Rock glaciers support alpine biodiversity and may respond more slowly to warming than snow or glaciers. While responses of snow and glaciers to climate change are relatively well understood, a robust assessment of rock glacier environmental niche, future distributions of rock glaciers and potential for development of rock glaciers from current glaciers is lacking. Using process-relevant, high-resolution environmental descriptors, we develop a species distribution model of the topographic, geologic and hydroclimatic niche of rock glaciers that provides novel estimates of potential rock glacier distributions for different climates. We identify mean annual air temperature and headwall area as the dominant controls on rock glacier spatial distributions, with rock glaciers more likely to be found in areas with mean annual temperatures close to −5°C, little rain, northern aspects and broad headwalls. While rock glacier climate equilibration may take hundreds of years, we find that equilibration to present climate will result in a 50% reduction in rock glacier habitat and equilibration to late 21st-century climate under a high-end warming scenario will result in a 99% reduction in rock glacier habitat across the western USA. Under future conditions, we find limited potential for glacier to rock glacier transformation (3% of glacierized area), concentrated in cold, high elevation, moderate precipitation areas.

Melting and calving of glaciers and ice caps in Antarctica and Greenland could potentially contribute significantly to global sea level rise. Updates to existing outlines that provide critical glacier baseline information in both regions could help in the analysis of particular changes in glacier parameters such as area and volume from time-series inventories. Here we synthesize previously established techniques and apply new multi-source datasets to update glacier outlines in selected test areas of Antarctica and Greenland, as well as to reduce uncertainties and errors during the mapping process. The workflow includes mapping glacier boundaries, subdividing glaciers by watersheds and assigning glacier attributes. Complicated glacier scenarios and updating challenges in polar regions are discussed and demonstrated by representative case studies. For the first time in Antarctica, we analyze the effect of terminus types on mapped glacier areas, and in Greenland we compare the differences with glacier mapping results using Landsat OLI and ETM+. With new data sources, the methods described in this study might help to create glacier outlines on a larger scale in Antarctica and Greenland. Although data sources can be substituted, the enormous amount of manual labor required to update glacier inventories remains a significant challenge.

We developed a multi-frequency, multi-Global Navigation Satellite System (GNSS) positioning instrument optimized for autonomous applications in the cryosphere. At lower power requirements and a fraction of the cost and weight compared to commercially available options, this instrument simplifies field usage and associated logistics. In this paper, we assess several baseline aspects of performance in a polar environment relative to geodetic receivers commonly used for glaciological applications. Evaluations of precision and relative accuracy of positioning show millimeter to centimeter-level (‘geodetic-grade’) quality of this instrument, making it a competitive alternative for GNSS glaciological and geophysical applications such as monitoring surface elevation change and ice flow. An array of these instruments, tested in the field on the Greenland Ice Sheet, also demonstrated robustness throughout the polar winter and met power and reliability requirements.

Innovations in geodesy enable widespread analysis of glacier surface elevation change and geodetic mass balance. However, coincident glacier area data are less widely available, causing inconsistent handling of glacier area change. Here we quantify the bias introduced into meters water equivalent (m w.e.) specific geodetic mass balance results when using a fixed, maximum glacier area, and illustrate the bias for five North American glaciers. Sites span latitudes from the northern U.S. Rocky Mountains (48°N) to the Central Alaska Range (63°N) between 1948 and 2021. Results show that fixed (maximum) area treatment subdues the m w.e. mass change signal, underestimating mass balance by up to 19% in our test cases. This bias scales with relative glacier area change and the mass balance magnitude. Thus, the bias for specific geodetic mass balances will be most pronounced across rapidly deglaciating regions. Our analysis underscores the need for temporally resolved glacier area in geodetic mass balance studies.

The Jostedalsbreen ice cap is mainland Europe's largest ice cap and accommodates 20% (458 km2 in 2019) of the total glacier area of mainland Norway. Jostedalsbreen and its meltwater contribute to global sea-level rise and to local water management, hydropower and tourism economies and livelihoods. In this study, we construct a digital terrain model (DTM) of the ice cap from 1966 aerial photographs, which by comparing to an airborne LiDAR DTM from 2020, we compute changes in surface elevation and geodetic mass balances. The area mapped in both surveys cover about 3/4 of the ice cap area and 49 of 82 glaciers. The measured glacier area has decreased from 363.4 km2 in 1966 to 332.9 km2 in 2019, i.e. a change of −30 km2 or −8.4% (−0.16% a−1), which is in line with the percentage reduction in area for Jostedalsbreen as a whole. The mean geodetic mass balance over the 49 glaciers was −0.15 ± 0.01 m w.e. a−1, however, large variability is evident between glaciers, e.g. Nigardsbreen (−0.05 m w.e. a−1), Austdalsbreen (−0.28 m w.e. a−1) and Tunsbergdalsbreen (−0.36 m w.e. a−1) confirming differences also found by the glaciological records for Nigardsbreen and Austdalsbreen.

