Knowledge of ice-sheet catchments is critical for mass-balance assessments, especially glacier-scale input–output budgets. This study explores variations in the catchment of Sermeq Kujalleq, or Jakobshavn Isbrø, Greenland. Six observation-based catchment delineations are evaluated along with a 16-member catchment ensemble calculated from ice-sheet models within the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). The ‘present-day’ ISMIP6 ensemble mean area was found to be $\sim 6.3\%$ larger than the mean of the observed catchments. Ensemble spreads were comparable in size, $\pm 12.3\%$ and $\pm 15.4\%$, suggesting models are able to delineate the present-day catchment with the same degree of uncertainty as observational methods. The mean catchment area of a 13-member ISMIP6 ensemble shows temporal variation, increasing $\sim [ 2.7,\; \, 5.7,\; \, 9.1] \%$ under three ocean forcing scenarios and a RCP8.5 projection based on one GCM from 2015 to 2100, primarily as the southern catchment boundary migrates southward. This is interpreted as Sermeq Kujalleq exhibiting dynamic piracy, re-directing ice away from adjacent land terminating glaciers. For mass-balance assessments, present-day catchment delineation is more important than capturing the temporal evolution of individual catchments. However, the modeled temporal changes in catchment area are potentially underestimated, as the models exhibit insufficient acceleration of inland ice flow.

Extending the record of glacier area changes into the past improves our understanding of climate change impacts. Although analogue maps showing historic glacier extents are abundant, digital outlines from before the satellite era are sparse as the digitisation of moraines and trimlines on freely available satellite images is challenging. With the now available very high-resolution images provided by Web Map Services (WMS), new doors are open for the precise digitisation. Here, we used the ESRI WMS to digitise Little Ice Age (LIA) glacier extents and present area changes since the LIA in four selected regions along with a detailed uncertainty analysis. We used modern glacier outlines as a starting point and additionally consulted Sentinel-2 images, the ArcticDEM and historic maps for interpretation. Dating records from the literature allowed calculating area change rates. In total, 493 LIA glaciers (4640 km2, now 891 ice bodies with 3590 km2) were digitised, yielding relative area changes of −20% (−0.14% a−1), −15% (−0.10% a−1), −26% (−0.16% a−1) and −61% (−0.19% a−1) for Alaska, Baffin Island, Novaya Zemlya and the tropics, respectively. The ESRI WMS images are a great asset to precisely map moraines and trimlines, but information about the timing of the related extents requires further sources.

Due to adverse snow and cloud conditions, only a few inventories are available for the maritime glaciers in New Zealand. These are difficult to compare as different approaches and baseline data have been used to create them. In consequence, glacier fluctuations in New Zealand over the past two decades are only known for a few glaciers based on field observations. Here we present the results of a new inventory for the ‘year 2000’ (some scenes are from 2001 and 2002) that is based on glacier outlines from a recently published inventory for the year 2016 and allowed consistent change assessment for nearly 3000 glaciers over this period. The year 2000 inventory was created by manual on-screen digitizing using Landsat ETM+ satellite imagery (15 m panchromatic band) in the background and the year 2016 outlines as a starting point. Major challenges faced were late and early seasonal snow, clouds and shadow, the geo-location mismatch between Landsat and Sentinel-2 as well as the correct interpretation of ice patches and ice under debris cover. In total, we re-mapped 2967 glaciers covering an area of 885.5 km2 in 2000, which is 91.7 km2 (or 10.4%) more than the 793.8 km2 mapped in 2016. Area change rates (mean rate −0.65% a−1) increase towards smaller glaciers. Strongest area loss from 2000 to 2016 occurred at elevations ~1900 m but the highest relative loss was found below 800 m a.s.l. In total, 109 glaciers split into two or more entities and 264 had wasted away by 2016.

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.

