Assessing the impact of ice thickness uncertainty on future glacier evolution in the Himalayas using a higher-order glacier flow model

Abstract. Sweden currently hosts around 270 glaciers, four of which belong to the 61 reference glaciers monitored worldwide. Eight Swedish glaciers disappeared during the warm summer of 2024, and under the global warming scenario associated with current climate policies, all four Swedish reference glaciers (Mårmaglaciären, Storglaciären, Rabots glaciär, and Riukojietna) are projected to vanish within this century. Such change will have implications for people, ecosystems, infrastructure, and local meteorological processes, highlighting the need to better constrain the resultant emerging post-glacial landscapes. During 2024–2025, we conducted radio-echo sounding (RES) surveys on the four Swedish reference glaciers and obtained a total of 38 205 ice thickness point measurements. The mean measured ice thicknesses are 98 ± 14.5 m for Mårmaglaciären, 90 ± 14.6 m for Storglaciären, 85 ± 14.1 m for Rabots glaciär, and 35 ± 7.9 m for Riukojietna. The corresponding maximum measured ice thicknesses are 241, 225, 158, and 88 m, respectively. The RES-derived ice thickness measurements were used to produce high-resolution (10 × 10 m) maps of ice thickness distribution and subglacial topography for each reference glacier. The resulting mean distributed ice thicknesses and ice volumes are 96 m and 0.32 km3 (Mårmaglaciären), 85 m and 0.25 km3 (Storglaciären), 72 m and 0.23 km3 (Rabots glaciär), and 34 m and 0.10 km3 (Riukojietna), respectively. The RES data for the four reference glaciers are available at https://doi.org/10.17043/tarfala-marma-res-survey-2, https://doi.org/10.17043/tarfala-storglaciaren-res-survey-2, https://doi.org/10.17043/tarfala-rabot-res-survey-2, and https://doi.org/10.17043/tarfala-rivgojiehkki-res-survey-2 (Wang et al., 2026e, f, g, h). The ice thickness and subglacial topography for the four reference glaciers are available at https://doi.org/10.17043/tarfala-marma-res-3, https://doi.org/10.17043/tarfala-storglaciaren-res-3, https://doi.org/10.17043/tarfala-rabot-res-3, and https://doi.org/10.17043/tarfala-rivgojiehkki-res-3 (Wang et al., 2026a, b, c, d).

This study investigates the aerodynamic characteristics of crescent-shaped iced conductors through combined wind tunnel experiments and numerical analysis. Wind tunnel tests were conducted to obtain both steady and unsteady aerodynamic coefficients, the latter measured using an oscillating conductor model. The steady coefficients were acquired under various wind velocities ranging from 10 to 18m/s and ice thicknesses of 14, 24 and 33mm, covering trans-critical and super-critical Reynolds number regimes. Analytical expressions relating steady coefficients to the angle of attack were derived via polynomial fitting. A BP neural network model was subsequently developed and trained on this experimental data to predict aerodynamic coefficients for untested conditions. Furthermore, a MATLAB-based quasi-static model was established to convert steady coefficients into unsteady equivalents, enabling a direct comparison with the unsteady oscillation test data to validate the quasi-static assumption. The results confirm that the quasi-static assumption retains reasonable applicability in the studied regime. More importantly, the developed BP neural network demonstrates robust predictive capability, with its outputs showing close agreement with wind tunnel measurements, achieving determination coefficients exceeding 0.95. This work provides enhanced analytical tools and validated data for improving the prediction of conductor galloping-a critical wind-induced vibration-thereby contributing to the safety assessment and structural design of overhead transmission lines.