Semantic segmentation is a critical part of observation-driven research in glaciology. Using remote sensing to quantify how features change (e.g. glacier termini, supraglacial lakes, icebergs, crevasses) is particularly important in polar regions, where glaciological features may be spatially small but reflect important shifts in boundary conditions. In this study, we assess the utility of the Segment Anything Model (SAM), released by Meta AI Research, for cryosphere research. SAM is a foundational AI model that generates segmentation masks without additional training data. This is highly beneficial in polar science because pre-existing training data rarely exist. Widely-used conventional deep learning models such as UNet require tens of thousands of training labels to perform effectively. We show that the Segment Anything Model performs well for different features (icebergs, glacier termini, supra-glacial lakes, crevasses), in different environmental settings (open water, mélange, and sea ice), with different sensors (Sentinel-1, Sentinel-2, Planet, timelapse photographs) and different spatial resolutions. Due to the performance, versatility, and cross-platform adaptability of SAM, we conclude that it is a powerful and robust model for cryosphere research.

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.

Over half of the recent mass loss from the Greenland ice sheet, and its associated contribution to global sea level rise, can be attributed to increased surface meltwater runoff, with the remainder a result of dynamical processes such as calving and ice discharge. It is therefore important to quantify the distribution of melting on the ice sheet if we are to adequately understand past ice sheet change and make predictions for the future. In this article, we present a novel semi-empirical approach for characterising ice sheet surface conditions using high-resolution synthetic aperture radar (SAR) backscatter data from the Sentinel-1 satellite. We apply a state-space model to nine sites within North-East Greenland to identify changes in SAR backscatter, and we attribute these to different surface types with reference to optical satellite imagery and meteorological data. A set of decision-making rules for labelling ice sheet melting states are determined based on this analysis and subsequently applied to previously unseen sites. We show that our method performs well in (1) recognising some of the ice sheet surface types such as snow and dark ice and (2) determining whether the surface is melting or not melting. Sentinel-1 SAR data are of high spatial resolution; thus, in developing a method to identify the state of the surface from these data, we improve our capability to understand the variation of ice sheet melting across time and space.

Glaciers in the Russian High Arctic have undergone accelerated mass loss due to atmospheric and oceanic warming in the Barents–Kara Sea region. Most studies have concentrated on the western Barents–Kara sector, despite evidence of accelerating mass loss as far east as Severnaya Zemlya. However, long-term trends in glacier change on Severnaya Zemlya are largely unknown and this record may be complicated by surge-type glaciers. Here, we present a long-term assessment of glacier change (1965–2021) on Severnaya Zemlya and a new inventory of surge-type glaciers using declassified spy-satellite photography (KH-7/9 Hexagon) and optical satellite imagery (ASTER, Sentinel-2A, Landsat-4/5 TM and 8 OLI). Glacier area reduced from 17 053 km2 in 1965 to 16 275 in 2021 (−5%; mean: −18%, max: −100%), with areal shrinkage most pronounced at land-terminating glaciers on southern Severnaya Zemlya, where there is a recent (post-2010s) increase in summer atmospheric temperatures. We find that surging may be more widespread than previously thought, with three glaciers classified confirmed as surge-type, eight as likely to have surged and nine as possible, comprising 11% of Severnaya Zemlya's 190 glaciers (37% by area). Under continued warming, we anticipate accelerated retreat and increased likelihood of surging as basal thermal regimes shift.

Close-range sensors are employed to observe glaciological processes that operate over short timescales (e.g. iceberg calving, glacial lake outburst floods, diurnal surface melting). However, under poor weather conditions optical instruments fail while the operation of radar systems below 17 GHz do not have sufficient angular resolution to map glacier surfaces in detail. This letter reviews the potential of millimetre-wave radar at 94 GHz to obtain high-resolution 3-D measurements of glaciers under most weather conditions. We discuss the theory of 94 GHz radar for glaciology studies, demonstrate its potential to map a glacier calving front and summarise future research priorities.

