Orals: Mon, 28 Apr | Room 1.61/62
The Juneau Icefield, Alaska, lost ice at an accelerated rate after 2005, relative to the past 250 years. Rates of area shrinkage were found to be 5 times faster from 2015–2019 than from 1979–1990. The continuation of this trend could push glacial retreat beyond the point of possible recovery.
Climate-driven ice loss from glaciers and icefields has been shown to contribute to rising sea-levels, with Alaska expected to remain the largest regional contributor to this effect up to the year 2100. Alaskan glaciers are particularly vulnerable to changes in the climate because they are often top-heavy (with more area at a higher altitude) and located on plateaus. In addition, these factors make Alaskan glaciers more prone to threshold behaviour, in which exceeding a tipping point could result in an irreversible recession. Longer-term records of Alaskan glacier change are needed to understand how climate change impacts these glaciers.
We used historical records, aerial photographs, 3D terrain maps, and satellite imagery to reconstruct Juneau Icefield glacier behaviour over the past 250 years. We observed steady glacier volume loss at a rate of approximately 0.65 km3 per year between 1770–1979. This rate accelerated to approximately 3 km3 per year between 1970–2010 and then doubled to 5.9 km3 per year between 2010–2020. This ice loss acceleration between 2010–2020 was accompanied by a glacial thinning rate 1.9 times higher than that from 1979–2000 and increased icefield fragmentation. This reduction in icefield accumulation area is contributing to a positive feedback loop, including increasing glacier disconnection and fragmentation. Lowering albedo occurs where surfaces such as darker rock are increasingly exposed, reducing solar reflectivity, and further contributing to the recession.
The findings suggest that a physical mechanism are contributing to this icefield moving towards an irreversible tipping point in glacier recession. This greater understanding of Alaskan glacier ice loss mechanisms could improve projections of near-future sea level rise.
How to cite: Davies, B., McNabb, R., Bendle, J., Carrivick, J., Ely, J., Holt, T., Markle, B., Nicholson, L., and Pelto, M.: Accelerating loss of Alaskan Glaciers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5778, https://doi.org/10.5194/egusphere-egu25-5778, 2025.
We report on the mass balance evolution and climate sensitivities of four glaciers from moderately dry to moderately wet climate zones of High Mountain Asia over the last five decades. We focus on Chhota Shigri Glacier located in the western Himalaya (RGI region: South Asia west), Tuyuksu and Sary Tor glaciers (Northern and Central Tien Shan, Central Asia), and an unnamed glacier (hereafter Glacier No. 4) (Eastern Himalaya, South Asia east). Continentality index indicates Chhota Shigri and Sary Tor as most continental (43 and 41) glaciers, Tuyuksu as intermediate (34) and Glacier No. 4 as the most maritime glacier (22). Using declassified spy satellite imagery from the 1970s and 1980s and recent high-resolution optical satellite images, we estimated glacier mass loss rates ranging from -0.3 ± 0.1 m w.e a-1 for Chhota Shigri and Tuyuksu glaciers (1971-2020), -0.4 ± 0.1 m w.e. a⁻¹ for Glacier No. 4 (1969–2022), and -0.6 ± 0.1 m w.e a-1 for Sary Tor Glacier (1973- 2023). We calibrated a mass balance model (SnowModel) coupled with an ice dynamics model to simulate the long-term annual and seasonal mass balance of each glacier. Subsequently, we used the calibrated model to calculate the dynamic mass balance sensitivity of each glacier to the changes in temperature and precipitation. Our results reveal that Sary Tor Glacier is least sensitive to climate changes. However, as this glacier has observed significantly increasing temperature over the last decades, it may witness an increasing mass loss due to its strong sensitivity to temperature changes. Chhota Shigri Glacier’s mass balance is less sensitive to changes in temperature and precipitation compared to Tuyuksu Glacier. In addition, no significant trends in either temperature or precipitation was observed, implying a more stable response of the glacier to climate in near future. Tuyuksu Glacier accumulates mass both in summer and winter, and it is strongly influenced by temperature changes. With no significant increase in precipitation to offset the mass loss due to increased temperature, this glacier will likely experience an increased mass loss in coming decades. Glacier No. 4 has the highest sensitivity to climate. With a warming trend observed in this region, this glacier is expected to witness highest mass loss among the four in the coming years.
How to cite: Bhattacharya, A., Mukherjee, K., Ghuffar, S., King, O., Bolch, T., and Menounos, B.: Variabilities in Climate Sensitivities and Mass Balance of Four High Mountain Asian Glaciers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4653, https://doi.org/10.5194/egusphere-egu25-4653, 2025.
