Satellite-observed acceleration of glacier velocity on the Antarctic Peninsula in response to climate warming

Rock glacier velocity monitored by annual in-situ geodetic surveys: Long-term challenges, solutions and suggestions

Temporal glacier velocity variations and their controlling factors in the Nathorstbreen glacier system, Svalbard

With an area of 13,000 km2 and more than 60 outlet glaciers (tidewater or lake-terminating), the Southern Patagonian Icefield (SPI) stores a substantial volume of freshwater, and its accelerating melt contributes to global sea level rise. In addition to monitoring frontal retreat and ice thinning, tracking near-terminus glacier surface velocity can provide key insight into glacier dynamics. Here, we aimed to understand the current state of the SPI and to explore the dynamic restructuring of the glaciers in comparison with previous results. Considering that ice velocity acceleration near termini can be indicative of a drastic ice thinning and calving, during 2019–2020, we investigated the surface velocity of glaciers in the SPI using feature and speckle tracking. We calculated velocity maps (450 in total) from Sentinel-1 SAR images. Velocity ranged from 0 to 6571 myr−1 for the whole study period, taking into account the 846 one square kilometer subsamples. Mean values of the topographic parameters (elevation, slope, aspect) have variable correlation with the mean velocity values, while mean ice thickness does not have a strong correlation with velocity. Nevertheless, mean velocities show association between near-frontal motion acceleration and calving, as observed in tidewater glaciers and four lake-terminating glaciers. Considering along-length changes in the glaciers, it is found that there are glaciers with upward increasing velocities, downward increasing velocities, and with a single velocity peak and multiple velocity peaks. Comparing our measurements with previous studies, we found major dynamic changes in several glaciers. A massive calving event at Pío XI Glacier significantly affected its velocity for months. The slowdown observed at 13–14 km from the terminus of the Jorge Montt Glacier contrasts with all previous studies that showed an acceleration of the glacier in this area. Our observations indicate rapid changes in some of the SPI glaciers, which suggests their unstable state.

Abstract. Glaciers and ice sheets cover some 15 million square kilometers of the Earth's surface, shaping continental landscapes and modifying climate on a global scale. Recent decades of atmospheric and oceanic warming have induced rapid glacier loss worldwide that has caused sea level rise, flooding, changes to Earth's overall energy balance, and changes in water resources. Accounting for the total impact of glacier change requires observations on a global scale, and planning for future change will require improved understanding of the physical controls that govern glacier change. One key factor that dictates glacier and ice sheet loss is changes in rates of ice flow, the physics of which remain poorly constrained. Our physical understanding of ice flow can be advanced with high-resolution monitoring of glacier flow in near-real time. Automated tracking of glacier flow from space became possible with the launch of Landsat 4 in 1982. Since then, an increasing number of optical and radar satellite sensors have provided a full decade of year-round, global data coverage. This recent plethora of data has introduced new challenges for efficiently processing such large and myriad data streams in a standardized manner with low latency. Here we present the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) global glacier velocity dataset, which is freely available to the public and is currently on major release version 2.0. ITS_LIVE has computed surface velocities using every, excluding those with high cloud cover, available image from Landsat 4 through Landsat 9 as well as Sentinel-1 and Sentinel-2, creating a global glacier velocity record of over 36 million image pairs dating back to 1982. The ITS_LIVE processing chain automatically performs feature tracking on more than 20 000 image pairs per day, within minutes of image availability, and will soon include data from Sentinel-1C and NASA-ISRO SAR Mission (NISAR) satellites. This paper describes the ITS_LIVE processing chain and provides guidance for working with the cloud-optimized velocity data it produces.

