Showing papers in "The Cryosphere in 2016"

A new map of permafrost distribution on the Tibetan Plateau

Abstract: . The Tibetan Plateau (TP) has the largest areas of permafrost terrain in the mid- and low-latitude regions of the world. Some permafrost distribution maps have been compiled but, due to limited data sources, ambiguous criteria, inadequate validation, and deficiency of high-quality spatial data sets, there is high uncertainty in the mapping of the permafrost distribution on the TP. We generated a new permafrost map based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated this map using various ground-based data sets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and soil properties (moisture content and bulk density). The temperature at the top of permafrost (TTOP) model was applied to simulate the permafrost distribution. Permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06 × 106 km2 (0.97–1.15 × 106 km2, 90 % confidence interval) (40 %), 1.46 × 106 (56 %), and 0.03 × 106 km2 (1 %), respectively, excluding glaciers and lakes. Ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) were used to validate the model. Validation results showed that the kappa coefficient varied from 0.38 to 0.78 with a mean of 0.57 for the five IRs and 0.62 to 0.74 with a mean of 0.68 within the three transects. Compared with earlier studies, the TTOP modelling results show greater accuracy. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.

On the recent contribution of the Greenland ice sheet to sea level change

Abstract: . We assess the recent contribution of the Greenland ice sheet (GrIS) to sea level change. We use the mass budget method, which quantifies ice sheet mass balance (MB) as the difference between surface mass balance (SMB) and solid ice discharge across the grounding line (D). A comparison with independent gravity change observations from GRACE shows good agreement for the overlapping period 2002–2015, giving confidence in the partitioning of recent GrIS mass changes. The estimated 1995 value of D and the 1958–1995 average value of SMB are similar at 411 and 418 Gt yr−1, respectively, suggesting that ice flow in the mid-1990s was well adjusted to the average annual mass input, reminiscent of an ice sheet in approximate balance. Starting in the early to mid-1990s, SMB decreased while D increased, leading to quasi-persistent negative MB. About 60 % of the associated mass loss since 1991 is caused by changes in SMB and the remainder by D. The decrease in SMB is fully driven by an increase in surface melt and subsequent meltwater runoff, which is slightly compensated by a small (

Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model

Abstract: . With the aim of studying the recent Greenland ice sheet (GrIS) surface mass balance (SMB) decrease relative to the last century, we have forced the regional climate MAR (Modele Atmospherique Regional; version 3.5.2) model with the ERA-Interim (ECMWF Interim Re-Analysis; 1979–2015), ERA-40 (1958–2001), NCEP–NCARv1 (National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis version 1; 1948–2015), NCEP–NCARv2 (1979–2015), JRA-55 (Japanese 55-year Reanalysis; 1958–2014), 20CRv2(c) (Twentieth Century Reanalysis version 2; 1900–2014) and ERA-20C (1900–2010) reanalyses. While all these forcing products are reanalyses that are assumed to represent the same climate, they produce significant differences in the MAR-simulated SMB over their common period. A temperature adjustment of +1 °C (respectively −1 °C) was, for example, needed at the MAR boundaries with ERA-20C (20CRv2) reanalysis, given that ERA-20C (20CRv2) is ∼ 1 °C colder (warmer) than ERA-Interim over Greenland during the period 1980–2010. Comparisons with daily PROMICE (Programme for Monitoring of the Greenland Ice Sheet) near-surface observations support these adjustments. Comparisons with SMB measurements, ice cores and satellite-derived melt extent reveal the most accurate forcing datasets for the simulation of the GrIS SMB to be ERA-Interim and NCEP–NCARv1. However, some biases remain in MAR, suggesting that some improvements are still needed in its cloudiness and radiative schemes as well as in the representation of the bare ice albedo. Results from all MAR simulations indicate that (i) the period 1961–1990, commonly chosen as a stable reference period for Greenland SMB and ice dynamics, is actually a period of anomalously positive SMB (∼ +40 Gt yr−1) compared to 1900–2010; (ii) SMB has decreased significantly after this reference period due to increasing and unprecedented melt reaching the highest rates in the 120-year common period; (iii) before 1960, both ERA-20C and 20CRv2-forced MAR simulations suggest a significant precipitation increase over 1900–1950, but this increase could be the result of an artefact in the reanalyses that are not well-enough constrained by observations during this period and (iv) since the 1980s, snowfall is quite stable after having reached a maximum in the 1970s. These MAR-based SMB and accumulation reconstructions are, however, quite similar to those from Box (2013) after 1930 and confirm that SMB was quite stable from the 1940s to the 1990s. Finally, only the ERA-20C-forced simulation suggests that SMB during the 1920–1930 warm period over Greenland was comparable to the SMB of the 2000s, due to both higher melt and lower precipitation than normal.

Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations

Abstract: . Detailed information on the spatiotemporal snow depth distribution is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Today, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network like the one in Switzerland, with more than one measurement station per 10 km2 on average, is not able to capture the large spatial variability of snow depth present in alpine terrain. Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, in most countries such data acquisition is costly if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UASs), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Compared to manual measurements, such systems are relatively cost-effective and can be applied very flexibly to cover terrain not accessible from the ground. In this study, we map snow depth at two different locations: (a) a sheltered location at the bottom of the Fluela valley (1900 m a.s.l.) and (b) an exposed location on a peak (2500 m a.s.l.) in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) of less than 0.07 to 0.15 m on meadows and rocks and a RMSE of less than 0.30 m on sections covered by bushes or tall grass, compared to manual probe measurements. This new measurement technology opens the door for efficient, flexible, repeatable and cost-effective snow depth monitoring over areas of several hectares for various applications, if the national and regional regulations permit the application of UASs.

How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment

Abstract: . 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.

Sea-Ice Indicators of Polar Bear Habitat

Abstract: . Nineteen subpopulations of polar bears (Ursus maritimus) are found throughout the circumpolar Arctic, and in all regions they depend on sea ice as a platform for traveling, hunting, and breeding. Therefore polar bear phenology – the cycle of biological events – is linked to the timing of sea-ice retreat in spring and advance in fall. We analyzed the dates of sea-ice retreat and advance in all 19 polar bear subpopulation regions from 1979 to 2014, using daily sea-ice concentration data from satellite passive microwave instruments. We define the dates of sea-ice retreat and advance in a region as the dates when the area of sea ice drops below a certain threshold (retreat) on its way to the summer minimum or rises above the threshold (advance) on its way to the winter maximum. The threshold is chosen to be halfway between the historical (1979–2014) mean September and mean March sea-ice areas. In all 19 regions there is a trend toward earlier sea-ice retreat and later sea-ice advance. Trends generally range from −3 to −9 days decade−1 in spring and from +3 to +9 days decade−1 in fall, with larger trends in the Barents Sea and central Arctic Basin. The trends are not sensitive to the threshold. We also calculated the number of days per year that the sea-ice area exceeded the threshold (termed ice-covered days) and the average sea-ice concentration from 1 June through 31 October. The number of ice-covered days is declining in all regions at the rate of −7 to −19 days decade−1, with larger trends in the Barents Sea and central Arctic Basin. The June–October sea-ice concentration is declining in all regions at rates ranging from −1 to −9 percent decade−1. These sea-ice metrics (or indicators of habitat change) were designed to be useful for management agencies and for comparative purposes among subpopulations. We recommend that the National Climate Assessment include the timing of sea-ice retreat and advance in future reports.

The darkening of the Greenland ice sheet: trends, drivers, and projections (1981-2100)

Abstract: . The surface energy balance and meltwater production of the Greenland ice sheet (GrIS) are modulated by snow and ice albedo through the amount of absorbed solar radiation. Here we show, using space-borne multispectral data collected during the 3 decades from 1981 to 2012, that summertime surface albedo over the GrIS decreased at a statistically significant (99 %) rate of 0.02 decade−1 between 1996 and 2012. Over the same period, albedo modelled by the Modele Atmospherique Regionale (MAR) also shows a decrease, though at a lower rate ( ∼ −0.01 decade−1) than that obtained from space-borne data. We suggest that the discrepancy between modelled and measured albedo trends can be explained by the absence in the model of processes associated with the presence of light-absorbing impurities. The negative trend in observed albedo is confined to the regions of the GrIS that undergo melting in summer, with the dry-snow zone showing no trend. The period 1981–1996 also showed no statistically significant trend over the whole GrIS. Analysis of MAR outputs indicates that the observed albedo decrease is attributable to the combined effects of increased near-surface air temperatures, which enhanced melt and promoted growth in snow grain size and the expansion of bare ice areas, and to trends in light-absorbing impurities (LAI) on the snow and ice surfaces. Neither aerosol models nor in situ and remote sensing observations indicate increasing trends in LAI in the atmosphere over Greenland. Similarly, an analysis of the number of fires and BC emissions from fires points to the absence of trends for such quantities. This suggests that the apparent increase of LAI in snow and ice might be related to the exposure of a "dark band" of dirty ice and to increased consolidation of LAI at the surface with melt, not to increased aerosol deposition. Albedo projections through to the end of the century under different warming scenarios consistently point to continued darkening, with albedo anomalies averaged over the whole ice sheet lower by 0.08 in 2100 than in 2000, driven solely by a warming climate. Future darkening is likely underestimated because of known underestimates in modelled melting (as seen in hindcasts) and because the model albedo scheme does not currently include the effects of LAI, which have a positive feedback on albedo decline through increased melting, grain growth, and darkening.

Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years

Abstract: . A new long-term data record of Fram Strait sea ice area export from 1935 to 2014 is developed using a combination of satellite radar images and station observations of surface pressure across Fram Strait. This data record shows that the long-term annual mean export is about 880 000 km2, representing 10 % of the sea-ice-covered area inside the basin. The time series has large interannual and multi-decadal variability but no long-term trend. However, during the last decades, the amount of ice exported has increased, with several years having annual ice exports that exceeded 1 million km2. This increase is a result of faster southward ice drift speeds due to stronger southward geostrophic winds, largely explained by increasing surface pressure over Greenland. Evaluating the trend onwards from 1979 reveals an increase in annual ice export of about +6 % per decade, with spring and summer showing larger changes in ice export (+11 % per decade) compared to autumn and winter (+2.6 % per decade). Increased ice export during winter will generally result in new ice growth and contributes to thinning inside the Arctic Basin. Increased ice export during summer or spring will, in contrast, contribute directly to open water further north and a reduced summer sea ice extent through the ice–albedo feedback. Relatively low spring and summer export from 1950 to 1970 is thus consistent with a higher mid-September sea ice extent for these years. Our results are not sensitive to long-term change in Fram Strait sea ice concentration. We find a general moderate influence between export anomalies and the following September sea ice extent, explaining 18 % of the variance between 1935 and 2014, but with higher values since 2004.

An automated methodology for differentiating rock from snow, clouds and seain Antarctica from Landsat 8 imagery: a new rock outcrop map and areaestimation for the entire Antarctic continent

Abstract: . As the accuracy and sensitivity of remote-sensing satellites improve, there is an increasing demand for more accurate and updated base datasets for surveying and monitoring. However, differentiating rock outcrop from snow and ice is a particular problem in Antarctica, where extensive cloud cover and widespread shaded regions lead to classification errors. The existing rock outcrop dataset has significant georeferencing issues as well as overestimation and generalisation of rock exposure areas. The most commonly used method for automated rock and snow differentiation, the normalised difference snow index (NDSI), has difficulty differentiating rock and snow in Antarctica due to misclassification of shaded pixels and is not able to differentiate illuminated rock from clouds. This study presents a new method for identifying rock exposures using Landsat 8 data. This is the first automated methodology for snow and rock differentiation that excludes areas of snow (both illuminated and shaded), clouds and liquid water whilst identifying both sunlit and shaded rock, achieving higher and more consistent accuracies than alternative data and methods such as the NDSI. The new methodology has been applied to the whole Antarctic continent (north of 82°40′ S) using Landsat 8 data to produce a new rock outcrop dataset for Antarctica. The new data (merged with existing data where Landsat 8 tiles are unavailable; most extensively south of 82°40′ S) reveal that exposed rock forms 0.18 % (21 745 km2) of the total land area of Antarctica: half of previous estimates.

A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015)

Abstract: . This study presents a data set of daily, 1 km resolution Greenland ice sheet (GrIS) surface mass balance (SMB) covering the period 1958–2015. Applying corrections for elevation, bare ice albedo and accumulation bias, the high-resolution product is statistically downscaled from the native daily output of the polar regional climate model RACMO2.3 at 11 km. The data set includes all individual SMB components projected to a down-sampled version of the Greenland Ice Mapping Project (GIMP) digital elevation model and ice mask. The 1 km mask better resolves narrow ablation zones, valley glaciers, fjords and disconnected ice caps. Relative to the 11 km product, the more detailed representation of isolated glaciated areas leads to increased precipitation over the southeastern GrIS. In addition, the downscaled product shows a significant increase in runoff owing to better resolved low-lying marginal glaciated regions. The combined corrections for elevation and bare ice albedo markedly improve model agreement with a newly compiled data set of ablation measurements.

Reduced melt on debris-covered glaciers: investigations from Changri Nup Glacier, Nepal

Abstract: Approximately 25 % of the glacierized area in the Everest region is covered by debris, yet the surface mass balance of debris-covered portions of these glaciers has not been measured directly. In this study, ground-based measurements of surface elevation and ice depth are combined with terrestrial photogrammetry, unmanned aerial vehicle (UAV) and satellite elevation models to derive the surface mass balance of the debris-covered tongue of Changri Nup Glacier, located in the Everest region. Over the debris-covered tongue, the mean elevation change between 2011 and 2015 is −0.93 m year−1 or −0.84 m water equivalent per year (w.e. a−1). The mean emergence velocity over this region, estimated from the total ice flux through a cross section immediately above the debris-covered zone, is +0.37 m w.e. a−1. The debris-covered portion of the glacier thus has an area-averaged mass balance of −1.21 ± 0.2 m w.e. a−1 between 5240 and 5525 m above sea level (m a.s.l.). Surface mass balances observed on nearby debris-free glaciers suggest that the ablation is strongly reduced (by ca. 1.8 m w.e. a−1) by the debris cover. The insulating effect of the debris cover has a larger effect on total mass loss than the enhanced ice ablation due to supraglacial ponds and exposed ice cliffs. This finding contradicts earlier geodetic studies and should be considered for modelling the future evolution of debris-covered glaciers.