Debris-covered glaciers (DCG) are common in most parts of High Mountain Asia (HMA). Existing studies show that DCG have been losing mass at similar or even higher rates than debris-free glaciers (DFG). However, the process driving the response of DCG to climate change are much more heterogenous than those of DFG. Understanding the evolution of DCG is further complicated by the development glacial lakes which have significant impacts on glacier dynamics.
To investigate the characteristics and development of the DCG a long time series of observations is beneficial. Here, we present the mass balance and surface evolution of selected DCGs located in different parts of HMA since the last 60 years using historical KH-4 and KH-9 stereo imagery and contemporary high-resolution stereo images such as Pléiades. In addition, we analyse their velocity changes since the 1980s using available data from ITS_Live and calculated annual and seasonal velocities from Sentinel-1 and 2 data.
Our results show that DCGs have slowed-down on average and the surface of DCGs have become rougher indicating the evolution of ice cliffs and supra-glacial lakes. Most DCG have large stagnant tongues, a reverse elevation change gradient at the distal part of the tongue and no visible signs of retreat (“Khumbu type”). In contrast, others show flow activity throughout the tongue and are retreating. Their surface elevation change gradient is similar to DFG (“Kangshung type”). The lake-terminating DCG are also active throughout, have the highest velocity at the end of the tongue and show the highest mass loss. We found topography to be one of the main drivers of heterogeneity. Work is ongoing to analyse various climate parameters to better understand the reasons for the heterogeneity and investigate the similarities and differences in the seasonal velocity of DCGs.
How to cite: Bolch, T., Baldacchino, F., and Bhattacharya, A.: Variable evolution of debris-covered glaciers in High Mountain Asia during the last several decades, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11329, https://doi.org/10.5194/egusphere-egu25-11329, 2025.
Slip at the ice-bed interface (basal motion) dominates the flow of many glaciers, and it is uncertain whether this velocity component will increase or slow in a warmer world. Past results from an idealized flowline glacier model show that declining basal motion induces a two-phase response that initially accelerates glacier retreat in a warming climate on a multidecadal timescale but lessens centennial-scale retreat and mass loss. In the present work, we utilize existing field-collected and remotely-sensed constraints on ice thickness, ice surface velocity, and the change in each of these terms to constrain the current rate of basal motion and its change over the past ~40 years. We focus on the ~1500 global glaciers with higher density of field-based ice thickness measurements in the GlaThiDa dataset (>18 measurements points per glacier). Utilizing these ice thickness and surface velocity constraints, we employ a flow model to estimate the rate of basal motion as the residual between observed surface velocity and modeled ice deformation. We first estimate the contribution of varying basal motion to observed changes in surface velocity across the study glaciers. We then estimate these glaciers’ retreat and thinning responses to changing velocity and compare these with the magnitudes expected from atmospheric warming, constrained by published point measurements, mass balance models, and snowline observations. These results will constrain the extent to which evolving ice dynamics have amplified or mitigated the response of global glaciers to climate change over past decades. Further, this knowledge will provide insight into the potential importance of varying basal motion on projections of future glacier change, with implications for global sea level rise as well as local water resource and ecosystem management.
How to cite: Armstrong, W., Dehecq, A., Hock, R., Brun, F., Gagliardini, O., Gillet-Chaulet, F., Gilbert, A., Gimbert, F., Millan, R., and Vincent, C.: Investigating the role of evolving basal motion in modulating global glacier change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13219, https://doi.org/10.5194/egusphere-egu25-13219, 2025.
The existence of cold firn and ice within the European Alps provides an invaluable source of paleoclimatic data with the capability to reveal the nature of anthropogenic forcing in Western Europe over the preceding centuries. Unfortunately, continued atmospheric warming has initiated the thermal degradation of cold firn to that of a temperate firn facie, where infiltrating meltwater compromises this vital archive. However, there is currently limited knowledge regarding the physical transition of firn between these different thermal regimes.
We present the application of a modified version of the spatially distributed Coupled Snow and Ice Model in Python (COSIPY) to the high-altitude glacierised saddle of Colle Gnifetti (4,450 m a.s.l.) of the Monte Rosa massif, Swiss/Italian Alps. Forced by an extensively quality-checked meteorological time series from the Capanna Margherita (4,560 m a.s.l.), with a distributed accumulation model to represent the prevalent on-site wind scouring patterns, the evolution of the cold firn’s thermal regime is investigated between 2003 and 2023. Our results show a continuation of previously identified trends of increasing surface melt at a rate of 0.54 cm w.e. yr −2, representing a doubling over the 21-year period. This influx of additional meltwater and the resulting latent heat release from refreezing drives englacial warming at a rate of 0.045 °C yr −1, comparable to in-situ measurements. Since 1991, a measured warming of 1.5 °C (0.046 °C yr −1) has been observed at 20 m depth with a marked inversion in the temperature gradient developing in the 15-30 m depth range. While this remains below the local rate of atmospheric warming (0.073 °C yr −1), in lower altitude regions (∼ 4,300 m a.s.l.) simulated warming is considerably greater suggesting a rapid transition from cold to temperate firn is occurring – potentially indicative of future conditions at Colle Gnifetti. However, uncertainty is high in this region as the simulation is particularly sensitive to changes to the model’s parameterisations – principally those controlling albedo and percolation – and crucially the length and simulated depth of the model spin-up.
