detachments. Understanding their distribution is therefore critical for hazard assessment. Yet englacial temperature measurements in the Alps remain sparse and are biased toward high-elevation accumulation areas, while the thermal state of mid- and lower-elevation ablation areas is largely unknown. Extended melt seasons and refreezing of meltwater in cold firn have been associated with warming at high elevations, whereas firn loss at lower elevations may reduce meltwater retention and latent heat input. Modeling studies suggest that this imbalance can lead to cooling in ablation areas, an effect that may be particularly pronounced for very small glaciers, where internal heat production from glacier dynamics is minimal.

Here, we present a new englacial temperature dataset from six small Swiss Alpine glaciers (3000–3800 m a.s.l.), directly addressing the lack of observations in mid- to lower-elevation ablation areas that are poorly constrained by existing measurements. The dataset combines borehole thermometry with ground-penetrating radar surveys. Polythermal conditions were identified in three glaciers, with the cold–temperate transition surface (CTS) occurring at depths of 14–25 m. Below the seasonal surface layer, ice temperatures generally ranged from temperate conditions to –2.1 °C. Two of the glaciers exhibit a recurring pattern in which temperate ice at higher elevations transitions downslope into fully or partially frozen glacier tongues. At the third polythermal site, the CTS was detected at several locations between 17 and 22 m depth, while basal thermal conditions remain partly unresolved. One glacier appears predominantly cold, and at two additional sites, shallow thermistors recorded year-round cold conditions within the seasonal layer, while temperate ice at depth cannot be ruled out. Ground-penetrating radar reflectivity is generally consistent with borehole-derived thermal conditions, characterized by low reflectivity in cold ice and enhanced reflectivity in temperate zones. Our findings suggest that polythermal-type glaciers in the European Alps may be more widespread than previously recognized, with important implications for glacial hazard assessment and for understanding climate-driven changes in smaller Alpine glaciers.

How to cite: Beer, J., Jacquemart, M., Huss, M., Santin, I., Clara Racz, G., Ogier, C., Hösli, L., Moser, R., Irving, J., and Farinotti, D.: Polythermal conditions in small glaciers in the Swiss Alps, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8358, https://doi.org/10.5194/egusphere-egu26-8358, 2026.

Glacier ice thickness models are fundamental to studies of glaciology, hydrology, and climatology. They play a key role in estimating ice volume, simulating future glacier evolution, and projecting meltwater runoff changes. However, ice thickness measurements (e.g., ice penetrating radar) only cover about 14% of global glacier area and disparity exists in existing ice thickness models inferred from glacier surface information, making it difficult for glaciologists to accurately simulate and project the future evolution of mountain glaciers and its impact on global sea level change and regional water supply. This study developed a 1.98 km resolution ice thickness model of the West Kunlun glaciers by inverting geophysical data surveyed through an Airbus AS350-B3e helicopter. We analyzed the errors associated with the inversion techniques, evaluated the accuracy of the ice thickness model using ice penetrating radar data, and calculated the ice volume over the surveyed region. Through model comparisons, glacier topographic features not resolvable in previously published models were identified and their potential impacts were analyzed. The ice thickness model developed in this study could provide fundamental data sets for the study of the response of glaciers to climate change and thus contributes to an improved modeling and projection of future evolution of mountain glaciers and its impact on global sea level change and regional water supply.

How to cite: Yang, J. and Shu, Q.: Ice thickness of the West Kunlun glaciers revealed by airborne geophysical survey, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4618, https://doi.org/10.5194/egusphere-egu26-4618, 2026.

The Antarctic Peninsula is among the most rapidly warming regions on Earth and has experienced widespread glacier retreat and acceleration since at least the 1980s, with significant implications for global sea level rise. Glacier change in this region unfolds across a wide range of timescales, spanning from short-lived dynamic events that can trigger persistent adjustments to recurring seasonal variability. However, Earth observation datasets that capture glaciological variables such as ice velocity or calving front dynamics at intra-annual timescales remain scarce. This is largely due to the small size and fast ice flow of Antarctic Peninsula glaciers, combined with complex topography, variable climate, and extreme weather conditions.

Here, we address this observational gap by leveraging a newly developed dataset of sub-seasonal terminus area change records (2013–2023) together with high-resolution satellite-derived ice surface velocity measurements (2014– 2024) to investigate the dynamics of 42 key outlet glaciers on the northern Antarctic Peninsula.

Our results reveal widespread glacier retreat and acceleration, with cumulative ice loss amounting to ~279 km². The majority of this loss (73 %) was observed for glaciers on the eastern Antarctic Peninsula, particularly within the Larsen B embayment, and is attributed to major calving events in early 2022. Although 71 % of the glaciers accelerated over the study period, most eastern glaciers displayed slight trends of slowdown – except for those in the Larsen B embayment, where initial deceleration was followed by abrupt and pronounced velocity increases after the calving events, with some glaciers more than doubling their flow speed. Seasonal analysis further indicates substantial inter-annual variability, with two-thirds of glaciers exhibiting strong seasonal velocity fluctuations, and around half displaying comparable signals in terminus area change.

Overall, the findings demonstrate the persistence of long-term trends of glacier retreat and flow acceleration, while also highlighting substantial spatial and temporal heterogeneity in glacier dynamics across the region, underscoring the need for temporally and spatially detailed monitoring.

