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Observations of glacier mass changes are key to understanding the response of glaciers to climate change and related impacts, such as regional runoff, ecosystem changes, and global sea level rise. Spaceborne optical and radar sensors make it possible to quantify glacier elevation changes, and thus multi-annual mass changes, on a regional and global scale. However, estimates from a growing number of studies show a wide range of results with differences often beyond uncertainty bounds. Here, we present the outcome of a community-based inter-comparison experiment using spaceborne optical stereo (ASTER) and synthetic aperture radar interferometry (TanDEM-X) data to estimate elevation changes for defined glaciers and target periods that pose different assessment challenges. Using provided or self-processed digital elevation models (DEMs) for five test sites, 12 research groups provided a total of 97 spaceborne elevation-change datasets using various processing approaches. Validation with airborne data showed that using an ensemble estimate is promising to reduce random errors from different instruments and processing methods but still requires a more comprehensive investigation and correction of systematic errors. We found that scene selection, DEM processing, and co-registration have the biggest impact on the results. Other processing steps, such as treating spatial data voids, differences in survey periods, or radar penetration, can still be important for individual cases. Future research should focus on testing different implementations of individual processing steps (e.g. co-registration) and addressing issues related to temporal corrections, radar penetration, glacier area changes, and density conversion. Finally, there is a clear need for our community to develop best practices, use open, reproducible software, and assess overall uncertainty to enhance inter-comparison and empower physical process insights across glacier elevation-change studies.

Glacier mass balance reconstructions provide a means of placing relatively short observational records into a longer-term context. Here, we use multiple proxies from Pinus cembra trees from God da Tamangur, combining tree ring anatomy and stable isotope chronologies to reconstruct seasonal glacier mass balance (i.e., winter, summer, and annual mass balance) for the nearby Silvretta Glacier over the last 2 centuries. The combination of tree ring width, radial diameter of earlywood cell lumina, and latewood radial cell wall thickness provides a highly significant reconstruction for summer mass balance, whereas for the winter mass balance, the correlation was less significant but still robust when radial cell lumina were combined with δ18O records. A combination of the reconstructed winter and summer mass balances allows the quantification of the annual mass balance of the Silvretta Glacier for which in situ measurements date back to 1919. Our reconstruction indicates a substantial increase in glacier mass during the first half of the 19th century and an abrupt termination of this phase after the end of the Little Ice Age. Since the 1860s, negative glacier mass balances have been dominant and mass losses accelerate as anthropogenic warming picks up in the Alps.

In order to assess future glacier evolution and meltwater runoff, accurate knowledge on the volume and the ice thickness distribution of glaciers is crucial. However, in situ observations of glacier thickness are sparse in many regions worldwide due to the difficulty of undertaking field surveys. This lack of in situ measurements can be partially overcome by remote-sensing information. Multi-temporal and contemporaneous data on glacier extent and surface elevation provide past information on ice thickness for retreating glaciers in the newly deglacierized regions. However, these observations are concentrated near the glacier snouts, which is disadvantageous because it is known to introduce biases in ice thickness reconstruction approaches. Here, we show a strategy to overcome this generic limitation of so-called retreat thickness observations by applying an empirical relationship between the ice viscosity at locations with in situ observations and observations from digital elevation model (DEM) differencing at the glacier margins. Various datasets from the European Alps are combined to model the ice thickness distribution of Alpine glaciers for two time steps (1970 and 2003) based on the observed thickness in regions uncovered from ice during the study period. Our results show that the average ice thickness would be substantially underestimated (∼ 40 %) when relying solely on thickness observations from previously glacierized areas. Thus, a transferable topography-based viscosity scaling is developed to correct the modelled ice thickness distribution. It is shown that the presented approach is able to reproduce region-wide glacier volumes, although larger uncertainties remain at a local scale, and thus might represent a powerful tool for application in regions with sparse observations.

Accelerating glacier melt rates were observed during the last decades. Substantial ice loss occurs particularly during heat waves that are expected to intensify in the future. Because measuring and modelling glacier mass balance on a daily scale remains challenging, short-term mass balance variations, including extreme melt events, are poorly captured. Here, we present a novel approach based on computer-vision techniques for automatically determining daily mass balance variations at the local scale. The approach is based on the automated recognition of colour-taped ablation stakes from camera images and is tested and validated at six stations installed on three Alpine glaciers during the summers of 2019–2022. Our approach produces daily mass balance with an uncertainty of ±0.81 cm w.e. d−1, which is about half of the accuracy obtained from visual readouts. The automatically retrieved daily mass balances at the six sites were compared to average daily mass balances over the last decade derived from seasonal in situ observations to detect and assess extreme melt events. This allows analysing the impact that the summer heat waves which occurred in 2022 had on glacier melt. Our results indicate 23 d with extreme melt, showing a strong correspondence between the heat wave periods and extreme melt events. The combination of below-average winter snowfall and a suite of summer heat waves led to unprecedented glacier mass loss. The Switzerland-wide glacier storage change during the 25 d of heat waves in 2022 is estimated as 1.27 ± 0.10 km3 of water, corresponding to 35 % of the overall glacier mass loss during that summer. The same 25 d of heat waves caused a glacier mass loss that corresponds to 56 % of the average mass loss experienced over the entire melt season during the summers 2010–2020, demonstrating the relevance of heat waves for seasonal melt.

More than 13% of the area of the Caucasus glaciers is covered by debris affecting glacier mass balance. Using the Caucasus as example, we introduce a new model configuration that incorporates a physically-based subroutine for the evolution of supraglacial debris into the Global Glacier Evolution Model (GloGEMflow), enabling its application at a regional level. Temporal evolution of debris cover is coupled to glacier dynamics allowing the thickest debris to accumulate in the areas with low velocity. The future evolution of glaciers in the Northern Caucasus is assessed for five Shared Socioeconomic Pathways (SSP) and significance of explicitly incorporating debris-cover formulation in regional glacier modeling is evaluated. Under the more aggressive scenarios, glaciers are projected to disappear almost entirely except on Mount Elbrus, which reaches 5,642 m above sea level, by 2,100. Under the SSP1-1.9 scenario, glacier ice volume stabilizes by 2040. This finding stresses the importance of meeting the Paris Climate Agreement goals and limiting climatic warming to 1.5 °C. We compare evolution of glaciers in the Kuban (more humid western Caucasus) and Terek (drier central and eastern Caucasus) basins. In the Kuban basin, ice loss is projected to proceed at nearly double the rate of that in the Terek basin during the first half of the 21st century. While explicit inclusion of debris cover in modeling leads to a less pronounced projected ice loss, the maximum differences in glacier length, area, and volume occur before 2,100, especially for large valley glaciers diminishing towards the end of the century. These projections show that on average, fraction of debris-covered ice will increase while debris cover will become thinner towards the end of the 21st particularly under the more aggressive scenarios. Overall, the explicit consideration of debris cover has a minor effect on the projected regional glacier mass loss but it improves the representation of changes in glacier geometry locally.

