Search Results (176)

A forty-year record (1984–2023) of glacier mass balance and areal extent measurement documented the decline and loss of the Ice Worm Glacier in the North Cascade Range, Washington. After a period of minor variations from 1944 to 1986, the glacier lost 83% of its area from 1986 to 2023 and had a cumulative mass loss of −31.5 m w.e. In 2023, the area at 32,000 m² and the majority of the ice thickness at 2–10 m was insufficient to generate movement. The bottom of the glacier was observed in all existing crevasse features, and stream channels in 2023 at depths of 2–10 m. An ice cave extended the length of the glacier in 2024 illustrating an ice thickness of less than 8 m. This glacier area loss has led to declining glacier runoff into Hyas Creek and the Cle Elum River. Full article

The Patagonia Icefield, the largest ice mass in the Southern Hemisphere outside Antarctica, has experienced significant growth and expansion of ice-contact lakes in recent decades, with lake surface water temperature (LSWT) being one of the key influencing factors. LSWT affects glacier melting at the waterline and accelerates glacier mass loss. However, the observations of ice-contact LSWT are often limited to short-term, site-based field measurements, which hinders long-term, whole-lake monitoring. This study examines LSWT for the three largest ice-contact lakes in the Patagonia Icefield—Lake Argentino, Lake Viedma, and Lake O’Higgins, each exceeding 1000 km²—and the three largest nearby non-ice-contact lakes for comparison using MODIS data between 2002 and 2022. In 2022, the mean LSWTs for Lake Argentino, Lake Viedma, and Lake O’Higgins were 7.2, 7.0, and 6.4 °C, respectively. In summer, ice-contact lakes exhibited wider LSWT ranges and more pronounced cooling near glacier termini and warming farther away compared to other seasons, demonstrating glacier melt cooling and its seasonal variability. Over the past 20 years, both Lake Viedma and Lake O’Higgins showed a warming rate of +0.20 °C dec⁻¹, p > 0.1, with slower warming near the glacier, reflecting glacier contact suppression on the LSWT trend. Conversely, Lake Argentino displayed a significant warming rate of +0.43 °C dec⁻¹ (p < 0.05), with faster rates near the glacier terminus, possibly linked to a prolonged and large (>64 km²) iceberg accumulation event from March 2010 to October 2011 in Glacier Upsala’s fjord. Iceberg mapping shows that larger events caused more pronounced short-term (24 days) LSWT cooling in Lake Argentino’s ice-proximal region. This study highlights the role of glacier–lake interactions including calving events in regulating ice-contact lake water temperature. Full article

Temperate glaciers in the Kangri Karpo region of the southeastern Qinghai–Tibet Plateau (QTP) have experienced significant ablation in recent decades, increasing the risk of glacier-related hazards and impacting regional water resources. However, the spatial and temporal pattern of mass loss in these glaciers remains inadequately quantified. In this study, we used ASTER L1A stereo images to construct a high-resolution elevation time series and provide a comprehensive spatial–temporal assessment of glacier elevation change from 2000 to 2024. The results indicate that almost all glaciers have experienced rapid ablation, with an average surface elevation decrease of −18.35 ± 5.13 m, corresponding to a rate of −0.76 ± 0.21 m yr⁻¹. Glaciers in the region were divided into the northern and southern basins, with average rates of −0.79 ± 0.17 m yr⁻¹ and −0.72 ± 0.13 m yr⁻¹, respectively. A notable difference in acceleration trends between the two basins was observed, with the elevation rate increasing from −0.78 ± 0.17m yr⁻¹ to −1.04 ± 0.17 m yr⁻¹ and from −0.52 ± 0.13 m yr⁻¹ to −0.92 ± 0.13 m yr⁻¹, respectively. The seasonal cycle was identified in glacier surface elevation change, with an accumulation period from November to March followed by a prolonged ablation period. The seasonal amplitude decreased with elevation, with higher elevations exhibiting longer accumulation periods and less ablation. Correlation analysis with meteorological data indicated that higher summer temperatures and increased summer rainfall intensify elevation loss, while increased spring snowfall may reduce ablation. Our analysis highlights distinct variations in glacier elevation changes across different locations, elevations, and climatic conditions in the Kangri Karpo region, providing valuable insights into glacier responses to environmental changes on the Tibetan Plateau. Full article