Ice fall incidents, such as detached ice chunks from bridge stay cables, pose not only serious safety hazards to pedestrians and vehicles below but also significant serviceability issues, as bridge closures required for inspection or ice removal can lead to costly disruptions. The current trend of climate change exacerbates this kind of hazard. The availability of a reliable engineering tool, such as an accurate numerical model grounded in nanoscale melt-front physics, is imperative to provide a clear insight into the ice detachment mechanism and develop effective de-icing solutions. Classical molecular dynamics simulations are conducted in the current study to investigate the melting of an ice cube in an atomically flat silver slab. The TIP4P/ice water model is adopted and the simulation is conducted in canonical ensemble with a layer-resolved Langevin thermostat. The phase evolution is tracked via the averaged tetrahedral order parameter, while systematically varying five controls: the depth of heated layers, the silver substrate thickness, the ice thickness, the lateral confinement, and the ice crystal contact orientation (basal vs prism). Results show that melting is controlled primarily by the substrate temperature; variations in heat-conducting-layer count had a minor influence and converged to similar end states. Doubling the ice thickness increases the melt time approximately by three times, whereas relaxing periodic boundaries reshapes the melt into domes or spreading films. Presenting the basal plane instead of a prism plane accelerates loss of crystalline order. Collectively, the simulations yield a numerically consistent set of parameters that not only advances the existing knowledge of nanoscale ice melting simulation but can also be transferred to continuum-scale de-icing simulations, enabling accurate modeling of melt-induced ice detachment from structural components, such as bridge stay cables.

The underside of the ice: Exploring the relationship between ice thickness and the roughness of the ice-water interface for freshwater lakes in Central Ontario

Perito Moreno is one of the largest glaciers in the Southern Patagonian Ice Field. Known until recently for its unique stability against climate change, favoured by the stabilizing effect of a subglacial ridge, it is now undergoing a distinct transition. We processed images from Pléiades-SPOT satellites during 2015–2023 to create digital elevation models and compute their difference, showing an average ice thickness change of −2.7 m a −1 in the terminal area. This rapid downwasting, accelerating since 2020, is likely driven by recent atmospheric warming and severe droughts, causing the glacier front to retreat beyond its pinning point. We assessed the ablation rate at the glacier terminus by solving the mass balance equation as a function of surface elevation change, velocity field, and ice thickness along two transects, one located close to the calving front. Surface velocity was derived from 88 Sentinel-2 images at 10 m resolution, acquired from 2019 to 2024, and processed using Imgraft software. Specifically, we integrated the mass balance equation over the time required for the glacier to travel between the upstream and downstream transects. In contrast to spatial integration, this approach leverages the mean trajectory velocity, effectively smoothing out local instabilities and rendering the results robust against the high uncertainty of pointwise velocities. The ablation rate of −16.4 m w.e. a −1 during 2015–2023 is consistent with recent measurements from ablation stakes, validating the reliability of the proposed time integral framework. • Perito Moreno glacier shows rapid thinning, with an average ice thickness change of −2.7 m yr −1 in the terminal area during 2015–2023. • Time integral of mass balance equation provides consistent estimate of ablation between two transects • Mass balance analysis, supported by Pléiades-SPOT DEMs and Sentinel-2 velocity fields, indicates strong surface lowering at the glacier front. • The ablation rate in the downstream area is −16.4 m w.e. yr −1 , in agreement with previous in situ stake measurements.

This paper presents the results of a laboratory study of ultrasonic pulse reflection from freshwater ice during a complete freeze-thaw cycle of the ice cover. Measurements were conducted in a small ice tank at the Arctic and Antarctic Research Institute. The maximum ice thickness was 57 cm, and the freeze-thaw cycle lasted 90 days. A sonar with a carrier frequency of 200 kHz operated continuously at the bottom. The transceiver antenna was oriented vertically upward toward the water surface. The underwater sonar measured and stored the reflected pulses throughout the experiment. Analysis of the reflected pulse data made it possible to study ice thickness dynamics and to obtain estimates of the average speed of sound in ice and the sound attenuation coefficient in ice over the entire measurement period. A simple empirical model for the shape of an acoustic pulse reflected from a freshwater ice cover is proposed. In this model, the reflected signal is represented as the sum of reflections from the undisturbed water surface, shifted by the travel time of the acoustic wave in the ice, with the reflection from the upper boundary of the ice cover additionally multiplied by the sound attenuation coefficient in ice.

