The Cryosphere Discussions

Published by European Geosciences Union
Online ISSN: 1994-0432
We report for the first time on the discovery of calcium carbonate crystals as ikaite (CaCO3*6H2O) in sea ice from the Arctic (Kongsfjorden, Svalbard). This finding demonstrates that the precipitation of calcium carbonate during the freezing of sea ice is not restricted to the Antarctic, where it was observed for the first time in 2008. This finding is an important step in the quest to quantify its impact on the sea ice driven carbon cycle and should in the future enable improvement parametrization sea ice carbon models.
Glaciers are important water storages on a seasonal and long-term time scale. Where high mountains are surrounded by arid lowlands, glacier runoff is an important source of water during the growing season. This situation can be found in the Altay mountains in Southern Siberia, where the recent glacierization of >700 km<sup>2</sup> is subject to continuous mass loss, even though the shrinking is comparably slow. The glacier retreat is accompanied by an extension of supra-glacial moraine, which itself strongly influences ablation rates. To quantify these effects, the spatial evolution of debris cover since 1952 was analysed for three glaciers in the North Chuya Ridge using satellite and airborne imagery. In summer 2007, an ablation experiment was carried out on debris covered parts of Maliy Aktru glacier. Thermistors in different depths within the moraine provided data to calculate thermal resistance of the debris. A set of ablation stakes was installed at locations with differing debris thickness and observed regularly throughout the entire melt season. Air temperature from an AWS was used to calculate degree day factors in dependence of the debris thickness. To take into account the shading effect of surrounding walls and peaks, the potential solar radiation and its evolution throughout the summer was determined from a digital elevation model. This allows us to extrapolate our measurements from Maliy Aktru to the other two glaciers of the Aktru basin and to estimate basin melt rates. In addition accumulated ice melt was derived for 12 glaciers in the North Chuya Range. Changes in summer runoff from the 1960s are compared to the results from our melt model and the evolution of debris cover is analysed in respect to the melt activity.
Schematic diagram showing different glacio-hydrological systems of the Himalaya and altitudinal distribution of summer and winter precipitation. Hypothesis proposed suggests varying river flow response to the cryospheric/climatic changes. (A) River flow changes are governed by the variations in summer and winter precipitation with higher glacier component during low summer runoff. (B) River flow changes are depended on variations in the snow cover characteristics and glacier melting. (C) Rivers are entirely fed by glaciers and permafrost melting and flow variation is governed directly by temperature variation.  
(A) Discharge anomalies of River Satluj at Bhakra from 1920–2004 and (B) All- India summer monsoon rainfall anomalies from 1871–2004. Shaded bars show stationery/advancement periods of many glaciers in the Himalaya and Trans-Himalayan region. Period between 1945 to 1960 experienced high discharge associated with strong monsoon. Since 70's widespread recession of glaciers are reported from the region, but with reduced runoff as compared to 1950's. (Data source: Haryana Irrigation Department, 2001, Singh and Jain, 2002,  
A large number of Himalayan glacier catchments are under the influence of humid climate with snowfall in winter (November–April) and South-West monsoon in summer (June–September) dominating the regional hydrology. Such catchments are defined as &apos;&apos;Himalayan catchment&apos;&apos;, where the glacier melt water contributes to the river flow during the period of annual high flows produced by the monsoon. Other two major glacio-hydrological regimes of the Himalaya are winter snow dominated Alpine catchments of the Kashmir and Karakoram region and cold-arid regions of the Ladakh mountain range. Factors influencing the river flow variations in a &apos;&apos;Himalayan catchment&apos;&apos; were studied in a micro scale glacier catchment in the Garhwal Himalaya, covering an area of 77.8 km2. Discharge data generated from three hydrometric stations established at different altitudes of the Din Gad stream during the summer ablation period of 1998, 1999, 2000, 2001, 2003 and 2004. These data has been analysed along with winter/summer precipitation, temperature and mass balance data of the Dokriani glacier to study the role of the glacier and precipitation in determining the runoff variations along the stream continuum from the glacier snout to 2360 m a.s.l. Study shows that the inter-annual runoff variations in a &apos;&apos;Himalayan glacier catchment&apos;&apos; is directly linked with the precipitation rather than mass balance changes of the glacier. Study suggest that warming induced initial increase of glacier degraded runoff and subsequent decline is a glaciers mass balance response and cannot be translated as river flow response in a &apos;&apos;Himalayan catchment&apos;&apos; as suggested by the IPCC, 2007. Study also suggest that the glacier runoff critically influence the headwater river flows during the years of low summer discharge and proposes that the Himalayan catchment could experience higher river flows and positive glacier mass balance regime together in association with strong monsoon. This paper intended to highlight the importance of creating credible knowledge on the Himalayan cryospheric processes to develop a global outlook on river flow response to cryospheric change and locally sustainable water resources management strategies.