Abstract. Rock glacier velocity is now widely acknowledged as an Essential Climate Variable for permafrost. However, representing decadal regional spatiotemporal velocity patterns remains challenging due to the limited availability of high-resolution (<5 m) remote sensing data. In contrast, medium-resolution satellite data (10–15 m) covering several decades are globally available but have not been widely used for rock glacier kinematics. This study presents a robust methodological approach combining pairwise feature-tracking image correlation with medium-resolution Landsat 7/Landsat 8 optical imagery, surface displacement time-series inversion and the automatic detection of persistent moving areas (PMAs). Applied to rock glacier monitoring in the semiarid Andes of South America, this methodology enables the detection and quantification of the surface kinematics of 153 rock glaciers, 124 landslides and 105 unclassified landforms over 24 years across a 2250 km2 area. This is the first time that Landsat images have been used to quantify rock glacier displacement time series. The study estimates an average velocity of 0.30±0.07 m yr−1 for all PMAs, with rock glaciers moving 23 % faster (0.37 m yr−1) over the 24-year period. Some large rock glaciers and debris-frozen landforms exhibit surface velocities exceeding 2 m yr−1. The results align well with high-resolution imagery, recent Global Navigation Satellite System measurements and previous inventories. However, the Landsat 7/Landsat 8 (L7/8) imagery-derived velocities are underestimated by approximately 20 %–30 % on average. High uncertainties between consecutive image pairs limit the reliability of interpreting annual velocity variations. However, decadal velocity changes exceeding the uncertainties were observed in only 2 % of PMAs, with two (one) rock glaciers exhibiting significant acceleration (deceleration) over the past two decades. Our calculations show that decadal velocity changes <0.4 m yr−1 are generally within the uncertainty range when using L7/8 data, with sensitivity depending on the reference period. Despite these limitations, our results highlight the correlation between velocity trends and topographic parameters such as PMA size, orientation, slope and elevation. These relationships suggest that permafrost thaw may influence the occurrence of high-altitude landslides. Overall, this study demonstrates the feasibility of using medium-resolution optical satellite imagery for monitoring rock glacier velocity over several decades.

Abstract Glacial lake outburst floods (GLOFs) caused by mass movement into lakes are common disaster chains in High Mountain Asia (HMA). However, the volumes of potential avalanche sources and the associated overtopping flood processes remain inadequately understood, hindering GLOF hazard assessments. We developed a comprehensive framework to quantify mass movement volumes and simulate GLOF process chains by integrating remote sensing data with hydrological models. We applied our methodology to Jiongpu Co, the largest glacial lake in southeastern Tibet. First, analysis of optical images revealed lake expansion from 2000 to 2024. Second, we assessed the volume of potential glacier avalanche using three‐dimensional glacier velocities from multi‐track Synthetic Aperture Radar (SAR) images. The estimated volume is 1.8 ± 0.06 × 10 8 m 3 . Third, deformation on the surrounding slopes was investigated based on the time‐series InSAR method, revealing a potential landslide volume of 3.5 ± 0.2 × 10 8 m 3 . Next, we retrieved overtopping volumes from the potential glacier avalanche and landslide, which are 1.94 ± 0.1 × 10 7 m 3 and 9.89 ± 0.6 × 10 7 m 3 , respectively. Finally, we evaluated the GLOF process chain under these two scenarios using the HEC‐RAS model. Our integrated approach enhances GLOF monitoring and modeling, offering applicability to other glacial lakes for risk assessment and mitigation.

Glaciers and rock glaciers are essential components of the cryosphere in the Andes of Argentina and Chile, serving as significant freshwater reservoirs and playing a crucial hydrological role as the region experiences warming and drying trends. Although the climate response of glaciers and rock glaciers can be different, studies evaluating simultaneous changes in both glaciers and rock glaciers remain scarce. Here, we analyze glacier geodetic mass balance and rock glacier surface elevation changes in the Monte San Lorenzo in Central Patagonia during 2018–2023, using sub-meter Pléiades digital elevation models (DEMs). Our findings reveal a record glacier mass loss rate (−1.49 m ± 0.16 w.e. a−1), the highest recorded in the past 60 years for this region. Elevation changes in the six studied rock glaciers ranged from slightly negative to moderately positive (+0.27 ± 0.88 m to −0.46 ± 0.81 m), with their distribution patterns suggesting the occurrence of ʿice-debris complexesʾ. Additionally, we present the first (2008–2023) rock glacier kinematic assessment in the Patagonian Andes applying feature-tracking to Pléiades and ALOS PRISM satellite images, and find median velocities ranging between 0.14 m a−1 and 0.43 m a−1. While glaciers in the region showed unprecedented negative mass balance conditions since the mid-20th century -coinciding with rising air temperatures and declining precipitation- rock glacier velocities have remained relatively stable across the two sampled epochs (2008–2018 and 2018–2023). The different response of glaciers and rock glaciers reflects the particular response mechanisms and timing in which each of them couples with the climate.