Icing threatens the safety of aviation, power-transmission and wind-energy systems, yet concealed or transparent ice remains difficult to detect. Here we report a freezing-induced near-infrared (NIR) phosphorescence (FIP) imaging strategy based on aryl-substituted pyrrolo[3,2-b]pyrrole probes PP4P-X (X=F-, Br-, I-, NO3 -, and SCN-). Across the PP4P-X series, freezing broadly amplifies the steady-state emission, whereas a NIR phosphorescence band at 750nm enables deep-penetration, low-background imaging with pronounced counterion dependence. The FIP turn-on is strongest for PP4P-F, followed by PP4P-Br, switching from undetectable emission to intense phosphorescence. Mechanistic investigations reveal that specific adsorption of F-/Br- at the ice-water interface induces dense aggregation at the freezing front, strengthening molecular interactions to promote intersystem crossing and suppress triplet non-radiative decay. Leveraging this interfacial regulation, PP4P-F enables high-contrast, centimeter-scale ice imaging in diverse frozen media, with a 152-fold increase in signal-to-background ratio (SBR). In wind-tunnel aircraft icing tests, FIP imaging accurately maps the onset, thickness evolution, and downstream propagation of ice along the wing leading edge and correlates with laser-measured ice thickness. Overall, this work establishes a noncontact, in situ, and quantitative approach for "invisible ice" detection and provides a framework for NIR phosphorescent probes in frozen-phase monitoring.

With the increase in extreme weather events, icing disasters pose a significant threat to the safe and stable operation of distribution lines. In this study, a finite element model for stress analysis of iced conductors is established, and the dynamic stress characteristics of three types iced conductors under fluctuating wind conditions are analyzed, with particular attention given to the effects of varying ice thicknesses and wind speeds on the maximum conductor stress. Results show that JKLYJ-10/70 exceeds its tensile limit at an ice thickness of 27 mm, JL/G1A-50/8 reaches its tensile capacity around 47 mm, while JL/G1A-120/20 remains within safe limits even with 50 mm of ice. To achieve accurate dynamic stress prediction, a hybrid model combining a Long Short-Term Memory network and Dynamic Kalman Filtering is proposed. Under the condition of 10 mm ice thickness and 15 m/s wind speed, the proposed method achieves the lowest root mean square error among all compared algorithms, with a value of only 17.02 N, and the model also exhibits the lowest mean absolute error with a value of 16.69 N. The power spectral density exhibits dominant peaks at 1.76 Hz and 2.3 Hz, with the proposed method providing the closest agreement. Relative errors at these frequencies are only 2.49% and 0.78%, indicating that the proposed method more effectively captures the dynamic stress response of iced conductors under fluctuating wind conditions.

Abstract Antarctic ice-sheet sounding is critical for advancing insights into polar environmental systems. Seismic exploration constitutes an effective technique for Antarctic ice-sheet detection, as seismic waves exhibit substantial penetration depth and high resolution in
homogeneous snow-ice media. Nevertheless, extreme low temperatures, harsh ambient conditions, and the heterogeneous geographic and environmental characteristics of the Antarctic region impose significant constraints on both detection efficiency and precision.
To address these limitations, this paper proposes a seismic signal receiving system specifically engineered for the heterogeneous and harsh Antarctic environment. For detection efficiency, the system incorporates wired, wireless, and autonomous storage nodes to enable a distributed hybrid network, coupled with a power management module reducing the standby power from 7 W to 30 mW, and a wind-solar hybrid energy supply unit supporting operation down to -50◦C. To enhance precision, a neural network-based calibration method is utilized to mitigate temperature-induced drift in the analog-to-digital converter (ADC), achieving a calibration accuracy of 9.3 x 10−3 ppm. Additionally, high-precision acquisition and synchronization schemes are adopted, which realize a time synchronization precision of ±50 ns, input-referred noise of 0.20 μVrms@40 dB, and a dynamic range of 130 dB. Field validation experiments were performed near Taishan Station. The system successfully recorded signals from an artificial seismic source, based on which the ice thickness at the survey site was estimated to be 3.6 km; this estimation is highly consistent with data acquired via ground-penetrating radar (GPR). These findings verify the system’s performance and reliability, thereby laying a critical technological foundation for subsequent Antarctic ice-sheet investigations.

