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Observation of glacier surface characteristics through remotely sensed time-series data is essential for understanding glacier seasonality, mass balance, and long-term trends. Yet, the reliability of these observations depends significantly on the quality of the time-series data. This study presents a meticulous preprocessing scheme to improve the quality of Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Snow Index (NDSI) time-series data for glacier monitoring. We propose a three-step algorithm specifically crafted to overcome the challenges associated with cloud contamination reduction, outlier removal and data gap handling. This innovative approach iteratively compares the median values of automatically adjusted asymmetrical moving windows to achieve convergence, removing outliers using minimal window size to keep the temporal resolution as high as possible. The methodology’s effectiveness is demonstrated through its application to two glaciers from the United States Geological Survey (USGS) Benchmark Project, showcasing significant improvements in the quality of smoothed MODIS NDSI time series. These results affirm the efficacy of the proposed scheme in rendering a more reliable evaluation of glacier surface condition and seasonal fluctuations. Consequently, this study contributes significant methodological advancements to the fields of remote sensing and glaciology, enhancing the accuracy of glacier monitoring techniques.

We use the apparent horizontal shift of an englacial tephra layer outcrop to calculate local glacier mass balance on Sléttjökull, a lobe of Mýrdalsjökull in Southern Iceland. For this approach, the dipping angle of the englacial tephra layer in the glacier upstream of the outcrop and the flow velocity of the ice need to be known. An earlier investigation was expanded by the application of ground-penetrating radar, detecting the depth of the tephra along tracks with a total length of 10 km. Interpolation between the tracks enables us to derive the dipping angle of the layer along several flow lines. Together with glacier surface velocities, determined from feature tracking, we are able to estimate the local surface mass balance from the horizontal displacement of the tephra outcrop using freely available satellite imagery without additional fieldwork. The earlier local balance series was extended to the period 2014/15 to 2019/20. Although the results for the individual profiles differ slightly from each other, they show the same temporal pattern and clear variations from year to year. The results are compared to traditional mass-balance data from Hofsjökull. The two series show a good agreement in their interannual variability. [ABSTRACT FROM AUTHOR]

Glaciers in the Alps are losing mass at unprecedented and accelerating rates. Monitoring of glacier mass change as well as relevant atmospheric parameters plays an important role in improving understanding of local and downstream impacts. We present sub-seasonal, seasonal, and annual glaciological mass balance data and meteorological observations from Mullwitzkees and Venedigerkees, two glacier monitoring sites in the Hohe Tauern range of the Austrian Alps. Ablation stake networks were established on Mullwitzkees in 2006/07 and on Venedigerkees in 2011/12. Monitoring is ongoing. In addition to stake readings at sub-seasonal intervals, accumulation measurements (snow pits and probing) are carried out seasonally. The glaciological dataset consists of sub-seasonal floating-date measurements as well as fixed-date seasonal and annual values. The fixed-date glacier-wide mass balance was derived from annual point mass balance values. Automatic weather stations measuring standard meteorological parameters were installed near Mullwitzkees and Venedigerkees in 2020 and 2019, respectively. Meteorological data are provided in 10 min intervals. Uncertainties in individual point mass balance measurements were computed following the approach of the Swiss Glacier Monitoring (GLAMOS) programme, taking into account estimated density and reading errors. The sub-seasonal mass balance records highlight shorter-term variability in mass loss and the linkage with meteorological conditions. The most negative annual point mass balance recorded in the period of record was -5.8 ± 0.66 m w.e. at an elevation of 2536 m on Venedigerkees, and 2022 stands out as the most negative mass balance year to date in both time series, particularly at higher elevations. The cumulative specific mass balances (glacier-wide) over the period of record were -14.68 m w.e. at Mullwitzkees and -8.79 m w.e. at Venedigerkees. Data are available in the PANGAEA publication series and the associated datasets. The main publication series are updated annually. The Mullwitzkees mass balance datasets can be found in (10.1594/PANGAEA.965660) and (10.1594/PANGAEA.965719). The Venedigerkees data can be found in (10.1594/PANGAEA.965648) and (10.1594/PANGAEA.965729). [ABSTRACT FROM AUTHOR]

The presented study aims to apply a method for monitoring the retreat of mountain glaciers in the Alpine region of the Swiss Alps, which consists of using optical satellite imagery and their spectral capabilities to observe snow and ice objects on the earth's surface. Satellite imagery with its big legacy archive dating back to 1972 for Landsat imagery, can be of big help to track and monitor the alpine glaciers retreat for long periods and serve as a database for modelling and predicting the glaciers retreat in the future. By combining different satellite data processing approaches, results have been obtained on the spatial distribution and dynamics of the Morteratsch Glacier over a period of 51 years. The focus of the study is to track the changes that have occurred along the positions of the ice front (terminus) in the glacier's ablation zone to obtain information about the glacier's dynamics during the study period. [ABSTRACT FROM AUTHOR]

The Ili River Basin, a crucial transboundary river in the arid region of Central Asia, plays a significant role in the region's ecology and water resources. However, current methods for monitoring glacier area changes in this region face challenges in automation and accuracy due to the complex terrain and climatic conditions. This study aims to evaluate the effectiveness of the Google Earth Engine (GEE) platform for monitoring glacier area changes in the Ili River Basin from 1992 to 2020, with a focus on improving data accuracy and processing efficiency. Utilizing the Landsat data series, we employed the random forest (RF) classification algorithm within the GEE platform to extract glacier areas, optimizing a multidimensional feature set using the Jeffries–Matusita (JM) distance method, and applied visual interpretation for data refinement. Our results demonstrated that the GEE platform, combined with the RF algorithm, provided high accuracy in glacier monitoring, achieving an overall accuracy of 89% and a kappa coefficient of 0.85. During the study period, the glacier area in the Ili River Basin decreased by 184.76 km2, with an average annual retreat rate of 6.84 km2, most notably between 3800 and 4400 m in elevation. The analysis revealed that temperature changes had a more pronounced impact on glacier dynamics than precipitation. This approach significantly enhances image utilization efficiency and data processing speed, offering a reliable tool for monitoring glacier dynamics. Future research should focus on integrating additional environmental variables and extending the temporal scope to further refine glacier dynamics modeling and predictions. [ABSTRACT FROM AUTHOR]