The glaciers of the Himalayas are essential for water resources in South Asia and the Qinghai–Tibet Plateau, but they are undergoing accelerated mass loss, posing risks to water security and increasing glacial hazards. This study examines long-term changes in the geometry and flow speeds of both land- and lake-terminating glaciers at the headwaters of the Yarlung Zangbo River, using field measurements, remote sensing, and numerical ice flow modeling. We observed significant heterogeneity in glacier behaviors across the region, with notable differences between glacier terminus types and even among neighboring glaciers of the same type. Between 1974 and 2020, glacier thinning and mass loss rates doubled in the early 21st century ($-0.57\pm 0.05$ m w.e. a⁻¹) compared to 1974–2000 ($-0.24\pm 0.11$ m w.e. a⁻¹). While lake-terminating glaciers generally experienced more rapid retreat and mass loss, the land-terminating N241 Glacier displayed comparable mass loss rates. Lake-terminating glaciers retreated by over 1000 m between 1990 and 2019, while land-terminating glaciers retreated by less than 750 m. The ITS_LIVE velocity dataset showed higher and more variable flow speeds in lake-terminating glaciers. Numerical modeling from 2000 to 2017 revealed divergent changes in flow regimes, with lake-terminating glaciers generally experiencing acceleration, while land-terminating glaciers showed either a slowing down or stable flow behavior. Our findings underscore the significant role of lake-terminating glaciers in contributing to ice mass loss, emphasizing the need for advanced glacier models that incorporate dynamic processes such as frontal calving and longitudinal coupling. Full article

Climate change is resulting in significant transformations in mountain areas all over the world, causing the melting of glacier ice, reduction in snow accumulation, and permafrost loss. Changes in the mountain cryosphere are not only modifying flora and fauna distributions but also affecting the stability of slopes in those regions. For all these reasons, and because of the risks these phenomena pose to the population, the dentification of dangerous areas is a crucial step in the development of risk reduction strategies. While several methods and examples exist that cover the assessment and computation of single sub-components, there is still a lack of application of risk assessment due to glacier melting over large areas in which the final result can be directly employed in the design of risk mitigation policies at regional and municipal levels. This research is focused on landslides and gravitational movements on slopes resulting from rapid glacier melting phenomena in the Valle d’Aosta region in Italy, with the aim of providing a tool that can support spatial planning in response to climate change in Alpine environments. Through the conceptualization and development of a GIS-based and multi-criteria approach, risk is then estimated by defining hazard indices that consider different aspects, combining the experience acquired from studies carried out in various disciplinary fields, to obtain a framework at the regional level. This first assessment is then deepened for the Lys River Valley, where the mapping of hazardous areas was implemented, obtaining a classification of buildings according to their hazard score to estimate the potential damage and total risk relating to possible slope instability events due to ice melt at the local scale. Full article

Monitoring land use/land cover (LULC) dynamics facilitates effective management and mitigation measures by providing timely and accurate information on the landscape. This study investigates LULC dynamics in Sagarmatha National Park (SNP), one of the most popular destinations for mountain tourism, and Khaptad National Park (KNP), which are emerging destinations, though popular among domestic tourists. A random forest classification algorithm was employed to generate LULC dynamics using Landsat data. High-resolution Planet Scope images and Google Earth images were used for accuracy assessment. Archived tourist and climatic data were analyzed to explore the impacts on LULC change. Cellular automata–artificial neural network (CA-ANN)-based LULC predictions were employed to predict future LULC. LULC dynamics of SNP revealed an increase in bare land, grassland, shrubland, glacial lakes, agriculture, and water bodies; however, snow/glacier and forest cover experienced substantial decreases of 140.25 km² and 15.36 km², respectively, from 1989 to 2021. In KNP, LULC dynamics showed an increasing trend in grassland, agriculture, water bodies, and bare land; however, forest and shrubland experienced a decrease of 18.63 km² and 10.48 km². The forest loss (19.33 km²) in the buffer zone of KNP was greater compared to the buffer zone of SNP (13.45 km²). The increment in built-up area was 0.80 km² in SNP and 1.11 km² in KNP, indicating escalating tourist activities and population growth. For SNP, the mean annual precipitation and temperature data from 1994 to 2023 showed decreasing and increasing patterns, respectively. However, the mean annual precipitation and temperature trends in KNP demonstrated an increasing pattern. Under the business-as-usual scenario, the estimated forest loss will be 1.61 km² in SNP by 2032 and 23.8 km² in KNP by 2030. A significant decline in snow/glaciers is projected for the core zone of SNP, with a loss of 22.84 km² expected by 2032. This study provides a baseline information on LULC changes in SNP and KNP. Further, it showcases the necessity of diversified national park policies as per the requirement. Full article

