Orals: Fri, 8 May, 08:30–12:30 | Room L1
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 21st 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 19th 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.
The Southern Patagonian Icefield, the largest temperate ice body in the Southern Hemisphere, is among the regions with the highest mass-loss rates globally. Most of this mass loss is driven by large, water-terminating outlet glaciers. Their response to climate change, however, is heterogeneous in time and space. For water-terminating glaciers, subglacial topography plays a key role in modulating their response to climate change, yet it remains largely unknown, especially near glacier termini.
We present results from two campaigns in 2022 and 2024, during which we conducted helicopter-borne GPR measurements of three of the largest Argentine outlet glaciers: Glaciar Upsala, Glaciar Viedma, and Glaciar Perito Moreno. Our measurements, covering 232 km of flight tracks, reveal the complex subglacial topography in the lower regions of these glaciers and show bed reflections of up to 800 m depth at Glaciar Upsala. Our data also shows Glaciar Perito Moreno lies on a pronounced subglacial bedrock ridge, which has largely contributed to its past stability.
In addition, we incorporated our measurements into an established ice-thickness reconstruction to derive the basin-wide ice-thickness distribution and, thus, the subglacial topography. Our ice-thickness maps indicate that the three glaciers had a combined ice volume of 831 km³ in the year 2000, which is more than six times the total ice volume of the European Alps combined.
While the rerteat of Glaciar Upsala and Viedma has slowed down, Glaciar Perito Moreno shows increased surface-lowering rates, from 0.34 m a⁻¹ (2000-2019) to 5.5 m a⁻¹ (2019-2024), accompanied by glacier acceleration and frontal retreat. After almost 100 years, the glacier has started to detach from its pinning point. Using a simple numerical model, we show that buoyancy-driven retreat of several kilometres could occur in the near future if lowering rates persist.
How to cite: Koch, M., Sommer, C., Blindow, N., Berkhoff, J., Skvarca, P., Fürst, J., and Braun, M. H.: Mapping bedrock topography and ice thickness distribution of Patagonian outlet glaciers using ground-penetrating radar, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18052, https://doi.org/10.5194/egusphere-egu26-18052, 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.
The surface mass balance (SMB) of glaciers represents a direct link to the local climate and is a key variable in modelling glacier response to climate change. While the SMB is traditionally measured at point locations with ablation stakes or snowpits, recent advances allow estimation of spatially distributed SMB using remotely sensed data of surface elevation change, ice velocity, and ice thickness by solving the mass continuity equation. Such inverse approaches offer a promising alternative to field-based SMB data collection, particularly for model calibration and large-scale assessments. However, SMB inversion approaches vary in spatial coverage, assumptions, and solution strategies as well as in using data of different resolutions and temporal consistency—raising questions about their comparability, performance, and uncertainties.
The Continuity approaches for mass balance Intercomparison eXercise (ContinuIX) is a community effort organized through an IACS Working Group that aims to compare existing continuity approaches for SMB estimation and to deliver clear guidelines and recommendations for future developers and users of SMB products derived from these methods. The first objective of ContinuIX focuses on compiling a benchmark dataset with high-quality, contemporaneous observational data (surface elevation change, velocity, thickness, and in situ SMB), as well as controlled synthetic test cases. The next activities will involve a structured intercomparison experiment using these best possible datasets to assess differences between approaches.
Here, we present progress on the benchmark dataset of phase one, which includes extensive contemporaneous observations of eight glaciers across multiple regions. This dataset may be of value for a wide range of glaciological studies. Additionally, we apply and present first results of mass continuity methods to demonstrate how distributed SMB products can be derived, providing a preview of the types of comparisons envisioned for the next objective of ContinuIX. This presentation is intended not only to share initial results, but also to invite input and discussion from the community as we shape the next steps of ContinuIX. We particularly welcome ideas, feedback, and expressions of interest from potential contributors or users of continuity-derived SMB products.
How to cite: Izeboud, M., Wells, A., Fürst, J. J., Kneib, M., Miles, E., Devaux-Chupin, V., Van Tricht, L., Henning, K., and Zekollari, H.: Exploring contemporaneous observational datasets to derive glacier surface mass balance from continuity approaches (ContinuIX working group), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13647, https://doi.org/10.5194/egusphere-egu26-13647, 2026.