Glacier retreat transforms landscapes in polar and mountainous regions. Yet, the topography of the emerging terrain remains poorly known. Here, we present a physically consistent, global map of the ice-covered topography beneath all glaciers on Earth distinct from the ice sheets, derived from the three-dimensional higher-order Instructed Glacier Model, and constrained by extensive observational datasets. The map allows us to identify > 50,000 possible future lakes in the presently ice-covered landscape, with a maximum total volume of 3,138 km3—enough to store 7 mm sea-level equivalent (SLE). Additionally, we estimate the total global glacier volume at 149.41 ± 29.28 × 103 km3 (308 ± 60 mm SLE). Large overdeepenings near glacier fronts in High Mountain Asia suggest an increased risk for glacier lake outburst floods under glacier retreat. The subglacial topography and ice thickness data offer new opportunities for diverse cryospheric and Earth system studies, including refined projections of glacier changes and landscape evolution of deglaciated terrain.

Analysis of the influence of ice thickness on cavity evolution and motion characteristics of a cylinder during high-speed water entry

Snow atop Antarctic sea ice plays a critical role in modulating sea ice growth, surface energy balance, and ocean–atmosphere interactions. However, it also introduces substantial uncertainty into satellite altimeter-based sea ice thickness (SIT) estimates. Ku-band radar altimeters, such as CryoSat-2 (CS-2), are often processed using threshold-based retrackers that implicitly assume the maximum radar intensity return originates near the snow–ice interface. In practice, layered snowpacks featuring wet snow, brine infiltration, and ice lenses can shift the primary scattering contribution upward, leading to overestimated freeboard and higher SIT estimates. In Part I of this study, we used physically based waveform decomposition to quantify the vertical distribution of radar backscatter under Weddell Sea conditions. Building on these insights, Part II introduces an optimized threshold first-maximum retracker algorithm (TFMRA) for CS-2, tuned using airborne observations from NASA’s Operation IceBridge (OIB) over the Weddell Sea. We identify a 70% retracking threshold that minimizes freeboard bias and improves consistency with independent observations. Applying this snow-aware retracker to 46 CRYO2ICE collocated tracks (2020–2022), we retrieve snow depth from the ICESat-2 and CS-2 freeboard difference and reduce mean SIT by ∼ 0.1 m relative to the ESA Baseline-E product in the southern Weddell Sea. Monte-Carlo (MC) perturbations of OIB snow retrievals, combined with CS-2 threshold-sensitivity tests, indicate an intrinsic ∼ 0.2 m uncertainty in OIB snow depth and a similar lower-bound CRYO2ICE snow-depth uncertainty of ∼ 0.21-0.24 m at 10 km scales. Our results offer practical guidance for altimeter algorithm development and are directly relevant to upcoming dual-frequency radar missions such as ESA’s CRISTAL. • A 70% TFMRA threshold reduces radar freeboard bias, and improves Antarctic CryoSat-2 SIT. • Snow-aware CS-2 retracking tuned with OIB and CRYO2ICE sharpens snow depth and SIT. • OIB and CRYO2ICE snow depth errors ≥ 0.2 m constrain altimetry and guide CRISTAL.