Our research also greatly contributed to the development of the latest version 2.0 of the COSIPY model which includes critical bug fixes, the addition of new parameterisations and performance enhancements to benefit the wider modelling community.
How to cite: Gastaldello, M., Mattea, E., Hoelzle, M., and Machguth, H.: Modelling Cold Firn Evolution at Colle Gnifetti, Swiss/Italian Alps, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17699, https://doi.org/10.5194/egusphere-egu25-17699, 2025.
Knowledge of glacier ice volumes is crucial for constraining future sea level potential, evaluating freshwater resources, and assessing impacts on societies, from regional to global. Motivated by the disparity in existing ice volume estimates, we developed a global machine learning framework to model the ice thickness of individual glaciers. IceBoost is a gradient-boosted tree regression model, trained with 3.7 million global ice thickness measurements and an array of 34 numerical features. The model's error aligns within 10% of existing models outside polar regions, and is 30% to 40% lower at high latitudes. We find that providing supervision through available thickness measurements can further reduce the error of individual glaciers by up to a factor 2 to 3. A feature ranking analysis reveals that geodetic information is the most informative variable, while incorporating ice velocity improves model performance by 6% at high latitudes. A major feature of IceBoost is its ability to generalize globally, including in ice sheet peripheries. We present the model, discuss the advantages and shortcomings of a machine learning approach, estimate errors, and provide updated regional glacier volumes.
How to cite: Maffezzoli, N., Rignot, E., Barbante, C., Petersen, T., and Vascon, S.: A global machine learning system for glacier ice volumes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1960, https://doi.org/10.5194/egusphere-egu25-1960, 2025.
Mountain glaciers are a major contributor to sea-level rise and serve as an important freshwater resource for many mountainous regions. Accurate mass balance estimates are therefore essential for predicting and managing the global and local impacts of climate change. In a warming climate, glaciers will experience increased liquid precipitation and melt, making it crucial to better understand and model the associated surface processes. In this study, we present a modelling approach developed to investigate the dynamic interaction between surface liquid water and glacier mass balance using the SURFEX-ISBA-Crocus model. As Crocus is primarily a snowpack model, some adaptations were necessary for its application to glacier environments. The research focuses on a specific process: the retention of liquid water at the ice surface, which affects both the mass and surface energy budgets.
Our implementation temporarily retains liquid water from melt or rain events when glacier ice is exposed at the surface. This water impacts the energy balance and can refreeze over time depending on meteorological conditions. To prevent over-accumulation, excess water is drained according to a predefined coefficient. This process has a significant impact on glacier properties, through the presence of liquid water at the surface and the production of refrozen ice, which directly affects the albedo and mass balance.
We applied this new development to Mera Glacier in Nepal to analyse its impact on point mass balance, mass fluxes such as melt and refreezing, and their seasonal variations. The case study highlighted the role of the liquid water reservoir in modulating the effects of melt and rain events. During the pre-monsoon season, the developed model showed greater mass loss due to surface liquid water, which enhanced warming rather than compensating through refreezing. In contrast, during the monsoon and post-monsoon seasons, the behaviour shifted, with the developed version showing less negative mass balance as refreezing increased. The mean annual difference between the two model versions was 0.22m w.e. over the four simulated years, with a larger difference of 0.38 m w.e. observed in 2021-2022. Sensitivity tests on key parameters of the buffer model indicated that the differences are driven not only by the amount of liquid water retained, but also by a positive feedback on albedo, which strongly influences the energy balance.
To further validate and refine the method, future work will focus on comparing this modelling approach with observations and measurements.
How to cite: Goutard, A., Réveillet, M., Brun, F., Six, D., Amory, C., Fettweis, X., Fourteau, K., Lafaysse, M., and Roussel, L.: Impact of surface liquid water retention on glacier mass balance: application to Mera Glacier (Nepal) using SURFEX-ISBA-Crocus, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10188, https://doi.org/10.5194/egusphere-egu25-10188, 2025.