Abstract Temperate glaciers in the southeastern Tibetan Plateau are shrinking rapidly in response to ongoing climate change. This study focuses on the Baishui River Glacier No. 1, a typical temperate glacier in the Yulong Snow Mountain. Through field observations over four years, we have obtained records and valuable data on the mass balance, ice flow velocity and emergence velocity. The results show that it has been in a state of negative mass balance in recent 4‐years. The mass loss ranges from 1.17 ± 0.18 to 1.46 ± 0.25 m w.e., with an average annual mass loss of 1.29 ± 0.17 m w.e. The average ice flow velocity is ~29.24 ± 3.51 m yr−1, with spatial differences related to glacier morphology and mass turnover. These differences can be attributed to the glacier's morphological characteristics (such as width, slope, thickness and crevasse) and the large mass turnover conditions. In its low‐latitude wet climate, BRG1 has a fast emergence velocity of ~4.07 ± 1.03 m yr−1. The emergent ice flow is insufficient cannot offset melting. Slope change uncertainties hamper calculating surface mass balance from emergence velocity. Our data reveals a significant correlation (r2 = 0.69) between ice flow velocity and emergence velocity, and a very significant negative one (r2 = 0.78) between ice flow velocity and mass balance. Faster ice flow transports more ice to lower, warmer areas, accelerating melting. The data presented in this article offers valuable and useful insights into the physical ice flow model of such low‐latitude temperate glaciers.

Remote sensing is a key tool to derive glacier surface velocities but existing mapping methods, such as cross-correlation techniques, can fail where surface properties change temporally or where large velocity variations occur spatially. High-resolution datasets, such as UAV imagery, offer a promising solution to tackle these issues and to study small-scale glacier dynamics, but new workflows are required to handle such data. Therefore, we tested the potential of new deep learning-based image-matching algorithms for deriving glacier surface velocities across the ablation area of a glacier with strong spatial variability in surface velocities (<5 m/yr to >100 m/yr) and substantial changes in surface properties between image acquisitions. For a thorough comparison of state-of-the-art methods and sensors, we applied three different techniques (cross-correlation using geoCosiCorr3D, feature tracking with ORB using SeaIceDrift and the new deep learning-based method using ICEpy4D) and three different platforms (Sentinel-2, PlanetScope, UAVs) to estimate glacier surface velocities. Results showed lowest errors for velocities derived with the deep learning-based approach applied to UAV imagery (RMSE = 2.17 m/yr, R2 = 0.99), followed by cross-correlation using Sentinel-2 images (RMSE = 21.0 m/yr, R2 = 0.59) and the deep learning-based approach with PlanetScope data (RMSE = 21.28 m/yr, R2 = 0.36). Cross-correlation with geoCosiCorr3D resulted in comparably high errors with the UAV dataset (RMSE = 36.22 m/yr, R2 = 0.24), whereas ORB-based feature tacking showed lowest performance with all sensors. Spatial patterns of computed velocities indicate that applying existing cross-correlation methods for areas with regular displacements or low glacier velocities yields suitable results on UAV data, but innovative deep learning-based approaches are required for resolving rapid changes in velocities or in surface properties. This novel method benefits from improved keypoint detection and matching through training using neural networks and data characterized by challenging geometries, outlier minimization and more robust descriptors by applying cross-attention layers. We conclude that continued development of deep learning-based feature tracking approaches for glacier velocity computations may substantially improve UAV-based velocity derivations applied to challenging situations. This method is able to deliver reliable displacement data in situations where traditional methods fail, which implies a new level of detail in understanding and interpreting glacier dynamics.