The mass balance of the Greenland Ice Sheet is strongly influenced by the dynamics of its outlet glaciers. Therefore, it is of paramount importance to accurately and continuously monitor these glaciers, especially the variation in their frontal positions. A temporally comprehensive parameterization of glacier calving is essential for understanding dynamic changes and constraining ice sheet modeling. However, many current calving front records are limited in terms of temporal resolution as they rely on manual delineation, which is laborious and not appropriate considering the increasing amount of satellite imagery available. In this contribution, we address this problem by applying an automated method to extract calving fronts from optical satellite imagery. The core of this workflow builds on recent advances in the field of deep learning while taking full advantage of multispectral input information. The performance of the method is evaluated using three independent test datasets. For the three datasets, we calculate mean delineation errors of 61.2, 73.7, and 73.5 m, respectively. Eventually, we apply the technique to Landsat-8 imagery. We generate 9243 calving front positions across 23 outlet glaciers in Greenland for the period 2013–2021. Resulting time series not only resolve long-term and seasonal signals but also resolve subseasonal patterns. We discuss the implications for glaciological studies and present a first application for analyzing the effect of bedrock topography on calving front variations. Our method and derived results represent an important step towards the development of intelligent processing strategies for glacier monitoring, opening up new possibilities for studying and modeling the dynamics of Greenland's outlet glaciers. [ABSTRACT FROM AUTHOR]

Mountain glaciers are sensitive to climate variability and can be of great importance for downstream populations due to their hydrological significance. Synthetic Aperture Radar (SAR) images are often used to monitor the characteristics of glaciers based on the backscattering coefficient. However, the influence of satellite orbit and polarization when collecting images for wide regions has not been well considered. This study focuses on the extraction of wet snow in summer and firn in winter in West Kunlun Shan and the Tibet Interior Mountains by using Sentinel-1 C-band SAR data. The investigated regions have different climate patterns. We compare backscatter coefficient distributions for wet snow and firn, derived from maximum likelihood classification under various polarizations, alongside their respective ratios and show that polarization has a minor impact on the identification and monitoring of both wet snow and firn. However, a comparison of the wet snow ratios at different satellite orbits reveals notable differences between ascending and descending orbits in summer. We furthermore show, by analyzing weather stations on glaciers, that such effect can be related to the different acquisition time and different temperatures in the morning and afternoon and therefore to the orbit. In contrast, firn ratios across different orbits show less variation in winter, and the monitoring results consistently align with the patterns of ablation and accumulation typical under both climatic influences. These findings demonstrate glaciers' sensitivity to temperature fluctuations and the radar wave's responsiveness to surface characteristics. Consequently, when employing SAR for glacier monitoring, it is crucial to consider the influence of orbit and polarization, in combination with temperature variations, and whether the season is winter or summer. [ABSTRACT FROM AUTHOR]

The increasing global warming trend has resulted in the mass loss of most glaciers. The Urumqi Vally, located in the dry and cold zone of China, and its widely dispersed glaciers are significant to the regional ecological environment, oasis economic development, and industrial and agricultural production. This is representative of glaciers in Middle Asia and represents one of the world's longest observed time series of glaciers, beginning in 1959. The Urumqi Headwater Glacier No. 1 (UHG-1) has a dominant presence in the World Glacier Monitoring Service (WGMS). This paper supplies a comprehensive analysis of past studies and future modeling of glacier changes in the Urumqi Valley. It has received insufficient attention in the past, and the mass balance of UHG-1 was used to verify that the geodetic results and the OGGM model simulation results are convincing. The main conclusions are: The area of 48.68 ± 4.59 km2 delineated by 150 glaciers in 1958 decreased to 21.61 ± 0.27 km2 delineated by 108 glaciers in 2022, with a reduction of 0.47 ± 0.04 km2·a−1 (0.96% a−1 in 1958–2022). The glacier mass balance by geodesy is −0.69 ± 0.11 m w.e.a−1 in 2000–2022, which is just deviating from the measured result (−0.66 m w.e.a−1), but the geodetic result in this paper can be enough to reflect the glacier changes (−0.65 ± 0.11 m w.e.a−1) of the URB in 2000–2022. The future loss rate of area and volume will undergo a rapid and then decelerating process, with the fastest and slowest inflection points occurring around 2035 and 2070, respectively. High temperatures and large precipitation in summer accelerate glacier loss, and the corresponding lag period of glacier change to climate is about 2–3 years. [ABSTRACT FROM AUTHOR]

Geosynchronous spaceborne–airborne (GEO-SA) ultra-high-frequency ultra-wideband bistatic synthetic aperture radar (UHF UWB BiSAR) provides high-precision images for marine and polar environments, which are pivotal in glacier monitoring and sea ice thickness measurement for polar ocean mapping and navigation. Contrasting with traditional high-frequency BiSAR, it faces unique challenges, such as the considerable spatial variability, significant range–azimuth coupling, and vast volumes of echo data, which impede high-resolution image reconstruction. This paper presents an improved bistatic nonlinear chirp scaling (NLCS) algorithm for imaging oceanic scenes with GEO-SA UHF UWB BiSAR. This methodology extends the two-dimensional (2-D) spectrum up to the sixth order via the method of series reversion (MSR) to meet accuracy demands and then employs an elliptical model to elucidate the alterations in the azimuth frequency modulation (FM) rate mismatch. Initially, the imaging geometry and signal model are introduced, and then a separation of bistatic slant ranges based on the configuration is proposed. In addition, during range processing, after eliminating linear range cell migration (RCM), the derivation process for the sixth-order 2-D spectrum is detailed and an improved filter is applied to correct the high-order RCM. Finally, during azimuth processing, the causes of the FM rate mismatch are analyzed, a cubic perturbation function derived from the elliptical model is used for FM rate equalization, and a unified sixth-order filter is applied to complete the azimuth compression. Experimental results with point targets and natural oceanic scenes validate the outstanding efficacy of the proposed NLCS algorithm, particularly in imaging quality enhancements for GEO-SA UHF UWB BiSAR. [ABSTRACT FROM AUTHOR]