Glaciers and ice caps worldwide are in strong decline, and models project this trend to continue with future warming, with strong natural and socioeconomic implications. The Jostedalsbreen ice cap is the largest ice cap on the European continent (500 km2 in 1966, 458 km2 in 2019) and occupies 20% of the total glacier area of mainland Norway. Here we simulate the evolution of Jostedalsbreen since 1960, and its fate in a changing climate in the 21st-century and beyond (2300). This ice cap contains glacier units with a great diversity in shape, steepness, hypsometry, and flow speed. We employ a coupled model system annually accounting for the mass-balance elevation feedback, with 3-d ice dynamics and simulated surface mass balance constrained by Bayesian inference. We find that Jostedalsbreen may lose 12-74% of its present-day volume, depending on future emissions. Regardless of scenario, the ice cap is likely to split into three parts during the second half of the 21st century. Our results suggest that Jostedalsbreen will likely be more resilient than many smaller glaciers and ice caps in Scandinavia. However, we show in simulations to the year 2300 that by the year 2100, the ice cap may be committed to a complete disappearance during the 22nd century, under high emissions. Under medium 21st-century emissions, the ice cap is bound to shrink by 90% until 2300. Further simulations indicate that substantial mass losses undergone until 2100 are irreversible. Our study illustrates a model approach for complex ice masses with numerous outlet glaciers such as ice caps, and how tightly linked future mass loss is to future greenhouse-gas emissions. Finally, uncertainties in future climate conditions appear to be the largest source of uncertainty in future evolution of ice caps like Jostedalsbreen.
How to cite: Åkesson, H., Hauknes Sjursen, K., Andreassen, L. M., Vikhamar Schuler, T., Dunse, T., Kusk Gillespie, M., Robson, B. A., Schellenberger, T., and Clement Yde, J.: Recent history and future demise of Jostedalsbreen, the largest ice cap in mainland Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10323, https://doi.org/10.5194/egusphere-egu25-10323, 2025.
Modeling future glacier evolution is traditionally divided into two steps. The first step, known as inverse modeling, involves estimating "hidden" variables (such as distributed ice thickness) to ensure the model aligns with available observations, thereby reconstructing the current full subglacial and supraglacial states. The second step, forward modeling, uses the initial state derived from the inverse model and simulates its evolution under a given climate forcing. Despite advancements in data availability to constrain inverse modeling and improvements in the representation of physical processes, several challenges persist. These include artificial biases and uncertainties, such as the "initial shock" problem, which arises when ice flow and surface mass balance are not physically balanced. These issues stem largely from the difficulty of reconciling hypothesized physical equations with observational data, especially as the volume of available data increases.
Generalized automatic differentiation (the main tool that permits deep learning) and advancements in parallel computing present unprecedented opportunities to address these challenges. By enabling the exploration of large spaces of glacier states, these technologies make it possible to identify states consistent with both ice physics and observations -- an approach that is computationally infeasible with traditional data assimilation methods. More specifically, physics-informed deep learning is a powerful tool that has the capability to merge the two essential steps (data assimilation by inverse modeling, and forward modeling) into a single framework. In this framework, both observational data as well as physics are seen as constraints that can be enforced in a similar manner, allowing for the discovery of composite, consistent solutions. Most importantly, the intrinsic structure of neural networks makes them highly efficient for computational tasks on GPUs as needed for global modeling, where traditional CPU-based solvers suffer from computational bottlenecks.
This work reviews the latest advancements in the Instructed Glacier Model (IGM), a next-generation glacier evolution model leveraging automatic differentiation and physics-informed deep learning to simulate ice flow and topographical change. IGM, a Python-based framework, integrates ice thermomechanics, surface mass balance, and mass conservation while emphasizing user accessibility, modularity, and reproducibility. The model takes benefit of recent libraries and tools such as: i) TensorFlow for high computational efficiency on GPUs and effective data assimilation, ii) OGGM for enhanced data accessibility, and iii) Hydra for streamlined configuration management. We demonstrate IGM’s versatility through applications in paleo and contemporary glacier modeling. Finally, we illustrate the added value of merging inverse and forward modeling into a unified framework. This approach reduces uncertainties by bridging the gap between data and physics, addressing the persistent challenge of inferring spatially distributed ice thickness while ensuring alignment with observed ice flow.
How to cite: Jouvet, G., Cook, S., Finley, B., Leger, T., and Maussion, F.: Unified forward and inverse glacier modeling with IGM, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7262, https://doi.org/10.5194/egusphere-egu25-7262, 2025.