Spatio-temporal reconstruction of winter glacier mass balance is important for assessing long-term impacts of climate change. However, high-altitude regions significantly lack reliable observations, which is limiting the calibration of glaciological and hydrological models. Reanalysis products provide estimates of snow precipitation also for remote high-mountain regions, but this data come with inherent uncertainty, and assessing their biases is difficult given the low quantity and quality of available (long-term) in situ observations. In this study, we aim at improving knowledge on the spatio-temporal variations in winter glacier mass balance by exploring the combination of data from reanalyses and direct snow accumulation observations on glaciers using machine learning. We use the winter mass balance data of 95 glaciers distributed over the European Alps, western Canada, Central Asia and Scandinavia and compare them with the total precipitation from the ERA5 and the MERRA-2 reanalysis products during the snow accumulation seasons from 1981 until 2019. We develop and apply a machine learning model to adjust the precipitation from the reanalysis products along the elevation profile of the glaciers and consequently to reconstruct the winter mass balance in both space (for glaciers without observational data) and time (filling observational data gaps). The employed machine learning model is a gradient boosting regressor (GBR), which combines several meteorological variables from the reanalyses (e.g. air temperature, relative humidity) with topographical parameters. These GBR-derived estimates are evaluated against the winter mass balance data using (i) independent glaciers (site-independent GBR) and (ii) independent accumulation seasons (season-independent GBR). Both approaches resulted in reduced biases and increased correlation between the precipitation of the original reanalyses and the winter mass balance data of the glaciers. Generally, the GBR models have also shown a good representation of the spatial (vertical elevation intervals) and temporal (years) variability of the winter mass balance on individual glaciers.

Global hydrological models have become a valuable tool for a range of global impact studies related to water resources. However, glacier parameterization is often simplistic or non-existent in global hydrological models. By contrast, global glacier models do represent complex glacier dynamics and glacier evolution, and as such, they hold the promise of better resolving glacier runoff estimates. In this study, we test the hypothesis that coupling a global glacier model with a global hydrological model leads to a more realistic glacier representation and, consequently, to improved runoff predictions in the global hydrological model. To this end, the Global Glacier Evolution Model (GloGEM) is coupled with the PCRaster GLOBal Water Balance model, version 2.0 (PCR-GLOBWB 2), using the eWaterCycle platform. For the period 2001–2012, the coupled model is evaluated against the uncoupled PCR-GLOBWB 2 in 25 large-scale (>50 000 km2), glacierized basins. The coupled model produces higher runoff estimates across all basins and throughout the melt season. In summer, the runoff differences range from 0.07 % for weakly glacier-influenced basins to 252 % for strongly glacier-influenced basins. The difference can primarily be explained by PCR-GLOBWB 2 not accounting for glacier flow and glacier mass loss, thereby causing an underestimation of glacier runoff. The coupled model performs better in reproducing basin runoff observations mostly in strongly glacier-influenced basins, which is where the coupling has the most impact. This study underlines the importance of glacier representation in global hydrological models and demonstrates the potential of coupling a global hydrological model with a global glacier model for better glacier representation and runoff predictions in glacierized basins.

The monitoring of glaciers in Switzerland has a long tradition, yet glacier changes during the 20th century are only known through sparse observations. Here, we estimate a halving of Swiss glacier volumes between 1931 and 2016 by mapping historical glacier elevation changes at high resolution. Our analysis relies on a terrestrial image archive known as TerrA, which covers about 86 % of the Swiss glacierised area with 21 703 images acquired during the period 1916–1947 (with a median date of 1931). We developed a semi-automated workflow to generate digital elevation models (DEMs) from these images, resulting in a 45 % total glacier coverage. Using the geodetic method, we estimate a Swiss-wide glacier mass balance of −0.52 ± 0.09 m w.e. a−1 between 1931 and 2016. This equates to a 51.5 ± 8.0 % loss in glacier volume. We find that low-elevation, high-debris-cover, and gently sloping glacier termini are conducive to particularly high mass losses. In addition to these glacier-specific, quasi-centennial elevation changes, we present a new inventory of glacier outlines with known timestamps and complete attributes from around 1931. The fragmented spatial coverage and temporal heterogeneity of the TerrA archive are the largest sources of uncertainty in our glacier-specific estimates, reaching up to 0.50 m w.e. a−1. We suggest that the high-resolution mapping of historical surface elevations could also unlock great potential for research fields other than glaciology.

Glacier monitoring in Switzerland has resulted in some of the longest and most complete data series globally. Mass balance observations at individual locations, starting in the 19th century, are the backbone of the monitoring as they represent the raw and original glaciological data demonstrating the response of snow accumulation and snow/ice melt to changes in climate forcing. So far, however, the variety of sources of historic measurements has not been systematically processed and documented. Here, we present a new complete and extensive point glacier mass balance dataset for the Swiss Alps that provides attributes for data quality and corresponding uncertainties. Original sources were digitized or re-assessed to validate or to correct existing entries and to identify metadata. The sources of data are highly diverse and stem from almost 140 years of records, originating from handwritten field notes, unpublished project documents, various digital sources, published reports, and meta-knowledge of the observers. The project resulted in data series with metadata for 63 individual Swiss glaciers, including more than 60 000 point observations of mass balance. Data were systematically analysed and homogenized, e.g. by supplementing partly missing information based on correlations inferred from direct measurements. A system to estimate uncertainty in all individual observations was developed indicating that annual point balance is measured with a typical error of 0.07 m water equivalent (w.e.), while the average error in winter snow measurements is 0.20 m w.e. Our dataset permits further investigating the climate change impacts on Swiss glaciers. Results show an absence of long-term trends in snow accumulation over glaciers while melt rates have substantially increased over the last 3 decades. The complete dataset is available at DOI https://doi.org/10.18750/massbalance.point.2021.r2021 (GLAMOS, 2021).

Ongoing climate change and associated glacier retreat is causing rapid environmental change, including shifts in high-alpine landscapes. Glacier lakes, which can form in topographical depressions left behind by glacier retreat, are prominent features within such landscapes. Whilst model-based estimates for the number and area of future glacier lakes exist for various mountain regions across the world, the exact morphology and temporal evolution remain largely unassessed. Here, we leverage a recently released, measurement-based estimate for the subglacial topography of all glaciers in the Swiss Alps to provide an estimate about the number, size, time of emergence, and sediment infill of future glacier lakes. The topographical information is based on 2450 km of measured ice thickness profiles, whilst the temporal evolution of glaciers is obtained from a glacier evolution model forced with an ensemble of climate projections. We estimate that up to 683 potential lakes with an area >5000 m2 and a depth >5 m could emerge across the Swiss Alps if glaciers were to disappear completely, with the potential to hold a total water volume of up to 1.16 [1.05, 1.32] km3 (numbers and 95 % confidence interval). For a middle-of-the-road climate scenario, we estimate that about 10 % (0.12 [0.04, 0.18] km3) and 48 % (0.56 [0.26, 0.67] km3) of this volume could be realized by 2050 and 2100, respectively. In a first-order assessment, we also estimate that ca. 45 % of the newly emerging glacier lakes (260 out of 570) will be transient features, i.e. will disappear again before the end of the century owing to refilling with sediments released by glacial erosion and proglacial sediment transport.

Currently, about 12 %–13 % of High Mountain Asia’s glacier area is debris-covered, which alters its surface mass balance. However, in regional-scale modelling approaches, debris-covered glaciers are typically treated as clean-ice glaciers, leading to a bias when modelling their future evolution. Here, we present a new approach for modelling debris area and thickness evolution, applicable from single glaciers to the global scale. We derive a parameterization and implement it as a module into the Global Glacier Evolution Model (GloGEMflow), a combined mass-balance ice-flow model. The module is initialized with both glacier-specific observations of the debris' spatial distribution and estimates of debris thickness. These data sets account for the fact that debris can either enhance or reduce surface melt depending on thickness. Our model approach also enables representing the spatiotemporal evolution of debris extent and thickness. We calibrate and evaluate the module on a selected subset of glaciers and apply GloGEMflow using different climate scenarios to project the future evolution of all glaciers in High Mountain Asia until 2100. Explicitly accounting for debris cover has only a minor effect on the projected mass loss, which is in line with previous projections. Despite this small effect, we argue that the improved process representation is of added value when aiming at capturing intra-glacier scales, i.e. spatial mass-balance distribution. Depending on the climate scenario, the mean debris-cover fraction is expected to increase, while mean debris thickness is projected to show only minor changes, although large local thickening is expected. To isolate the influence of explicitly accounting for supraglacial debris cover, we re-compute glacier evolution without the debris-cover module. We show that glacier geometry, area, volume, and flow velocity evolve differently, especially at the level of individual glaciers. This highlights the importance of accounting for debris cover and its spatiotemporal evolution when projecting future glacier changes.