Box-and-whisker plots for simulated specific sediment and organic carbon yields from n = 21 345 
Many mountain belts sustain prolonged snow cover for parts of the year, although enquiries into rates of erosion in these landscapes have focused almost exclusively on the snow-free periods. This raises the question of whether annual snow cover contributes significantly to modulating rates of erosion in high-relief terrain. In this context, the sudden release of snow avalanches is a frequent and potentially relevant process, judging from the physical damage to subalpine forest ecosystems, and the amount of debris contained in avalanche deposits. To quantitatively constrain this visual impression and to expand the sparse existing literature, we sampled sediment concentrations of n = 28 river-spanning snow-avalanche deposits (snow bridges) in the eastern Swiss Alps, and infer an orders-of-magnitude variability in specific fine sediment and organic carbon yields (1.8 to 830 t km-2 yr-1, and 0.04 to 131 t C km-2 yr-1, respectively). A Monte Carlo simulation demonstrates that, with a minimum of free parameters, such variability is inherent to the geometric scaling used for computing specific yields. Moreover, the widely applied method of linearly extrapolating plot-scale sample data may be prone to substantial under- or over-estimates. A comparison of our inferred yields with previously published work demonstrates the relevance of wet snow avalanches as prominent agents of soil erosion and transporters of biogeochemical constituents to mountain rivers. Given that a number of snow bridges persisted below the insulating debris cover well into the summer months, snow-avalanche deposits also contribute to regulating in-channel sediment and organic debris storage on seasonal timescales. Finally, our results underline the potential shortcomings of neglecting erosional processes in the winter and spring months in mountainous terrain subjected to prominent snow cover.
Outlet glacier catchments. D = Daugaard Jensen, K = Kangerdlugssuaq, H = Helheim, I = Ikertivaq, G = Gyldenlove, J = Jakobshavn Isbrae, R = Rink Isbrae (including Umiamako and Ingia Isbrae), KO = Kong Oscar, P = Petermann, N = Nioghalvfjerdsbrae. Dates for the sample speed map images are listed in Table 1, and the velocity data extraction points are marked with X's. Shaded relief and bathymetry based on the International Bathymetric Chart of the Arctic Ocean (Jakobsson et al., 2008).
Difference in mean summer temperature between 1982-1995 and 1996-2010. Over land: ERA-interim summer (June-August) 2 m air temperature. Over ocean: OISST summer (July-September) sea surface temperature.
Surface flow speeds (red squares) and frontal positions (blue triangles) for the Kong Oscar, Petermann, Nioghalvfjerdsbrae and Daugaard Jensens glaciers (see Fig. 1 for locations).
The Greenland ice sheet is experiencing increasing rates of mass loss, the majority of which results from changes in discharge from tidewater glaciers. Both atmospheric and ocean drivers have been implicated in these dynamic changes but understanding the nature of the response has been hampered by the lack of measurements of glacier flow rates predating the recent period of warming. Here, using Landsat-5 data from 1985 onwards, we extend back in time the record of surface velocities and ice-front position for 16 of Greenland's most significant glaciers, and compare these to more recent data from Landsat-7 and SAR. Climate re-analysis and sea-surface temperatures from 1982 show that since 1995 most of Greenland and its surrounding oceans have experienced significant overall warming, and a switch to a warming trend. During the earlier period of climate consistency, major tidewater outlet glaciers around Greenland, including Kangerdlugssuaq and Helheim, were dynamically stable. Since the mid-1990s, glacier discharge has consistently been both greater and more variable, adding weight to the hypothesis that dynamic change is a rapid response to climate forcing. Both air and ocean temperatures in this region are predicted to continue to warm, and will undoubtedly drive further change in outlet glacier discharge.