Posters on site: Mon, 28 Apr, 10:45–12:30 | Hall X5
Climate warming causes increased glacier ablation around the globe. This leads to decreasing surface albedos, which trigger positive melt-albedo feedbacks, fostering continuous glacier darkening whose intensity depends on glacier-specific, topo-climatic factors. Here, we present an analysis of regional disparities of glacier darkening across the European Alps over the period 2000-2023. We derive temporal means and trends of the summer albedo of 152 glaciers from the MODIS MOD10A1 snow product. Based on this data we introduce and calculate a new measure called "glacier darkening resilience", which combines albedo mean and trend to a theoretical time span needed for the albedo to reduce to zero. Our results reveal negative albedo trends on all glaciers (-0.037±0.012 per decade). On 112 glaciers, these trends are statistically significant. The Silvretta Alps are identified as the hot spot of Alpine glacier darkening, with a decadal albedo trend of -0.059 and a darkening resilience of 69.1 years. The Adamello-Presanella Alps, in contrast, show the highest darkening resilience (215.9 years) with a decadal albedo trend of just -0.021. We find that the mean glacier albedos are primarily governed by local climates, while their trends are rather influenced by topographic factors that differ between Western and Eastern Alps.
How to cite: Möller, M., Möller, R., and Mayer, C.: Regional disparities and topo-climatic controls of glacier darkening across the European Alps since 2000, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10167, https://doi.org/10.5194/egusphere-egu25-10167, 2025.
Glacier surges are periods of significantly increased ice flow due to ice-dynamic feedbacks, in contrast to more conventional advances or other responses due to changes in mass balance. In the Arctic, a ring of surging glacier clusters can be found extending from Alaska-Yukon to Novaya Zemlya. The ‘Arctic ring’ encapsulates Svalbard, an archipelago with a long history of glaciological observations and consequently measurements of glacier surges. However, estimates of the number of surge-type glaciers across the archipelago range between 10% and 90% depending on the classification technique used. To better understand the causes, drivers and impacts of glacier surges in Svalbard, improved monitoring is required and new techniques developed to extend the observational record of active surge dynamics. In this contribution, we review the benefits and limitations of different approaches for monitoring and detecting glacier surges in Svalbard. We use this to compile a new database of surge-type glaciers in Svalbard, which also contains data on surge characteristics e.g. terminus change and velocity. We find that 36% of glaciers in Svalbard have displayed surge-type behaviour throughout our observational and landform record, rising to 51% when removing glaciers smaller than 1 km2. Of all the glaciers in Svalbard, only 9% have been directly observed to surge in Svalbard. Since the 2000s, satellite monitoring has enabled detection of most surges of glaciers with large catchments, and the launch of the Copernicus Sentinels in 2014 has further enhanced our monitoring capabilities. Current surge detection is based upon tracking the speed of glaciers over time, elevation changes, terminus advances particularly in historical data sets, and more recently automatically detecting surface changes related to a surge such as increased crevassing. Geophysical sensors are critical for observing subglacial conditions and further work is required to improve deployment strategies on heavily crevassed glaciers. Past surge behaviour can be inferred by employing a landsystems approach and using historical archives such as maps, photographs and field notes. Improvements in our ability to detect surges has started to reveal more complex surge dynamics that suggests the binary classification of a glacier as surge-type or not breaks down. This has implications for how we understand the mechanisms through which glaciers build up energy during quiescence which enables ice flow acceleration during a surge.
How to cite: Harcourt, W. D., Pearce, D. M., Gajek, W., Lovell, H., Kääb, A., Benn, D. I., Luckman, A., Hann, R., Kohler, J., Mannerfelt, E. S., Strozzi, T., McCerery, R., and Davies, B.: The distribution of glacier surge behaviour in Svalbard and implications for understanding unstable ice flow, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12624, https://doi.org/10.5194/egusphere-egu25-12624, 2025.
Glacial Lake Outburst Floods (GLOFs) are a recurring threat in the Karakorum of Gilgit-Baltistan, Pakistan. Numerous surge-type glaciers in the region periodically advance at time intervals of around 10-25 years and dam up streams to create ice-dammed lakes. These lakes empty in sometimes catastrophic outburst floods one to three times a year for several years once an ice dam has formed. Although the downstream population is aware of the risk, early warning systems are being established by the government, and protection measures are being undertaken, even the most recent outburst floods, e.g. at Shishper Glacier, have caused significant damage to essential infrastructure such as the Karakoram Highway and local settlements.
In summer 2024 a team of four members of the GOTHECA project carried out fieldwork missions at 6 surge-type glaciers in the upper Hunza Valley and at two glaciers in Shigar Valley. We collected repeat UAV data on eight glaciers, UAV data of GLOF lake bathymetry for three locations, GPR data on three glaciers, temperature gradient data together with local students, and established a weather station in Shimshal Valley thanks to collaboration with partners from Pakistan. The aim of this data collection is to provide ground-truth for satellite data, to better understand the current state and characteristics of local surge-type glaciers, and to better quantify and model past and future GLOFs in Gilgit-Baltistan.