Measuring glacier mass change worldwide is essential to document the impact of climate change, understand glacier-related hazards and assess the contribution of the cryosphere to sea-level rise. Over the last two decades, three remote-sensing techniques have been used to measure glacier mass change: digital elevation model (DEM) differencing, altimetry and gravimetry. The Glacier Mass Balance Intercomparison Exercise (GlaMBIE, ESA-funded) aims to compile, homogenize and combine these regional glacier mass change observations.
One intriguing outcome from the first GlaMBIE phase (2022–24) was a systematic difference of region-wide elevation change measured using ASTER DEM differencing (dDEM) and CryoSat-2 radar altimetry. In most cases, dDEM resulted in more negative values in all glacier regions with an average regional difference of 0.08 ± 0.07 m w.e. yr-1 (The GlaMBIE Team, 2025). The work presented here is part of the second GlaMBIE phase (2025–27). It aims at describing in more detail and understanding the differences between these two techniques. We focus on major Icelandic ice caps as test sites as they present a good coverage for both techniques and are also covered with high resolution, precise dDEM data (e.g., airborne lidar in 2013 and Pléiades in 2020 for Hofsjökull ice cap).
Our preliminary results indicate that the differences between published ASTER (Hugonnet et al., 2021) and CryoSat-2 (Jakob and Gourmelen, 2023) estimates are also found at ice cap and glacier scale. Next, we plan to compare the methods over the exact same period, and evaluate them using accurate validation data. We will also test the sensitivity to the software used to generate the DEMs, to alternative processing of CryoSat-2 data, and to the post-processing of the data (altimetry and DEMs) to find the key reasons for the systematic difference.
How to cite: Guyez, A., Berthier, E., Jakob, L., Gourmelen, N., Piermattei, L., Webster, C., U. Nussbaumer, S., Zemp, M., M.C. Belart, J., and Jóhannesson, T.: Glacier elevation change estimates: decoding the systematic differences between radar altimetry and DEM differencing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9325, https://doi.org/10.5194/egusphere-egu26-9325, 2026.
Mapping of elevation changes across large glacier regions is an essential basis for future IPCC reports. The first Glacier Mass Balance Intercomparison Exercise (GlaMBIE) established a community estimate of global glacier mass change [1]. However, the method of InSAR DEM differencing remains an underrepresented data source in this experiment.
For the second GlaMBIE data contribution, we aim to update our existing DEM Differencing processing pipeline [2]. It will be implemented on the high performance “Terrabyte” platform at the Earth Observation Center (EOC) of DLR. Unlike our previous contribution [2], which relied on targeted acquisitions to cover entire glacier regions, we will exploit the existing TanDEM‑X catalogue. This strategy facilitates future processing of large glacierized regions worldwide.
Recent advances regarding the uncertainty assessment of TanDEM-X DEM Differences will be fully incorporated in this pipeline [3, 4]. Special attention is given to reducing possible biases due to signal penetration. This bias is mitigated by differencing carefully selected TanDEM-X acquisitions from the same season with unchanged SAR geometry, reducing penetration differences between DEMs. Moreover, the relative importance of SAR signal penetration for accurate mass balance measurements also reduces with the length of the observation period.
In this work we will calculate the elevation change of all glacierized regions in Iceland based on available acquisitions in the TanDEM-X catalogue. Because the majority of TanDEM-X data were originally tasked and intended for the TanDEM-X Global DEMs, the final coverage will naturally gravitate towards these acquisitions, however alternative more suitable scenes in the catalogue will be substituted. A penetration-bias-optimized coverage for Iceland is best achieved by targeting the 2013 - 2021 period, with replacement scenes from other times possible.
We will investigate several spatial and temporal extrapolation strategies to fill gaps in Icelandic glacier coverage that must be left intentionally without measurements because the only available scenes are suspected of being affected by signal‑penetration biases.