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 and the periglacial environment in Argentina have been protected by the Law since 2010. This legislation required the development of the first National Glacier Inventory (NGI), which was officially presented in May 2018 and based on satellite images spanning between 2004 and 2016. Here, we present the methods and results of the NGI, summarize the glaciers’ morphological and spatial characteristics, and compare our results to previous regional and global inventories. The NGI reveals an impressive variety of ice masses including rock glaciers, permanent snowfields, mountain and valley glaciers with varying amounts of debris-cover and large outlet glaciers. The Argentinean Andes contain 16 078 ice masses covering an area of 5769 km2 between 200 and 6900 m a.s.l. Comparison of the combined national inventories of Argentina and Chile (~30 000 glaciers and 28 400 km2) with the Randolph Glacier Inventory 6.0 for the Southern Andes (~16 000 glaciers and 29 400 km2), shows that there are large differences in extent and number of glaciers in some sub-regions. The NGI represents an improvement for a better understanding of Argentina's freshwater reservoirs and provides detailed information for the preservation and study of ice masses along 4000 km of the Southern Andes.

Glacial retreat in response to warming climates in the arid Xinjiang region of northwestern China directly impacts downstream water resources available for local communities. We used high-resolution satellite imagery from 1969 to 2014 to delineate spatial changes in 54 active glaciers in the upper Kaidu River Basin in the Tian Shan as well as their past expanses during the Little Ice Age (LIA). We manually delineated their boundaries based on the interpretation of glacial, geomorphic and topographic features. From the total glacier surface area, we estimated glacier volume and mass. From 1969 to 2014, glacier area decreased by 10.1 ± 1.0 km2 (relative loss of 34.2 ± 3.5%) and mass by 1.025 ± 0.108 Gt (relative loss of 43 ± 4.6%). From the LIA maximum (est. 1586 CE) to 1969, relative losses were less (25.7 ± 4.3% area loss and 33.1 ± 5.7% mass loss). Our results indicate that glacier recession is accelerating over time and that the glaciers are currently losing over 1.5 times more relative area than elsewhere in the Tian Shan. Using linear and non-linear projections, we estimate that these glaciers may disappear between 2050 and 2150 CE if climatic warming continues at the same pace.

Climate change has led to a significant shrinkage of glaciers in the Tropical Andes during the last decades. Recent multi-temporal quantifications of ice mass loss at mountain range to regional scale are missing. However, this is fundamental information for future water resource planning and glacier change projections. In this study, we measure temporally consistent glacier area changes and geodetic mass balances throughout the Bolivian Cordillera Real and Tres Cruces based on multi-sensor remote-sensing data. By analyzing multi-spectral satellite images and interferometric SAR data, a glacier recession of 81 ± 18 km2 (29%; 5.1 ± 1.1 km2 a−1), a geodetic mass balance of −403 ± 78 kg m−2 a−1 and a total ice mass loss of 1.8 ± 0.5 Gt is derived for 2000–2016. In the period 2013–2016, ice mass loss was 21% above the average rate. A retreat rate of 15 ± 5 km2 a−1 and a mass budget of −487 ± 349 kg m−2 a−1 are found in this more recent period. These higher change rates can be attributed to the strong El Niño event in 2015/16. The analyses of individual glacier changes and topographic variables confirmed the dependency of the mass budget and glacier recession on glacier aspect and median elevation.

To obtain information on changes in glacier mass balance in the central Nyainqentanglha Range, a comprehensive study was carried out based on digital-elevation models derived from the 1968 topographic maps, the Shuttle Radar Topography Mission DEM (2000) and TerraSAR-X/TanDEM-X (2013). Glacier area changes between 1968 and 2016 were derived from topographic maps and Landsat OLI images. This showed the area contained 715 glaciers, with an area of 1713.42 ± 51.82 km2, in 2016. Ice cover has been shrinking by 0.68 ± 0.05% a−1 since 1968. The glacier area covered by debris accounted for 11.9% of the total and decreased in the SE–NW directions. Using digital elevation model differencing and differential synthetic aperture radar interferometry, a significant mass loss of 0.46 ± 0.10 m w.e. a−1 has been recorded since 1968; mass losses accelerated from 0.42 ± 0.20 m w.e. a−1 to 0.60 ± 0.20 m w.e. a−1 between 1968–2000 and 2000–2013, with thinning noticeably greater on the debris-covered ice than the clean ice. Surface-elevation changes can be influenced by ice cliffs, as well as debris cover and land- or lake-terminating glaciers. Changes showed spatial and temporal heterogeneity and a substantial correlation with climate warming and decreased precipitation.

