This session invites contributions that advance the coupling of observational datasets (satellite, airborne, and in situ) with numerical models (ice dynamics, permafrost, hydrological, hydrochemical, and Earth System Models). We welcome abstracts that address:
- Improved representation of snow, ice, and permafrost processes in models through assimilation of Earth observation and field data.
- Case studies linking local observations to large-scale dynamical models, including contributions to CMIP, ISMIP, CORDEX, SnowMIP, and Copernicus.
- Quantification of the impacts of land ice and permafrost change on sea level, ocean circulation, hydrology and ecosystems.
- Process understanding of ice sheet or glacier dynamics, and assessment of changes on decadal to centennial timescales.
- Process understanding by integrated observations of Atmosphere-Cryosphere-Hydrosphere coupled systems at glaciated catchment scale.
- Development of tools and approaches that bridge gaps between modelling and monitoring communities, including applications of AI and machine learning.
We particularly encourage contributions from Horizon Europe projects such as ICELINK (North Atlantic land ice and climate interactions), LIQUIDICE (impacts of inland ice, snow, and permafrost change on water resources and society), and CryoSCOPE (novel observations and process modelling of globally significant cold spots), and other related initiatives.
By bringing together observational and modelling perspectives, this session aims to advance process understanding, improve predictive capability, and foster interdisciplinary collaboration across cryosphere disciplines.
Orals: Thu, 7 May, 14:00–15:45 | Room 1.34
The Polar Regions in the Earth System (PolarRES) project financed by the European Union’s Horizon 2020 research and innovation programme involved more than 80 researchers from 21 organisations across Europe, Asia, and North America. The project, which began in September 2020 produced an ensemble of high-resolution regional climate simulations for the Arctic and Antarctic in support of impact assessments in the polar regions. These simulations from the PolarRES project used a novel storylines approach and a multi-disciplinary framework to develop century-long climate projections at spatial scales of approximately 12km which is unprecedentedly high resolution for any multi-model ensemble covering the Arctic for such a long period of time. The PolarRES ensemble followed the CORDEX protocol and are publicly available for the wider scientific community. In this talk, I will present an overview of the PolarRES simulations, their performance, and show some recent applications of these climate simulations for studying the impacts of future climate change in the Arctic.
How to cite: Mooney, P.: Storylines of Arctic Climate Change: High-resolution climate projections for the Arctic , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12816, https://doi.org/10.5194/egusphere-egu26-12816, 2026.
Snow cover strongly influences the surface energy budget, affects seasonal temperature patterns, and shapes regional climate feedbacks. Observation-based estimates indicate that snow–albedo feedbacks can substantially amplify local warming. Yet climate models may underestimate these effects, as limited simulated temperature increases, underestimated snow loss, or mistimed snow melt, particularly in spring and early summer, can dampen the representation of key feedbacks linking snow cover, surface energy fluxes, and near-surface temperature. Such mismatches suggest that important cryosphere–atmosphere interactions may be insufficiently captured in current simulations.
In this study, we link observational datasets and reanalyses with EURO-CORDEX regional climate model simulations to assess how well snow processes are represented across Europe. How well do model-simulated changes in snow amount and seasonality reproduce observed trends in timing and magnitude, and how do differences in snow representation influence surface energy fluxes and near-surface temperatures? By systematically comparing modeled and observed snow-related variables, we aim to identify biases in snow accumulation and melt processes and assess their implications for snow–temperature feedbacks. Addressing these questions is critical for regional climate projections, as underrepresented snow–temperature feedbacks may lead to underestimation of future warming and associated extremes in snow-sensitive regions.
How to cite: Börsig, S., Schumacher, D. L., Kotlarski, S., and Seneviratne, S. I.: Changes in Snow Cover from EURO-CORDEX Simulations and Observations: Implications for Surface Energy Budgets and Climate Feedbacks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18457, https://doi.org/10.5194/egusphere-egu26-18457, 2026.
Snow sublimation remains poorly quantified globally, with published estimates spanning orders of magnitude (≈0.01mm/day to >6mm/day), corresponding to ~ 5-90% of winter snowfall. This large uncertainty limits our ability to accurately quantify water availability to downstream ecosystems, as vapor losses through sublimation reduce meltwater availability. Here, we quantify surface snow sublimation over one full winter season (November 2024 to June 2025) at a high-elevation alpine site (Weissfluhjoch Versuchsfeld, 2455 m a.s.l., Switzerland) using continuous eddy-covariance measurements from an integrated open-path gas analyzer and sonic anemometer (IRGASON). We applied an eXtreme Gradient Boosting (XGB) model to estimate surface snow sublimation and used TreeExplainer-based Shapley Additive Explanations (SHAP) to quantify the relative importance of different meteorological variables on modeled sublimation.