Glaciers in the Alps are losing mass at unprecedented and accelerating rates. Monitoring of glacier mass change as well as relevant atmospheric parameters plays an important role in improving understanding of local and downstream impacts. We present subseasonal, seasonal, and annual glaciological mass balance data and meteorological observations from Mullwitzkees and Venedigerkees, two glacier monitoring sites in the Hohe Tauern range of the Austrian Alps. Ablation stake networks were established on Mullwitzkees in 2006/07 and on Venedigerkees in 2011/12. Monitoring is ongoing. In addition to stake readings at subseasonal intervals, accumulation measurements (snow pits and probing) are carried out seasonally. The glaciological data set consists of subseasonal floating date measurements as well as fixed date seasonal and annual values. Fixed date glacier wide mass balance was derived from annual point mass balance values. Automatic weather stations measuring standard meteorological parameters were installed near Mullwitzkees and Venedigerkees in 2020 and 2019, respectively. Meteorological data is provided in 10 minute intervals. Uncertainties for individual point mass balance measurements were computed following the approach of the Swiss glacier monitoring service (GLAMOS), taking into account estimated density and reading errors. The subseasonal mass balance records highlight shorter term variability in mass loss and the linkage with meteorological conditions. The most negative annual point mass balance recorded in the period of record was -5.8 ± 0.66 m w.e. at an elevation of 2536 on Venedigerkees. 2022 stands out as the most negative mass balance year to date in both time series, particularly at higher elevations. The cumulative specific mass balance (glacier wide) over the period of record was -14.68 m w.e. at Mullwitzkees and -8.79 m w.e. at Venedigerkees. Data is available in PANGAEA publication series and the associated datasets. The main publication series are updated annually. The Mullwitzkees mass balance datasets can be found at: doi: 10.1594/PANGAEA.965660 and doi: 10.1594/PANGAEA.965719. The Venedigerkees data can be found at doi: 10.1594/PANGAEA.965648 and doi: 10.1594/PANGAEA.965729. [ABSTRACT FROM AUTHOR]

Multitemporal glacier monitoring through the digitalization of old topographic maps in a Digital Terrain Models and comparison to the present. [ABSTRACT FROM AUTHOR]

Studying glacier changes is essential for understanding global glacier mass balance, patterns in climate change, and the potential consequences they may have. The glaciers of Geladandong Mountain serve as a crucial water source for the Yangtze River and its downstream regions. Any changes in the glacier at the river source will directly impact the ecological environment and water recycling process downstream. This study presents an approach for monitoring Geladandong Mountain glacier elevation changes using ICESat-2 data combined with a Binned Multilevel Regression Fitting Method (BMRFM). We analysed multi-year ICESat-2 data, considering various topographic features, to understand glaciers' annual and seasonal elevation changes. Our research reveals significant spatial heterogeneity in glacier elevation changes, influenced by altitude, slope, and aspect factors. It demonstrates the effectiveness of ICESat-2 in glacier monitoring, offering insights into the impacts of climate change on glacier dynamics. Moreover, the results indicate a predominant trend of ongoing melting at lower altitudes, with a small amount of accretion at higher elevations. Over the last two decades, the overall elevation change rate is −0.23 ± 0.12 metres per year. Seasonal analysis shows substantial glacier thickening from April to August, primarily due to increased precipitation offsetting elevated temperatures. This study offers a robust method for monitoring glaciers using satellite data, thereby advancing the precision and reliability of glacier research. [ABSTRACT FROM AUTHOR]

Glaciers in the Alps are losing mass at unprecedented and accelerating rates. Monitoring of glacier mass change as well as relevant atmospheric parameters plays an important role in improving understanding of local and downstream impacts. We present sub-seasonal, seasonal, and annual glaciological mass balance data and meteorological observations from Mullwitzkees and Venedigerkees, two glacier monitoring sites in the Hohe Tauern range of the Austrian Alps. Ablation stake networks were established on Mullwitzkees in 2006/07 and on Venedigerkees in 2011/12. Monitoring is ongoing. In addition to stake readings at sub-seasonal intervals, accumulation measurements (snow pits and probing) are carried out seasonally. The glaciological dataset consists of sub-seasonal floating-date measurements as well as fixed-date seasonal and annual values. The fixed-date glacier-wide mass balance was derived from annual point mass balance values. Automatic weather stations measuring standard meteorological parameters were installed near Mullwitzkees and Venedigerkees in 2020 and 2019, respectively. Meteorological data are provided in 10 min intervals. Uncertainties in individual point mass balance measurements were computed following the approach of the Swiss Glacier Monitoring (GLAMOS) programme, taking into account estimated density and reading errors. The sub-seasonal mass balance records highlight shorter-term variability in mass loss and the linkage with meteorological conditions. The most negative annual point mass balance recorded in the period of record was −5.8 ± 0.66 m w.e. at an elevation of 2536 m on Venedigerkees, and 2022 stands out as the most negative mass balance year to date in both time series, particularly at higher elevations. The cumulative specific mass balances (glacier-wide) over the period of record were −14.68 m w.e. at Mullwitzkees and −8.79 m w.e. at Venedigerkees. Data are available in the PANGAEA publication series and the associated datasets. The main publication series are updated annually. The Mullwitzkees mass balance datasets can be found in Stocker-Waldhuber et al. (2016) (https://doi.org/10.1594/PANGAEA.965660) and Stocker-Waldhuber et al. (2024d) (https://doi.org/10.1594/PANGAEA.965719). The Venedigerkees data can be found in Seiser and Fischer (2016) (https://doi.org/10.1594/PANGAEA.965648) and Seiser et al. (2024d) (https://doi.org/10.1594/PANGAEA.965729).

We developed automated ablation stakes to measure colocated in situ changes in relative glacier-surface elevation and climatological drivers of ablation. The designs, refined over 10 years of development and deployments, implement open-source hardware and common building materials. The ablation stakes record distance to the snow/ice surface, air temperature and relative humidity every 1–15 min. Using these high-frequency data, we demonstrate that melt factors calculated using standard melt-rate vs temperature regressions converge over averaging windows of approximately 12 h or greater. Furthermore, we evaluate an integral approach to estimating temperature-index melt factors for ablation. In a test case on Glaciar Perito Moreno, Argentina, this integral approach reveals an overall positive-degree-day melt factor of 7.5 mm w.e. $^\circ$ C−1 d−1. We describe four deployments with iteratively improved designs and provide a list of materials required to construct an automated ablation stake. [ABSTRACT FROM AUTHOR]