Wave climate in the Arctic 1992-2014: seasonality and trends

Abstract: . Over the past decade, the diminishing Arctic sea ice has impacted the wave field, which depends on the ice-free ocean and wind. This study characterizes the wave climate in the Arctic spanning 1992–2014 from a merged altimeter data set and a wave hindcast that uses CFSR winds and ice concentrations from satellites as input. The model performs well, verified by the altimeters, and is relatively consistent for climate studies. The wave seasonality and extremes are linked to the ice coverage, wind strength, and wind direction, creating distinct features in the wind seas and swells. The altimeters and model show that the reduction of sea ice coverage causes increasing wave heights instead of the wind. However, trends are convoluted by interannual climate oscillations like the North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation. In the Nordic Greenland Sea the NAO influences the decreasing wind speeds and wave heights. Swells are becoming more prevalent and wind-sea steepness is declining. The satellite data show the sea ice minimum occurs later in fall when the wind speeds increase. This creates more favorable conditions for wave development. Therefore we expect the ice freeze-up in fall to be the most critical season in the Arctic and small changes in ice cover, wind speeds, and wave heights can have large impacts to the evolution of the sea ice throughout the year. It is inconclusive how important wave–ice processes are within the climate system, but selected events suggest the importance of waves within the marginal ice zone.

Heterogeneous glacier thinning patterns over the last 40 years in LangtangHimal, Nepal

Abstract: . This study presents volume and mass changes of seven (five partially debris-covered, two debris-free) glaciers in the upper Langtang catchment in Nepal. We use a digital elevation model (DEM) from 1974 stereo Hexagon satellite data and seven DEMs derived from 2006–2015 stereo or tri-stereo satellite imagery (e.g., SPOT6/7). The availability of multiple independent DEM differences allows the identification of a robust signal and narrowing down of the uncertainty about recent volume changes. The volume changes calculated over several multiyear periods between 2006 and 2015 consistently indicate that glacier thinning has accelerated with respect to the period 1974–2006. We calculate an ensemble-mean elevation change rate of –0.45 ± 0.18 m a−1 for 2006–2015, while for the period 1974–2006 we compute a rate of −0.24 ± 0.08 m a−1. However, the behavior of glaciers in the study area is heterogeneous, and the presence or absence of debris does not seem to be a good predictor for mass balance trends. Debris-covered tongues have nonlinear thinning profiles, and we show that recent accelerations in thinning correlate with the presence of supraglacial cliffs and lakes. At stagnating glacier areas near the glacier front, however, thinning rates decreased with time or remained constant. The April 2015 Nepal earthquake triggered large avalanches in the study catchment. Analysis of two post-earthquake DEMs revealed that the avalanche deposit volumes remaining 6 months after the earthquake are negligible in comparison to 2006–2015 elevation changes. However, the deposits compensate about 40 % the mass loss of debris-covered tongues of 1 average year.

Mapping snow depth in open alpine terrain from stereo satellite imagery

Abstract: . To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. Here, we examine the potential of very-high-resolution (VHR) optical stereo satellites to this purpose. Two triplets of 0.70 m resolution images were acquired by the Pleiades satellite over an open alpine catchment (14.5 km2) under snow-free and snow-covered conditions. The open-source software Ame's Stereo Pipeline (ASP) was used to match the stereo pairs without ground control points to generate raw photogrammetric clouds and to convert them into high-resolution digital elevation models (DEMs) at 1, 2, and 4 m resolutions. The DEM differences (dDEMs) were computed after 3-D coregistration, including a correction of a −0.48 m vertical bias. The bias-corrected dDEM maps were compared to 451 snow-probe measurements. The results show a decimetric accuracy and precision in the Pleiades-derived snow depths. The median of the residuals is −0.16 m, with a standard deviation (SD) of 0.58 m at a pixel size of 2 m. We compared the 2 m Pleiades dDEM to a 2 m dDEM that was based on a winged unmanned aircraft vehicle (UAV) photogrammetric survey that was performed on the same winter date over a portion of the catchment (3.1 km2). The UAV-derived snow depth map exhibits the same patterns as the Pleiades-derived snow map, with a median of −0.11 m and a SD of 0.62 m when compared to the snow-probe measurements. The Pleiades images benefit from a very broad radiometric range (12 bits), allowing a high correlation success rate over the snow-covered areas. This study demonstrates the value of VHR stereo satellite imagery to map snow depth in remote mountainous areas even when no field data are available.

The modelled surface mass balance of the Antarctic Peninsula at 5.5 km horizontal resolution

Abstract: . This study presents a high-resolution (∼ 5.5 km) estimate of surface mass balance (SMB) over the period 1979–2014 for the Antarctic Peninsula (AP), generated by the regional atmospheric climate model RACMO2.3 and a firn densification model (FDM). RACMO2.3 is used to force the FDM, which calculates processes in the snowpack, such as meltwater percolation, refreezing and runoff. We evaluate model output with 132 in situ SMB observations and discharge rates from six glacier drainage basins, and find that the model realistically simulates the strong spatial variability in precipitation, but that significant biases remain as a result of the highly complex topography of the AP. It is also clear that the observations significantly underrepresent the high-accumulation regimes, complicating a full model evaluation. The SMB map reveals large accumulation gradients, with precipitation values above 3000 mm we yr−1 in the western AP (WAP) and below 500 mm we yr−1 in the eastern AP (EAP), not resolved by coarser data sets such as ERA-Interim. The average AP ice-sheet-integrated SMB, including ice shelves (an area of 4.1 × 105 km2), is estimated at 351 Gt yr−1 with an interannual variability of 58 Gt yr−1, which is dominated by precipitation (PR) (365 ± 57 Gt yr−1). The WAP (2.4 × 105 km2) SMB (276 ± 47 Gt yr−1), where PR is large (276 ± 47 Gt yr−1), dominates over the EAP (1.7 × 105 km2) SMB (75 ± 11 Gt yr−1) and PR (84 ± 11 Gt yr−1). Total sublimation is 11 ± 2 Gt yr−1 and meltwater runoff into the ocean is 4 ± 4 Gt yr−1. There are no significant trends in any of the modelled AP SMB components, except for snowmelt that shows a significant decrease over the last 36 years (−0.36 Gt yr−2).