Over the 2024-25 winter season, cumulative net sublimation was 31±21mm, equivalent to 5.1±3.6% of winter snowfall, with a mean daily rate of 0.15 mm/day, placing our estimates at the lower end of previous compilations. During the accumulation period, sublimation accounted for 48% of cumulative winter sublimation and was primarily driven by vapor pressure deficit. In contrast, 52% of cumulative sublimation occurred when the snowpack was melting. For this period, net incoming radiation emerged as the dominant statistical driver of sublimation. Notably, net radiation is only indirectly represented in current energy-balance formulations of physically-based snow models, revealing potential limitations in existing Monin-Obukhov parameterizations. Our results therefore highlight the importance of continuous eddy-covariance observations throughout winter periods for accurately constraining snow sublimation and highlight potential biases in Earth System Models that do not explicitly represent radiative controls on sublimation.
How to cite: Anglin, I., Teuling, R., Floriancic, M., Asemann, P., Lehning, M., and Beria, H.: Magnitude and controls of snow sublimation at a high-elevation Swiss alpine site , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18102, https://doi.org/10.5194/egusphere-egu26-18102, 2026.
Rapid changes in the cryosphere, including permafrost, glaciers, and snow cover, are increasingly altering polar environments, with significant implications for climate feedbacks, hydrology, ecosystem functioning, and biogeochemical cycles. In polar regions, these transformations are particularly pronounced in post-glacial landscapes, where surface and subsurface processes respond sensitively to ongoing climatic forcing.
This study presents the results of long-term investigations of permafrost distribution and degradation in the Hornsund area (Svalbard), based on electrical resistivity tomography (ERT) surveys conducted between 2010 and 2025. Geophysical measurements were carried out across a range of geomorphological settings, including marine terraces, mountain slopes, coastal zones, and the forefields of retreating glaciers. The multi-site and multi-temporal ERT dataset enabled detailed identification and characterization of permafrost occurrence, thickness, and internal structure under varying environmental conditions.
The 15-year observation period provides a robust basis for assessing spatio-temporal changes in permafrost distribution and for identifying signs of progressive degradation in selected areas. Observed resistivity patterns indicate a reduction in permafrost continuity and thickness. These results contribute to improved quantification of the impacts of permafrost change on hydrological regimes, sediment and nutrient transport, coastal stability, and ecosystem dynamics. The findings highlight the importance of long-term geophysical monitoring in reducing uncertainties associated with projections of cryosphere climate interactions and their broader environmental consequences.
How to cite: Kondracka, M., Oryński, S., Ignatiuk, D., Kasprzak, M., Senderak, K., and Kot, M.: Changes in permafrost distribution in the Hornsund Area (Svalbard) based on ERT surveys from 2010 - 2025, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21280, https://doi.org/10.5194/egusphere-egu26-21280, 2026.
Accurate prediction of permafrost thaw requires understanding soil freeze-thaw dynamics, yet current climate models assume pure water freezing points that may be inadequate for real soils. Traditional freeze-thaw theory suggests that salt in soil water increases Gibbs free energy, lowering the soil freezing point and enabling sub-zero unfrozen states (SUS). While these physical and chemical interactions have been documented in laboratory studies, they have not been evaluated by large-scale Earth observations. Here, by integrating satellite-derived freeze-thaw states with soil property datasets, we investigated thermal dynamics and mechanisms of SUS events across seasonally frozen soils of the Northern Hemisphere using machine learning and statistical analyses. Using satellite observations, we estimate a representative soil freezing point of 271.83 K, characterized by the median temperature of first seasonal freezing, which is nearly 1.3 °C lower than that of pure water. SUS events showed a wide occurrence temperature range (interquartile: 269.04–272.74 K), with 37.67% occurring at temperatures below the median freezing point. These low-temperature events are mainly driven by soil salinity and spontaneous entropy-increasing thawing processes. We compared observed freezing point depression with a simple physicochemical model incorporating soil salinity and moisture effects, which demonstrated strong agreement. These findings suggest that climate models assuming a 0 °C freezing point may underestimate active layer thawing rates and permafrost degradation risks. Our results indicate an urgent need to incorporate freezing point depression in Earth system models to accurately predict permafrost stability, with important implications for climate projections and ecosystem management.
How to cite: Dong, Z. and Fan, Y.: Global Patterns of Soil Freeze-Thaw States Below 0 °C, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2483, https://doi.org/10.5194/egusphere-egu26-2483, 2026.
Western Disturbances (WDs) are upper-tropospheric synoptic-scale systems embedded in the subtropical westerly jet stream, playing a critical role in winter precipitation across the north and northwest Indian subcontinent, including the Himalayas. This study synthesizes insights from multi-decadal analyses (1980–2019) using reanalysis datasets (ERA5, MERRA-2, NCEP-CFSR/CFSv2) to characterize the evolving dynamics, precipitation patterns, and regional impacts of WDs. In the core WD zone of north India, although WD frequency remains relatively stable, a sharp decline (~49%) in intense (strong and extreme) WDs and associated precipitation suggests an increasingly inhibitive dynamic environment with reduced moisture advection. Conversely, over the Karakoram region, WDs have intensified in recent decades, exhibiting a ~10% rise in precipitation intensity and contributing up to ~65% of the total seasonal snowfall. This enhanced snowfall sustains the so-called “Karakoram Anomaly”, a regional glacier stability or mass gain contrasting widespread glacial retreat elsewhere in the Himalayas. The anomaly correlates with declining non-WD snowfall (~17%) and increased baroclinic instability, along with a notable eastward shift (~9.7°E) in the genesis zone of Karakoram WDs toward regions with higher cyclogenesis potential, convergence, and moisture availability. Furthermore, a slowdown in WD propagation speeds has led to more intense and prolonged precipitation events in the region. Collectively, these findings highlight the divergent regional impacts of WDs across the western Himalayas and underscore their central role in driving winter hydroclimate variability, glacier dynamics, and climate change responses in one of the most climate-sensitive regions on Earth.