AutoICE: An automated tool for estimating ice thickness and volume of glaciers in mountain regions

Volcanic eruptions and glacial ice have occurred at virtually all latitudes and altitudes throughout Mars history. To assess the astrobiological potential of processes and microenvironments associated with lava flows onto glacial ice, we explore: (1) the influence of lava flow loading on the flow behavior of underlying ice, (2) whether, and for how long, wet-based conditions might occur and be sustained in otherwise cold-based glacial environments, and (3) the immediate fate of the meltwater generated, whether moulins can be generated, and whether and for how long wet-based conditions are generated by such processes. We employ a 1D time-dependent solution of the heat-flow equation to solve for the transient temperature field within a column of ice subjected to instantaneous deposition of a hot lava layer, exploring the parameter space by examining six different initial surface temperatures and three potential geothermal fluxes to characterize a range of past climates/geological regimes. We observe an initial pulse of accelerated flow due to the increased loading by the lava and consequent increase in the driving stress. A secondary pulse of acceleration occurs as the temperature wave from the lava penetrates the ice and reaches the bed, where the bulk of the deformation occurs in response to the warmer, softer ice. We observe basal melting as the bed briefly reaches the melting point and characterize the amounts of water produced during such brief basal melting intervals. Examination of the meltwater generated below, and in moats adjacent to the superposed lava, shows that completely full moats can propagate cracks through km-thick ice, and such crevasses can remain open (moulins) if they are at least 90% full. The greatest volume of drained water is produced by thin lava over thick ice, but the longest duration draining events occur for moderate lava thicknesses over thinner ice. Locally wet-based glacial conditions could persist below the superposed lava flow for durations well over ∼103 years. We explore the detailed consequences of lava flow/ice interaction, highlighting those most important for the formation and dispersal of potential cryophilic microbiota on Mars, opening new windows of Mars history for astrobiological research and exploration.

Glacial loading in salt-bearing sedimentary basins drives complex interactions between brittle sediment faulting and viscous salt flow, which standalone DEM or FEM models cannot fully capture due to extreme rheological contrasts. To bridge this gap, we developed a 3D two-way coupled DEM–FEM framework that integrates granular deformation in sediments and ice (Ansys Rocky) with visco-elasto-plastic salt flow (Ansys Mechanical) through Python-scripted bidirectional data exchange. We tested the framework on a 60 km basin subjected to differential ice loading (2–4 km thickness). The simulations show that salt mobility substantially amplifies and reorganizes deformation, increasing fault counts by 9.3% and average fault density by 20% compared to rigid-base models. Faulting increases non-linearly (≈16.5%) with ice thickness, while fault dips remain stable between 25.5° and 27.5°, indicating that orientation is governed by sediment friction rather than loading magnitude. These results demonstrate that salt flow exerts a first-order control on stress redistribution, focusing deformation near ice margins and within specific strata. The coupled workflow provides a reproducible tool for analyzing multiphysics feedbacks in rheologically layered glaciotectonic systems.

The primary productivity of phytoplankton (PPeu) is critical to the carbon cycle in aquatic ecosystems. However, in complex lakes covered by ice, the estimation of PPeu using remote sensing techniques is constrained. To address this limitation, this study developed an estimation model for ice-covered PPeu by incorporating optical parameters such as the ice surface refractive index and the extinction coefficient of the ice layer into the vertical generalized production model (VGPM). This approach overcomes the challenges associated with remote sensing-based estimation of PPeu during ice-covered periods. The results indicate that the annual carbon sequestration of the WLSHL is 1.72 × 104 t C, with an average annual PPeu of 316.96 mg C·m−2·d−1. In addition to the indicators that are directly involved in the estimation of PPeu, the environmental factors that affect PPeu include water temperature (WT), ice thickness (IT), snow, water depth (D), total dissolved solids (TDSs), salinity (S), ammonia nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and oxidation–reduction potential (ORP). The PPeu in the ice period is found to be only 17% lower than that in the ice-free period. However, the PPeu during the ice period is considerably higher than that during the ice + snow period. The findings indicate that the impact of freezing on PPeu during the winter is relatively limited, whereas the influence of snowfall is more pronounced. In order to mitigate the elevated PPeu and the occurrence of algal blooms during the summer, the intensity of underwater radiation can be regulated on a periodic basis. To optimize the function of the carbon sink in winter lakes, the PPeu can be enhanced through initiatives such as water replenishment prior to freezing and snow removal following freezing.