neXtSIM: a new Lagrangian sea ice model

Abstract: . The Arctic sea ice cover has changed drastically over the last decades. Associated with these changes is a shift in dynamical regime seen by an increase of extreme fracturing events and an acceleration of sea ice drift. The highly non-linear dynamical response of sea ice to external forcing makes modelling these changes and the future evolution of Arctic sea ice a challenge for current models. It is, however, increasingly important that this challenge be better met, both because of the important role of sea ice in the climate system and because of the steady increase of industrial operations in the Arctic. In this paper we present a new dynamical/thermodynamical sea ice model called neXtSIM that is designed to address this challenge. neXtSIM is a continuous and fully Lagrangian model, whose momentum equation is discretised with the finite-element method. In this model, sea ice physics are driven by the combination of two core components: a model for sea ice dynamics built on a mechanical framework using an elasto-brittle rheology, and a model for sea ice thermodynamics providing damage healing for the mechanical framework. The evaluation of the model performance for the Arctic is presented for the period September 2007 to October 2008 and shows that observed multi-scale statistical properties of sea ice drift and deformation are well captured as well as the seasonal cycles of ice volume, area, and extent. These results show that neXtSIM is an appropriate tool for simulating sea ice over a wide range of spatial and temporal scales.

Impacts of snow and organic soils parameterization on northern Eurasian soil temperature profiles simulated by the ISBA land surface model

Abstract: . In this study we analyzed how an improved representation of snowpack processes and soil properties in the multilayer snow and soil schemes of the Interaction Soil-Biosphere-Atmosphere (ISBA) land surface model impacts the simulation of soil temperature profiles over northern Eurasian regions. For this purpose, we refine ISBA's snow layering algorithm and propose a parameterization of snow albedo and snow compaction/densification adapted from the detailed Crocus snowpack model. We also include a dependency on soil organic carbon content for ISBA's hydraulic and thermal soil properties. First, changes in the snowpack parameterization are evaluated against snow depth, snow water equivalent, surface albedo, and soil temperature at a 10 cm depth observed at the Col de Porte field site in the French Alps. Next, the new model version including all of the changes is used over northern Eurasia to evaluate the model's ability to simulate the snow depth, the soil temperature profile, and the permafrost characteristics. The results confirm that an adequate simulation of snow layering and snow compaction/densification significantly impacts the snowpack characteristics and the soil temperature profile during winter, while the impact of the more accurate snow albedo computation is dominant during the spring. In summer, the accounting for the effect of soil organic carbon on hydraulic and thermal soil properties improves the simulation of the soil temperature profile. Finally, the results confirm that this last process strongly influences the simulation of the permafrost active layer thickness and its spatial distribution.

Review article: Inferring permafrost and permafrost thaw in the mountains of the Hindu Kush Himalaya region

Abstract: . The cryosphere reacts sensitively to climate change, as evidenced by the widespread retreat of mountain glaciers. Subsurface ice contained in permafrost is similarly affected by climate change, causing persistent impacts on natural and human systems. In contrast to glaciers, permafrost is not observable spatially and therefore its presence and possible changes are frequently overlooked. Correspondingly, little is known about permafrost in the mountains of the Hindu Kush Himalaya (HKH) region, despite permafrost area exceeding that of glaciers in nearly all countries. Based on evidence and insight gained mostly in other permafrost areas globally, this review provides a synopsis on what is known or can be inferred about permafrost in the mountains of the HKH region. Given the extreme nature of the environment concerned, it is to be expected that the diversity of conditions and phenomena encountered in permafrost exceed what has previously been described and investigated. We further argue that climate change in concert with increasing development will bring about diverse permafrost-related impacts on vegetation, water quality, geohazards, and livelihoods. To better anticipate and mitigate these effects, a deepened understanding of high-elevation permafrost in subtropical latitudes as well as the pathways interconnecting environmental changes and human livelihoods are needed.