How to cite: Kumar, P.: Mid-Latitude Dynamical Changes Explain Persistent Glacier Stability in the Karakoram, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18778, https://doi.org/10.5194/egusphere-egu26-18778, 2026.
The detailed, physically-based, one-dimensional snowpack model SURFEX/ISBA-Crocus was used to simulate the seasonal and annual surface mass balance (SMB) of the five largest Icelandic glaciers (Vatnajökull, Langjökull, Hofsjökull, Mýrdalsjökull and Drangajökull) for the period of 1990–2024, for which annual mass-balance measurements are available. The model is forced using the high-resolution Copernicus Arctic Regional Reanalysis (CARRA) dataset. Near-surface air temperature from CARRA was downscaled using a daily lapse rate (multi-year average for each day of the year) using Digital Elevation Models (DEM) with 100-m or 250-m resolution. In addition, a precipitation/elevation gradient of 10% per 100 m was applied using the elevation difference between the higher-resolution DEM and the CARRA DEM following a reclassification of rainfall and snowfall to take into account the downscaled temperature. Daily albedo from the Moderate Resolution Imaging Spectroradiometer (MODIS), data for 2000–2024, and observations from the Icelandic Glacier Automatic Weather Station (ICE-GAWS) network, data for 2001–2024, as well as the glacier mass-balance data, are used to calibrate the model. An intermediate complexity modeling strategy was considered in this work, which takes into account the effect of light absorbing particles (LAP) on albedo using an LAP-informed and spatially variable snow-darkening coefficient to control the time evolution of snow albedo in the visible range. Roughness length of pure snow (Z0snow) in the range of 0.1–10 mm was also used as a calibration parameter. Multi-year mean albedo values from MODIS were calculated for the period of 2000–2017 to represent the end-of-summer ice albedo, used as inputs to the model at each of the SMB measuring stakes. The modeled seasonal and annual SMB results were compared to measurements at more than 150 stakes on the five glaciers. Summer and winter mass balances were well predicted by the model (the model explains 70–80% of the variance, RMSE = 0.6–0.9 m w.e.). The modeled albedo was compared with the observed albedo values from MODIS and ICE-GAWS data. The model captures the temporal evolution of albedo relatively well, but generally underestimates high albedo values and overestimates low albedo values. The model was also not able to capture variability in ice albedo during the ablation season due to the use of a constant multi-year average ice albedo, which results in an underestimation of the highest melt values. Further improvements in the model are under development, including a correction of the multi-year late-summer ice albedo from MODIS to improve summer melt estimation.
How to cite: Zaqout, T., Pálmason, B., and Jóhannesson, T.: Energy-balance modeling of glacier mass balance in Iceland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12418, https://doi.org/10.5194/egusphere-egu26-12418, 2026.
The ongoing retreat of glaciers in Svalbard potentially exposes a permafrost-free glacier forefield (talik), which in certain cases also can become exploited by CH4-saturated groundwater. In order to understand potential gas transfer to forefields linked to changing groundwater recharge and subglacial pressures, we present a coupled model for ice-dynamics, sub-glacial water flow and a geo-thermal groundwater-permafrost model, all included and coupled together in the package Elmer/Ice. The thermo-mechanical ice-flow problem is solved using the Stokes equations, sub-glacial hydrology by GlaDS. With the additional geo-thermal groundwater-permafrost model we are in a position to study the complete transient hydrological and thermal system from glacier surface - with prescribed moulin recharge - down to the sub-permafrost aquifer and can trace groundwater paths with a seasonal resolution. Along the well studied glacier Midtre Lovénbren we demonstrate the importance of producing consistent initial conditions (in particular for permafrost distribution) and show transient simulation results that are qualitatively able to reproduce observed seasonal outflows of subglacial water in the glacier forefield.
How to cite: Zwinger, T., Hodson, A., and Irvine-Fynn, T.: Changes in sub-glacial and bedrock hydrology by retreating glaciers in Svalbard, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2956, https://doi.org/10.5194/egusphere-egu26-2956, 2026.
As ice sheets melt, they contribute to sea level rise, a process that varies regionally due to gravitational, rotational, and deformational effects, making location-specific projections essential for effective coastal adaptation. Here, we present the Mass Balance and Sea Level module of the ESA Digital Twin Component (DTC) for the Ice Sheets system, which is developed as a precursor to ice efforts within the EU's Destination Earth (DestinE) platform.