The geodetic mass balance of a glacier corresponds to glacier-wide volume changes, converted to mass changes using density assumptions. It is typically calculated by differencing multi-temporal digital elevation models. In this study, we show how the annual geodetic mass balance of a glacier can be derived from uncrewed aerial vehicle (UAV) data. The presented workflow is applied to two small- to medium-sized glaciers in the Kyrgyz Tien Shan (Central Asia): Bordu glacier and Sary-Tor glacier. The obtained geodetic mass balance is compared with the glaciological mass balance derived from a network of ablation stakes and snow pits. A previously calibrated mass-balance model is used to correct for the difference in acquisition dates. The results show that the determined geodetic mass balance matches closely with the glaciological mass balance. Besides, for both glaciers the geodetic mass balance does not seem to be particularly sensitive to the assumptions regarding volume-to-mass conversion. Therefore, our results demonstrate that UAVs can serve as a valuable instrument to quantify the annual geodetic mass balance and to validate the glaciological mass balance. The conventional glaciological mass-balance estimation often relies on interpolation and extrapolation methods, whereas UAVs offer the potential for direct data acquisition over the entire glacier surface. [ABSTRACT FROM AUTHOR]

Poland as well as other countries keep extensive collections of 20th and 21st-century aerial photos, which are underexploited compared to such other archival materials as satellite imagery. Meanwhile, they offer significant research potential in various areas, including urban development, land use changes, and long-term environmental monitoring. Archival photographs are detailed, often obtained every five to ten years, and feature high resolution, from 20 cm to 1 m. Their overlap can facilitate creating precise digital models that illustrate topography and land cover, which are essential variables in many scientific contexts. However, rapidly transforming these photographs into geographically accurate measurements of the Earth's surface poses challenges. This article explores the obstacles in automating the processing of historical photographs and presents the main scientific research directions associated with these images. Recent advancements in enhancing work˚ows, including the development of modern digital photogrammetry tools, algorithms, and machine learning techniques are also discussed. These developments are crucial for unlocking the full potential of aerial photographs, making them easier accessible and valuable for a broader range of scientific fields. These underutilized photographs are increasingly recognized as vital in various research domains due to technological advancements. Integrating new methods with these historical images offers unprecedented opportunities for scientific discovery and historical understanding, bridging the past with the future through innovative research techniques. [ABSTRACT FROM AUTHOR]

Constructing high-precision subsidence basins is of paramount importance for mining subsidence monitoring. Traditional unmanned aerial vehicle (UAV) photogrammetry techniques typically construct subsidence basins by directly differencing digital elevation models (DEMs) from different monitoring periods. However, this method often neglects the influence of horizontal displacement on the accuracy of the subsidence basin. Taking a mining area in Ordos, Inner Mongolia, as an example, this study employed the normalized cross-correlation (NCC) matching algorithm to extract horizontal displacement information between two epochs of a digital orthophoto map (DOM) and subsequently corrected the horizontal position of the second-epoch DEM. This ensured that the planar positions of ground feature points remained consistent in the DEM before and after subsidence. Based on this, the vertical displacement in the subsidence area (the subsidence basin) was obtained via DEM differencing, and the parameters of the post-correction subsidence basin were inverted using the probability integral method (PIM). The experimental results indicate that (1) the horizontal displacement was influenced by the gully topography, causing the displacement within the working face to be segmented on both sides of the gully; (2) the influence of the terrain on the subsidence basin was significantly reduced after correction; (3) the post-correction surface subsidence curve was smoother than the pre-correction curve, with abrupt error effects markedly diminished; (4) the accuracy of the post-correction subsidence basin increased by 43.12% compared with the total station data; and (5) comparing the measured horizontal displacement curve with that derived using the probability integral method revealed that the horizontal displacement on the side of an old goaf adjacent to the newly excavated working face shifted toward the advancing direction of the new working face as mining progressed. This study provides a novel approach and insights for using low-cost UAVs to construct high-precision subsidence basins. [ABSTRACT FROM AUTHOR]

The Eastern Tianshan region, influenced by the far-field effect of northward compression and expansion of the Qinghai-Xizang block, features highly developed Late Quaternary active faults that exhibit significant neotectonic activity. Historically, the Barkol-Yiwu Basin, located to the north of the Eastern Tianshan, experienced two major earthquakes in 1842 and 1914, each with a magnitude of M71/2. In contrast, the Hami Basin on the southern margin of the Eastern Tianshan has no historical records of any major earthquakes, and its seismic potential, mechanisms, and future earthquake hazards remain unclear. Based on satellite image interpretation and field surveys, this study identified a relatively recent and well-preserved seismic surface rupture zone with good continuity in the Liushugou area of the western segment of the Northern Margin Fault of the Hami Basin (HMNF), which is the seismogenic structure responsible for the rupture. The surface rupture zone originates at Kekejin in the east, extends intermittently westward through Daipuseke Bulake and Liushugou, and terminates at Wuzun Bulake, with a total length of approximately 21 km. The rupture zone traverses the youngest geomorphic surface units, such as river beds or floodplains and first-order terraces (platforms), and is characterized by a series of single or multiple reverse fault scarps. The morphology of fault scarps is clear, presenting a light soil color with heights ranging from 0.15 m to 2.13 m and an average displacement of 0.56 m, suggesting that this surface rupture zone likely represents the most recent seismic event. Comparison with historical earthquake records in the Eastern Tianshan region suggests that the rupture zone may have been formed simultaneously with the Xiongkuer rupture zone by the 1842 M71/2 earthquake along the boundary faults on both sides of the Barkol Mountains, exhibiting a flower-like structural pattern. Alternatively, it might represent a separate, unrecorded seismic event occurring shortly after the 1842 earthquake. The estimated magnitude of the associated earthquake is about 6.6~6.9. Given that surface-rupturing earthquakes have already occurred in the western segment, the study indicates that the Erdaogou–Nanshankou section of the HMNF has surpassed the average recurrence interval for major earthquakes, indicating a potential future earthquake hazard. [ABSTRACT FROM AUTHOR]