References
[1] Zemp, M., Jakob, L., Dussaillant, I., Nussbaumer, S. U., Gourmelen, N., Dubber, S., A, G., Abdullahi, S., Andreassen, L. M., Berthier, E., Bhattacharya, A., Blazquez, A., Boehm Vock, L. F., Bolch, T., Box, J., Braun, M. H., Brun, F., Cicero, E., Colgan, W., … The GlaMBIE Team. (2025). Community estimate of global glacier mass changes from 2000 to 2023. Nature, 1–7. https://doi.org/10.1038/s41586-024-08545-z
[2] Abdel Jaber, W., Rott, H., Floricioiu, D., Wuite, J., & Miranda, N. (2019). Heterogeneous spatial and temporal pattern of surface elevation change and mass balance of the Patagonian ice fields between 2000 and 2016. The Cryosphere, 13(9), 2511–2535. https://doi.org/10.5194/tc-13-2511-2019
[3] Hugonnet, R., Brun, F., Berthier, E., Dehecq, A., Mannerfelt, E. S., Eckert, N., & Farinotti, D. (2022). Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 6456–6472. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://doi.org/10.1109/JSTARS.2022.3188922
[4] Li, S., & Hajnsek, I. (2025). Geodetic glacier mass balance in the Karakoram (2011–2019) from TanDEM-X: An InSAR DEM differencing framework. Remote Sensing of Environment, 331, 115023. https://doi.org/10.1016/j.rse.2025.115023
How to cite: Krieger, L., Diaconu, C.-A., Abdullahi, S., Ramanath, S., and Floricioiu, D.: Elevation Change of Icelandic Glaciers from TanDEM‑X DEM Differencing with Penetration‑Bias‑Optimized Scene Selection , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10689, https://doi.org/10.5194/egusphere-egu26-10689, 2026.
The Patagonian Andes host the largest glacierized area in the Southern Hemisphere outside Antarctica and play a key role in regional freshwater resources and global sea-level rise. Meltwater discharge from Patagonian glaciers contributes to sea-level rise, while changes in freshwater runoff threaten downstream ecosystems and water availability. In particular, the Northern Patagonian Icefield (NPI), Southern Patagonian Icefield (SPI), and Cordillera Darwin Icefield (CDI) are vast temperate ice bodies and rank among the Earth`s mountain regions with the highest glacier mass-loss rates.
Here, we present new observations of glacier mass change across the Patagonian Andes for the period 2000–2025. We combine multi-mission remote sensing data, including synthetic aperture radar (SAR) digital elevation models (DEMs) from the TanDEM-X mission and satellite altimetry from CryoSat-2 and ICESat-2, to derive glacier-specific and regional geodetic mass changes. In addition, we account for ice mass loss committed by frontal ablation by estimating subaqueous volume change of lake- and marine-terminating glaciers from observed terminus retreat and ice thickness reconstructions.
Comparison with climate observations reveal a region-wide warming trend since the beginning of the 21st century. However, regional glacier mass change exhibits pronounced spatial and temporal heterogeneity. NPI glaciers show a marked acceleration in mass loss after 2013, while at SPI mass loss rates remained comparatively stable until 2019, after which annual mass loss increased to levels similar to the NPI. Similarly, the CDI exhibits a distinct increase in mass loss in recent years, after a short intermediate period of mass loss deceleration. Glacier-specific analyses of surface elevation change and ice flow velocity at major outlet glaciers reveal enhanced surface lowering and increased flow speeds near glacier termini over the past decade, due to intensified dynamic thinning. The observed regional and temporal variability in glacier response is likely linked to previously reported variations in precipitation and snowfall amounts. Overall, annual specific mass loss of the NPI and SPI since 2019 (~ -1.5 m w.e./a) has increased by more than 50% compared to the early 2000s (~ -1.0 m w.e./a).
How to cite: Sommer, C., Koch, M., Temme, F., Warnstedt, A., and Braun, M.: Untangling multi-annual to decadal ice mass loss of glaciers in the Patagonian Andes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20460, https://doi.org/10.5194/egusphere-egu26-20460, 2026.
Glaciers are crucial components of the Earth's climate system and serve as indicators of climate change. Their substantial mass loss due to global warming significantly contributes to sea-level rise and impacts regional hydrology, downstream ecosystems and settlements. Despite considerable advancements in observational and modeling techniques, accurately quantifying glacier responses to climate change and predicting their future behavior remain complex challenges, particularly in regions characterized by rapidly changing glaciers and complex topography. In this study, we present a spatially resolved time series of annual glacier mass balance and elevation change for the Southern Andes from 2002 to 2025, derived from ASTER digital elevation models (DEMs). All available austral summer-season DEMs were compiled to minimize seasonal bias, and an automated processing workflow was developed to generate elevation change maps for the entire region as well as for individual glaciers. This approach enables consistent, large-scale monitoring without reliance on in-situ measurements, making it particularly valuable for remote and data-scarce regions. Elevation differences were converted to mass balance estimates using density assumptions, allowing both regional-scale assessments and detailed analysis of glacier complexes. Our results reveal pronounced spatial and temporal variability in glacier thinning, including periods of accelerated mass loss and localized heterogeneity linked to topographic and climatic factors. The developed methodology provides a scalable framework for long-term glacier monitoring and contributes to improved understanding of regional cryosphere dynamics and their implications for water resources and sea-level rise.