Many tidewater glaciers in Greenland are known to have undergone significant retreat during the last century following their Little Ice Age maxima. Where it is possible to reconstruct glacier change over this period, they provide excellent records for comparison to climate records, and calibration/validation for numerical models. These records therefore allow tests of numerical models that seek to simulate tidewater glacier behaviour over multi-decadal to centennial timescales. Here we present a detailed record of behaviour from Kangiata Nunaata Sermia (KNS), SW Greenland, between 1859-2012 and compare it against available oceanographic and atmospheric temperature variability between 1871-2012. We also use these records to evaluate the ability of a well-established one-dimensional flow-band model to replicate behaviour for the observation period. The record of terminus change demonstrates that KNS has advanced/retreated in phase with atmosphere and ocean climate anomalies averaged over multi-annual to decadal timescales. Results from an ensemble of model runs demonstrate that observed dynamics can be replicated, with changes in atmospheric forcing not needing to be offset by changes in oceanic forcing sensitivity. Furthermore, successful runs always require a significant atmospheric forcing component, while an oceanic forcing component is not always needed. Although the importance of oceanic forcing cannot be discounted, these results demonstrate that changes in atmospheric forcing are likely to be a primary driver of the terminus fluctuations of KNS from 1859-2012.
We used Interprovincial Boundary Commission Survey (IBCS) maps of the Alberta–British Columbia (BC) border (1903–1924), BC Terrain Resource Information Management (TRIM) data (1982–1987), and Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery (2000–2002 and 2006) to document planimetric changes in glacier cover in the Central and Southern Canadian Rocky Mountains between 1919 and 2006. Total glacierized area decreased by 590 ± 100 km<sup>2</sup> (40 ± 7%), with 17 of 523 glaciers disappearing and 124 glaciers fragmenting into multiple ice masses. Fourteen of the glaciers that disappeared were less than 0.5 km<sup>2</sup>, and glaciers smaller than 1.0 km<sup>2</sup> experienced the greatest relative area loss (64 ± 17%). Variation in area loss increased with small glaciers, suggesting local topographic setting controls the response of these glaciers to climate change. Absolute area loss negatively correlates with slope and minimum elevation, and relative area change negatively correlates with mean and median elevations. Similar average rates of area change were observed for the periods 1919–1985 and 1985–2001, at −6.3 ± 0.9 km<sup>2</sup> yr<sup>−1</sup> (−0.4 ± 0.1% yr<sup>−1</sup>) and −5.0 ± 0.5 km<sup>2</sup> yr<sup>−1</sup> (−0.3 ± 0.1% yr<sup>−1</sup>), respectively. The rate of area loss significantly increased for the period 2001–2006, −19.3 ± 2.4 km<sup>2</sup> yr<sup>−1</sup> (−1.3 ± 0.2% yr<sup>−1</sup>), with continued high minimum and accumulation season temperature anomalies and variable precipitation anomalies.
Mass balance variations of Glaciar San Rafael, the most equatorial tidewater glacier in the North Patagonian Icefield, are reconstructed over the period 1950–2005 using NCEP-NCAR reanalysis climate data together with sparse, local historical observations of air temperature, precipitation, accumulation, ablation, thinning, calving, and glacier retreat. The combined observations over the past 50 yr indicate that Glaciar San Rafael has thinned and retreated since 1959, with a total mass loss of ~22 km<sup>3</sup> of ice equivalent. Over that period, except for a short period of cooling from 1998–2003, the climate has become progressively warmer and drier, which has resulted primarily in pervasive thinning of the glacier surface and a decrease in calving rates, with only minor acceleration in retreat of the terminus. A comparison of calving fluxes derived from the mass balance variations and from theoretical calving and sliding laws suggest that calving rates are inversely correlated with retreat rates, and that terminus geometry is more important than changes in balance fluxes to the terminus in driving calving dynamics. For Glaciar San Rafael, regional climate warming has not yet resulted in the significant changes in glacier length seen in other calving glaciers in the region, emphasizing the complex dynamics between climate inputs, topographic constraints and glacier response in calving glacier systems.