Greenland's peripheral glaciers are losing mass at an accelerated rate and are contributing significantly to sea level rise, but only a few direct observations are available. In this study, we use the unique combination of high-resolution remote sensing data and direct mass balance observations to quantify the contribution of a singular avalanche event to the mass balance of Freya Glacier (74.38° N, 20.82° W), a small (5.5 km2, 2021) mountain glacier in Northeast Greenland. Elevation changes calculated from repeated photogrammetric surveys in August 2013 and July 2021 show a high spatial variability, ranging from -11 to 18 m, with a glacier-wide mean of 1.56 ± 0.10 m (1.33 ± 0.21 m w.e.). After applying a seasonal correction of -0.6 ± 0.05 m w.e., the geodetic mass balance over the entire 8-year period (2013–2014 to 2020–2021) is found to be 0.73 ± 0.22 m w.e. A significant influence over the near-decadal mass balance stems from the exceptional winter mass balance of 2017–2018, which was 2.5 standard deviations above average (1.89 ± 0.05 m w.e.). After heavy snowfall in mid-February 2018, snow avalanches from the surrounding slopes affected more than one-third of the glacier surface and contributed 0.35 ± 0.04 m w.e., which is close to 20 % of the total winter mass balance of 2017–2018. Remote sensing data show that Freya Glacier is also prone to avalanches in other years but to a lesser spatial extent. Due to a gap in mass balance point observations caused by high accumulation rates (buried stakes) and the COVID-19 pandemic, the recently reported glacier-wide annual mass balances are rather crude estimates and show a negative bias of -0.22 m w.e. a−1 compared to the geodetic mass balance. Finally, we speculate that the projected future warming may increase the likelihood of extreme snowfall, thus potentially increasing the contribution of snow avalanches to the mass balance of mountain glaciers in Northeast Greenland. [ABSTRACT FROM AUTHOR]

In the central Eastern Alps, an increasing number of high-altitude streams draining ice-rich permafrost display high concentrations of toxic solutes, such as Al, F- , Mn, and Ni, that may strongly exceed drinking water limits. To obtain novel insights into the causes for the mobilization of toxic solutes and to assess the environmental hazard, here we present a 2-year dataset (2021, 2022) of monitoring a high alpine stream originating from an intact rock glacier located in eastern Switzerland. The monitoring includes monthly sampling and discharge measurements, as well as continuous tracking of the geogenic fluxes of toxic solutes, using a pressure and conductivity probe. Our monitoring revealed high annual fluxes of up to 10 ta-1 with strong seasonal variations. In particular, the fluxes were highest during the warm summer months and showed strong correlations with hydraulic events such as snowmelt and heavy rainfall. These correlations likely occurred because the mobilization of toxic solutes reflects the last step of a complicated sequence of coupled processes, including (i) the oxidation of sulfides producing sulfuric acid and promoting the dissolution of solutes from the host rock, (ii) temporal storage and long-term enrichment of the dissolved solutes in rock glacier ice, and (iii) their final hydraulic mobilization during climate-change-induced accelerated degradation of rock glaciers. In the studied catchment, the concentrations of toxic solutes strongly exceeded the drinking water limits down to an altitude of 1900 m a.s.l. This depicts a significant hazard for the farmers and their products using the catchment in summer, while the hazard for larger streams in populated areas further downstream is considered limited. Since the fluxes of toxic solutes downstream of rock glaciers likely reflect their final hydraulic mobilization from the solute-enriched rock glacier ice, we hypothesize that flux measurements may serve as a novel environmental tracer to study permafrost degradation. [ABSTRACT FROM AUTHOR]

Projecting the global evolution of glaciers is crucial to quantify future sea-level rise and changes in glacier-fed rivers. Recent intercomparison efforts have shown that a large part of the uncertainties in the projected glacier evolution is driven by the glacier model itself and by the data used for initial conditions and calibration. Here, we quantify the effect that mass balance observations, one of the most crucial data sources used in glacier modelling, have on glacier projections. For this, we model the 21st century global glacier evolution under Coupled Model Intercomparison Phase 6 project (CMIP6) climate scenarios with the Global Glacier Evolution Model (GloGEM) calibrated to match glacier-specific mass balance observations, as opposed to relying on regional mass balance observations. We find that the differences in modelled 21st century glacier changes can be large at the scale of individual glaciers (up to several tens of percent), but tend to average out at regional to global scales (a few percent at most). Our study thus indicates that the added value of relying on glacier-specific observations is at the subregional and local scale, which will increasingly allow projecting the glacier-specific evolution and local impacts for every individual glacier on Earth. To increase the ensemble of models that project global glacier evolution under CMIP6 scenarios, simulations are also performed with the Open Global Glacier Model (OGGM). We project the 2015–2100 global glacier loss to vary between 25 ± 15 % (GloGEM) and 29 ± 14 % (OGGM) under SSP1-2.6 to 46 ± 26 % and 54 ± 29 % under SSP5-8.5 (ensemble median, with 95 % confidence interval; calibration with glacier-specific observations). Despite some differences at the regional scale and a slightly more pronounced sensitivity to changing climatic conditions, our results agree well with the recent projections by Rounce et al. (2023), thereby projecting, for any emission scenario, a higher 21st century mass loss than the current community estimate from the second phase of the Glacier Model Intercomparison Project (GlacierMIP2). [ABSTRACT FROM AUTHOR]

Ice avalanche (IA) has a strong concealment and sudden characteristics, which can cause severe disasters. The early identification of IA hidden danger is of great value for disaster prevention and mitigation. However, it is very difficult, and there is poor efficiency in identifying it by site investigation or manual remote sensing. So, an artificial intelligence method for the identification of IA hidden dangers using a deep learning model has been proposed, with the glacier area of the Yarlung Tsangpo River Gorge in Nyingchi selected for identification and validation. First, through engineering geological investigations, three key identification indices for IA hidden dangers are established, glacier source, slope angle, and cracks. Sentinel-2A satellite data, Google Earth, and ArcGIS are used to extract these indices and construct a feature dataset for the study and validation area. Next, key performance metrics, such as training accuracy, validation accuracy, test accuracy, and loss rates, are compared to assess the performance of the ResNet50 (Residual Neural Network 50) and VGG16 (Visual Geometry Group 16) models. The VGG16 model (96.09% training accuracy) is selected and optimized, using Early Stopping (ES) to prevent overfitting and L2 regularization techniques (L2) to add weight penalties, which constrained model complexity and enhanced simplicity and generalization, ultimately developing the ES-L2-VGG16 (Early Stopping—L2 Norm Regularization Techniques—Visual Geometry Group 16) model (98.61% training accuracy). Lastly, during the validation phase, the model is applied to the Yarlung Tsangpo River Gorge glacier area on the Tibetan Plateau (TP), identifying a total of 100 IA hidden danger areas, with average slopes ranging between 34° and 48°. The ES-L2-VGG16 model achieves an accuracy of 96% in identifying these hidden danger areas, ensuring the precise identification of IA dangers. This study offers a new intelligent technical method for identifying IA hidden danger, with clear advantages and promising application prospects. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is the largest glacier reserve outside the Antarctic and Arctic regions. Climate warming has affected the reserve of freshwater resources and led to frequent glacier disasters. However, due to its extreme environment of hypoxia and low pressure, it is extremely difficult to obtain data. Compared with other traditional monitoring methods such as makers and satellite remote sensing technology, Ground-Based (GB) radar systems have the advantages of convenient carrying and installation, sub-second level sampling, and sub-millimeter measurement accuracy. They can be used as an effective way to study the short-term rapid movement changes in glaciers. Based on a self-built GB radar system, monitoring experiments were conducted on two glacier termini on the TP. The movement speed of the Rongbuk glacier terminus on Mount Qomolangma was obtained through time-series interferometric measurement as 4.10 cm/day. When the altitude was about 5200 m, the glacier movement speed was 7.74 cm/day, indicating the spatial differences with altitude changes. And in another region, the movement speed of the Yangbulake glacier terminus on Mount Muztag Ata was 198.96 cm/day, indicating significant changes in glacier movement. The cross-validation of Sentinel-1 data during the same period proved the effectiveness of GB radar system interferometry in measuring glacier movement speed and also provided field validation data for remote sensing inversion. [ABSTRACT FROM AUTHOR]