Over recent decades, the number of outlet glaciers terminating in lakes in Iceland has increased in line with climate warming. The mass-balance changes of these lake-terminating outlet glaciers are sensitive to rising air temperatures, due to altered glacier dynamics and increased surface melt. This study aims to better understand the relationship between proglacial lake development, climate, glacier dynamics and glacier structure at Fjallsjökull, a large, lake-terminating outlet glacier in south-east Iceland. We used satellite imagery to map glacier terminus position and lake extent between 1973 and 2016, and a combination of aerial and satellite imagery to map the structural architecture of the glacier's terminus in 1982, 1994 and 2011. The temporal evolution of ice surface velocities between 1990 and 2018 was calculated using feature tracking. Statistically significant increases in the rate of terminus retreat and lake expansion were identified in 2001, 2009 and 2011. Our surface velocity and structural datasets revealed the development of localised flow ‘corridors’ over time, which conveyed relatively faster flow towards the glacier's terminus. We attribute the overall changes in dynamics and structural architecture at Fjallsjökull to rising air temperatures, but argue that the spatial complexities are driven by glacier specific factors, such as basal topography.

Despite their importance for mass-balance estimates and the progress in techniques based on optical and thermal satellite imagery, the mapping of debris-covered glacier boundaries remains a challenging task. Manual corrections hamper regular updates. In this study, we present an automatic approach to delineate glacier outlines using interferometrically derived synthetic aperture radar (InSAR) coherence, slope and morphological operations. InSAR coherence detects the temporally decorrelated surface (e.g. glacial extent) irrespective of its surface type and separates it from the highly coherent surrounding areas. We tested the impact of different processing settings, for example resolution, coherence window size and topographic phase removal, on the quality of the generated outlines. We found minor influence of the topographic phase, but a combination of strong multi-looking during interferogram generation and additional averaging during coherence estimation strongly deteriorated the coherence at the glacier edges. We analysed the performance of X-, C- and L- band radar data. The C-band Sentinel-1 data outlined the glacier boundary with the least misclassifications and a type II error of 0.47% compared with Global Land Ice Measurements from Space inventory data. Our study shows the potential of the Sentinel-1 mission together with our automatic processing chain to provide regular updates for land-terminating glaciers on a large scale.

The first satellite-derived inventory of glaciers and rock glaciers in Chile, created from Landsat TM/ETM+ images spanning between 2000 and 2003 using a semi-automated procedure, is presented in a single standardized format. Large glacierized areas in the Altiplano, Palena Province and the periphery of the Patagonian icefields are inventoried. The Chilean glacierized area is 23 708 ± 1185 km2, including ~3200 km2 of both debris-covered glaciers and rock glaciers. Glacier distribution varies as a result of climatic gradients with latitude and elevation, with 0.8% occurring in the Desert Andes (17°30′–32° S); 3.6% in the Central Andes (32–36° S), 6.2% in the Lakes District and Palena Province (36–46° S), and 89.3% in Patagonia and Tierra del Fuego (46–56° S). Glacier outlines, across all glacierized regions and size classes, updated to 2015 using Landsat 8 images for 98 complexes indicate a decline in areal extent affecting mostly clean-ice glaciers (−92.3 ± 4.6 km2), whereas debris-covered glaciers and rock glaciers in the Desert and Central Andes appear nearly unchanged in their extent. Glacier attributes estimated from this new inventory provide valuable insights into spatial patterns of glacier shrinkage for assessing future glacier changes in response to climate change.