Our approach integrates multi-decadal radar altimetry observations and land surface temperature records to diagnose the contemporary ice sheet mass balance for Greenland, based on machine learning techniques to capture fine-scale spatial patterns in mass change. Additionally, our sea-level module computes regionally resolved sea level fingerprints that account for far-field effects of ice sheet mass redistribution, translating ice sheet changes into location-specific projections along European coasts.
Here, we demonstrate the operational capability through scenario-based applications, quantifying how different mass loss pathways affect coastal regions distinctly across Europe. Further, the system's modular architecture also enables interoperability with ocean and atmosphere components within DestinE, when ready, supporting integrated what-if scenario exploration.
Ultimately, by operationalizing the connection between satellite observations and regional sea level projections, the DTC Ice Sheets module may help bridge the observational-modeling divide and provide stakeholders with actionable insights for climate adaptation.
How to cite: Simonsen, S. B. and the DTC Ice Sheets Team: DTC Ice Sheets: Regional Sea Level Fingerprints from EO-Constrained Mass Balance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5285, https://doi.org/10.5194/egusphere-egu26-5285, 2026.
Posters on site: Tue, 5 May, 10:45–12:30 | Hall X5
Record high temperatures have recently been driving significant melting of the Greenland ice sheet, glaciers and permafrost. This ice loss, leading to increased fresh water into the North Atlantic region, risks destabilizing ocean circulation and weather patterns, with severe consequences for local communities in Greenland, Iceland and beyond.
The EU-funded project ICELINK aims to bridge the knowledge gap between climate models, ice-flow models, satellite observations and in-situ observations to accelerate the understanding of how glaciers and ice sheets in the North Atlantic respond to climate change, and their impacts on climate and ecosystems. Through improved understanding of snow, surface mass balance and the ice dynamical response to meltwater runoff, ICELINK will provide new knowledge of the processes that control the evolution of the Greenland ice sheet and Icelandic glaciers in response to global warming. Specifically, ICELINK will work with local communities to co-develop knowledge and strengthen adaptation strategies, helping them to mitigate risks and build resilience on hydrology and ecosystem risks. Further, ICELINK will use Icelandic glaciers as a data-observation laboratory to study the response of the Greenland ice sheet in a warmer world with more melting.
The presentation will discuss the importance of including observation-based knowledge to understand the mass loss from the Greenland ice sheet and Icelandic glaciers, which is a key focus of ICELINK. We will give an update on our research towards obtaining consistent observations-and-model-integrated datasets on surface mass balance (SMB), the ice dynamical response to surface melt and historical records of climate forcing trends and variability. These are key components in understanding the melting of North Atlantic ice and assessing the impact on Earth’s climate.
How to cite: Hvidberg, C. S., Cook, E., Aðalgeirsdóttir, G., and James, T. D. and the ICELINK team: Linking observations and models to advance knowledge of melting ice in Greenland and Iceland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19020, https://doi.org/10.5194/egusphere-egu26-19020, 2026.
Like most ice caps and glaciers worldwide, Icelandic glaciers are losing mass and retreating as a result of a warming climate. Here, we link satellite observations and dynamic ice-flow modeling to produce robust long-term projections of the five largest Icelandic ice caps—Vatnajökull, Langjökull, Hofsjökull, Mýrdalsjökull, and Eyjafjallajökull—until 2300 under the RCP 8.5 scenario. The simulations are conducted using the Parallel Ice Sheet Model (PISM), forced by climatic mass balance fields from a regional climate model.
PISM is initialized by constraining ice-flow parameters using satellite-derived surface velocities from Sentinel-1 for the period 2015–2020. Simulated velocities are compared to observations to identify the best-fitting parameter set, and simulated thickness and area changes are evaluated against available geodetic measurements and glacier outlines. These observational constraints are used to improve confidence in subsequent long-term projections.
The calibrated ice-flow model is then used to simulate glacier evolution until 2100, and then the 2081–2100 climatic mass balance forcing is repeated to extend the simulations to 2300. The ice caps are projected to lose 15–30% of their volume and 7–22% of their area by 2100, increasing to 50–70% volume loss and 30-60% area loss by 2300.
How to cite: Schmidt, L. S., Aðalgeirsdóttir, G., Belart, J. M. C., and Noël, B.: Dynamic simulations of Icelandic ice cap evolution constrained by observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10991, https://doi.org/10.5194/egusphere-egu26-10991, 2026.
Dyngjujökull is a surge-type outlet glacier, which in 2025 covered ~1030 km2, corresponding to more than 1/8 of Vatnajökull ice cap. Dyngjujökull has a surge interval of 20–30 years with the last surge occurring in 1998–2000. During that surge, ~12 km3 of ice was transported from Dyngjujökull’s reservoir area to the receiving area and the glacier margin advanced by ~2 km. The motion of Dyngjujökull has been measured at mass-balance stakes near its centre flow line since 1993. In spring 2025, a GNSS station was deployed at stake location D7, at elevation 1350 m a.s.l., slightly above the glacier equilibrium line. The velocity at this site had in recent years been gradually increasing from 60 to 90 m a–1 repeating similar development as observed prior to the last surge. The measured average velocity at D7 in the summer 2025 was 150 m a–1, approximately the same as observed at the start of the last surge in summer 1998, strongly indicating the onset of a new surge. Here we will present the evolution of ice motion of Dyngjujökull at the start of this surge, in winter 2025–26, extracted from multiple radar satellites, including ICEYE, Sentinel-1, TerraSAR-X/TanDEM-X and SAOCOM, and GNSS stations operated on the glacier. We also aim to present elevation changes deduced from Pléiades satellite DEMs planned for February to April, 2026.