The current emphasis in the advancement of space-based synthetic-aperture radar (SAR) is on lightweight payloads under 100 kg with resolutions surpassing 1 m. This focus is directed toward meeting the launch criteria for multiple satellites on a single rocket and cutting costs. This article discusses the creation and progress of a Ku-band SAR payload for the Taijing-4(03) satellite, launched on 23 January 2024 and accompanied by four other satellites. The SAR payload design was customized to meet the demands of a micro-nano satellite platform, resulting in a lightweight, flat design weighing less than 80 kg, seamlessly integrated with the plate-shaped satellite platform. The article also introduces a beam optimization strategy for the phased array SAR antenna, significantly boosting the SAR system's performance. The SAR payload provides various operating modes like slide-spot, strip, Scan 1, Scan 2, and others, with a maximum achievable resolution exceeding 1 m. Extensive in-orbit testing of the payload produced numerous high-quality SAR images with potential uses in emergency disaster mitigation, safeguarding ecosystems, monitoring forests, managing crops, tracking sea ice, and more. [ABSTRACT FROM AUTHOR]

The Vilcanota is the second-largest snow-capped mountain range in Peru, featuring 380 individual glaciers, each with its own unique characteristics that must be studied independently. However, few studies have been conducted in the Vilcanota range to monitor and track the area and volume changes of the Suyuparina and Quisoquipina glaciers. Notably, there are only a few studies that have approached this issue using LIDAR technology. Our methodology is based on a combination of optical, radar and LIDAR data sources, which allowed for constructing coherent temporal series for the both the perimeter and volume changes of the Suyuparina and Quisoquipina glaciers while accounting for the uncertainty in the perimeter detection procedure. Our results indicated that, from 1990 to 2013, there was a reduction in snow cover of 12,694.35 m2 per year for Quisoquipina and 16,599.2 m2 per year for Suyuparina. This represents a loss of 12.18% for Quisoquipina and 22.45% for Suyuparina. From 2006 to 2013, the volume of the Quisoquipina glacier decreased from 11.73 km3 in 2006 to 11.04 km3 in 2010, while the Suyuparina glacier decreased from 6.26 km3 to 5.93 km3. Likewise, when analyzing the correlation between glacier area and precipitation, a moderate inverse correlation (R = −0.52, p < 0.05) was found for Quisoquipina. In contrast, the correlation for Suyuparina was low and nonsignificant, showing inconsistency in the effect of precipitation. Additionally, the correlation between the snow cover area and the annual mean air temperature (R = −0.34, p > 0.05) and annual minimum air temperature (R = −0.36, p > 0.05) was low, inverse, and not significant for Quisoquipina. Meanwhile, snow cover on Suyuparina had a low nonsignificant correlation (R = −0.31, p > 0.05) with the annual maximum air temperature, indicating a minimal influence of the measured climatic variables near this glacier on its retreat. In general, it was possible to establish a reduction in both the area and volume of the Suyuparina and Quisoquipina glaciers based on freely accessible remote sensing data. [ABSTRACT FROM AUTHOR]

Glacier meltwater is an indispensable water supply for billions of people living in the catchments of major Asian rivers. However, the role of glaciers on river runoff regulation is seldom investigated due to the lack of annual glacier mass balance observation. In this study, we employed an albedo-based model with a daily land surface albedo dataset to derive the annual glacier mass balance over the Tuotuo River Basin (TRB). During 2000–2022, an annual glacier mass balance range of −0.89 ± 0.08 to 0.11 ± 0.11 m w.e. was estimated. By comparing with river runoff records from the hydrometric station, the contribution of glacier mass change to river runoff was calculated to be 0.00–31.14% for the studied period, with a mean value of 9.97%. Moreover, we found that the mean contribution in drought years is 20.07%, which is approximately five times that in wet years (4.30%) and twice that in average years (9.49%). Therefore, our results verify that mountain glaciers act as a significant buffer against drought in the TRB, at least during the 2000–2022 period. [ABSTRACT FROM AUTHOR]

Since the 1970s, extensive halite extraction in Maceió, Brazil, has resulted in significant geological risks, including ground collapses, sinkholes, and infrastructure damage. These risks became particularly evident in 2018, following an earthquake, which prompted the cessation of mining activities in 2019. This study investigates subsidence deformation resulting from these mining operations, focusing on the collapse of Mine 18 on 10 December 2023. We utilized the Quasi-Persistent Scatterer Interferometric Synthetic Aperture Radar (QPS-InSAR) technique to analyze a dataset of 145 Sentinel-1A images acquired between June 2019 and April 2024. Our approach enabled the analysis of cumulative displacement, the loss of amplitude stability, the evolution of amplitude time series, and the amplitude change matrix of targets near Mine 18. The study introduces an innovative QPS-InSAR approach that integrates phase and amplitude information using amplitude time series to assess the lifecycle of radar scattering targets throughout the monitoring period. This method allows for effective change detection following sudden events, enabling the identification of affected areas. Our findings indicate a maximum cumulative displacement of −1750 mm, with significant amplitude changes detected between late November and early December 2023, coinciding with the mine collapse. This research provides a comprehensive assessment of deformation trends and ground stability in the affected mining areas, providing valuable insights for future monitoring and risk mitigation efforts. [ABSTRACT FROM AUTHOR]