How to cite: Leibrock, S., Slater, R. A. W., Hogg, A. E., and Baumhoer, C. A.: Monitoring of Antarctic Peninsula glacier terminus area change and ice surface velocity using dense satellite time series, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9511, https://doi.org/10.5194/egusphere-egu26-9511, 2026.

In this study, we present a high temporal resolution (30-minute) multi-view stereo (MVS) photogrammetric dataset capturing the front of the lake-terminating Perito Moreno Glacier during daylight over more than one year. We aim to provide novel data to investigate glacier dynamics, which are strongly affected by climate change and pose increasing risks to ecosystems and human infrastructure. The images for the photogrammetric reconstruction are automatically inspected and prepared to create high-precision 4D (3D + time) point clouds, which are then compared per epoch to detect surface changes along an approx. 300 m wide study reach.

The MVS system comprises eight DSLR cameras and uses 4G connectivity for daily data transfer, aiming for near-real-time monitoring. This has resulted in more than 75,000 images stored on a central server, which allows the calving analysis based on more than 5,000 models. To isolate image regions relevant for the generation of dense clouds with maximum precision across as many epochs as possible, the images are segmented using the artificial intelligence (AI)-based image segmentation model SAM2. The relevant regions are assessed using blur metrics, which identify low contrast caused by harsh glacier conditions, such as moisture or water droplets, thereby reducing the risk of including images of low quality that interfere with image correlation success.

The results of our image pre-processing demonstrate that lighting conditions have the greatest impact on image segmentation performance. In contrast, the final model quality of the 4D point cloud reconstructions, which are based on a multi-epoch multi-imagery (MEMI) strategy, is mostly affected by the presence of adjacent dynamically changing regions, such as floating ice on the lake, highlighting the need for masking these regions. Applying masking further seems to improve the robustness of detecting subtle glacier surface changes, which is essential for pre-failure deformation analysis, providing valuable input for future calving prediction efforts.

The point cloud sequences are analyzed using the Multiscale Model to Model Cloud Comparison (M3C2) algorithm to quantify surface changes. Although calibration parameters of focal length and principal point exhibit temporal variability, a constant calibration strategy is examined to ensure consistent alignment across all epochs, which furthermore enables the observation of glacier flow velocities in both horizontal and vertical directions. Initial results for a test period during a week in summer indicate that a constant calibration does not adversely affect model generation, suggesting that calibration stability may be sufficient under favorable summer conditions, while ongoing analyses will assess the robustness during winter months. Current efforts focus on refining dense cloud quality by separating glacier surfaces from points reconstructed on stable rock areas, which were intentionally retained during point cloud generation to provide stable reference regions for the MEMI workflow.

Our introduced workflow enables the creation of a reliable calving inventory, exceeding the spatio-temporal resolution of conventional glacier monitoring techniques. In a next step, we aim to combine the created calving inventory with associated dynamic parameters, such as glacier velocity, and with environmental variables to support the development of AI-based calving prediction models.

How to cite: Duran Vergara, L. C., Nagathihalli Lokesh, B., Blanch Gorriz, X., and Eltner, A.: 4D Multi-View Stereo Reconstruction for High-Resolution Calving Monitoring of Glacier Perito Moreno: A Basis for Dynamic Analysis and Prediction, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9409, https://doi.org/10.5194/egusphere-egu26-9409, 2026.

Tidewater glaciers in the Arctic and the Antarctic Peninsula are undergoing an unprecedented level of retreat owing to rising temperatures, driven by both ocean-induced melting and atmospheric warming of ice-sheets. Frontal ablation at tidewater glaciers occurs primarily through calving and submarine melting, each of which generates distinct sounds that can be detected using acoustic sensing. Calving generates impulsive transient sounds associated with the impact of the ice on the ocean surface, whereas submarine melting generates a more persistent acoustic signal due to release of pressurized bubbles trapped within the ice. These characteristics provide the opportunity to remotely monitor glacier frontal ablation over a long term using passive acoustics, and complement other modalities of glacial remote sensing. To better understand the physical acoustic variability in glacial bays, we undertook acoustic recordings in tidewater glacier bays in Greenland and the Antarctic Peninsula in 2024-2025 using a long vertical hydrophone array, which allows discrimination of sound emanating from glacier terminus melt. These measurements reveal the directionality of the melt-induced sound field, wide variation in acoustic levels and spatial, temporal and spectral characteristics in the acoustic field in the different glacial bays, and significant contributions from melting ice mélange. These were coupled with conductivity-temperature-depth measurements to understand the effect of thermohaline structure on the melt-induced acoustic field. We investigate the acoustic field characteristics including the directionality, spectrum and coherence, potential links with the water temperature in the bay, and place our findings in the context of earlier passive acoustic studies conducted in Svalbard during 2019-2023, drawing comparisons and contrasts across polar regions. Together, these advance the use of passive acoustics as a tool for long-term, remote monitoring of tidewater glacier ablation.

How to cite: Vishnu, H., Chitre, M., and Hoffmann-Kuhnt, M.: Passive acoustic signatures of frontal ablation at tidewater glaciers in the Antarctic Peninsula and Greenland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18630, https://doi.org/10.5194/egusphere-egu26-18630, 2026.