How to cite: Usoltseva, M., Pail, R., Wendt, A., and Mayer, C.: Two Decades of Glacier Mass Balance in the Southern Andes , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7746, https://doi.org/10.5194/egusphere-egu26-7746, 2026.
Nine very small glaciers (VSGs) have been identified in the northern Japanese Alps (e.g., Fukui et al., 2018; Arie et al., 2025). These VSGs persist under relatively warm conditions at elevations around 2,000 m, where the mean annual air temperature is approximately 2–3 ℃. Understanding the mechanism that enables their persistence is therefore an important scientific issue. However, long-term mass-balance observations and understanding of the flow mechanisms remain limited.
In this study, the mass balance of eight glaciers and perennial snow patch was observed from the 1960s to 2025, and interannual and seasonal variations in flow velocity were investigated at the Shakushizawa Glacier. The studied glaciers and snow patches―Hakubazawa, Shakushizawa, Kaerazuzawa, Karamatsuzawa, Kakunezato, Komado, Sannomado, Gozenzawa―are located at elevations of 1,700-2,700 m and are characterized by heavy snow accumulation (snow depth: 20-30 m) due to the northwesterly winter monsoon and frequent avalanches.
Cumulative mass balance from the 1960s to the mid-2010s showed only slight gains or losses; however, following the low-snowfall year of 2016, all glaciers and perennial snow patches experienced substantial mass loss by 2025. Meteorological observations (Hakuba AMeDAS) and ERA5 reanalysis data indicate no significant long-term decrease in snowfall since the 1950s, whereas melt amounts estimated using both an energy-balanzsce and a degree-day methods show an increasing trend. These results suggest that the recent acceleration of mass loss is mainly driven by enhanced summer melting associated with rising air temperatures.
Flow observations at the Shakushizawa Glacier show that annual flow velocities exceed those observed at the end of melt season, implying either accelerated internal deformation under heavy winter snow load or enhanced basal sliding during the early melt season.
How to cite: Takehana, Y., Narama, C., and Arie, K.: Observation of mass balance and flow of very small glaciers in northern Japanese Alps., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17071, https://doi.org/10.5194/egusphere-egu26-17071, 2026.
Previous studies have mapped end-of-season snowlines (ESS) on glaciers from satellite imagery to find their snowline altitudes (SLA) to use as a proxy for the glacier equilibrium line altitude (ELA). A line is traced along the boundary between snow and ice, then, from a digital elevation model (DEM), elevation values are extracted at regular intervals along the line. The average elevation of these points is taken to be the SLA. While this approach would be advantageous, as it offers a solution to measuring glacier ELAs in remote regions, it is prone to an oversampling bias. Where snow cover is patchy, for example, in shaded areas or where avalanching has occurred, a greater length of line is mapped in order to follow the snow-ice boundary than is required for smoother segments. This is regardless of whether the region contributes a larger area of snow cover or not. Consequently, SLA calculations are prone to oversampling from areas of irregular snow cover. Even when the ESS is mapped accurately and precisely, the SLA value may differ significantly from the true ELA. This poster investigates alternative methods of calculating the SLA from mapped ESSs to reduce bias towards patchy and irregular areas of snow cover.
How to cite: Hallford, M., Rea, B. R., Spagnolo, M., Sam, L., Singh, S., and Mullan, D.: Calculating Snowline Altitudes on Glaciers with Patchy and Irregular Snow Cover Using Satellite Imagery, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19873, https://doi.org/10.5194/egusphere-egu26-19873, 2026.
Satellite remote sensing has become a cornerstone for monitoring glacier surface velocity and strain rates, with normalized cross-correlation (NCC) techniques widely adopted due to their efficiency and robustness. However, current approaches to quantifying strain-rate uncertainty exhibit substantial limitations. They rely primarily on empirical statistics or classical error-propagation theory, which implicitly assumes spatially independent Gaussian velocity errors and fails to account for the numerical effects introduced by NCC algorithmic parameters and environmental conditions. As a result, strain-rate errors derived from NCC-based velocity fields are poorly characterised at sub-monthly timescales over rapidly evolving glaciers, and technical uncertainties cannot be effectively separated from systematic velocity-field mismatches, limiting the applicability of remote-sensing products in glacier dynamics studies.