This report summarises the main outcomes of the 4th edition of the workshop on Machine Learning (ML) for Earth System Observation and Prediction (ESOP / ML4ESOP) co-organised by the European Space Agency (ESA) and the European Centre for Medium-Range Weather Forecasts (ECMWF). The 4-day workshop was held on 7-10 May 2024 in a hybrid format at the ESA Frascati site with an interactive online component, featuring over 46 expert talks with a record number of submissions and about 800 registrations. The workshop offered leading experts a platform to exchange on the current opportunities, challenges and future directions for applying ML methodology to ESOP. To structure the presentations and discussions, the workshop featured five main thematic areas covering key topics and emerging trends. The most promising research directions and significant outcomes were identified by each thematic area's Working Group and are the focus of this document. [ABSTRACT FROM AUTHOR]

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) has great potential for development due to its advantages of the use of multiple beams, low energy consumption, high repetition frequency, and high measurement sensitivity. However, the weak photon signal emitted by the photon counting lidar is susceptible to the background noise caused by the sun and the atmosphere, which can seriously affect the processing and application of laser data. This paper proposes an improved DBSCAN clustering algorithm for denoising single photon laser point clouds in mountainous areas. Firstly, a grouping method based on elevation and distance statistics is proposed to reduce the influence of terrain undulations on denoising accuracy. Finally, an automatic radius search method is put forward to determine clustering radius of each group, automatically find the optimal radius, and improve the existing DBSCAN clustering method. The method proposed in this paper is compared with the classical DBSCAN algorithm. The results show that the proposed algorithm significantly improves denoising accuracy in mountainous areas and effectively filters out most background noise. [ABSTRACT FROM AUTHOR]

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Glaciers are considered to be 'climate-sensitive indicators' and 'solid reservoirs', and their changes significantly impact regional water security. The mass balance (MB) from 2011 to 2020 of the Qiyi Glacier in the northeast Tibetan Plateau is presented based on field observations. The glacier showed a persistent negative balance over 9 years of in-situ observations, with a mean MB of −0.51 m w.e. yr−1. The distributed energy-mass balance model was used for glacier MB reconstruction from 1980 to 2020. The daily meteorological data used in the model were from HAR v2 reanalysis data, with automatic weather stations located in the middle and upper parts of the glacier used for deviation correction. The average MB over the past 40 years of the Qiyi Glacier was −0.36 m w.e. yr−1 with the mass losses since the beginning of the 21st century, being greater than those in the past. The glacier runoff shows a significant increasing trend, contributing ∼81% of the downstream river runoff. The albedo disparity indicates that the net shortwave radiation is much higher in the ablation zone than in the accumulation zone, accelerating ablation-area expansion and glacier mass depletion. The MB of the Qiyi Glacier is more sensitive to temperature and incoming shortwave radiation variation than precipitation. The MB presented a non-linear reaction to the temperature and incoming shortwave radiation. Under future climate warming, the Qiyi Glacier will be increasingly likely to deviate from the equilibrium state, thereby exacerbating regional water balance risks. It is found that the mass losses of eastern glaciers are higher than those of western glaciers, indicating significant spatial heterogeneity that may be attributable to the lower altitude and smaller area distribution of the eastern glaciers. [ABSTRACT FROM AUTHOR]

Tropical glaciers in the central Andes are vital water resources and crucial climate indicators, currently undergoing rapid retreat. However, understanding their vulnerability to the combined effects of persistent warming, the El Niño and La Niña climate phenomena, and interannual fluctuations remains limited. Here, we automate the mapping of key mass balance parameters on the Quelccaya Ice Cap (QIC) in Peru, one of the largest tropical ice caps. Using Landsat's near-infrared (NIR) band, we analyze snow cover area (SCA) and total area (TA) and calculate the accumulation area ratio (AAR) and equilibrium-line altitude (ELA) over nearly 40 years (1985–2023). Between 1985 and 2022, the QIC lost ∼58 % and ∼37 % of its SCA and TA, respectively. We show that the QIC's reduction in SCA and rise in ELA are exacerbated by El Niño events, which are strongly correlated with the preceding wet season's Oceanic Niño Index (ONI). Further, expansion in the QIC's SCA is observed during all La Niña years, except during the 2021–2022 La Niña. Although this is a singular event, it could indicate a weakened ability for SCA recovery and an accelerated decline in the future, primarily driven by anthropogenic warming. [ABSTRACT FROM AUTHOR]

This article provides a comprehensive overview of all currently available datasets of the Long-term Ecosystem Research (LTER) site Oberes Stubachtal. The site is located in the Hohe Tauern mountain range (Eastern Alps, Austria) and includes both protected areas (Hohe Tauern National Park) and unprotected areas (Stubach valley). While the main research focus of the site is on high mountains, glaciology, glacial hydrology, and biodiversity, the eLTER Whole-System Approach (WAILS) was used for data selection. This approach involves a systematic screening of all available data to assess their suitability as eLTER Standard Observations (SOs). This includes the geosphere, atmosphere, hydrosphere, biosphere, and sociosphere. These SOs are fundamental to the development of a comprehensive long-term ecosystem research framework. In total, more than 40 datasets have been collated for the LTER site Oberes Stubachtal and included in the Dynamic Ecological Information Management System—Site and Data Registry (DEIMS-SDR), the eLTER's data platform. This paper provides a detailed inventory of the datasets and their primary attributes, evaluates them against the WAILS-required observation data, and offers insights into strategies for future initiatives. All datasets are made available through dedicated repositories for FAIR (findable, accessible, interoperable, reusable) use. [ABSTRACT FROM AUTHOR]

This paper investigates the ability of a relatively low cost, commercially available uncrewed aerial vehicle (UAV), the DJI Mavic 3 Multispectral, to perform cryospheric research. The performance of this UAV, where applicable, is compared to a similar but higher cost system, the DJI Matrice 350, equipped with a Micasense RedEdge-MX Multispectral dual-camera system. The Mavic 3 Multispectral was tested at three field sites: the Lemon Creek Glacier, Juneau Icefield, AK; the Easton Glacier, Mt. Baker, WA; and Bagley Basin, Mt. Baker, WA. This UAV proved capable of mapping the spatial distribution of red snow algae on the surface of the Lemon Creek Glacier using both spectral indices and a random forest supervised classification method. The UAV was able to assess the timing of snowmelt and changes in suncup morphology on snow-covered areas within the Bagley Basin. Finally, the UAV was able to classify glacier surface features using a random forest algorithm with an overall accuracy of 68%. The major advantages of this UAV are its low weight, which allows it to be easily transported into the field, its low cost compared to other alternatives, and its ease of use. One limitation would be the omission of a blue multispectral band, which would have allowed it to more easily classify glacial ice and snow features. [ABSTRACT FROM AUTHOR]