ABSTRACT Assessing glacier surface height changes provides crucial insights into glacier mass loss and the impact of climate variability. Remote sensing images play a vital role in providing data points for monitoring. Oftentimes, the glacier height change observation is sparse with notable time intervals, yet it is unclear whether these sparse observations are within seasonal variations. Thus, data with high-temporal resolution are necessary to 1) establish sufficiently dense observations to achieve enhanced conclusions; 2) derive higher-level data, such as motion velocity, to assess the level of global warming and climate change. PlanetScope satellite constellations can provide global daily/weekly observations with a 4 m ground sample distance (GSD). In this work, we report a study on monitoring fast dynamic glaciers in mid-latitude mountain regions in America and Asia using the derived time-series 3D elevation models from PlanetScope. The study includes three sites: La Perouse Glacier (North America), Viedma Glacier (South America), and Skamri Glacier (Central Asia). Based on PlanetScope data, we derived near bi-monthly 4-m resolution 3D elevation models for the year of 2019–2023 using satellite stereo photogrammetry, to track the ice flow in 3D. The results can be used to decorrelate the factors from seasonable variation: the Viedma Glacier is observed thinner over time with a slower flow rate; although through a single and short-term observation, the thinning rate of La Perouse Glacier is shown accelerating, we did not observe evidence that La Perouse Glacier and Skamri Glacier have obvious thinning other than its seasonable variations within a few years of time frames (since the PlanetScope images were available). By focusing on the local surface motion variations, our study shows that the glacier velocity varies with regional climate, geography, and hydrology, with a notable 45-day lag response between climate factors and flow speed in Viedma and Skamri Glaciers.

In recent years, the number and capability of Synthetic Aperture Radar (SAR) sensors in ow Earth orbit has grown considerably, with multiple commercial satellites now capable of capturing sub-metre resolution imagery. In this study, we present the first application of such very-fine resolution SAR imagery to measure ice velocity of a high mountain glacier. To achieve this, we apply feature tracking to a pair of Capella images in spotlight mode (0.35 m resolution) acquired in July 2021 over Baltoro Glacier in the Karakoram, Pakistan, and compare the results to ice velocities derived from feature tracking using more commonly employed TerraSAR-X Stripmap (3 m) and Sentinel-1 Interferometric Wide (IW) (5 × 20 m) imagery. We show that Capella-derived velocities reveal subtle features that are not evident in velocities derived using coarser resolution imagery. In particular, slower moving ice at the glacier margin, variations in velocity between different flow units, and lateral fluctuations reflecting the local topography are all more clearly resolved. However, the small footprint of the imagery and lack of stable ground within the frame poses a challenge for co-registration, resulting in an inherent, and spatially varying, bias of up to 0.5 m/day in the measured offsets. We reduce this error to ∼0.1 m/day using a global shift and propose that the derived data then show potential to advance knowledge in a range of glaciological disciplines.

By considering two differential interferometric SAR signals, recovered from synthetic aperture radar (SAR) images, it has been possible to estimate the glacier velocity vector, from a method proposed by the authors Joughin, Kwok, and Fahnestock (JKF) in 1998. Although the JKF method normally works well under certain SAR observation conditions, we found a reformulated version of the main equation of this technique that may improve this interesting methodology. Thus, we present a mathematical review of this method, and a validation of our result in terms of accuracy, with some computer simulations. The innovation proposed is a simplified way to implement JKF’s work in the Sentinel Application Platform (SNAP) software, exemplified with some images from the Canadian Arctic. Generally, a north–east–up displacement estimation is considered, by using reference orthogonal coordinates, independent of the SAR image coordinates. However, we propose a methodology to estimate this velocity vector in terms of ascending or descending image coordinates. Given the importance of the JKF work, we believe that this investigation could contribute to the improvement of this technique, beyond the existence of other modern and independent methodologies.