Sea ice extent for (a) March, (b) June, (c) September for the Sea Ice Index (blue) and original (dashed lines) and adjusted (solid lines) XPM (green) and Hadley (red). March shows good agreement between Hadley and the satellite products and thus little adjustment, but a clear discontinuity between Hadley and SII is apparent in the June and September fields.  
Monthly trends for the Hadley period (1953–1978), the satellite period (1979–2011), and the overall record (1953–2011) in % decade −1 . The final separated points on the right indicate the annual average (Ann). The error bars represent the 1σ range of the trend.  
The monthly standardized anomaly for January 1953 through December 2011, relative to 1981–2010 average period. Each value is the monthly anomaly normalized by the standard deviation for the month. Monthly values are in dark blue; a 12-month running mean is overlaid in pink.  
Observations for passive microwave satellite sensors have provided a continuous and consistent record of sea ice extent since late 1978. Earlier records, compiled from ice charts and other sources exist, but are not consistent with the satellite record. Here, a method is presented to adjust a compilation of pre-satellite sources to remove discontinuities between the two periods and create a more consistent combined 59-yr timeseries spanning 1953–2011. This adjusted combined timeseries shows more realistic behavior across the transition between the two individual timeseries and thus provides higher confidence in trend estimates from 1953 through 2011. The long-term timeseries is used to calculate linear trend estimates and compare them with trend estimates from the satellite period. The results indicate that trends through the 1960s were largely positive (though not statistically significant) and then turned negative by the mid-1970s and have been consistently negative since, reaching statistical significance (at the 95% confidence level) by the late 1980s. The trend for September (when Arctic extent reaches its seasonal minimum) for the satellite period, 1979–2011 is –12.9% decade<sup>–1</sup>, nearly double the 1953–2011 trend of –6.8% decade<sup>–1</sup> (relative to the 1981–2010 mean). The recent decade (2002–2011) stands out as a period of persistent decline in ice extent. The combined 59-yr timeseries puts the strong observed decline in the Arctic sea ice cover during 1979–2011 in a longer-term context and provides a useful resource for comparisons with historical model estimates.
Morphometric properties of the 33-glacier subset. 
Cariboo Mountains subregions showing subset of 33 glaciers, including extents for 1952, 1970, 1985, and 2005. Panels show 2 from left to righttheCastle, Quanstrom, and Premier subregions. Numerical glacier identification, numbered by 2005 surface area from 3 smallest to largest, corresponds to that of Tables 2 and 4. 4  Cariboo Mountains subregions showing subset of 33 glaciers, including extents for 1952, 1970, 1985, and 2005. Panels show from left to right the Castle, Quanstrom, and Premier subregions. Numerical glacier identification, numbered by 2005 surface area from smallest to largest, corresponds to that of Tables 2 and 4.
Box-and-whisker plots showing the maximum, interquartile range, median, and 2 minimum of surface elevation residuals of 275 checkpoints. Checkpoints are used to 3 determine relative accuracy of stereo models and bias correctionfor measurement of 4 surface elevation change of glaciers in the Castle and Quanstrom regions in three periods. 5 6
Average annual thickness change in meters of water equivalent. 
We calculated dimensional change for 33 glaciers in the Cariboo Mountains of British Columbia for the latter half of the twentieth century. All glaciers receded during the period 1952–2005; area retreat averaged −0.19 ± 0.05% a−1. From 1952 to 1985, nine glaciers advanced. Following 1985, retreat rates accelerated to −0.41 ± 0.12% a−1. Thinning rates likewise accelerated, from −0.14 ± 0.04 m w.e. a−1 (1952–1985) to −0.50 ± 0.07 m w.e. a−1 for the period 1985–2005. Temperatures increased from the earlier to the latter period for the ablation (+0.38 °C) and accumulation (+0.87 °C) seasons, and average precipitation decreased, particularly in the accumulation season (−32 \unit{mm}, −3.2%). Our comparison of surface area change with glacier morphometry corroborates previous studies that show primary relations between extent change and surface area. We also find, however, that the strength and sign of these relations varied for different epochs.