The interest in the enhancement of innovative solutions in the geospatial data classification domain from integrated aerial methods is rapidly growing. The transition from unstructured to structured information is essential to set up and arrange geodatabases and cognitive systems such as digital twins capable of monitoring territorial, urban, and general conditions of natural and/or anthropized space, predicting future developments, and considering risk prevention. This research is based on the study of classification methods and the consequent segmentation of low-altitude airborne LiDAR data in highly forested areas. In particular, the proposed approaches investigate integrating unsupervised classification methods and supervised Neural Network strategies, starting from unstructured point-based data formats. Furthermore, the research adopts Machine Learning classification methods for geo-morphological analyses derived from DTM datasets. This paper also discusses the results from a comparative perspective, suggesting possible generalization capabilities concerning the case study investigated. [ABSTRACT FROM AUTHOR]

The mass balance of the Greenland Ice Sheet is strongly influenced by the dynamics of its outlet glaciers. Therefore, it is of paramount importance to accurately and continuously monitor these glaciers, especially the variation in their frontal positions. A temporally comprehensive parameterization of glacier calving is essential for understanding dynamic changes and constraining ice sheet modeling. However, many current calving front records are limited in terms of temporal resolution as they rely on manual delineation, which is laborious and not appropriate considering the increasing amount of satellite imagery available. In this contribution, we address this problem by applying an automated method to extract calving fronts from optical satellite imagery. The core of this workflow builds on recent advances in the field of deep learning while taking full advantage of multispectral input information. The performance of the method is evaluated using three independent test datasets. For the three datasets, we calculate mean delineation errors of 61.2, 73.7, and 73.5 m, respectively. Eventually, we apply the technique to Landsat-8 imagery. We generate 9243 calving front positions across 23 outlet glaciers in Greenland for the period 2013–2021. Resulting time series not only resolve long-term and seasonal signals but also resolve subseasonal patterns. We discuss the implications for glaciological studies and present a first application for analyzing the effect of bedrock topography on calving front variations. Our method and derived results represent an important step towards the development of intelligent processing strategies for glacier monitoring, opening up new possibilities for studying and modeling the dynamics of Greenland's outlet glaciers.

We use data from the Gravity Recovery and Climate Experiment and its Follow-On mission (GRACE/GRACE-FO) from April 2002 to December 2022 to analyze interannual glacial mass changes in High Mountain Asia (HMA) and its subregions and their driving factors. Glacial mass changes in the HMA subregions show clear regional characteristics. Interannual glacial mass changes in the HMA region are closely related to interannual oscillations of precipitation and temperature, and are also correlated with El Niño–Southern Oscillation (ENSO). Glacial mass changes in the regions (R1–R6) are dominated by precipitation, and ENSO affects interannual glacial mass changes mainly by affecting precipitation. In region (R7) and region (R8), the glacial mass changes are mainly controlled by temperature. ENSO also affects the interannual glacial mass changes by affecting interannual changes in temperature. The interannual glacial mass changes in regions (R9–R11) are jointly dominated by temperature and precipitation, and also related to ENSO. Another interesting finding of this study is that glacial mass changes in the western part of HMA (R1–R6) show a clear 6–7-year oscillation, strongly correlated with a similar oscillation in precipitation, while in the eastern part (R9–R11), a 2–3-year oscillation was found in both glacial mass change and precipitation, as well as temperature. These results verify the response of interannual HMA glacial mass changes to climate processes, crucial for understanding regional climate dynamics and sustainable water resource management. [ABSTRACT FROM AUTHOR]

The geological environment damage caused by coal mining subsidence has become an important factor affecting the sustainable development of mining areas. Reconstruction of the Coal Mining Subsidence Field (CMSF) is the key to preventing geological disasters, and the needs of CMSF reconstruction cannot be met by solely relying on a single remote sensing technology. The combination of Unmanned Aerial Vehicle (UAV) and Synthetic Aperture Radar (SAR) has complementary advantages; however, the data fusion strategy by refining the SAR deformation field through UAV still needs to be updated constantly. This paper proposed a Prior Weighting (PW) method based on Satellite Aerial (SA) heterogeneous remote sensing. The method can be used to fuse SAR and UAV Light Detection and Ranging (LiDAR) data for ground subsidence parameter inversion. Firstly, the subsidence boundary of Differential Interferometric SAR (DInSAR) combined with the large gradient subsidence of Pixel Offset Tracking (POT) was developed to initialize the SAR preliminary CMSF. Secondly, the SAR preliminary CMSF was refined by UAV LiDAR data; the weights of SAR and UAV LiDAR data are 0.4 and 0.6 iteratively. After the data fusion, the subsidence field was reconstructed. The results showed that the overall CMSF accuracy improved from ±144 mm to ±51 mm. The relative errors of the surface subsidence factor and main influence angle tangent calculated by the physical model and in situ measured data are 1.3% and 1.7%. It shows that the proposed SAR/UAV fusion method has significant advantages in the reconstruction of CMSF, and the PW method contributes to the prevention and control of mining subsidence. [ABSTRACT FROM AUTHOR]

Aldegondabreen is a relatively small (5.3 km2) land-terminating glacier located in Nordeskiöld Land of Svalbard, ~10 km southwest of Barentsburg. Cumulative mass balance during 2002–20 equalled −21.79 m w.e., which corresponds to 37% of the total mass loss. The annual mass balance (B a) varied from −0.24 to −2.19 m w.e., while the winter mass balance (B w) ranged between 0.36 and 0.85 m w.e. B a and B w were strongly correlated with the positive degree-day sums and solid precipitation amounts, respectively, measured at the Barentsburg weather station. There was also a strong correlation (r = 0.76) between B a and B w, which shows that winter accumulation amplifies the consecutive summer ice melt by changing the surface albedo. The trend in both observational series is not detectable because the period from 2005 to 2013 was characterized by relatively high B w and not very negative B a values. This was also observed on the other Svalbard glaciers, and was related to prevailing north-westerly flows over Svalbard during the summer. Therefore, the decadal periodicity of the Aldegondabreen mass balance follows general archipelago patterns that are determined by regional-scale factors. Thus, the surface mass-balance time series, which is now the longest one in the central part of the Spitsbergen Island, is representative for the archipelago. [ABSTRACT FROM AUTHOR]