Accuracy of snow depth estimation in mountain and prairie environments by an unmanned aerial vehicle

Abstract: . Quantifying the spatial distribution of snow is crucial to predict and assess its water resource potential and understand land–atmosphere interactions. High-resolution remote sensing of snow depth has been limited to terrestrial and airborne laser scanning and more recently with application of structure from motion (SfM) techniques to airborne (manned and unmanned) imagery. In this study, photography from a small unmanned aerial vehicle (UAV) was used to generate digital surface models (DSMs) and orthomosaics for snow cover at a cultivated agricultural Canadian prairie and a sparsely vegetated Rocky Mountain alpine ridgetop site using SfM. The accuracy and repeatability of this method to quantify snow depth, changes in depth and its spatial variability was assessed for different terrain types over time. Root mean square errors in snow depth estimation from differencing snow-covered and non-snow-covered DSMs were 8.8 cm for a short prairie grain stubble surface, 13.7 cm for a tall prairie grain stubble surface and 8.5 cm for an alpine mountain surface. This technique provided useful information on maximum snow accumulation and snow-covered area depletion at all sites, while temporal changes in snow depth could also be quantified at the alpine site due to the deeper snowpack and consequent higher signal-to-noise ratio. The application of SfM to UAV photographs returns meaningful information in areas with mean snow depth > 30 cm, but the direct observation of snow depth depletion of shallow snowpacks with this method is not feasible. Accuracy varied with surface characteristics, sunlight and wind speed during the flight, with the most consistent performance found for wind speeds

Past ice-sheet behaviour: retreat scenarios and changing controls in the Ross Sea, Antarctica

Abstract: . Studying the history of ice-sheet behaviour in the Ross Sea, Antarctica's largest drainage basin can improve our understanding of patterns and controls on marine-based ice-sheet dynamics and provide constraints for numerical ice-sheet models. Newly collected high-resolution multibeam bathymetry data, combined with two decades of legacy multibeam and seismic data, are used to map glacial landforms and reconstruct palaeo ice-sheet drainage. During the Last Glacial Maximum, grounded ice reached the continental shelf edge in the eastern but not western Ross Sea. Recessional geomorphic features in the western Ross Sea indicate virtually continuous back-stepping of the ice-sheet grounding line. In the eastern Ross Sea, well-preserved linear features and a lack of small-scale recessional landforms signify rapid lift-off of grounded ice from the bed. Physiography exerted a first-order control on regional ice behaviour, while sea floor geology played an important subsidiary role. Previously published deglacial scenarios for Ross Sea are based on low-spatial-resolution marine data or terrestrial observations; however, this study uses high-resolution basin-wide geomorphology to constrain grounding-line retreat on the continental shelf. Our analysis of retreat patterns suggests that (1) retreat from the western Ross Sea was complex due to strong physiographic controls on ice-sheet drainage; (2) retreat was asynchronous across the Ross Sea and between troughs; (3) the eastern Ross Sea largely deglaciated prior to the western Ross Sea following the formation of a large grounding-line embayment over Whales Deep; and (4) our glacial geomorphic reconstruction converges with recent numerical models that call for significant and complex East Antarctic ice sheet and West Antarctic ice sheet contributions to the ice flow in the Ross Sea.

Modeling debris-covered glaciers: response to steady debris deposition

Abstract: . Debris-covered glaciers are common in rapidly eroding alpine landscapes. When thicker than a few centimeters, surface debris suppresses melt rates. If continuous debris cover is present, ablation rates can be significantly reduced leading to increases in glacier length. In order to quantify feedbacks in the debris–glacier–climate system, we developed a 2-D long-valley numerical glacier model that includes englacial and supraglacial debris advection. We ran 120 simulations on a linear bed profile in which a hypothetical steady state debris-free glacier responds to a step increase of surface debris deposition. Simulated glaciers advance to steady states in which ice accumulation equals ice ablation, and debris input equals debris loss from the glacier terminus. Our model and parameter selections can produce 2-fold increases in glacier length. Debris flux onto the glacier and the relationship between debris thickness and melt rate strongly control glacier length. Debris deposited near the equilibrium-line altitude, where ice discharge is high, results in the greatest glacier extension when other debris-related variables are held constant. Debris deposited near the equilibrium-line altitude re-emerges high in the ablation zone and therefore impacts melt rate over a greater fraction of the glacier surface. Continuous debris cover reduces ice discharge gradients, ice thickness gradients, and velocity gradients relative to initial debris-free glaciers. Debris-forced glacier extension decreases the ratio of accumulation zone to total glacier area (AAR). Our simulations reproduce the "general trends" between debris cover, AARs, and glacier surface velocity patterns from modern debris-covered glaciers. We provide a quantitative, theoretical foundation to interpret the effect of debris cover on the moraine record, and to assess the effects of climate change on debris-covered glaciers.