Short-term glacier variations can be important for water supplies or hydropower production, and glaciers are important indicators of climate change. This is why the interest in near-real-time mass balance nowcasting is considerable. Here, we address this interest and provide an evaluation of continuous observations of point mass balance based on online cameras transmitting images every 20 min. The cameras were installed on three Swiss glaciers during summer 2019, provided 352 near-real-time point mass balances in total, and revealed melt rates of up to 0.12 m water equivalent per day (mw.e.d-1) and of more than 5 mw.e. in 81 d. By means of a particle filter, these observations are assimilated into an ensemble of three TI (temperature index) and one simplified energy-balance mass balance models. State augmentation with model parameters is used to assign temporally varying weights to individual models. We analyze model performance over the observation period and find that the probability for a given model to be preferred by our procedure is 39 % for an enhanced TI model, 24 % for a simple TI model, 23 %, for a simplified energy balance model, and 14 % for a model employing both air temperature and potential solar irradiation. When compared to reference forecasts produced with both mean model parameters and parameters tuned on single mass balance observations, the particle filter performs about equally well on the daily scale but outperforms predictions of cumulative mass balance by 95 %–96 %. A leave-one-out cross-validation on the individual glaciers shows that the particle filter is also able to reproduce point observations at locations not used for model calibration. Indeed, the predicted mass balances is always within 9 % of the observations. A comparison with glacier-wide annual mass balances involving additional measurements distributed over the entire glacier mostly shows very good agreement, with deviations of 0.02, 0.07, and 0.24 mw.e.

The glacier-dammed Lac des Faverges, located on Glacier de la Plaine Morte (Swiss Alps), has drained annually as a glacier lake outburst flood since 2011. In 2018, the lake volume reached more than 2 × 106 m3, and the resulting flood caused damage to the infrastructure downstream. In 2019, a supraglacial channel was dug to artificially initiate a surface lake drainage, thus limiting the lake water volume and the corresponding hazard. The peak in lake discharge was successfully reduced by over 90 % compared to 2018. We conducted extensive field measurements of the lake-channel system during the 48 d drainage event of 2019 to characterize its hydraulics and thermodynamics. The derived Darcy–Weisbach friction factor, which characterizes the water flow resistance in the channel, ranges from 0.17 to 0.48. This broad range emphasizes the factor's variability and questions the choice of a constant friction factor in glacio-hydrological models. For the Nusselt number, which relates the channel-wall melt to the water temperature, we show that the classic, empirical Dittus–Boelter equation with the standard coefficients does not adequately represent our measurements, and we propose a suitable pair of coefficients to fit our observations. This hints at the need to continue research into how heat transfer at the ice–water interface is described in the context of glacial hydraulics.

Lakes in contact with glacier margins can impact glacier evolution as well as the downstream biophysical systems, flood hazard, and water resources. Recent work suggests positive feedbacks between glacier wastage and ice-marginal lake evolution, although precise physical controls are not well understood. Here, we quantify ice-marginal lake area change in understudied northwestern North America from 1984–2018 and investigate climatic, topographic, and glaciological influences on lake area change. We delineate time series of sampled lake perimeters (n=107 lakes) and find that regional lake area has increased 58 % in aggregate, with individual proglacial lakes growing by 1.28 km2 (125 %) and ice-dammed lakes shrinking by 0.04 km2 (−15 %) on average. A statistical investigation of climate reanalysis data suggests that changes in summer temperature and winter precipitation exert minimal direct influence on lake area change. Utilizing existing datasets of observed and modeled glacial characteristics, we find that large, wide glaciers with thick lake-adjacent ice are associated with the fastest rate of lake area change, particularly where they have been undergoing rapid mass loss in recent times. We observe a dichotomy in which large, low-elevation coastal proglacial lakes have changed most in absolute terms, while small, interior lakes at high elevation have changed most in relative terms. Generally, the fastest-changing lakes have not experienced the most dramatic temperature or precipitation change, nor are they associated with the highest rates of glacier mass loss. Our work suggests that, while climatic and glaciological factors must play some role in determining lake area change, the influence of a lake's specific geometry and topographic setting overrides these external controls.

With the Paris Agreement, the urgency of limiting ongoing anthropogenic climate change has been recognised. More recent discussions have focused on the difference of limiting the increase in global average temperatures below 1.0, 1.5, or 2.0 ∘C compared to preindustrial levels. Here, we assess the impacts that such different scenarios would have on both the future evolution of glaciers in the European Alps and the water resources they provide. Our results show that even half-degree differences in global temperature targets have important implications for the changes predicted until 2100, and that – for the most optimistic scenarios – glaciers might start to partially recover, owing to possibly decreasing temperatures after the end of the 21st century.

Accurate and reliable solid precipitation estimates for high mountain regions are crucial for many research applications. Yet, measuring snowfall at high elevation remains a major challenge. In consequence, observational coverage is typically sparse, and the validation of spatially distributed precipitation products is complicated. This study presents a novel approach using reliable daily snow water equivalent (SWE) estimates by a cosmic ray sensor on two Swiss glacier sites to assess the performance of various gridded precipitation products. The ground observations are available during two and four winter seasons. The performance of three readily-available precipitation data products based on different data sources (gauge-based, remotely-sensed, and re-analysed) is assessed in terms of their accuracy compared to the ground reference. Furthermore, we include a data set, which corresponds to the remotely-sensed product with a local adjustment to independent SWE measurements. We find a large bias of all precipitation products at a monthly and seasonal resolution, which also shows a seasonal trend. Moreover, the performance of the precipitation products largely depends on in situ wind direction during snowfall events. The varying performance of the three precipitation products can be partly explained with their compilation background and underlying data basis.

Although worldwide inventories of glacier area have been coordinated internationally for several decades, a similar effort for glacier ice thicknesses was only initiated in 2013. Here, we present the third version of the Glacier Thickness Database (GlaThiDa v3), which includes 3 854 279 thickness measurements distributed over roughly 3000 glaciers worldwide. Overall, 14 % of global glacier area is now within 1 km of a thickness measurement (located on the same glacier) – a significant improvement over GlaThiDa v2, which covered only 6 % of global glacier area and only 1100 glaciers. Improvements in measurement coverage increase the robustness of numerical interpolations and model extrapolations, resulting in better estimates of regional to global glacier volumes and their potential contributions to sea-level rise. In this paper, we summarize the sources and compilation of glacier thickness data and the spatial and temporal coverage of the resulting database. In addition, we detail our use of open-source metadata formats and software tools to describe the data, validate the data format and content against this metadata description, and track changes to the data following modern data management best practices. Archived versions of GlaThiDa are available from the World Glacier Monitoring Service (e.g., v3.1.0, from which this paper was generated: https://doi.org/10.5904/wgms-glathida-2020-10; GlaThiDa Consortium, 2020), while the development version is available on GitLab (https://gitlab.com/wgms/glathida, last access: 9 November 2020).