We present preliminary results from repeated UAV surveys and from some of the first GPR surveys on these surge-type glaciers in the upper Hunza Valley, providing insights about volumes of former and potential future ice-dammed lakes, ice dynamics, and thermal properties of glacier tongues. With air temperatures of nearly 30 degrees Celsius measured at the tongue of Yazghil Glacier at 3000 m.a.s.l. at noon in summer, daily melt rates were extremely high at more than 0.15 m/day, but the glacier tongue was advancing at several decimeters per day, indicating a potential onset of a surge. Radargrams for three surge-type glaciers indicate alternating zones of warm and cold ice, suggesting polythermal characteristics of these glacier tongues even when not actively surging.
How to cite: Egli, P., Enzenhofer, U., Lappe, R., Hillisch, L., Ayub, G., Hussain, Z., Raza, G., Steiner, J., and Gong, Y.: Insights from fieldwork on surge-type glaciers with GLOF potential in Gilgit-Baltistan: preliminary results from UAV surveys, GPR surveys, and meteorological measurements , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10525, https://doi.org/10.5194/egusphere-egu25-10525, 2025.
Glacier retreat and the transition from land to lake termini can accelerate mass loss through various feedback mechanisms. This study examines the dynamic changes during the land-to-lake transition of four neighboring glaciers (Exploradores, Grosse, Reichter and Gualas) located in the maritime-humid climate of the western Northern Patagonian Icefields, where ablation rates on glacier terminal tongues can reach up to 20 m w.e. annually.
We conducted the first bathymetric surveys on the glacier’s proglacial lakes and integrated data on ice velocity, elevation changes, front retreat, and front depth to identify the main controls on glacier retreat. Three transition stages were observed: (i) initial thinning with slow front retreat, (ii) increased glacier velocity and terminus flotation leading to rapid disintegration into large tabular icebergs, and (iii) formation of a stable calving front on prograde or <5º retrograde bedrock slopes, with a slowdown in velocity followed by smaller calving events. One debris-covered glacier left large sections of dead ice, while debris-free glaciers efficiently produced large tabular icebergs (>500 m).
While Grosse, Gualas and Reicher Glacier developed a calving front, Exploradores Glacier is currently in stage (i) to (ii), characterized by increased velocity and flotation. Identifying this stage is critical for Exploradores Glacier not only for glaciological interest, but also due to a rapid increase in lake area in the coming years, which will heighten the risk for tourists accessing the terminal glacier tongue, a major attraction visited by up to 9,000 tourists annually. Due to insufficient ice bedrock information to fully assess flotation conditions, we discuss the potential of using ice velocity (widely available nowadays through satellite), geometry and elevation changes to predict rapid retreat stages.
In the Patagonian Icefields, overdeepened areas currently covered by ice are expected to fill with water as glaciers retreat. Understanding the impacts and processes during glacial lake development will enhance the interpretation of paleo-records and predictions of glacier responses to climate change in future environmental systems.
How to cite: Irarrazaval, I., Somos-Valenzuela, M., Lizama, E., Morales, B., Egli, P., Dussaillant, I., and Reid, B.: Changes in glacier dynamics during land-to-lake glaciers transition in Patagonian glaciers. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7609, https://doi.org/10.5194/egusphere-egu25-7609, 2025.
Glacier-climate models are crucial for understanding and predicting climate change impacts on snow and glacier-fed regions. However, their accuracy depends heavily on the quality of climate input data. While general circulation models (GCMs) provide broad-scale insights, their coarse spatial resolution limits their ability to capture fine-scale climatic variability, especially in complex mountainous regions. We integrate high-resolution Regional Climate Models (RCMs) and Convection-Permitting Models (CPMs) into a glacier-climate coupled model namely Open Global Glacier Model (OGGM) to improve equilibrium line altitude (ELA) projections for the glaciers of Aosta valley. We calibrate OGGM using the snow line altitude (SLA) dataset. SLA at the end of the ablation season is an indicator of climate change and a proxy to equilibrium line altitude (ELA). We compute SLA by incorporating satellite imagery of Landsat data for calibration period through image segmentation. K-Means Clustering is utilizing to divide the image into three classes: snow, ice and barren. By computing snow cover ratio across various elevations, the SLA is computed. The clustered classes are validated with manual segmentation while the SLA time series is by the dataset provided by the World Glacier Monitoring Service (WGMS). Historical ELA is constructed based on the Historical Instrumental climatological Time series of the greater Alpine region (HISTALP) for the calibration period. The calibration period gives Pearson’s correlation coefficient of 0.69. We force the high resolution RCMS and CPMs for both the historical period (1985-2005) and future period (2006-2100). The reason is to validate the model for both periods and to analyze whether the provided models perform well in the historical period or not. The RCMs and the CPMs offer advantages over the GCMs by resolving finer-scale atmospheric processes, such as orographic precipitation and temperature gradients, crucial for accurate glacier modeling. Our results indicate that the RCM and the CPM reduce biases in the ELA predictions, aligning more closely with observational data compared to GCM-driven simulations. These advancements highlight the transformative potential of high-resolution climate models in glacier research, offering more reliable projections of glacier mass loss, water resource availability, and climate-driven hazards in alpine regions.