In this study, we utilized Random Forest machine learning classification to assess the current state of glaciers in the western United States using Sentinel-2A satellite imagery. By analyzing Sentinel-2A imagery from September 2020 and comparing it to the RGI inventory, the study determined the current conditions of the glaciers. Our findings unveiled a significant reduction in both glacier area and volume in the western United States since the mid-20th century. Currently, the region hosts 2878 glaciers and perennial snowfield spanning eight states, covering a total area of 428.32 ± 7.8 km² with a corresponding volume of 9.00 ± 0.9 km³. During the study period, a loss of 244.31 km² in glacier area was observed, representing a 36.32% decrease when contrasted with the RGI boundaries. The volume lost during this period amounted to 4.96 km³, roughly equivalent to 4.7 gigatons of water. Among the states, Washington experienced the most significant glacier area reduction, with a loss of 133.16 km². Notably, glaciers in the North Cascade Range of Washington, such as those in Mt. Baker and Mt. Shuksan, now cover, on average, only 85% of their original glacier boundaries with ice and snow at the conclusion of the 2020 hydrological year. Major glaciers, including the White River Glacier, West Nooksack Glacier, and White Chuck Glacier, have lost more than 50 percent of their original area. Full article

Arctic tidewater glaciers are retreating, serving as key indicators of global warming. This study aims to assess how subglacial hydrology affects glacier front retreat by comparing two glacier–fjord models of the Hansbreen glacier: one incorporating a detailed subglacial hydrology model and another simplifying the subglacial discharge to a single channel centered in the flow line. We first validate the subglacial hydrology model by comparing its discharge channels with observations of plume activity. Simulations conducted from April to December 2010 revealed that the glacier front position aligns more closely with the observations in the coupled model than in the simplified version. Furthermore, the mass loss due to calving and submarine melting is greater in the coupled model, with the calving mass loss reaching 6 Mt by the end of the simulation compared to 4 Mt in the simplified model. These findings highlight the critical role of subglacial hydrology in predicting glacier dynamics and emphasize the importance of detailed modeling in understanding the responses of Arctic tidewater glaciers to climate change. Full article

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. Full article

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. Full article

The intense changes in glaciers in the southeastern Tibetan Plateau (SETP) have essential impacts on regional water resource management. In order to study the seasonal fluctuations of glaciers in this region and their relationship with climate change, we focus on the Yigong Zangbo River Basin in the SETP, extract the annual and seasonal variations of glaciers in the basin during 2018–2023, and analyze their spatio-temporal characteristics through the seasonal-trend decomposition using the LOESS (STL) method. Finally, combining the Extreme Gradient Boosting (XGBoost) model and the Shapley additive explanations (SHAP) model, we assess the comprehensive impact of meteorological factors such as temperature and snowfall on glacier changes. The results indicate that glaciers in the Yigong Zangbo River Basin experienced remarkable mass loss during 2018–2023, with an average annual melting rate of −0.83 ± 0.12 m w.e.∙yr⁻¹. The glacier mass exhibits marked seasonal fluctuations, with increases in January–March (JFM) and April–June (AMJ) and noticeable melting in July–September (JAS) and October–December (OND). The changes over these four periods are 2.12 ± 0.04 m w.e., 0.93 ± 0.15 m w.e., −1.58 ± 0.19 m w.e., and −1.32 ± 0.17 m w.e., respectively. Temperature has been identified as the primary meteorological driver of glacier changes in the study area, surpassing the impact of snowfall. This study uses advanced altimetry data and meteorological data to monitor and analyze glacier changes, which provides valuable data for cryosphere research and also validates a set of replicable research methods, which provides support for future research in related fields. Full article

The glaciers in southeastern Tibet Plateau (SETP) influenced by oceanic climate are sensitive to global warming, and there remains a notable deficiency in accurate multitemporal change analyses of these glaciers. We conduct glacier inventories in the Yigong Zangbo River Basin (YZRB) in SETP for the years 1988, 2015, and 2023 utilizing Landsat and Sentinel-2 imagery, and analyze the glacier spatiotemporal variation incorporating the existing glacier inventory data. Since the 1970s until 2023, the glaciers significantly retreated at a rate of 0.76 ± 0.11%·a⁻¹, with the area decreasing from 2583.09 ± 88.80 km² to 1635.89 ± 71.74 km², and the ice volume reducing from 221.7017 ± 7.9618 km³ to 152.7429 ± 6.1747 km³. The most significant retreat occurred in glaciers smaller than 1 km². Additionally, glaciers on southern aspects retreated slower than the northern counterparts. The glaciers in the western YZRB witnessed a significantly greater shrinkage rate than those in the eastern section, with the most pronounced changes occurring in Aso Longbu River Basin. Furthermore, severe glacier mass deficits were observed from 2000 to 2019, averaging a loss rate of 0.57 ± 0.06 m w.e. a⁻¹. The continuous rise in air temperature has primarily induced a general widespread glacier change in the YZRB. However, diverse topography led to spatial variability in glacier changes with discrepancies as large as several times. The features of individual glaciers, such as glacier size, debris cover, and the development of ice-contact glacial lakes enhanced the local complexity of glacier change and elusive response behaviors to climate warming led by the different topographic conditions. Full article