Subglacial hydrology plays an important role in controlling glacier behaviour, influencing glacier retreat and the resulting contributions to sea level rise. Here we present a detailed seasonal data set from four soft-bedded temperate glaciers and demonstrate a continuum of subglacial hydrology from channelized to a multichannel distributed behaviour. Our results illustrate how this continuum may be affected by till grain size and subaqueous processes, and we quantify the relative timings of basal sliding and deformation. These different hydrologies have a distinctive seasonal velocity pattern, which although have been identified using a multi-data stream, we suggest can be classified using solely Sentinel-1 satellite-based glacier velocity data. The ability to categorize subglacial glacier hydrology over a much larger data set would allow a better parameterization of subglacial processes for ice sheet models.

Abstract The subglacial geology beneath Devon Ice Cap (DIC) is not well understood. An airborne radar study published in 2018 suggested the presence of a hypersaline, subglacial lake beneath DIC where geologic modeling suggested that the source of the brine was an underlying evaporite‐rich sedimentary unit. However recent surface based seismic and electromagnetic data have revealed the absence of subglacial water beneath the center of DIC. Continued studies of this subglacial environment require knowledge of the sediments and bedrock beneath the ice. In this study we combine previously published geology and geothermal studies with new surface‐based magnetotelluric, airborne gravity and aeromagnetic data, to investigate the subglacial geology under DIC. The integrated results show that beneath the center of DIC there is likely a frozen sedimentary unit (3,000–6,000 Ωm) overlying unfrozen crystalline basement rocks of the Canadian shield (400–2,000 Ωm), at depths of 1,500 m–2,000 m. This agrees with recent studies of ice dynamics on DIC, where glacier velocities are low (<20 m a−1), within the interior regions of DIC implying the ice is dominantly frozen to the bed. Furthermore, relatively low‐density sedimentary rocks (∼2.2 g/cm3) are the likely cause of the gravity low (−50 to −70 mgal) observed in the northeast of the ice cap and could have implications for future ice dynamics.

Rock glaciers are prevalent across the Tien Shan and exhibit complex, but poorly understood kinematics linked to climate and environmental fluctuations. This study employed a frequency domain cross-correlation method to investigate rock glacier velocities in the Northern Tien Shan. We compared different sources of satellite imagery, including 0.5m Pléiades, 3m Planet, 10m Sentinel-2 and 15m Landsat-8 data. Analysis of high-resolution Pléiades imagery in the Central Ile Alatau showed considerable spatial heterogeneity in flow. The highest median velocity of 0.65 m/yr was observed on Timofeyeva rock glacier, with an upper quartile value of 0.90 m/yr. Ordzhonikidze and Morennyi rock glaciers also exhibited high activity, with upper quartile values of 1.91 m/yr and 0.96 m/yr, respectively, despite considerably lower mean and median values than Timofeyeva. We observed bimodal velocity distributions on a number of rock glaciers, highlighting the limitations of using mean and median statistics for characterising rock glacier activity. Sentinel-2 data was capable of detecting kinematic patterns that closely reflected those identified by high-resolution Pléiades data. Velocities were derived from Sentinel-2 imagery for 672 rock glaciers across the Northern Tien Shan over a 7-year period (2016–2023). Many of the larger rock glaciers in the regional inventory exhibited active areas with velocities that exceeded 2 m per year. Topographic analysis in the Central Ile Alatau and visual inspection showed the fastest velocities to generally occur on lower, flatter areas near the rock glacier front. However, topography did not entirely explain the spatial flow heterogeneity. We interpret that these spatial patterns in activity are related to individual rock glacier’s internal structure.