How to cite: Pálsson, F., Magnússon, E., Drouin, V., Nagler, T., Tolpekin, V., Belart, J. M. C., Wuite, J., Hannesdóttir, H., Jóhannesson, T., Óskarsson, B. V., and Gunnarsson, A.: The onset of a surge in Dyngjujökull outlet glacier in N-Vatnajökull, Iceland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20800, https://doi.org/10.5194/egusphere-egu26-20800, 2026.
The archipelago of Svalbard, at 76-80oN, is located at the heart of the continuous permafrost zone, which means that all exposed areas (glacier-free) are covered by 100-400m thick permafrost. Permafrost in valleys is often saline due to Early Holocene seawater ingression, followed by regression and permafrost aggradation. We studied the chemistry and Ra isotopes of ground ice from saline permafrost at the Adventdalen valley, central Svalbard. Cores recovered from two adjacent drillholes, 10 km from the sea, within the Early Holocene seawater ingression, showed significantly different compositions. While one core, with up to seawater salinity, showed similar-to-seawater composition, ground ice in two less saline cores exhibited clear evidence for water-rock interaction. The cores also showed substantial differences in their radium isotopes. Ratios of long to short-lived isotopes (e.g. 226Ra/223Ra) in the ground ice of the less saline cores were much higher than in the more saline one (activity ratios of <<20 and >20, respectively). Notably, Ra isotope ratios in the latter were similar to (i.e. in secular equilibrium with) the ratios of their radioactive parents (e.g. 230Th/227Ac) on sediment surfaces (CEC fraction), while in the less saline cores, ratios were closer to parent ratios in the bulk sediments.
Another drillhole, 5 km from the sea, intruded a cryopeg (permafrost with overcooled brines), with hypersaline ground ice from 20m to 4m below surface and brine (50,000mg Cl l-1) that flowed into the borehole at a depth of 11m. Composition of both brine and the ground ice was indistinguishable from that of seawater, indicative of freezing-associated solute rejection with no crystallization or water-rock interaction involved. Importantly, (226Ra/223Ra) activity ratios in brine and the ground ice were significantly lower than the equilibrium ratios (mostly <<10).
It is suggested that the high (226Ra/223Ra) ground ice of the less saline cores represent the original Early Holocene sediment fluids, which had interacted with sediments, diluted and froze upon exposure to the atmosphere. On the other hand, the low (226Ra/223Ra) ground ice of the more saline cores is evidently much younger (no time for diffusion of the long-lived 226Ra from inside the grains), probably produced by Late Holocene brine infiltration from the underlying basement, which is evident in the brine found in the second site.
These observations demonstrate the complex history of permafrost and its liability to fluid migration. This further highlights another aspect in permafrost’s vulnerability and sensitivity to the ongoing climate change and warming.
How to cite: Weinstein, Y., Rotem, D., Harlavan, Y., and Christiansen, H. H.: Brine flow in permafrost, time constraints by Ra isotopes , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12264, https://doi.org/10.5194/egusphere-egu26-12264, 2026.
Deglaciation, declining seasonal snow cover, and permafrost thaw are among the most visible consequences of climate change. Yet, the implications of these cryosphere changes for river runoff—and for practical water management—remain insufficiently quantified. This study contributes to a broader initiative aimed at comprehensive assessment of past and future climate-driven changes in snow- and ice-dominated regions.
We applied graphical–analytical hydrograph separation into genetic runoff components (baseflow, spring snowmelt, rainfall floods, thaw floods) to 94 gauging stations from the Norwegian Streamflow Reference Dataset for 1960–2024, using the grwat R package. Daily discharge was combined with watershed-averaged daily precipitation and air temperature from the ERA5 reanalysis as input. We identify two key hydrograph transformations associated with cryosphere change: (1) a reduction in the volume of the spring snowmelt flood (vårflom) and (2) an intensification of winter thawing processes. The latter manifests as either higher runoff volumes during episodic winter thaw and rain-on-snow floods, or an increase in the frequency and duration of thaw-flood events, particularly since the 1990s–2000s.
As many Norwegian hydropower reservoirs were designed to capture spring snowmelt and release water during winter, these shifts imply increasing mismatch between inflow seasonality and existing regulation strategies. Possible operational tensions include reduced spring refill reliability, higher winter spill risk, or changing flood-control constraints. The observed trends therefore highlight a need to adapt reservoir operations to the likely continued redistribution of runoff from spring toward winter.
The study was funded by the European Union’s Horizon Europe research and innovation programme through the project LIQUIDICE (grant number: 101184962).