As glaciers adjust their size in response to climate variations, long-term changes in meltwater production can be expected, affecting the local availability of water resources. We investigate glacier runoff in the period 1955–2016 in the Maipo River basin (4843 km2, 33.0–34.3∘ S, 69.8–70.5∘ W), in the semiarid Andes of Chile. The basin contains more than 800 glaciers, which cover 378 km2 in total (inventoried in 2000). We model the mass balance and runoff contribution of 26 glaciers with the physically oriented and fully distributed TOPKAPI (Topographic Kinematic Approximation and Integration)-ETH glacio-hydrological model and extrapolate the results to the entire basin. TOPKAPI-ETH is run at a daily time step using several glaciological and meteorological datasets, and its results are evaluated against streamflow records, remotely sensed snow cover, and geodetic mass balances for the periods 1955–2000 and 2000–2013. Results show that in 1955–2016 glacier mass balance had a general decreasing trend as a basin average but also had differences between the main sub-catchments. Glacier volume decreased by one-fifth (from 18.6±4.5 to 14.9±2.9 km3). Runoff from the initially glacierized areas was 177±25 mm yr−1 (16±7 % of the total contributions to the basin), but it shows a decreasing sequence of maxima, which can be linked to the interplay between a decrease in precipitation since the 1980s and the reduction of ice melt. Glaciers in the Maipo River basin will continue retreating because they are not in equilibrium with the current climate. In a hypothetical constant climate scenario, glacier volume would reduce to 81±38 % of the year 2000 volume, and glacier runoff would be 78±30 % of the 1955–2016 average. This would considerably decrease the drought mitigation capacity of the basin.

Comprehensive assessments of global glacier mass changes based on a variety of observations and prevailing methodologies have been published at multi-annual intervals. For the years in between, the glaciological method provides annual observations of specific mass changes but is suspected to not be representative at the regional to global scales due to uneven glacier distribution with respect to the full sample. Here, we present a simple approach to estimate and correct for this bias in the glaciological sample and, hence, to provide an ad hoc estimate of global glacier mass changes and corresponding sea-level equivalents for the latest years, i.e. about -300±250 Gt in 2016/17 and -500±200 Gt in 2017/18.

Snow water equivalent (SWE) measurements of seasonal snowpack are crucial in many research fields. Yet accurate measurements at a high temporal resolution are difficult to obtain in high mountain regions. With a cosmic ray sensor (CRS), SWE can be inferred from neutron counts. We present the analyses of temporally continuous SWE measurements by a CRS on an alpine glacier in Switzerland (Glacier de la Plaine Morte) over two winter seasons (2016/17 and 2017/18), which differed markedly in the amount and timing of snow accumulation. By combining SWE with snow depth measurements, we calculate the daily mean density of the snowpack. Compared to manual field observations from snow pits, the autonomous measurements overestimate SWE by +2 % ± 13 %. Snow depth and the bulk snow density deviate from the manual measurements by ±6 % and ±9 %, respectively. The CRS measured with high reliability over two winter seasons and is thus considered a promising method to observe SWE at remote alpine sites. We use the daily observations to classify winter season days into those dominated by accumulation (solid precipitation, snow drift), ablation (snow drift, snowmelt) or snow densification. For each of these process-dominated days the prevailing meteorological conditions are distinct. The continuous SWE measurements were also used to define a scaling factor for precipitation amounts from nearby meteorological stations. With this analysis, we show that a best-possible constant scaling factor results in cumulative precipitation amounts that differ by a mean absolute error of less than 80 mm w.e. from snow accumulation at this site.

Extreme low and high flows can have negative economic, social, and ecological effects and are expected to become more severe in many regions due to climate change. Besides low and high flows, the whole flow regime, i.e., annual hydrograph comprised of monthly mean flows, is subject to changes. Knowledge on future changes in flow regimes is important since regimes contain information on both extremes and conditions prior to the dry and wet seasons. Changes in individual low- and high-flow characteristics as well as flow regimes under mean conditions have been thoroughly studied. In contrast, little is known about changes in extreme flow regimes. We here propose two methods for the estimation of extreme flow regimes and apply them to simulated discharge time series for future climate conditions in Switzerland. The first method relies on frequency analysis performed on annual flow duration curves. The second approach performs frequency analysis of the discharge sums of a large set of stochastically generated annual hydrographs. Both approaches were found to produce similar 100-year regime estimates when applied to a data set of 19 hydrological regions in Switzerland. Our results show that changes in both extreme low- and high-flow regimes for rainfall-dominated regions are distinct from those in melt-dominated regions. In rainfall-dominated regions, the minimum discharge of low-flow regimes decreases by up to 50 %, whilst the reduction is 25 % for high-flow regimes. In contrast, the maximum discharge of low- and high-flow regimes increases by up to 50 %. In melt-dominated regions, the changes point in the other direction than those in rainfall-dominated regions. The minimum and maximum discharges of extreme regimes increase by up to 100 % and decrease by less than 50 %, respectively. Our findings provide guidance in water resource planning and management and the extreme regime estimates are a valuable basis for climate impact studies. Highlights Estimation of 100-year low- and high-flow regimes using annual flow duration curves and stochastically simulated discharge time series Both mean and extreme regimes will change under future climate conditions. The minimum discharge of extreme regimes will decrease in rainfall-dominated regions but increase in melt-dominated regions. The maximum discharge of extreme regimes will increase and decrease in rainfall-dominated and melt-dominated regions, respectively.

Glaciers in the European Alps play an important role in the hydrological cycle, act as a source for hydroelectricity and have a large touristic importance. The future evolution of these glaciers is driven by surface mass balance and ice flow processes, of which the latter is to date not included explicitly in regional glacier projections for the Alps. Here, we model the future evolution of glaciers in the European Alps with GloGEMflow, an extended version of the Global Glacier Evolution Model (GloGEM), in which both surface mass balance and ice flow are explicitly accounted for. The mass balance model is calibrated with glacier-specific geodetic mass balances and forced with high-resolution regional climate model (RCM) simulations from the EURO-CORDEX ensemble. The evolution of the total glacier volume in the coming decades is relatively similar under the various representative concentrations pathways (RCP2.6, 4.5 and 8.5), with volume losses of about 47 %–52 % in 2050 with respect to 2017. We find that under RCP2.6, the ice loss in the second part of the 21st century is relatively limited and that about one-third (36.8 % ± 11.1 %, multi-model mean ±1σ) of the present-day (2017) ice volume will still be present in 2100. Under a strong warming (RCP8.5) the future evolution of the glaciers is dictated by a substantial increase in surface melt, and glaciers are projected to largely disappear by 2100 (94.4±4.4 % volume loss vs. 2017). For a given RCP, differences in future changes are mainly determined by the driving global climate model (GCM), rather than by the RCM, and these differences are larger than those arising from various model parameters (e.g. flow parameters and cross-section parameterisation). We find that under a limited warming, the inclusion of ice dynamics reduces the projected mass loss and that this effect increases with the glacier elevation range, implying that the inclusion of ice dynamics is likely to be important for global glacier evolution projections.