Spatial variability in mass loss of glaciers in the Everest region, central Himalayas, between 2000 and 2015

Abstract: . Region-wide averaging of Himalayan glacier mass change has masked any catchment or glacier-scale variability in glacier recession; thus the role of a number of glaciological processes in glacier wastage remains poorly understood. In this study, we quantify mass loss rates over the period 2000–2015 for 32 glaciers across the Everest region and assess how future ice loss is likely to differ depending on glacier hypsometry. The mean mass balance of all 32 glaciers in our sample was −0.52 ± 0.22 m water equivalent (w.e.) a−1. The mean mass balance of nine lacustrine-terminating glaciers (−0.70 ± 0.26 m w.e. a−1) was 32 % more negative than land-terminating, debris-covered glaciers (−0.53 ± 0.21 m w.e. a−1). The mass balance of lacustrine-terminating glaciers is highly variable (−0.45 ± 0.13 to −0.91 ± 0.22 m w.e. a−1), perhaps reflecting glacial lakes at different stages of development. To assess the importance of hypsometry on glacier response to future temperature increases, we calculated current (Dudh Koshi – 0.41, Tama Koshi – 0.43, Pumqu – 0.37) and prospective future glacier accumulation area Ratios (AARs). IPCC AR5 RCP 4.5 warming (0.9–2.3 °C by 2100) could reduce AARs to 0.29 or 0.08 in the Tama Koshi catchment, 0.27 or 0.17 in the Dudh Koshi catchment and 0.29 or 0.18 in the Pumqu catchment. Our results suggest that glacial lake expansion across the Himalayas could expedite ice mass loss and the prediction of future contributions of glacial meltwater to river flow will be complicated by spatially variable glacier responses to climate change.

Evaluation of snow cover and snow depth on the Qinghai–Tibetan Plateau derived from passive microwave remote sensing

Abstract: . Snow cover on the Qinghai–Tibetan Plateau (QTP) plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW) remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow depth across the QTP, new algorithms should be developed to retrieve snow depth with higher spatial resolution and should consider the variation in brightness temperatures at different frequencies emitted from ground with changing ground features.

Glacier change and glacial lake outburst flood risk in the Bolivian Andes

Abstract: . Glaciers of the Bolivian Andes represent an important water resource for Andean cities and mountain communities, yet relatively little work has assessed changes in their extent over recent decades. In many mountain regions, glacier recession has been accompanied by the development of proglacial lakes, which can pose a glacial lake outburst flood (GLOF) hazard. However, no studies have assessed the development of such lakes in Bolivia despite recent GLOF incidents here. Our mapping from satellite imagery reveals an overall areal shrinkage of 228.1 ± 22.8 km2 (43.1 %) across the Bolivian Cordillera Oriental between 1986 and 2014. Shrinkage was greatest in the Tres Cruces region (47.3 %), followed by the Cordillera Apolobamba (43.1 %) and Cordillera Real (41.9 %). A growing number of proglacial lakes have developed as glaciers have receded, in accordance with trends in most other deglaciating mountain ranges, although the number of ice-contact lakes has decreased. The reasons for this are unclear, but the pattern of lake change has varied significantly throughout the study period, suggesting that monitoring of future lake development is required as ice continues to recede. Ultimately, we use our 2014 database of proglacial lakes to assess GLOF risk across the Bolivian Andes. We identify 25 lakes that pose a potential GLOF threat to downstream communities and infrastructure. We suggest that further studies of potential GLOF impacts are urgently required.

Surge dynamics and lake outbursts of Kyagar Glacier, Karakoram

Abstract: . 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.

Using a fixed-wing UAS to map snow depth distribution: an evaluation at peak accumulation

Abstract: . We investigate snow depth distribution at peak accumulation over a small Alpine area ( ∼ 0.3 km2) using photogrammetry-based surveys with a fixed-wing unmanned aerial system (UAS). These devices are growing in popularity as inexpensive alternatives to existing techniques within the field of remote sensing, but the assessment of their performance in Alpine areas to map snow depth distribution is still an open issue. Moreover, several existing attempts to map snow depth using UASs have used multi-rotor systems, since they guarantee higher stability than fixed-wing systems. We designed two field campaigns: during the first survey, performed at the beginning of the accumulation season, the digital elevation model of the ground was obtained. A second survey, at peak accumulation, enabled us to estimate the snow depth distribution as a difference with respect to the previous aerial survey. Moreover, the spatial integration of UAS snow depth measurements enabled us to estimate the snow volume accumulated over the area. On the same day, we collected 12 probe measurements of snow depth at random positions within the case study to perform a preliminary evaluation of UAS-based snow depth. Results reveal that UAS estimations of point snow depth present an average difference with reference to manual measurements equal to −0.073 m and a RMSE equal to 0.14 m. We have also explored how some basic snow depth statistics (e.g., mean, standard deviation, minima and maxima) change with sampling resolution (from 5 cm up to ∼ 100 m): for this case study, snow depth standard deviation (hence coefficient of variation) increases with decreasing cell size, but it stabilizes for resolutions smaller than 1 m. This provides a possible indication of sampling resolution in similar conditions.