Climate change has had a significant impact on glacier recession, particularly in the Arctic, where glacier meltwater is an important contributor to global sea-level rise. Therefore, it is important to accurately quantify glacier recession within this sensitive region, using multiple observations of glacier extent. In this study, we mapped 480 glaciers in Novaya Zemlya, Russian Arctic, using object-based image analysis applied to multispectral Landsat satellite imagery in Google Earth Engine and quantify the area changes between 1986–89 and 2019–21. The results show that in 1986–89, the total glacierized area was 22 990 ± 301 km2, in 2000–01 the area was 22 525 ± 308 km2 and by 2019–21 the glacier area reduced to 21 670 ± 292 km2, representing a total of 5.8% reduction in glacier area between 1986–89 and 2019–21. Higher glacier area loss was observed on the Barents Sea coast (7.3%) compared to the Kara (4.2%), reflecting previously observed differences in warming trends. The accuracy of the automatically generated outlines of each layer (1986–89, 2000–01 and 2019–21) was evaluated by comparing with manually corrected outlines (reference data) using random sampling, resulting in an overall accuracy estimate of between 96 and 97% compared to the reference data. This automated approach in Google Earth Engine is a promising tool for rapidly mapping glacier change that reduces the amount of time required to generate accurate glacier outlines.

A recent study (Millan and others, 2022a, Nature Geoscience 15(2), 124–129) claims that ice volume contained in all glaciers outside the ice sheets and its potential contribution to sea level is 20% less than previously estimated. However, the apparent decrease is largely due to differences in choice of domain, as the study excludes 80% of the glacier area in the Antarctic periphery that was included in previous global glacier volume estimates. The issue highlights the difficulty in separating glaciers from the ice-sheet proper, especially in Antarctica, and the need for both the glacier and ice-sheet communities to develop standards and protocols to avoid double-counting in global ice volume and mass-change assessments and projections. Process-based inversion models have replaced earlier scaling methods, but large uncertainties in global glacier volume estimation remain due to the ill-posed nature of the inversion problem and poorly constrained parameters emphasizing the need for more direct ice thickness observations.

Links between proglacial lakes and glacier dynamics are poorly understood but are necessary to predict how mountain glaciers will react to a warmer, wetter climate, where such lakes are expected to increase both in number and volume. Here, we examine a long-term (~120 year) record of terminus retreat, thinning and surface velocities from in-situ and remote sensing observations at the terminus of Kaskawulsh Glacier, Yukon, Canada, and determine the impact of a local proglacial hydrological reorganisation on glacier dynamics. After an initial deceleration during the late 1990s, terminus velocities increased at a rate of 3 m a−2 from 2000–12, while proglacial Slims Lake area increased simultaneously. The rapid drainage of the lake in May 2016 substantially altered the velocity profile, decreasing annual velocities by 48% within 3 km of the terminus between 2015 and 2021, at an average rate of ~ 12.5 m a−2. A key cause of the rapid drop in glacier motion was a reduction in flotation of the lower part of the glacier terminus after lake drainage. This has important implications for glacier dynamics and provides one of the first assessments of the impacts of a rapid proglacial lake drainage event on local terminus velocities.

Supraglacial drainage networks play an integral role in both glacier dynamics and run-off timing, and mapping them provides insight into their role in glacial systems. Here we present a reproducible approach for semi-automated mapping of supraglacial hydrologic features, which complements existing work in automated and manual mapping by providing clear definitions for identification of features. This framework uses a digital terrain model (DTM) to identify potential flow routes on the glacier surface, which are then classified using a set of standardized rules based on the DTM and an orthomosaic. We found that the normalized difference water index calculated from digital imagery was influenced by image brightness and introduce a new approach using average RGB values to correct for this. Using this framework we mapped supraglacial drainage networks at Nàłùdäy and Thores Glacier, Canada. The framework was easier to implement with high-resolution (0.5 m) imagery and DTMs, compared to data with lower resolution (10 m), due to the increased detail in topography and feature boundaries at high-resolution. Lower-resolution data captured larger streams (>2 pixels wide), however, indicating that the framework can still be used at this resolution. Mapping supraglacial hydrology using standardized methods opens possibilities for investigating many questions relating to changes in supraglacial hydrology over time.

Glacier change in Kenai Fjords National Park in southcentral Alaska affects local terrestrial, fresh water and marine ecosystems and will likely impact ecotourism. We used Landsat 4–8 imagery from 1984 through 2021 to manually map lower glacier ice margins for 19 maritime glaciers in Kenai Fjords National Park. Of these glaciers, six are tidewater, three are lake-terminating, six are land-terminating and four terminated in more than one environment throughout the study period. We used the mapped ice margins to quantify seasonal terminus position and areal change, including distinguishing between ice loss at glacier termini and along glacier margins. Overall, 13 glaciers substantially retreated (more than 2σ), 14 lost substantial area and only two underwent both net advance and area gain. The glaciers that had insubstantial length and area changes were predominantly tidewater. Cumulatively, the lower reaches of these 19 glaciers lost 42 km2 of ice, which was nearly evenly distributed between the terminus and the lateral margins. The rapid rate of glacier change and subsequent land cover changes are highly visible to visitors and locals at Kenai Fjords National Park, and this study quantifies those changes in terms of glacier length and area.