How to cite: Ayub, S., Camporeale, C., Ridolfi, L., Coppola, E., and Godio, A.: Enhancing Glacier-Climate Modeling: Integrating High-Resolution Climate Models for Improved Equilibrium Line Altitude Projections in the Alpine Glaciers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15055, https://doi.org/10.5194/egusphere-egu25-15055, 2025.
Observed glacier melt is a hallmark of modern climate change, yet a comprehensive attribution of industrial-era glacier retreat to human-caused warming remains to be settled. This challenge stems from difficulties in accurately simulating individual glacier behavior, which depends on poorly constrained factors like local geometry and historical climate conditions. Here, we adapt methodologies that have previously been applied to industrial-era temperature attribution, and apply them towards climate metrics of specific relevance to glacier mass balance. We use historical and natural-forcing-only simulations from the CMIP5 and CMIP6 climate-model archives, along with observational products of near-surface temperature (e.g. Berkeley Earth) to create a global map of anthropogenic melt-season temperature change. These temperature changes are translated into shifts in equilibrium line altitude (ELA), the boundary between a glacier’s accumulation and ablation zones. By applying these ELA shifts to example glacier profiles that match known Little Ice Age extents, we estimate the changes in ablation area and rates resulting from anthropogenic activity. This approach offers fresh insights on quantifying the impact of anthropogenic emissions on modern glacier retreat globally.
How to cite: Berdahl, M., Christian, J., Steig, E., and Roe, G.: Adapting temperature-attribution methodologies to understand industrial-era glacier retreat, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20608, https://doi.org/10.5194/egusphere-egu25-20608, 2025.
In the Southern Volcanic Zone of the Andes (~33°S - ~46°S), glaciers occur only on the highest peaks of active volcanoes. Many of these glaciers, hence, are located within craters or calderas that have a bowl-shaped basal geometry atypical to other mountain glaciers. Volcán Sollipulli, located at about 39° S, hosts a massive glacier that fills a caldera (diameter of ~4 km), with a relatively flat surface elevation of ~2060 m in 2023/2024. Ground-penetrating radar data from 2013 suggested a maximum ice thickness of approximately 750 m, making it the deepest measured body of ice in Chile, north of the Patagonian Ice Fields, thus harboring a vast amount of freshwater. Glaciers in the southern Andes are undergoing unabated retreat, resulting in reduced freshwater storage, increasing contribution to sea-level rise, and leading to the formation of glacial lakes, which implies the potential risk of glacial lake outburst floods (GLOFs).
We present a glaciological study of the caldera Sollipulli glacier, investigating the glacier surface elevation over the last decades using remote sensing data and field measurements, and discuss potential effects of the atypical geometry on its future evolution. While the glacier was already losing mass in the 2000 – 2015 period, our results show a nearly two-fold increase in melt rates since then, resulting in more than 60-m glacier thinning during the 21st century. The increasing melt coincides with observations of late summer snow absence on the entire glacier. This indicates that the freezing level has risen above the maximum glacier surface altitude, leading to shrinkage of the accumulation zone to a minimum or its disappearance. In consequence, the surface-lowering induced melt-elevation feedback is now further enhancing mass loss, in addition to the increased climate forcing. The evolution of existing and new marginal glacial lakes is providing hints on glacier hydrology and provides insights on the potential future lake formation that could affect the glacier’s role as a freshwater reservoir and GLOF risk.
How to cite: Arndt, J. E., Somos, M., Farías, D., Navas, S., Rivera, A., Xie, H., and Fernández, A.: Evolution of the caldera-filling glacier at Volcán Sollipulli, Chile, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15883, https://doi.org/10.5194/egusphere-egu25-15883, 2025.
Glaciers worldwide are retreating due to climate change driven by anthropogenic greenhouse gas emissions, but local human activities also impact glacier dynamics. This study models the effects of gold mining on Davydov glacier in the Central Tien Shan, Kyrgyzstan, from the Little Ice Age through 2100 using a 3D thermodynamic ice flow model. Historical evolution is constrained using satellite observations, while ice excavation from mining is simulated by removing ice within predefined masks. Results show that mining over the past two decades shortened the glacier by ~2 km and reduced its volume by 160 million m³ compared to a climate-only scenario. Projections indicate that if mining ceases, the glacier could advance temporarily by ~100 m because the current ice-flux is at present larger than the surface mass balance. Maintaining its position would require annual removal of up to 650,000 m³ of ice. By 2060, natural retreat is expected to extend beyond the mining site, with no significant differences between mining and no-mining scenarios. By 2100, volume losses range from -40% to -99%, depending on the climate scenario. Under a hypothetical return to Little Ice Age conditions, the glacier could fully recover within 500 years, but mining-induced landscape changes would lead to larger glacier regrowth, with ice thickness reaching up to 600 m due to central pit filling. This study underscores the long-term impacts of local human activities and landscape modifications on glacier geometry and dynamics.