The Paris agreement aims to hold global warming to well below 2 ∘C and to pursue efforts to limit it to 1.5 ∘C relative to the pre-industrial period. Recent estimates based on population growth and intended carbon emissions from participant countries suggest global warming may exceed this ambitious target. Here we present glacier volume projections for the end of this century, under a range of high-end climate change scenarios, defined as exceeding +2 ∘C global average warming relative to the pre-industrial period. Glacier volume is modelled by developing an elevation-dependent mass balance model for the Joint UK Land Environment Simulator (JULES). To do this, we modify JULES to include glaciated and unglaciated surfaces that can exist at multiple heights within a single grid box. Present-day mass balance is calibrated by tuning albedo, wind speed, precipitation, and temperature lapse rates to obtain the best agreement with observed mass balance profiles. JULES is forced with an ensemble of six Coupled Model Intercomparison Project Phase 5 (CMIP5) models, which were downscaled using the high-resolution HadGEM3-A atmosphere-only global climate model. The CMIP5 models use the RCP8.5 climate change scenario and were selected on the criteria of passing 2 ∘C global average warming during this century. The ensemble mean volume loss at the end of the century plus or minus 1 standard deviation is -64±5 % for all glaciers excluding those on the peripheral of the Antarctic ice sheet. The uncertainty in the multi-model mean is rather small and caused by the sensitivity of HadGEM3-A to the boundary conditions supplied by the CMIP5 models. The regions which lose more than 75 % of their initial volume by the end of the century are Alaska, western Canada and the US, Iceland, Scandinavia, the Russian Arctic, central Europe, Caucasus, high-mountain Asia, low latitudes, southern Andes, and New Zealand. The ensemble mean ice loss expressed in sea level equivalent contribution is 215.2±21.3 mm. The largest contributors to sea level rise are Alaska (44.6±1.1 mm), Arctic Canada north and south (34.9±3.0 mm), the Russian Arctic (33.3±4.8 mm), Greenland (20.1±4.4), high-mountain Asia (combined central Asia, South Asia east and west), (18.0±0.8 mm), southern Andes (14.4±0.1 mm), and Svalbard (17.0±4.6 mm). Including parametric uncertainty in the calibrated mass balance parameters gives an upper bound global volume loss of 281.1 mm of sea level equivalent by the end of the century. Such large ice losses will have inevitable consequences for sea level rise and for water supply in glacier-fed river systems.

Albedo feedback is an important driver of glacier melt over bare-ice surfaces. Light-absorbing impurities strongly enhance glacier melt rates but their abundance, composition and variations in space and time are subject to considerable uncertainties and ongoing scientific debates. In this study, we assess the temporal evolution of shortwave broadband albedo derived from 15 end-of-summer Landsat scenes for the bare-ice areas of 39 large glaciers in the western and southern Swiss Alps. Trends in bare-ice albedo crucially depend on the spatial scale considered. No significant negative temporal trend in bare-ice albedo was found on a regional to glacier-wide scale. However, at higher spatial scales, certain areas of bare ice, including the lowermost elevations and margins of the ablation zones, revealed significant darkening over the study period 1999 to 2016. A total glacier area of 13.5 km2 (equivalent to about 12 % of the average end-of-summer bare-ice area in the study area) exhibited albedo trends significant at the 95 % confidence level or higher. Most of this area was affected by a negative albedo trend of about −0.05 decade−1. Generally, bare-ice albedo exhibits a strong interannual variability, caused by a complex interplay of meteorological conditions prior to the acquisition of the data, local glacier characteristics and the date of the investigated satellite imagery. Although a darkening of glacier ice was found to be present over only a limited region, we emphasize that due to the recent and projected growth of bare-ice areas and prolongation of the ablation season in the region, the albedo feedback will considerably enhance the rate of glacier mass loss in the Swiss Alps in the near future.

Abstract Since rock glaciers are believed to be more resilient to climate change, water stores therein may become important water reservoirs in future, in particular in dry regions, which currently rely on glacial runoff. In order to estimate and evaluate the future runoff potential from permafrost and rock glaciers, distributed runoff models suitable for high Alpine catchments are needed. An extension to the distributed Glacier Evolution and Runoff Model (GERM) to include permafrost and rock glaciers in Alpine catchments is presented here, and compared to the established one dimensional (1D) physics‐based model SNOWPACK. The new permafrost component introduced to GERM treats permafrost as discreet depth layers in a 1D column for all grid cells, which have bulk thermal properties calculated from their constituents (ice, water, air, and solid component). The temperature evolution is computed using heat conduction and latent heat exchanges, modified by ventilation effects. Finally, we infer water runoff from permafrost degradation. Ground temperature variations calculated by both models are compared to borehole measurements at three Alpine sites and similar performances are found. Differences between the models are present in the amplitude of seasonal ground temperature variations, with SNOWPACK having a tendency to slightly overestimate them, while GERM underestimates them.

The European Alps, the cradle of pioneering glacial studies, are one of the regions where geological markers of past glaciations are most abundant and well-studied. Such conditions make the region ideal for testing numerical glacier models based on simplified ice flow physics against field-based reconstructions and vice versa.Here, we use the Parallel Ice Sheet Model (PISM) to model the entire last glacial cycle (120–0 ka) in the Alps, using horizontal resolutions of 2 and 1 km. Climate forcing is derived using two sources: present-day climate data from WorldClim and the ERA-Interim reanalysis; time-dependent temperature offsets from multiple palaeo-climate proxies. Among the latter, only the European Project for Ice Coring in Antarctica (EPICA) ice core record yields glaciation during marine oxygen isotope stages 4 (69–62 ka) and 2 (34–18 ka). This is spatially and temporally consistent with the geological reconstructions, while the other records used result in excessive early glacial cycle ice cover and a late Last Glacial Maximum. Despite the low variability of this Antarctic-based climate forcing, our simulation depicts a highly dynamic ice sheet, showing that Alpine glaciers may have advanced many times over the foreland during the last glacial cycle. Ice flow patterns during peak glaciation are largely governed by subglacial topography but include occasional transfluences through the mountain passes. Modelled maximum ice surface is on average 861 m higher than observed trimline elevations in the upper Rhône Valley, yet our simulation predicts little erosion at high elevation due to cold-based ice. Finally, despite the uniform climate forcing, differences in glacier catchment hypsometry produce a time-transgressive Last Glacial Maximum advance, with some glaciers reaching their modelled maximum extent as early as 27 ka and others as late as 21 ka.

Glacier surface mass balance observations in the Tien Shan and Pamir are relatively sparse and often discontinuous. Nevertheless, glaciers are one of the most important components of the high-mountain cryosphere in the region as they strongly influence water availability in the arid, continental and intensely populated downstream areas. This study provides reliable and continuous surface mass balance series for selected glaciers located in the Tien Shan and Pamir-Alay. By cross-validating the results of three independent methods, we reconstructed the mass balance of the three benchmark glaciers, Abramov, Golubin and Glacier no. 354 for the past 2 decades. By applying different approaches, it was possible to compensate for the limitations and shortcomings of each individual method. This study proposes the use of transient snow line observations throughout the melt season obtained from satellite optical imagery and terrestrial automatic cameras. By combining modelling with remotely acquired information on summer snow depletion, it was possible to infer glacier mass changes for unmeasured years. The model is initialized with daily temperature and precipitation data collected at automatic weather stations in the vicinity of the glacier or with adjusted data from climate reanalysis products. Multi-annual mass changes based on high-resolution digital elevation models and in situ glaciological surveys were used to validate the results for the investigated glaciers. Substantial surface mass loss was confirmed for the three studied glaciers by all three methods, ranging from −0.30 ± 0.19 to −0.41 ± 0.33 m w.e. yr−1 over the 2004–2016 period. Our results indicate that integration of snow line observations into mass balance modelling significantly narrows the uncertainty ranges of the estimates. Hence, this highlights the potential of the methodology for application to unmonitored glaciers at larger scales for which no direct measurements are available.