How to cite: Rets, E., Woods, R., Osuch, M., and Luks, B.: Detecting Cryosphere Signals in Runoff: Trends in Genetic Components in Norwegian Reference Streamflow and its Implication for Norwegian Hydropower Regulation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9937, https://doi.org/10.5194/egusphere-egu26-9937, 2026.
In cold regions, lake ice, which persists for months, influences the exchange of heat, momentum, and water between the earth’s surface and the atmosphere. Several lake models have been developed for simulating these exchanges, such as the Canadian Small Lake Model (CSLM) - a one-dimensional physical lake model that represents the thermal structure of lakes and their exchange of energy with the atmosphere, including the formation and evolution of ice and snow cover. These models do not always adequately simulate important parameters such as ice thickness, which in turns makes model evaluation an important, yet difficult task. The main challenge with model evaluation is the limited amount of observational data, since most northern lakes are in remote areas with limited accessibility.
This study presents an analysis of the temporal evolution of ice cover in two northern lakes over two winters and compares in situ measurements with the CSLM.
Field data were collected using an innovative temperature profiler. During the 2024-2025 winter, two profilers were deployed on two lakes in the boreal biome of Quebec, Canada: Piché Lake (0.15 km²; mean depth 2.2 m; ~47°N), a small lake surrounded by topography that facilitates snow accumulation leading to snow-ice formation, and Bernard Lake (4.6 km²; 13 m; ~51°N), a larger, more wind-exposed lake where thermal ice formation is dominant. During the 2025-2026 winter, only one profiler was deployed at Piché Lake. Profiler data were processed to generate a continuous dataset of ice and snow thickness for comparison with the CSLM outputs. The simulation was validated through manual measurements of ice and snow thickness at both Bernard and Piché Lakes, as well as upward-looking sonar measurements at Bernard Lake. Additional information on snow and ice properties was collected using snow pits, ice core sampling and visual observations using a GoPro camera, providing a more comprehensive basis for assessing and improving the representation of snow and ice processes in the CSLM.
Preliminary comparisons with CSLM indicate that the model generally underestimates maximum lake ice thickness. Also, the model predicts freeze-up earlier than observed, while it predicts breakup either earlier or later than observed. The contrasting ice processes at Piché and Bernard lakes, characterized by dominant snow-ice and thermal ice formation, respectively, provide a useful basis for evaluating the performance of the snow-ice production module in the model. Planned comparisons of snow cover will refine the module and improve the model’s representation of snow and ice.
Overall, this work advances understanding of atmosphere–cryosphere interactions and provides recommendations to improve CSLM performance.
How to cite: Brady, T., Thiboult, A., Ghobrial, T., Mackay, M., and Nadeau, D. F.: In situ measurements of ice growth and melt in two lakes of eastern Canada to improve ice representation in the Canadian Small Lake Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13566, https://doi.org/10.5194/egusphere-egu26-13566, 2026.
During the 33rd Bulgarian Antarctic expedition, the National Center of Meteorology (NCM), United Arab Emirates, successfully installed 365 days around the year, first UAE advanced automatic weather station on Livingstone Island, Antarctica. The station is equipped with ten high precision sensors, including air temperature (three thermometers), wind speed and direction, barometric pressure, relative humidity, global solar radiation, cumulative ultraviolet radiation, and satellite-based iridium communication for real-time data transmission.
The primary objective of this installation is to provide continuous, high-resolution meteorological observations under extreme Antarctic conditions, enabling detailed monitoring and analysis of local and mesoscale atmospheric processes. These observations contribute to a better understanding of climate variability and change in the Antarctic region, which plays a critical role in the global climate system.
In addition, the collected data supports regional and global scientific research initiatives by contributing to the international datasets and numerical weather predictions (NWP) models and Artificial Intelligence within the World Meteorological Organization (WMO) framework. This integration aims to enhance weather forecasting accuracy, early warning systems, and nowcasting capabilities, particularly for polar and downstream mid-latitude regions and furthermore.
The station also supports interdisciplinary research by providing valuable observations for studies related to atmospheric dynamics, surface-atmosphere interaction, glacier behavior, and potential links with seismic and volcanic activity. Through collaboration with international Antarctic research institutions and scientists, this initiative strengthens global partnerships, improves data sharing and addresses critical observational gaps in one of the world's most data-sparse environments.
This deployment represents a significant step toward long-term environmental monitoring in Antarctica and reinforces the UAE’s contribution to global climate research, early warning systems and informed decision-making for planetary protection through the Emirates Polar Program. This was UAE’s first step and more actions to climate is in progress.
How to cite: Al Kaabi, A., AlAmeri, B., Haroon, M., and Sapundjiev, P.: Continuous Weather Observation under extreme conditions – Antarctica, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15193, https://doi.org/10.5194/egusphere-egu26-15193, 2026.
Snow density is critical to the accurate simulation of energy exchange between the atmosphere and the underlying soil. Along with snow water equivalent (SWE) it is a key constraint on snow depth (HS). The snow density formulations used in global reanalyses have been developed and validated using detailed observational datasets but often from very limited locations. Unlike SWE and HS from global climate reanalyses which have been comprehensively evaluated using in situ observations, to our knowledge there are no similar hemispheric-scale assessments of snow density from these products. To address this gap, we use snow course observations from the NorSWE dataset to simultaneously evaluate SWE, SD, and snow density in five reanalysis products (ERA5, ERA5-Land, GLDAS2.1 Noah, JRA-3Q, MERRA2). We consider snow across the Northern Hemisphere over a range of snow classes and assess its seasonal evolution across the snow onset, peak and melt periods.