We develop a first-principles uncertainty theory by explicitly modelling the fundamental error mechanisms underlying NCC-derived velocity measurements. Building upon the classical error-propagation framework, we combine ordinary differential equations and stochastic process theory to rigorously derive analytical error expressions for two commonly used strain-rate formulations applied to NCC-derived velocity fields: nominal strain rate and logarithmic strain rate. The theory demonstrates that, although the nominal strain-rate error shares a similar mathematical structure with classical error propagation, its coefficients are substantially smaller than those predicted by traditional formulations. In contrast, the logarithmic strain rate (based on the Nye model and Alley grid-based implementation) converges to the true strain rate under normal circumstances, while degenerating to the nominal strain-rate solution in the worst case.
We validate the theoretical predictions using Helheim Glacier, Greenland, as a test case. Surface velocities are extracted from 616 Sentinel-2A/B image pairs with time baselines from 1 to 32 days, followed by statistical analysis of strain-rate errors. Under controlled NCC failure rates, the theoretical model achieves a goodness of fit exceeding R > 0.8, confirming the robustness of the proposed framework.
Our results further reveal a strong dependence of strain-rate error on temporal baseline and pixel distinguishing capacity. For longer baselines (Δt > 18 days over Helheim Glacier), high-strain environments such as shear margins lead to a loss of image similarity, increasing NCC failure rates and inducing systematic velocity-field errors that cause strain-rate overestimation. For shorter baselines (Δt < 10 days), nominal strain rates are strongly limited by pixel distinguishing capacity, producing random non-zero velocity artefacts over stable terrain. Owing to the error attenuation behaviour of logarithmic strain rate, the effective lower bound of usable time baselines is reduced to approximately 3 days, enabling high-temporal-resolution monitoring. Based on the derived error equations, we propose a practical time-baseline selection guideline that constrains random strain-rate errors induced by technical uncertainty, while facilitating the separation of systematic velocity-field errors.
Overall, this work provides an end-to-end uncertainty quantification framework linking remote-sensing techniques to glacier strain-rate products, offering a theoretical foundation for quality control, uncertainty assessment, and data assimilation in next-generation glacier strain-rate monitoring.
How to cite: Zhang, C., Wang, X., and Zhou, Y.: Uncertainty propagation from Sentinel-2A/B-derived velocity to glacier strain rates: a first-principles perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2248, https://doi.org/10.5194/egusphere-egu26-2248, 2026.
In-situ monitoring of calving process from lake-terminating glaciers in the Himalayas remain scarce, despite being a significant component controlling glacier retreat. Acquiring in-situ measurements are challenging due to harsh terrain and extreme weather conditions, which has typically resulted in the use of expensive, state-of-the-art terrestrial observational systems. Such limitation in data acquiring leads to an incomplete understanding of calving-induced glacial mass loss and retreat. In this study, we evaluate the effectiveness of a low-cost Raspberry-Pi based terrestrial photogrammetry system for annual monitoring of calving from lake-terminating glaciers. We tested the proposed system for monitoring calving at lake-terminating Panchinala-B Glacier, Indian Western Himalayas. The photogrammetry system consists of an array of Raspberry-Pi powered time-lapse cameras, which took multi-view stereo images of the glacier front face over a 12-month period between August 2023 and August 2024. The images were processed in a Structure-from-Motion (SfM) workflow to generate two, annually separated, point clouds. The Multiscale Model-to-Model Cloud Comparison (M3C2) distance of the annually separated point clouds yielded a mean terminus position change (retreat) of 0.88 m, with a mean absolute error of (+/-) 5.8 m. Using the above obtained parameters a calving rate and calving mass flux of 16.3 (+/-) 4.29 m/annum and 0.00017 (+/-) 0.000125 Gt/annum respectively can be quantified. Further, numerous environmental and system design-based challenges were encountered, which affected the quality of the obtained calving estimates. These challenges were carefully understood, and we provide further recommendations for the future use of similar low-cost systems for long-term glacier monitoring, which demonstrate good potential for characterising the magnitude and frequency of calving processes at lake-terminating glaciers.
How to cite: Mandal, S., Taylor, L., Ramsankaran, R., and Quincey, D.: Low-Cost Terrestrial Photogrammetry System for Monitoring Calving from Lake-Terminating Glaciers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-176, https://doi.org/10.5194/egusphere-egu26-176, 2026.