The mountain cryosphere of mainland Europe is recognized to have important impacts on a range of environmental processes. In this paper, we provide an overview on the current knowledge on snow, glacier, and permafrost processes, as well as their past, current, and future evolution. We additionally provide an assessment of current cryosphere research in Europe and point to the different domains requiring further research. Emphasis is given to our understanding of climate–cryosphere interactions, cryosphere controls on physical and biological mountain systems, and related impacts. By the end of the century, Europe's mountain cryosphere will have changed to an extent that will impact the landscape, the hydrological regimes, the water resources, and the infrastructure. The impacts will not remain confined to the mountain area but also affect the downstream lowlands, entailing a wide range of socioeconomical consequences. European mountains will have a completely different visual appearance, in which low- and mid-range-altitude glaciers will have disappeared and even large valley glaciers will have experienced significant retreat and mass loss. Due to increased air temperatures and related shifts from solid to liquid precipitation, seasonal snow lines will be found at much higher altitudes, and the snow season will be much shorter than today. These changes in snow and ice melt will cause a shift in the timing of discharge maxima, as well as a transition of runoff regimes from glacial to nival and from nival to pluvial. This will entail significant impacts on the seasonality of high-altitude water availability, with consequences for water storage and management in reservoirs for drinking water, irrigation, and hydropower production. Whereas an upward shift of the tree line and expansion of vegetation can be expected into current periglacial areas, the disappearance of permafrost at lower altitudes and its warming at higher elevations will likely result in mass movements and process chains beyond historical experience. Future cryospheric research has the responsibility not only to foster awareness of these expected changes and to develop targeted strategies to precisely quantify their magnitude and rate of occurrence but also to help in the development of approaches to adapt to these changes and to mitigate their consequences. Major joint efforts are required in the domain of cryospheric monitoring, which will require coordination in terms of data availability and quality. In particular, we recognize the quantification of high-altitude precipitation as a key source of uncertainty in projections of future changes. Improvements in numerical modeling and a better understanding of process chains affecting high-altitude mass movements are the two further fields that – in our view – future cryospheric research should focus on.

Knowledge of the ice thickness distribution of glaciers is important for glaciological and hydrological applications. In this contribution, we present two updated bedrock topographies and ice thickness distributions for Gries- and Findelengletscher, Switzerland. The results are based on ground-penetrating radar (GPR) measurements collected in spring 2015 and already-existing data. The GPR data are analysed using ReflexW software and interpolated by using the ice thickness estimation method (ITEM). ITEM calculates the thickness distribution by using principles of ice flow dynamics and characteristics of the glacier surface. We show that using such a technique has a significance advantage compared to a direct interpolation of the measurements, especially for glacier areas that are sparsely covered by GPR data. The uncertainties deriving from both the interpretation of the GPR signal and the spatial interpolation through ITEM are quantified separately, showing that, in our case, GPR signal interpretation is a major source of uncertainty. The results show a total glacier volume of 0.28 ± 0.06 and 1.00 ± 0.34 km3 for Gries- and Findelengletscher, respectively, with corresponding average ice thicknesses of 56.8 ± 12.7 and 56.3 ± 19.6 m.

Glacier mass loss is among the clearest indicators of atmospheric warming. The observation of these changes is one of the major objectives of the international climate monitoring strategy developed by the Global Climate Observing System (GCOS). Long-term glacier mass balance measurements are furthermore the basis for calibrating and validating models simulating future runoff of glacierised catchments. This is essential for Central Asia, which is one of the driest continental regions of the Northern Hemisphere. In the highly populated regions, water shortage due to decreased glacierisation potentially leads to pronounced political instability, drastic ecological changes and endangered food security. As a consequence of the collapse of the former Soviet Union, however, many valuable glacier monitoring sites in the Tien Shan and Pamir Mountains were abandoned. In recent years, multinational actors have re-established a set of important in situ measuring sites to continue the invaluable long-term data series. This paper introduces the applied monitoring strategy for selected glaciers in the Kyrgyz and Uzbek Tien Shan and Pamir, highlights the existing and the new measurements on these glaciers, and presents an example for how the old and new data can be combined to establish multi-decadal mass balance time series. This is crucial for understanding the impact of climate change on glaciers in this region.

Knowledge of the ice thickness distribution of glaciers and ice caps is an important prerequisite for many glaciological and hydrological investigations. A wealth of approaches has recently been presented for inferring ice thickness from characteristics of the surface. With the Ice Thickness Models Intercomparison eXperiment (ITMIX) we performed the first coordinated assessment quantifying individual model performance. A set of 17 different models showed that individual ice thickness estimates can differ considerably – locally by a spread comparable to the observed thickness. Averaging the results of multiple models, however, significantly improved the results: on average over the 21 considered test cases, comparison against direct ice thickness measurements revealed deviations on the order of 10 ± 24 % of the mean ice thickness (1σ estimate). Models relying on multiple data sets – such as surface ice velocity fields, surface mass balance, or rates of ice thickness change – showed high sensitivity to input data quality. Together with the requirement of being able to handle large regions in an automated fashion, the capacity of better accounting for uncertainties in the input data will be a key for an improved next generation of ice thickness estimation approaches.

The recent surge cycle of Kyagar Glacier, in the Chinese Karakoram, caused formation of an ice-dammed lake and subsequent glacial lake outburst floods (GLOFs) exceeding 40 million m3 in 2015 and 2016. GLOFs from Kyagar Glacier reached double this size in 2002 and earlier, but the role of glacier surging in GLOF formation was previously unrecognised. We present an integrative analysis of the glacier surge dynamics from 2011 to 2016, assessing surge mechanisms and evaluating the surge cycle impact on GLOFs. Over 80 glacier surface velocity fields were created from TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement), Sentinel-1A, and Landsat satellite data. Changes in ice thickness distribution were revealed by a time series of TanDEM-X elevation models. The analysis shows that, during a quiescence phase lasting at least 14 years, ice mass built up in a reservoir area at the top of the glacier tongue, and the terminus thinned by up to 100 m, but in the 2 years preceding the surge onset this pattern reversed. The surge initiated with the onset of the 2014 melt season, and in the following 15 months velocity evolved in a manner consistent with a hydrologically controlled surge mechanism. Dramatic accelerations coincided with melt seasons, winter deceleration was accompanied by subglacial drainage, and rapid surge termination occurred following the 2015 GLOF. Rapid basal motion during the surge is seemingly controlled by high water pressure, caused by input of surface water into either an inefficient subglacial drainage system or unstable subglacial till. The potential lake volume increased to more than 70 million m3 by late 2016, as a result of over 60 m of thickening at the terminus. Lake formation and the evolution of the ice dam height should be carefully monitored through remote sensing to anticipate large GLOFs in the near future.

Due to the relative lack of empirical field data, the response of very small glaciers (here defined as being smaller than 0.5 km2) to current atmospheric warming is not fully understood yet. Investigating their mass balance, e.g. using the direct glaciological method, is a prerequisite to fill this knowledge gap. Terrestrial laser scanning (TLS) techniques operating in the near infrared range can be applied for the creation of repeated high-resolution digital elevation models and consecutive derivation of annual geodetic mass balances of very small glaciers. This method is promising, as laborious and potentially dangerous field measurements as well as the inter- and extrapolation of point measurements can be circumvented. However, it still needs to be validated. Here, we present TLS-derived annual surface elevation and geodetic mass changes for five very small glaciers in Switzerland (Glacier de Prapio, Glacier du Sex Rouge, St. Annafirn, Schwarzbachfirn, and Pizolgletscher) and two consecutive years (2013/14–2014/15). The scans were acquired with a long-range Riegl VZ®-6000 especially designed for surveying snow- and ice-covered terrain. Zonally variable conversion factors for firn and bare ice surfaces were applied to convert geodetic volume to mass changes. We compare the geodetic results to direct glaciological mass balance measurements coinciding with the TLS surveys and assess the uncertainties and errors included in both methods. Average glacier-wide mass balances were negative in both years, showing stronger mass losses in 2014/15 (−1.65 m w.e.) compared to 2013/14 (−0.59 m w.e.). Geodetic mass balances were slightly less negative but in close agreement with the direct glaciological ones (R2 = 0.91). Due to the dense in situ measurements, the uncertainties in the direct glaciological mass balances were small compared to the majority of measured glaciers worldwide (±0.09 m w.e. yr−1 on average), and similar to uncertainties in the TLS-derived geodetic mass balances (±0.13 m w.e. yr−1).