Ice accumulation on power distribution lines leads to significant reliability issues, operational instability, and economic losses during extreme weather conditions. Accurate prediction and optimal placement of ice-melting devices are essential to mitigate these impacts and ensure continuous power delivery. Conventional optimization approaches often exhibit slower convergence, limited adaptability to nonlinear climatic variations, and inadequate prediction accuracy under uncertain environmental parameters. The objective to develop an intelligent and robust hybrid framework for optimal ice-melting equipment placement, enhancing prediction precision and system resilience. A new hybrid metaheuristic framework, PUGWO-TEABC-MNet, is formulated by integrating a Position-Updated Grey Wolf Optimizer (PUGWO), Tent-Elite Artificial Bee Colony (TEABC), and LSTM-based Memory Network (MNet) to ensure adaptive exploration and exploitation with dynamic memory learning. The framework optimally determines device placement by minimizing prediction error while modeling nonlinear climatic dependencies. Climatic datasets related to icing events, including wind speed, temperature, humidity, and ice thickness, were collected from Kaggle repositories. Data were normalized and partitioned into an 80:20 training–testing ratio. Principal Component Analysis (PCA) was used to retain the eight most significant components representing climatic influence. PUGWO initializes optimal search regions, TEABC refines global optima, and MNet captures sequential temporal patterns to improve predictive stability. The framework was implemented in Python using TensorFlow and Scikit-learn libraries. Performance metrics achieved include R² = 0.992, MAPE = 0.0042, and RMSE = 0.12, outperforming baseline BP and PSO-BP approaches. The proposed framework demonstrates superior forecasting accuracy and resilience, providing a cost-effective strategy for optimal ice-melting device deployment in power distribution networks.

As new airborne surveys of the Antarctic ice sheet are completed, the ever-enlarging survey dataset provides an opportunity for generating new 'Bedmaps' of ice thickness, surface and bed topography. These surveys are fundamental to improving our ability to predict the future of Antarctica, but other data-analysis challenges emerge because surveys often do not agree, large data gaps remain, the ice thickness changes or interpolation works well for one landscape but not another. Similar problems afflict other key Bedmap components: the coastline, the grounding line, rock outcrops, the ice shelves and the bathymetry. The process of merging the interpolated ice sheets and shelves and the grounded bed with the sea floor can also inject spurious cliffs and bumps in the grounding zone-exactly where ice-sheet models are most sensitive to flaws in their boundary conditions. In each case, unintended errors and artefacts that arise in the Bedmap grids require careful checking, correction and sometimes bespoke, local approaches to interpolation, slowing the process further. Here, I highlight the key challenges to overcome and address the question of how future Bedmaps can be automated to speed up the supply of new datasets demanded by the ice-sheet modelling community. This article is part of the Theo Murphy meeting issue 'Next generation ice-sheet bed measurements'.

Abstract. The Arctic during the Last Interglacial period (LIG) was considered warmer than it is today. The previous study points to a large difference in the degree of simulated annual-mean Arctic warming among models. While recent reconstructions suggest the disappearance of summer sea ice in the Arctic at the LIG, many climate models fail to capture this feature. It is thus essential to investigate sources of uncertainty in climate models. The current study examines the impact of the temperature-cloud phase relationship. Sensitivity studies are conducted for the first time to explore the potential importance of this relationship in simulating the LIG climate. Two different cloud parameter sets are used for an atmosphere-ocean general circulation model with and without the dynamic vegetation feedback. The model with cloud parametrization that permits liquid water at lower temperatures and a larger fraction of supercooled liquid water at the same temperature simulates a warmer preindustrial (PI) climate, greater annual-mean Arctic warming at the LIG, and substantially reduced summer sea ice cover at the LIG. It is demonstrated that the low-level clouds play a crucial role in controlling the Arctic response via the greenhouse effect. The result indicates the importance of the temperature-cloud phase relationship in simulating the Arctic climate at the LIG. It also highlights the importance of accurately simulating modern sea ice thickness and representing the processes that affect the fraction of supercooled liquid water in clouds.