The meltwater from glaciers in Alaska contributes strongly to global sea-level rise, but accurate determination is challenging as only two comparatively small glaciers have long-term measurements of annual mass balance (Gulkana and Wolverine). Simple upscaling of their values to the entire region is error-prone as their representativeness is unknown and might be biased. Alternatively, differencing digital elevation models (DEMs) from two epochs provides overall volume changes for a longer period of time that can be converted to mass changes using appropriate density assumptions. Here we combine outlines from two glacier inventories to determine glacier-specific elevation changes over a 50 year period for 3180 glaciers in western Alaska using DEM differencing. This allows us to determine the representativeness of the land-terminating Gulkana and Wolverine Glaciers for the entire region and to exclude calving glaciers (marine and lacustrine) from the sample. Mean changes for all land-terminating, lake-terminating and tidewater glaciers are –0.23 ± 0.44, –0.63 ± 0.40 and –0.64 ± 0.66 m a–1, respectively, and –0.7 and –0.6 m a–1 for the two mass-balance or benchmark glaciers. Thus fortuitously their changes better represent calving glaciers and the overall mean (–0.63 ± 1.14 m a–1) than the change of land-terminating glaciers, i.e. they are not representative for their own type. Different methods of considering potential DEM artefacts provide variable mean changes but the same general result.

Mapping changes in glacier extent from repeat optical satellite data has revealed widespread glacier decline in nearly all regions of the world over the past few decades. While numerous studies have documented the changes of the outlet glaciers of the Northern and Southern Patagonia Icefields (NPI/SPI), information about glacier changes in the Patagonian Andes (to the north of the NPI) is much scarcer. Here we present an assessment of area changes for glaciers mainly located in the Palena district of Chile based on glacier inventories for 1985, 2000 and 2011 that were derived from two consecutive Landsat scenes and a digital elevation model. The analysis revealed a dramatic area decline for the largest glaciers and total area loss of 25% from 1985 to 2011. The lower parts of several larger glaciers (>10 km2) melted completely. Area loss below 1000 m elevation was 50–100% in both periods, and 374 glaciers out of 1664 disappeared. The number of proglacial lakes increased from 223 to 327 and their area expanded by 11.6 km2 (59%) between 1985 and 2011. Seasonal snow persisting at high elevations in the 2011 scene was a major obstacle to glacier delineation, so the obtained area change rate of ~1% a–1 over the entire period is a lower-bound estimate. The observed climate trends (e.g. cooling in Puerto Montt) are in contrast to the observed shrinkage.

The Randolph Glacier Inventory (RGI) is a globally complete collection of digital outlines of glaciers, excluding the ice sheets, developed to meet the needs of the Fifth Assessment of the Intergovernmental Panel on Climate Change for estimates of past and future mass balance. The RGI was created with limited resources in a short period. Priority was given to completeness of coverage, but a limited, uniform set of attributes is attached to each of the ~198 000 glaciers in its latest version, 3.2. Satellite imagery from 1999–2010 provided most of the outlines. Their total extent is estimated as 726 800 ± 34 000 km2. The uncertainty, about ±5%, is derived from careful single-glacier and basin-scale uncertainty estimates and comparisons with inventories that were not sources for the RGI. The main contributors to uncertainty are probably misinterpretation of seasonal snow cover and debris cover. These errors appear not to be normally distributed, and quantifying them reliably is an unsolved problem. Combined with digital elevation models, the RGI glacier outlines yield hypsometries that can be combined with atmospheric data or model outputs for analysis of the impacts of climatic change on glaciers. The RGI has already proved its value in the generation of significantly improved aggregate estimates of glacier mass changes and total volume, and thus actual and potential contributions to sea-level rise.