How to cite: Van Tricht, L., Zekollari, H., Huss, M., Rybak, O., Satylkanov, R., and Farinotti, D.: Modelling the impact of mining activities on the dynamics and evolution of a Kyrgyz glacier, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1532, https://doi.org/10.5194/egusphere-egu25-1532, 2025.
Belvedere Glacier, in Italy, is the Alpine glacier with the highest elevation jump, starting from the East Massif of Monte Rosa over 4,000 m a.s.l., and with an ablation area ending at ca. 1,900 m a.s.l. . The deep debris layer, which covers and insulates the tongue of the glacier is indeed the reason why it still persists at such low altitudes. The modelling of dark glaciers melt and dynamics is made difficult by the changing debris cover layer. Here, thanks to the measurements campaign on Belvedere Glacier of 2024, where we installed a climate station, several thermistors, and ablation stakes, we calibrated an energy balance model to mimic ice melt. We also assessed debris layer thickness by reversing energy balance model using infrared satellite images. Dynamics of the glacier was modelled using Glen flow law and GPR measurements of ice thickness.
By coupling the energy balance model to Poli-Hydro hydrological model we were able to mimic the evolution of the glacier and the water resources of the area up to 2100 using 6 GCM from AR6.
How to cite: Dezuanni, P., Stucchi, L., Fugazza, D., Barbone, D., and Bocchiola, D.: Physical modelling of the retreat of Belvedere Glacier through the 21st century, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12993, https://doi.org/10.5194/egusphere-egu25-12993, 2025.
Due to ongoing glacier shrinkage caused by anthropogenic climate change, Col de Tsanfleuron (2803 m a.s.l.) in the western Swiss Alps, a former ice pass separating two neighbouring small mountain glaciers (Glacier de Tsanfleuron and Glacier du Sex Rouge), became ice-free in September 2022. The question arose as to whether or not the pass had – until 2022 – always been ice-covered throughout the Holocene. Both bedrock lithology of the now ice-free pass and anthropogenic disturbance likely impedes the application of surface exposure dating to answer this question. Therefore, the glaciers’ evolution was modelled from 11.5 ka until 2100 CE using the Instructed Glacier Model (IGM). Model calibration was carried out based on available glacier mass balance data. Due to the different quality and spatiotemporal resolution of available climate data, two different model runs were performed for the past (one from 11.5 ka to 2000 CE, and a second one from the Little Ice Age maximum (1850) to 2020). In addition, the future evolution of both glaciers was modelled until 2100 using an ensemble of 10 different GCM-RCM model chains for three different RCP scenarios. The three model runs were initialised with reconstructed or observational data for glacier extent, surface elevation and ice thickness. Validation of the modelling results was performed based on known evidence of Holocene glacier fluctuations in the Alps as well as using available 1850-present glacier area and volume data.
Even though the modelled fluctuations of Glacier de Tsanfleuron and Glacier du Sex Rouge show high temporal coherence with known advance and retreat phases for other alpine glaciers, modelled glacier extents and volumes are larger for the entire Holocene compared to in-situ measurements in 2019. According to preliminary modelling results, Col de Tsanfleuron was likely ice-covered throughout the Holocene until 2022. These results partly contrast with other studies, suggesting for instance that in the Alps various summits at higher altitude had been ice-free during the Holocene Thermal Maximum (~10.2 to ~4.2 ka). On the other hand, there is evidence that individual small alpine glaciers persisted during the entire Holocene. Our modelling results are subject to various uncertainties, e.g. related to the initial glacier area, surface elevation and volume, related to the climate data sets used, or related to the melt parameters applied and the modelling approach itself. For the period 1850-2020, our model is able to realistically trace the glaciers’ evolution at high spatiotemporal scale. Modelling results for the future predict the ultimate disappearance of both glaciers. Glacier du Sex Rouge will have completely vanished by around 2040, whereas, depending on the modelled climate scenario, the latest remnants of Glacier de Tsanfleuron will disappear between 2060 and 2080.
How to cite: Schild, J., Fischer, M., and Jouvet, G.: Modelling the fluctuations of two small alpine glaciers (Glacier de Tsanfleuron and Glacier du Sex Rouge, western Swiss Alps) throughout the Holocene (11.5 ka – 2100 CE), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18463, https://doi.org/10.5194/egusphere-egu25-18463, 2025.