Light-absorbing impurities in snow and ice control glacier melt as shortwave radiation represents the main component of the surface energy balance. Here, we investigate the long-term effect of snow impurities, i.e., mineral dust and black carbon (BC), on albedo and glacier mass balance. The analysis was performed over the period 1914–2014 for two sites on Claridenfirn, Swiss Alps, where an outstanding 100-year record of seasonal mass balance measurements is available. Information on atmospheric deposition of mineral dust and BC over the last century was retrieved from two firn/ice cores of high-alpine sites. A combined mass balance and snow/firn layer model was employed to assess the effects of melt and accumulation processes on the impurity concentration at the surface and thus on albedo and glacier mass balance. Compared to pure snow conditions, the presence of Saharan dust and BC lowered the mean annual albedo by 0.04–0.06 depending on the location on the glacier. Consequently, annual melt was increased by 15–19 %, and the mean annual mass balance was reduced by about 280–490 mm w.e. BC clearly dominated absorption which is about 3 times higher than that of mineral dust. The upper site has experienced mainly positive mass balances and impurity layers were continuously buried whereas at the lower site, surface albedo was more strongly influenced by re-exposure of dust and BC-enriched layers due to frequent years with negative mass balances.

The spatial representation of accumulation measurements is a major limitation for current glacier mass balance monitoring approaches. Here, we present a method for estimating annual accumulation rates on a temperate Alpine glacier based on the interpretation of internal reflection horizons (IRHs) in helicopter-borne ground-penetrating radar (GPR) data. For each individual GPR measurement, the signal travel time is combined with a simple model for firn densification and refreezing of meltwater. The model is calibrated at locations where GPR repeat measurements are available in two subsequent years and the densification can be tracked over time. Two 10.5 m long firn cores provide a reference for the density and chronology of firn layers. Thereby, IRHs correspond to density maxima, but not exclusively to former summer glacier surfaces. Along GPR profile sections from across the accumulation area we obtain the water equivalent (w.e.) of several annual firn layers. Because deeper IRHs could be tracked over shorter distances, the total length of analysed profile sections varies from 7.3 km for the uppermost accumulation layer (2011) to 0.1 km for the deepest (i.e. oldest) layer (2006). According to model results, refreezing accounts for 10% of the density increase over time and depth, and for 2% of the water equivalent. The strongest limitation to our method is the dependence on layer chronology assumptions. We show that GPR can be used not only to complement existing mass balance monitoring programmes on temperate glaciers but also to retrospectively extend newly initiated time series.

Since the mid-1980s, glaciers in the European Alps have shown widespread and accelerating mass losses. This article presents glacier-specific changes in surface elevation, volume and mass balance for all glaciers in the Swiss Alps from 1980 to 2010. Together with glacier outlines from the 1973 inventory, the DHM25 Level 1 digital elevation models (DEMs) for which the source data over glacierized areas were acquired from 1961 to 1991 are compared to the swissALTI3D DEMs from 2008 to 2011 combined with the new Swiss Glacier Inventory SGI2010. Due to the significant differences in acquisition dates of the source data used, mass changes are temporally homogenized to directly compare individual glaciers or glacierized catchments. Along with an in-depth accuracy assessment, results are validated against volume changes from independent photogrammetrically derived DEMs of single glaciers. Observed volume changes are largest between 2700 and 2800 m a.s.l. and remarkable even above 3500 m a.s.l. The mean geodetic mass balance is −0.62 ± 0.07 m w.e. yr−1 for the entire Swiss Alps over the reference period 1980–2010. For the main hydrological catchments, it ranges from −0.52 to −1.07 m w.e. yr−1. The overall volume loss calculated from the DEM differencing is −22.51 ± 1.76 km3.

Ice volume estimates are crucial for assessing water reserves stored in glaciers. Due to its large glacier coverage, such estimates are of particular interest for the Himalayan–Karakoram (HK) region. In this study, different existing methodologies are used to estimate the ice reserves: three area–volume relations, one slope-dependent volume estimation method, and two ice-thickness distribution models are applied to a recent, detailed, and complete glacier inventory of the HK region, spanning over the period 2000–2010 and revealing an ice coverage of 40 775 km2. An uncertainty and sensitivity assessment is performed to investigate the influence of the observed glacier area and important model parameters on the resulting total ice volume. Results of the two ice-thickness distribution models are validated with local ice-thickness measurements at six glaciers. The resulting ice volumes for the entire HK region range from 2955 to 4737 km3, depending on the approach. This range is lower than most previous estimates. Results from the ice thickness distribution models and the slope-dependent thickness estimations agree well with measured local ice thicknesses. However, total volume estimates from area-related relations are larger than those from other approaches. The study provides evidence on the significant effect of the selected method on results and underlines the importance of a careful and critical evaluation.

Glacier length is an important measure of glacier geometry. Nevertheless, global glacier inventories are mostly lacking length data. Only recently semi-automated approaches to measure glacier length have been developed and applied regionally. Here we present a first global assessment of glacier length using an automated method that relies on glacier surface slope, distance to the glacier margins and a set of trade-off functions. The method is developed for East Greenland, evaluated for East Greenland as well as for Alaska and eventually applied to all ~ 200 000 glaciers around the globe. The evaluation highlights accurately calculated glacier length where digital elevation model (DEM) quality is high (East Greenland) and limited accuracy on low-quality DEMs (parts of Alaska). Measured length of very small glaciers is subject to a certain level of ambiguity. The global calculation shows that only about 1.5% of all glaciers are longer than 10 km, with Bering Glacier (Alaska/Canada) being the longest glacier in the world at a length of 196 km. Based on the output of our algorithm we derive global and regional area–length scaling laws. Differences among regional scaling parameters appear to be related to characteristics of topography and glacier mass balance. The present study adds glacier length as a key parameter to global glacier inventories. Global and regional scaling laws might prove beneficial in conceptual glacier models.

Assessing and projecting the dynamic response of glaciers on the Antarctic Peninsula to changed atmospheric and oceanic forcing requires high-resolution ice thickness data as an essential geometric constraint for ice flow models. Here, we derive a complete bedrock data set for the Antarctic Peninsula north of 70° S on a 100 m grid. We calculate distributed ice thickness based on surface topography and simple ice dynamic modelling. Our approach is constrained with all available thickness measurements from Operation IceBridge and gridded ice flow speeds for the entire study region. The new data set resolves the rugged subglacial topography in great detail, indicates deeply incised troughs, and shows that 34% of the ice volume is grounded below sea level. The Antarctic Peninsula has the potential to raise global sea level by 69 ± 5 mm. In comparison to Bedmap2, covering all Antarctica on a 1 km grid, a significantly higher mean ice thickness (+48%) is found.

Changes in Switzerland's climate are expected to have major impacts on glaciers, the hydrological regime and the natural hazard potential in mountainous regions. Glacier de la Plaine Morte is the largest plateau glacier in the European Alps and thus represents a particularly interesting site for studying rapid and far-reaching effects of atmospheric warming on Alpine glaciers. Based on detailed field observations combined with numerical modelling, the changes in total ice volume of Glacier de la Plaine Morte since the 1950s and the dynamics of present glacier mass loss are assessed. Future ice melt and changes in glacier runoff are computed using climate scenarios, and a possible increase in the natural hazard potential of glacier-dammed lakes around Plaine Morte over the next decades is discussed. This article provides an integrative view of the past, current and future retreat of an extraordinary Swiss glacier and emphasizes the implications of climate change on Alpine glaciers.