Glacier monitoring has been internationally coordinated for more than 125 years. Despite this long history, there is no authoritative answer to the popular question: ‘Which glaciers are the largest in the world?’ Here, we present the first systematic assessment of this question and identify the largest glaciers in the world – distinct from the two ice sheets in Greenland and Antarctica but including the glaciers on the Antarctic Peninsula. We identify the largest glaciers in two domains: on each of the seven geographical continents and in the 19 first-order glacier regions defined by the Global Terrestrial Network for Glaciers. Ranking glaciers by area is non-trivial. It depends on how a glacier is defined and mapped and also requires differentiating between a glacier and a glacier complex, i.e. glaciers that meet at ice divides such as ice caps and icefields. It also depends on the availability of a homogenized global glacier inventory. Using separate rankings for glaciers and glacier complexes, we find that the largest glacier complexes have areas on the order of tens of thousands of square kilometers whereas the largest glaciers are several thousands of square kilometers. The world's largest glaciers and glacier complexes are located in the Antarctic, Arctic and Patagonia.

The overall trend of rapid retreat of Alpine glaciers contains considerable variability of responses at the scale of individual glaciers. As a step towards a regional assessment of glacier state that allows a detailed differentiation of single glaciers, we explore the potential of a self-organizing maps (SOM) algorithm to identify and cluster recurring patterns of thickness change at glaciers in western Austria. Using digital elevation models and glacier inventories for three time periods, we compute the frequency distribution of surface elevation change over the area of each glacier in the data set, for each period. The results of the SOM clustering show a distinct pattern shift over time: From 1969 to 1997, surface elevation change occurred at relatively uniform rates across a given glacier. Since 1997, the distribution of surface elevation change at individual glaciers has been far less uniform, indicating accelerated processes of disintegration. Tracking the evolution of individual glaciers throughout the time periods via the clusters highlights both the broader regional trend as well as glaciers that deviate from this trend, e.g. some very small, high elevation glaciers that have reverted to reduced and more uniform volume loss patterns.

Gridded glacier datasets are essential for various glaciological and climatological research because they link glacier cover with the corresponding gridded meteorological variables. However, there are significant differences between the gridded data and the shapefile data in the total area calculations in the Randolph Glacier Inventory (RGI) 6.0 at global and regional scales. Here, we present a new global gridded glacier dataset based on the RGI 6.0 that eliminates the differences. The dataset is made by dividing the glacier polygons using cell boundaries and then recalculating the area of each polygon in the cell. Our dataset (1) exhibits a good agreement with the RGI area values for those regions in which gridded areas showed a generally good consistency with those in the shapefile data, and (2) reduces the errors existing in the current RGI gridded dataset. All data and code used in this study are freely available and we provide two examples to demonstrate the application of this new gridded dataset.

In this study, we use aerial photographs, satellite imagery and field observations to quantify changes in the area, terminus length, snowline elevation and surface elevation of eight glaciers in the Alexandra Fiord region, eastern Ellesmere Island, between 1959 and 2019. Comparisons to written and pictorial descriptions from the British Arctic Expedition extend the record of change in terminus position and surface elevation to 1875 for Twin Glacier. Glacier area at Alexandra Fiord decreased by a total of 15.77 ± 0.65 km2 (11.77 ± 0.49%) between 1959 and 2019, the mean end of summer snowline increased in elevation by 360 ± 84 m (8 ± 2 m a−1) between 1974 and 2019, and the glaciers thinned at an average rate of 0.60 ± 0.06 m a−1 between 2001 and 2018. Annual rates of terminus retreat were ~3–5 times higher over the period 1974–2019 compared to 1875–1974, and rates of thinning were ~2–3 times higher over 2001–18 compared to 1875–2001. Our results are consistent with rates of change determined for other glaciers of similar size on Ellesmere Island, and with accelerated rates of ice loss coincident with regional increases in air temperature of ~1.5°C since the early 1980s.

Glaciers in the Tien Shan mountains contribute considerably to the fresh water used for irrigation, households and energy supply in the dry lowland areas of Kyrgyzstan and its neighbouring countries. To date, reconstructions of the current ice volume and ice thickness distribution remain scarce, and accurate data are largely lacking at the local scale. Here, we present a detailed ice thickness distribution of Ashu-Tor, Bordu, Golubin and Kara-Batkak glaciers derived from radio-echo sounding measurements and modelling. All the ice thickness measurements are used to calibrate three individual models to estimate the ice thickness in inaccessible areas. A cross-validation between modelled and measured ice thickness for a subset of the data is performed to attribute a weight to every model and to assemble a final composite ice thickness distribution for every glacier. Results reveal the thickest ice on Ashu-Tor glacier with values up to 201 ± 12 m. The ice thickness measurements and distributions are also compared with estimates composed without the use of in situ data. These estimates approach the total ice volume well, but local ice thicknesses vary substantially.