Maritime glaciers in the southeastern Tibetan Plateau (SETP) are particularly sensitive to changes in climate, and their changes directly and severely affect regional water security and glacier-related hazards. Given their large societal importance, a better understanding of the mass balance of maritime glaciers in the SETP, a key variable for characterizing the state of glacier health, is of great scientific interest. In this review, we synthesize in situ, satellite-based observations and simulations that present an overall accelerating negative mass balance of maritime glaciers in the SETP in recent decades. We hereby highlight a significant spatiotemporal difference in the mass balance of maritime glaciers across the SETP and investigate the drivers of the accelerated mass loss of these glaciers in recent years. We find that accelerated glacier mass loss agrees with the variabilities in temperatures rising and precipitation decreasing at regional scales, as well as the spatial patterns of widespread melt hotspots (e.g., thin debris, ice cliffs, supraglacial ponds, and surface streams), the expansion of glacial lakes, enlarged ice crevasses, and frequent ice avalanches. Finally, the challenges of the mass balance study of maritime glaciers and future perspectives are proposed. Our review confirms the urgent need to improve the existing glacier inventory and establish comprehensive monitoring networks in data-scarce glacierized catchments, and it suggests paying particular attention to the development of glacier mass-balance models that coupe multiple physical processes at different interfaces to predict the status of maritime glaciers and their responses to climate change. This study can inform the sustainable management of water resources and the assessment of socio-economic vulnerability due to glacier-related hazards in the SETP and its surroundings in the context of marked atmospheric warming. Full article

In the midlatitudes of the planet, we are facing the imminent disappearance of one of our best high-resolution (pre)historic climate and anthropogenic pollution archives, namely the loss of glacial ice, through accelerated global warming. To capture these records and interpret these vanishing archives, it is imperative that we extract ice-cores from midlatitude regions where glaciers still survive and analyse them within frameworks of inter-disciplinary research. In this paper, we focus on Georgia, part of the Greater Caucasus. Results of ice-core analyses from the region have never, to date, been integrated with its other abundant palaeo-environmental, archaeological and historical sources. We review the results of international projects on palaeo-environmental/geoarchaeological sediment archives, the archaeology of metal economies and preliminary ice-core data in Georgia. Collectively, we show that the different strands need to be integrated to fully explore relationships between climate/landscape change and human societal transformations. We then introduce an inclusive interdisciplinary framework for ongoing research on these themes, with an ultimate future goal of using data from the past to inform societal resilience strategies in the present. Full article

Lake-terminating glaciers are among the most severely retreating glacier types in high mountain areas. However, the characteristic of being covered by glacial lakes after retreat makes it hard to estimate their actual ice loss in recent years, as does the contribution of different parts in ice loss, which leads to significant obstacles not only in evaluating solid water resources but understanding inter-relationships between glacial ice and glacial lakes. This study presents a detailed investigation of Jiongpu Co, one of the biggest glacial lakes in the Tibetan Plateau, including its bathymetry and area evolution. The ice loss in the last two decades was analyzed using a multisource DEM dataset. The main results showed that from 1976 to 2021, Jiongpu Co had expanded from 1.19 ± 0.09 km² to 5.34 ± 0.07 km². The volume of Jiongpu Co showed a surprising increment from 0.09 ± 0.004 Gt to 0.66 ± 0.03 Gt from 1976 to 2021, leading to a subaqueous equivalent ice loss of 0.32 ± 0.01 Gt water from 2000 to 2020 and resulting in an underestimated ice loss of 0.06 Gt, 19% compared with previous evaluations. The total ice loss of the Jiongpu glacier was 1.52 ± 0.37 Gt from 2000 to 2020, and more than 1/3 ice loss was related to lake expansion (0.32 ± 0.01 Gt underwater, 0.19 ± 0.02 Gt above water). This study makes a further contribution to the understanding of ice loss in the complicated system of lake-terminating glaciers. Full article