Results show a large spread in snow density both in terms of its spatial pattern and average magnitude. Products that can reasonably estimate SWE and/or HS do not necessarily have accurate snow density representations and vice versa. For example, MERRA2 ranks in the middle of the assessed products in terms of SWE and HS skill but its snow densities are poorly correlated with observations, whereas GLDAS 2.1 (Noah 3.6) has some of the largest SWE and HS errors, but some of the smallest snow density errors. Inaccuracies in SWE, HS and density can compensate for each other in different ways and these relationships vary between reanalyses. By examining snow density alongside SWE and HS, we aim to diagnose the principal sources of error in reanalysis snow estimates as stemming from errors in the snow model and its structural implementation within the reanalysis or from biases in meteorological forcing.
How to cite: Mortimer, C., Mudryk, L., and Vionnet, V.: How well do global reanalyses estimate snow density?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13370, https://doi.org/10.5194/egusphere-egu26-13370, 2026.
The detection of liquid water and ice, as well as the discrimination between frozen and unfrozen geological materials, remains a major challenge in periglacial geophysics. Seismic refraction and electrical resistivity tomography are widely applied to address this problem (Hauck et al., 2011; Mollaret et al., 2020); however, similar velocity and resistivity anomalies may originate from distinct physical configurations, including pore-filling ice, massive ice bodies, or heterogeneous mixtures of frozen and unfrozen materials. This intrinsic non-uniqueness complicates the interpretation of field geophysical data and limits the ability to infer the elastic contribution of ice to the seismic response.
In this study, we investigate how the assumed physical behaviour and spatial distribution of ice influence the joint interpretation of seismic velocity and electrical resistivity responses. Field geophysical datasets are analysed using a phase-based petrophysical joint inversion framework that estimates volumetric fractions of liquid water, ice, air, and solid matrix by coupling seismic refraction velocities and electrical resistivity following four-phases model scheme (Wagner et al., 2019). The seismic forward response is governed by effective-medium rock-physics formulations that explicitly account for the elastic contribution of ice (Mavko et al., 2009), whereas electrical resistivity is primarily controlled by the connected liquid water phase under Archie-type assumptions (Archie, 1942).To support the interpretation of the field inversion results, a suite of synthetic models is constructed to represent end-member and transitional ice configurations, including pore-filling ice, massive ice, and patchy distributions of ice-bearing and ice-free domains. Ice-related elastic properties are modelled using self-consistent approximation (SCA) effective-medium theory (Mavko et al., 2009), while electrical properties remain dominated by liquid water content following Archie-type relationships (Archie, 1942). Synthetic seismic and electrical datasets are generated and inverted using the same workflow applied to the field data, providing physically consistent reference scenarios for interpretation.
Comparison between synthetic and field inversion results reveals systematic differences in the coupled seismic–electrical response associated with volumetric ice contributions versus elastically stiff ice contributions to the seismic response. While multiple ice configurations may reproduce either seismic velocity increases or resistivity anomalies independently (Hauck et al., 2011), only a limited subset of scenarios yields mutually consistent fits to both datasets when rock-physics constraints are considered. Mismatches between inferred phase fractions, seismic velocity enhancement, and resistivity contrasts serve as diagnostic indicators for rejecting physically implausible interpretations and avoiding interpretational pitfalls.
Although a unique determination of ice type is not achievable, the combined use of rock-physics-informed joint inversion and synthetic reference models significantly reduces interpretational ambiguity. The results highlight the value of physically constrained joint inversion as a diagnostic tool for assessing the presence and elastic relevance of subsurface ice in periglacial environments.
How to cite: Miño, A. L. and Pipan, M.: Subsurface ice interpretation using joint seismic-electrical responses and rock physics diagnostic, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21397, https://doi.org/10.5194/egusphere-egu26-21397, 2026.
Posters virtual: Tue, 5 May, 14:00–18:00 | vPoster spot 1a
EGU26-20743 | Posters virtual | VPS20
Machine Learning based Seasonal Streamflow Forecasting in Cold-Region Catchments: Insights from LamaH-Ice datasetTue, 05 May, 14:09–14:12 (CEST) vPoster spot 1a
Machine learning (ML) remains one of the best approaches for long-term seasonal streamflow forecasting in cold regions owing to its capacity to capture nonlinearity between inputs and outputs, as well as its scalability across hydroclimatic regimes. ML’s main advantage lies in the generalizability of these models when applied to heavily glacierized catchments. In this data-driven study, we mainly utilize the Extreme Gradient Boosting (XGBoost) regression to train and test seasonal streamflow predictions using the LArge-SaMple DAta for Hydrology and Environmental Sciences for Iceland (LamaH-Ice). This new dataset for Iceland, published in 2024 consists of topographic, hydroclimatic, land cover, vegetation, soil, geological, and glaciological attributes that are essential for understanding cryosphere–hydrology processes in cold regions. For more than 100 basins, time series information on meteorological forcings and variables relevant to cold-region hydrology, such as MODIS (Moderate Resolution Imaging Spectroradiometer) snow cover, glacier albedo are also available. The majority of gauged rivers in LamaH-Ice are reported to have minimal human disturbances, making the dataset particularly unique. The XGBoost model demonstrates strong predictive skill across the study basins, as indicated by Kling-Gupta Efficiency (KGE) and Nash-Sutcliffe Efficiency (NSE) metrics exceeding 0.98. Ultimately high-precision streamflow forecasting is needed to track hydrometeorological hazards and to aid our ability to manage water resources in cold regions, which are a source for irrigation and hydropower.