How much can we save? Impact of different emission scenarios on future snow cover in the Alps

Abstract: . This study focuses on an assessment of the future snow depth for two larger Alpine catchments. Automatic weather station data from two diverse regions in the Swiss Alps have been used as input for the Alpine3D surface process model to compute the snow cover at a 200 m horizontal resolution for the reference period (1999–2012). Future temperature and precipitation changes have been computed from 20 downscaled GCM-RCM chains for three different emission scenarios, including one intervention scenario (2 °C target) and for three future time periods (2020–2049, 2045–2074, 2070–2099). By applying simple daily change values to measured time series of temperature and precipitation, small-scale climate scenarios have been calculated for the median estimate and extreme changes. The projections reveal a decrease in snow depth for all elevations, time periods and emission scenarios. The non-intervention scenarios demonstrate a decrease of about 50 % even for elevations above 3000 m. The most affected elevation zone for climate change is located below 1200 m, where the simulations show almost no snow towards the end of the century. Depending on the emission scenario and elevation zone the winter season starts half a month to 1 month later and ends 1 to 3 months earlier in this last scenario period. The resulting snow cover changes may be roughly equivalent to an elevation shift of 500–800 or 700–1000 m for the two non-intervention emission scenarios. At the end of the century the number of snow days may be more than halved at an elevation of around 1500 m and only 0–2 snow days are predicted in the lowlands. The results for the intervention scenario reveal no differences for the first scenario period but clearly demonstrate a stabilization thereafter, comprising much lower snow cover reductions towards the end of the century (ca. 30 % instead of 70 %).

Intercomparison of snow density measurements: bias, precision, and vertical resolution

Abstract: . Density is a fundamental property of porous media such as snow. A wide range of snow properties and physical processes are linked to density, but few studies have addressed the uncertainty in snow density measurements. No study has yet quantitatively considered the recent advances in snow measurement methods such as micro-computed tomography (μCT) in alpine snow. During the MicroSnow Davos 2014 workshop, different approaches to measure snow density were applied in a controlled laboratory environment and in the field. Overall, the agreement between μCT and gravimetric methods (density cutters) was 5 to 9 %, with a bias of −5 to 2 %, expressed as percentage of the mean μCT density. In the field, density cutters overestimate (1 to 6 %) densities below and underestimate (1 to 6 %) densities above a threshold between 296 to 350 kg m−3, dependent on cutter type. Using the mean density per layer of all measurement methods applied in the field (μCT, box, wedge, and cylinder cutters) and ignoring ice layers, the variation between the methods was 2 to 5 % with a bias of −1 to 1 %. In general, our result suggests that snow densities measured by different methods agree within 9 %. However, the density profiles resolved by the measurement methods differed considerably. In particular, the millimeter-scale density variations revealed by the high-resolution μCT contrasted the thick layers with sharp boundaries introduced by the observer. In this respect, the unresolved variation, i.e., the density variation within a layer which is lost by lower resolution sampling or layer aggregation, is critical when snow density measurements are used in numerical simulations.

Snow fracture in relation to slab avalanche release: critical state for the onset of crack propagation

Abstract: . The failure of a weak snow layer buried below cohesive slab layers is a necessary, but insufficient, condition for the release of a dry-snow slab avalanche. The size of the crack in the weak layer must also exceed a critical length to propagate across a slope. In contrast to pioneering shear-based approaches, recent developments account for weak layer collapse and allow for better explaining typical observations of remote triggering from low-angle terrain. However, these new models predict a critical length for crack propagation that is almost independent of slope angle, a rather surprising and counterintuitive result. Based on discrete element simulations we propose a new analytical expression for the critical crack length. This new model reconciles past approaches by considering for the first time the complex interplay between slab elasticity and the mechanical behavior of the weak layer including its structural collapse. The crack begins to propagate when the stress induced by slab loading and deformation at the crack tip exceeds the limit given by the failure envelope of the weak layer. The model can reproduce crack propagation on low-angle terrain and the decrease in critical length with increasing slope angle as modeled in numerical experiments. The good agreement of our new model with extensive field data and the ease of implementation in the snow cover model SNOWPACK opens a promising prospect for improving avalanche forecasting.

Response of seasonal soil freeze depth to climate change across China

Abstract: . The response of seasonal soil freeze depth to climate change has repercussions for the surface energy and water balance, ecosystems, the carbon cycle, and soil nutrient exchange. Despite its importance, the response of soil freeze depth to climate change is largely unknown. This study employs the Stefan solution and observations from 845 meteorological stations to investigate the response of variations in soil freeze depth to climate change across China. Observations include daily air temperatures, daily soil temperatures at various depths, mean monthly gridded air temperatures, and the normalized difference vegetation index. Results show that soil freeze depth decreased significantly at a rate of −0.18 ± 0.03 cm yr−1, resulting in a net decrease of 8.05 ± 1.5 cm over 1967–2012 across China. On the regional scale, soil freeze depth decreases varied between 0.0 and 0.4 cm yr−1 in most parts of China during 1950–2009. By investigating potential climatic and environmental driving factors of soil freeze depth variability, we find that mean annual air temperature and ground surface temperature, air thawing index, ground surface thawing index, and vegetation growth are all negatively associated with soil freeze depth. Changes in snow depth are not correlated with soil freeze depth. Air and ground surface freezing indices are positively correlated with soil freeze depth. Comparing these potential driving factors of soil freeze depth, we find that freezing index and vegetation growth are more strongly correlated with soil freeze depth, while snow depth is not significant. We conclude that air temperature increases are responsible for the decrease in seasonal freeze depth. These results are important for understanding the soil freeze–thaw dynamics and the impacts of soil freeze depth on ecosystem and hydrological process.