Abstract Rock glaciers are distinctive debris landforms found worldwide in cold mountainous regions. They express the long‐term movement of perennially frozen ground. Rock Glacier Velocity (RGV), defined as the time series of the annualized surface velocity of a rock glacier unit or a part of it, has been accepted as an Essential Climate Variable Permafrost Quantity in 2022. This review aims to highlight the relationship between rock glacier velocity and climatic factors, emphasizing the scientific relevance of interannual rock glacier velocity in generating RGV products within the context of observed rock glacier kinematics. Under global warming, rock glacier velocity exhibits widespread (multi‐)decennial acceleration. This acceleration varies regionally in onset timing (from the 1950s to the 2010s) and magnitude (up to a factor of 10), and has been observed in regions such as the European Alps, High Mountain Asia, and the Andes. Despite different local conditions, a synchronous interannual velocity pattern prevails in the European Alps since the 2000s, highlighting the primary influence of climate. A common pattern is the seasonal velocity rhythm, which peaks in late summer to autumn and declines in spring. RGV assesses permafrost evolution via (multi‐)decennial and interannual changes in rock glacier velocity, influenced by air temperature shifts with varying time lags and snow cover effects. Although not integrated into the RGV products, seasonal variations should be examined. This rhythmic behavior is attributed to alterations in pore water pressure influenced by air temperature, snow cover, and ground water conditions.

Abstract. Degrading permafrost in rock glaciers has been reported from several sites in the European Alps. Changes in ground temperature and ice content are expected to affect the hydrogeological properties of rock glaciers and in turn modify the runoff regime and groundwater recharge in high-mountain environments. In this study, we investigate the use of an emerging geophysical method in permafrost studies to understand the hydrogeological properties of the active Gran Sometta rock glacier, which consists of a two-lobe tongue (a white and a black) whose lobes differ in their geologies. We present the application of spectral induced polarization (SIP) imaging, a method that provides quasi-continuous spatial information about the electrical conductivity and polarization of the subsurface, which are linked to hydrogeological properties. To quantify the water content and the hydraulic conductivity from SIP imaging results, we used the petrophysical dynamic stern layer model. The SIP results show a continuously frozen layer at 4–6 m depth along both lobes which hinders the infiltration of water, leading to a quick flow through the active layer. To evaluate our results, we conducted tracer experiments monitored with time-lapse electrical conductivity imaging, which confirms the hydraulic barrier associated with the frozen layer and allows the pore water velocity to be quantified (∼ 10−2 m s−1). Below the frozen layer, both lobes have distinct water content and hydraulic conductivity. We observed a higher water content in the black lobe, which moves faster than the white lobe, supporting the hypothesis that the water content at the shear horizon affects the rock glacier velocity. Our study demonstrates that the SIP method is able to provide valuable information for the hydrogeological characterization of rock glaciers.

Abstract Identifying early indicators of volcanic eruptions is a fundamental part of natural hazard management but is notoriously difficult. Here we consider whether monitoring changes in glacier velocity can help. We use satellite images to investigate changes in the surface velocity of Cone Glacier (Alaska) between November 2017 and January 2022, a period encompassing two eruptions of Mount Veniaminof on which the glacier sits. Our data show high glacier velocities months prior to these eruptions and low velocities immediately before, during and after the 2018 eruption, likely caused by volcanically triggered ice melt and associated changes in subglacial water pressures. Evidence for elevated velocities months prior to eruptions is particularly important and indicates that glacier speed-up might be an early indicator of volcanic unrest. Thus, glaciers could serve as tools for volcano monitoring and eruption forecasting since more than 2500 glaciers globally are located within 5 km of an active volcano.

Abstract Glacier ice flux is a key indicator of mass balance; therefore, accurate monitoring of ice dynamics is essential. Satellite-based methods are widely used for glacier velocity measurements but are limited by satellite revisit frequency. This study explores using seismic station internal GPS data to track glacier movement. While less accurate than differential GPS, this method offers high-temporal resolution as a by-product where seismic stations are deployed. Using a seismic station on Borebreen, Svalbard, we show that internal GPS provides reliable surface velocity measurements. When compared with satellite-inferred velocities, the results show a strong correlation, suggesting that the internal GPS, despite its inherent uncertainty, can serve as an efficient tool for glacier velocity monitoring. The high-temporal sampling reveals short-term dynamics of speed-up events and underscores the role of meltwater in driving these processes. This approach augments glacier observation networks at no additional cost.