Volume–area scaling is the most popular method for estimating the ice volume of large glacier samples. Here, a series of resampling experiments based on different sets of synthetic data is presented in order to derive an upper-bound estimate (i.e. a level achieved only within ideal conditions) for its accuracy. For real-world applications, a lower accuracy has to be expected. We also quantify the maximum accuracy expected when scaling is used for determining the glacier volume change, and area change of a given glacier population. A comprehensive set of measured glacier areas, volumes, area and volume changes is evaluated to investigate the impact of real-world data quality on the so-assessed accuracies. For populations larger than a few thousand glaciers, the total ice volume can be recovered within 30% if all data currently available worldwide are used for estimating the scaling parameters. Assuming no systematic bias in ice volume measurements, their uncertainty is of secondary importance. Knowing the individual areas of a glacier sample for two points in time allows recovering the corresponding ice volume change within 40% for populations larger than a few hundred glaciers, both for steady-state and transient geometries. If ice volume changes can be estimated without bias, glacier area changes derived from volume–area scaling show similar uncertainties to those of the volume changes. This paper does not aim at making a final judgement on the suitability of volume–area scaling as such, but provides the means for assessing the accuracy expected from its application.

Glacier-wide mass balance has been measured for more than sixty years and is widely used as an indicator of climate change and to assess the glacier contribution to runoff and sea level rise. Until recently, comprehensive uncertainty assessments have rarely been carried out and mass balance data have often been applied using rough error estimation or without consideration of errors. In this study, we propose a framework for reanalysing glacier mass balance series that includes conceptual and statistical toolsets for assessment of random and systematic errors, as well as for validation and calibration (if necessary) of the glaciological with the geodetic balance results. We demonstrate the usefulness and limitations of the proposed scheme, drawing on an analysis that comprises over 50 recording periods for a dozen glaciers, and we make recommendations to investigators and users of glacier mass balance data. Reanalysing glacier mass balance series needs to become a standard procedure for every monitoring programme to improve data quality, including reliable uncertainty estimates.

Glaciers all over the world are expected to continue to retreat due to the global warming throughout the 21st century. Consequently, future seasonal water availability might become scarce once glacier areas have declined below a certain threshold affecting future water management strategies. Particular attention should be paid to glaciers located in a karstic environment, as parts of the meltwater can be drained by underlying karst systems, making it difficult to assess water availability. In this study tracer experiments, karst modeling and glacier melt modeling are combined in order to identify flow paths in a high alpine, glacierized, karstic environment (Glacier de la Plaine Morte, Switzerland) and to investigate current and predict future downstream water availability. Flow paths through the karst underground were determined with natural and fluorescent tracers. Subsequently, geologic information and the findings from tracer experiments were assembled in a karst model. Finally, glacier melt projections driven with a climate scenario were performed to discuss future water availability in the area surrounding the glacier. The results suggest that during late summer glacier meltwater is rapidly drained through well-developed channels at the glacier bottom to the north of the glacier, while during low flow season meltwater enters into the karst and is drained to the south. Climate change projections with the glacier melt model reveal that by the end of the century glacier melt will be significantly reduced in the summer, jeopardizing water availability in glacier-fed karst springs.

The geodetic method is widely used for assessing changes in the mass balance of mountain glaciers. However, comparison of repeated digital elevation models only provides a glacier volume change that must be converted to a change in mass using a density assumption or model. This study investigates the use of a constant factor for the volume-to-mass conversion based on a firn compaction model applied to simplified glacier geometries with idealized climate forcing, and two glaciers with long-term mass balance series. It is shown that the "density" of geodetic volume change is not a constant factor and is systematically smaller than ice density in most cases. This is explained by the accretion/removal of low-density firn layers, and changes in the firn density profile with positive/negative mass balance. Assuming a value of 850 ± 60 kg m−3 to convert volume change to mass change is appropriate for a wide range of conditions. For short time intervals (≤3 yr), periods with limited volume change, and/or changing mass balance gradients, the conversion factor can however vary from 0–2000 kg m−3 and beyond, which requires caution when interpreting glacier mass changes based on geodetic surveys.

No abstract available.

This study addresses the extrapolation of in-situ glacier mass balance measurements to the mountain-range scale and aims at deriving time series of area-averaged mass balance and ice volume change for all glaciers in the European Alps for the period 1900–2100. Long-term mass balance series for 50 Swiss glaciers based on a combination of field data and modelling, and WGMS data for glaciers in Austria, France and Italy are used. A complete glacier inventory is available for the year 2003. Mass balance extrapolation is performed based on (1) arithmetic averaging, (2) glacier hypsometry, and (3) multiple regression. Given a sufficient number of data series, multiple regression with variables describing glacier geometry performs best in reproducing observed spatial mass balance variability. Future mass changes are calculated by driving a combined model for mass balance and glacier geometry with GCM ensembles based on four emission scenarios. Mean glacier mass balance in the European Alps is −0.31 ± 0.04 m w.e. a−1 in 1900–2011, and −1 m w.e. a−1 over the last decade. Total ice volume change since 1900 is −96 ± 13 km3; annual values vary between −5.9 km3 (1947) and +3.9 km3 (1977). Mean mass balances are expected to be around −1.3 m w.e. a−1 by 2050. Model results indicate a glacier area reduction of 4–18% relative to 2003 for the end of the 21st century.

The hydrology of high mountainous catchments is often predicted with conceptual precipitation-discharge models that simulate the snow accumulation and ablation behavior of a very complex environment using as only input temperature and precipitation. It is hereby often assumed that some glacier-wide annual balance estimates, in addition to observed discharge, are sufficient to reliably calibrate such a model. Based on observed data from Rhonegletscher (Switzerland), we show in this paper that information on the seasonal mass balance is a pre-requisite for model calibration. And we present a simple, but promising methodology to include point mass balance observations into a systematic calibration process. The application of this methodology to the Rhonegletscher catchment illustrates that even small samples of point observations do contain extractable information for model calibration. The reproduction of these observed seasonal mass balance data requires, however, a model structure modification, in particular seasonal lapse rates and a separate snow accumulation and rainfall correction factor. This paper shows that a simple conceptual model can be a valuable tool to project the behavior of a glacier catchment but only if there is enough seasonal information to constrain the parameters that directly affect the water mass balance. The presented multi-signal model identification framework and the simple method to calibrate a semi-lumped model on point observations has potential for application in other modeling contexts.

Global warming is expected to significantly affect the runoff regime of mountainous catchments. Simple methods for calculating future glacier change in hydrological models are required in order to reliably assess economic impacts of changes in the water cycle over the next decades. Models for temporal and spatial glacier evolution need to describe the climate forcing acting on the glacier, and ice flow dynamics. Flow models, however, demand considerable computational resources and field data input and are moreover not applicable on the regional scale. Here, we propose a simple parameterization for calculating the change in glacier surface elevation and area, which is mass conserving and suited for hydrological modelling. The Δh-parameterization is an empirical glacier-specific function derived from observations in the past that can easily be applied to large samples of glaciers. We compare the Δh-parameterization to results of a 3-D finite-element ice flow model. As case studies, the evolution of two Alpine glaciers of different size over the period 2008–2100 is investigated using regional climate scenarios. The parameterization closely reproduces the distributed ice thickness change, as well as glacier area and length predicted by the ice flow model. This indicates that for the purpose of transient runoff forecasts, future glacier geometry change can be approximated using a simple parameterization instead of complex ice flow modelling. Furthermore, we analyse alpine glacier response to 21st century climate change and consequent shifts in the runoff regime of a highly glacierized catchment using the proposed methods.