The second Chinese glacier inventory was compiled based on 218 Landsat TM/ETM+ scenes acquired mainly during 2006–10. The widely used band ratio segmentation method was applied as the first step in delineating glacier outlines, and then intensive manual improvements were performed. The Shuttle Radar Topography Mission digital elevation model was used to derive altitudinal attributes of glaciers. The boundaries of some glaciers measured by real-time kinematic differential GPS or digitized from high-resolution images were used as references to validate the accuracy of the methods used to delineate glaciers, which resulted in positioning errors of ±10 m for manually improved clean-ice outlines and ±30 m for manually digitized outlines of debris-covered parts. The glacier area error of the compiled inventory, evaluated using these two positioning accuracies, was ±3.2%. The compiled parts of the new inventory have a total area of 43 087 km2, in which 1723 glaciers were covered by debris, with a total debris-covered area of 1494 km2. The area of uncompiled glaciers from the digitized first Chinese glacier inventory is ∼8753 km2, mainly distributed in the southeastern Tibetan Plateau, where no images of acceptable quality for glacier outline delineation can be found during 2006–10.

Glacier change has been recognized as an important climate variable due to its sensitive response to climate change. Although there are a large number of glaciers distributed over the southeastern Qinghai–Tibetan Plateau, the region is poorly represented in glacier databases due to seasonal snow cover and frequent cloud cover. Here, we present an improved glacier inventory for this region by combining Landsat observations acquired over 2011–13 (Landsat 8/OLI and Landsat TM/ETM+), coherence images from Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar images and the Shuttle Radar Topography Mission (SRTM) DEM. We present a semi-automated scheme for integrating observations from multi-temporal Landsat scenes to mitigate cloud obscuration. Further, the clean-ice observations, together with coherence information, slope constraints, vegetation cover and water classification information extracted from the Landsat scenes, are integrated to determine the debris-covered glacier area. After manual editing, we derive a new glacier inventory containing 6892 glaciers >0.02 km2, covering a total area of 6566 ± 197 km2. This new glacier inventory indicates gross overestimation in glacier area (over 30%) in previously published glacier inventories, and reveals various spatial characteristics of glaciers in the region. Our inventory can be used as a baseline dataset for future studies including glacier change assessment.

To improve our knowledge of glacier area changes in the central Chilean and Argentinean Andes (32°9′S–33°4′S), two new glacier inventories from 1989 to 2013/14 are compared with a reinterpreted inventory from 1955. Comparisons show glacier area retreat of 30 ± 3% since 1955, decreasing from 134 to 94 km2 in 2013/14, whilst the annual rate of area loss showed a small increase (insignificant) between the periods of 1955–1989 and 1989–2013/14. Separate analysis of the 1989 and 2013/14 inventories, including a larger sample, revealed a higher rate of glacier change compared with the smaller samples of these inventories. Additionally, an analysis at ~5 year intervals for six major glaciers (1955–2013) indicates large variability in response times and area loss magnitudes. Glacier Olivares Alfa, for example, lost 63% of its ice area, while the Juncal Norte Glacier lost only 10% (1955–2013). The findings from this study improve our current knowledge base concerning widespread glacier decline in the southern Andes, and furthers monitoring efforts in this poorly described region of the world, a region containing vital water resources for populated areas in South America.

To better understand the recent wide-scale changes in glacier coverage, we created and compared two glacier inventories covering eastern Nepal, based on aerial photographs (1992) and high-resolution Advanced Land Observing Satellite (ALOS) imagery (2006–10). The ALOS-derived inventory contained 1034 debris-free and 256 debris-covered glaciers with total and average areas of 440.2 ± 33.3 and 0.42 km2 and 1074.4 ± 206.4 and 4.19 km2, respectively. We found that the debris-free glaciers have lost 11.2% (0.7 ± 0.1% a−1) of their area since 1992, whereas the number of glaciers increased by 5% because of fragmentation. The area change was significantly correlated by simple linear regression with minimum elevation (r = 0.30), maximum elevation (r = −0.18), altitudinal range (r = −0.50), glacier area (r = −0.62) and mean slope (r = 0.16), confirming that larger glaciers tended to lose a larger area (but a smaller percentage) than smaller glaciers. The intra-regional analysis of the glacier changes clearly showed higher shrinkage rates in the western massifs compared with the eastern massifs. In addition, 61 small glaciers covering an area of 2.4 km2 have completely disappeared since 1992.