References
Helgason, Hordur Bragi, and Bart Nijssen. “LamaH-Ice: LArge-SaMple DAta for Hydrology and Environmental Sciences for Iceland.” Earth System Science Data, vol. 16, no. 6, 13 June 2024, pp. 2741–2771, doi:10.5194/essd-16-2741-2024.
Strahlendorff, Mikko, et al. “Forestry Climate Adaptation with HarvesterSeasons Service—a Gradient Boosting Model to Forecast Soil Water Index SWI from a Comprehensive Set of Predictors in Destination Earth.” Frontiers in Remote Sensing, vol. 5, 20 Dec. 2024, doi:10.3389/frsen.2024.1360572.
How to cite: Prakasam, G., Strahlendorff, M., Kröger, A., and Gunnarsson, A.: Machine Learning based Seasonal Streamflow Forecasting in Cold-Region Catchments: Insights from LamaH-Ice dataset, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20743, https://doi.org/10.5194/egusphere-egu26-20743, 2026.
EGU26-16935 | Posters virtual | VPS20
Dust in the Arctic: feedbacks and interactions between climate change, aeolian dust and ecosystemsTue, 05 May, 14:15–14:18 (CEST) vPoster spot 1a
Dust in the Arctic is an emerging topic related to climate and environmental impacts. The United Nations (UN) General Assembles and the UN Coalition to Combat Desertification (UNCCD) have reiterated that the global frequency, intensity, and duration of Sand and Dust Storms (SDS) have increased in the last decade and that SDS have natural and human causes that can be exacerbated by desertification, land degradation, drought, biodiversity loss, and climate change. UNCCD and FAO have also highlighted that emerging SDS source areas have been associated with the warming of the Arctic and high latitude regions, the seasonal or permanent drying of inland waters and river deltas, or are following large-scale deforestation and wildfires, or even the ploughing of a single field. Loss of snow cover, retreat of glaciers, and increase in drought intensity due to climate change can lead to surface conditions that increase the likelihood of creation, continuation and expansion of SDS source areas.
Climatic feedback mechanisms and ecosystem impacts related to dust in the Arctic include direct radiative forcing (absorption and scattering), indirect radiative forcing (via clouds and cryosphere), semi-direct effects of dust on meteorological parameters, effects on atmospheric chemistry, as well as impacts on terrestrial, marine, freshwater, and cryosphere ecosystems. Here we give an overview of our recent understanding on dust emissions and their long-range transport routes, deposition, and ecosystem effects in the Arctic as presented in Meinander et al. (2025), part of the series of review papers of the Arctic Council Working Group AMAP (Arctic Monitoring and Assessment Program) and CAFF (Conservation of Arctic Flora and Fauna), where the target audience is the scientific community focusing on the Arctic. Additional audiences include policy advisers and other staff in environmental-related ministries.
We conclude that the multiple mechanisms related to dust emissions, transport and deposition both cool and warm the climate system, with an uncertain net effect. Dust plays a significant role in terrestrial and aquatic ecosystems, e.g., by providing nutrients, and with impacts on the availability of light and water. Due to Arctic warming, HLD dust emissions can be expected to increase. The contributions of LLD and HLD complicates the interpretation of how much different sources contribute to the dust loadings and corresponding temporal and spatial deposition patterns. Another challenge is that low latitude dust source emissions of road and agricultural dust is barely characterized.
Reference:
Meinander O, Uppstu A, Dagsson-Waldhauserova P, Groot Zwaaftink C, Juncher Jørgensen C, Baklanov A, Kristensson A, Massling A and Sofiev M (2025). Dust in the arctic: a brief review of feedbacks and interactions between climate change, aeolian dust and ecosystems. Front. Environ. Sci. Sec. Interdisciplinary Climate Studies, Volume 13 – 2025. doi: 10.3389/fenvs.2025.1536395. CAFF-special issue.
How to cite: Meinander, O., Uppstu, A., Dagsson-Waldhauserova, P., Groot-Zwaaftink, C., Juncher Jørgensen, C., Baklanov, A., Christenson, A., Massling, A., and Sofiev, M.: Dust in the Arctic: feedbacks and interactions between climate change, aeolian dust and ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16935, https://doi.org/10.5194/egusphere-egu26-16935, 2026.