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 was acquired from 1961 to 1991 are compared to the swissALTI3D DEMs from 2008–2011 combined with the new Swiss Glacier Inventory SGI2010. Due to the significant differences in acquisition date of the source data used, resulting 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 2700–2800 m a.s.l. and remarkable even above 3500 m a.s.l. The mean geodetic mass balance is −0.62 ± 0.03 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 ± 0.97 km3.
With the aim to force an ice dynamical model, the Greenland ice sheet (GrIS) surface mass balance (SMB) was modelled at different spatial resolutions (15–50 km) for the period 1990–2010, using the regional climate model MAR (Modèle Atmosphérique Régional) forced by the ERA-INTERIM reanalysis. This comparison revealed that (i) the inter-annual variability of the SMB components is consistent within the different spatial resolutions investigated, (ii) the MAR model simulates heavier precipitation on average over the GrIS with diminishing spatial resolution, and (iii) the SMB components (except precipitation) can be derived from a simulation at lower resolution with an ''intelligent'' interpolation. This interpolation can also be used to approximate the SMB components over another topography/ice sheet mask of the GrIS. These results are important for the forcing of an ice dynamical model, needed to enable future projections of the GrIS contribution to sea level rise over the coming centuries.
Time series of mean monthly total ice, multi-year ice (MYI) and first-year ice (FYI) area (km 2 ) within the Canadian Arctic Archipelago for June to September (A-D) from 1968-2012.
Spatial distribution of June and September total ice and multi-year ice (MYI) concentration anomalies (tenths) for 2004, 1997, 1979 and 1972 within the Canadian Arctic Archipelago (A-D). Anomalies calculated with respect to the 1981-2010 climatology.
Weekly time series of total ice (A), multi-year (MYI) (B) and first year ice (FYI) (C) area (km 2 ) for 1998, 2007, 2011 and 2012 in the Canadian Arctic Archipelago.
Spatial distribution of mean June to September sea level pressure (SLP; mb) anomalies for 2012, 2011, 2007 and 1998 (A-D). Anomalies calculated with respect to the 1981-2010 climatology.
Time series of the length of the navigation season for the northern route of the Northwest Passage and mean multi-year ice (MYI) area within the region, 1968-2012. The navigation season is defined by the Canadian Ice Service as a 17-week time window from 25 June to 15 October.
Record low mean September sea ice area in the Canadian Arctic Archipelago (CAA) was observed in 2011 (146 × 103 km2), a level that was nearly exceeded in 2012 (150 × 103 km2). These values eclipsed previous September records set in 1998 (200 × 103 km2) and 2007 (220 × 103 km2) and are ∼60% lower than the 1981–2010 mean September climatology. In this study, the driving processes contributing to the extreme light years of 2011 and 2012 were investigated, compared to previous extreme minima of 1998 and 2007, and contrasted against historic summer seasons with above average September ice area. The 2011 minimum was driven by positive July surface air temperature (SAT) anomalies that facilitated rapid melt, coupled with atmospheric circulation in July and August that restricted multi-year ice (MYI) inflow from the Arctic Ocean into the CAA. The 2012 minimum was also driven by positive July SAT anomalies (with coincident rapid melt) but further ice decline was temporarily mitigated by atmospheric circulation in August and September which drove Arctic Ocean MYI inflow into the CAA. Atmospheric circulation was comparable between 2011 and 1998 (impeding Arctic Ocean MYI inflow) and 2012 and 2007 (inducing Arctic Ocean MYI inflow). However, evidence of both preconditioned thinner Arctic Ocean MYI flowing into CAA and maximum landfast first-year ice (FYI) thickness within the CAA was more apparent leading up to 2011 and 2012 than 1998 and 2007. The rapid melt process in 2011 and 2012 was more intense than observed in 1998 and 2007 because of the thinner ice cover being more susceptible to positive SAT forcing. The thinner sea ice cover within the CAA in recent years has also helped counteract the processes that facilitate extreme heavy ice years. The recent extreme light years within the CAA are associated with a longer navigation season within the Northwest Passage.
Accurate measurements and simulations of Greenland Ice Sheet (GrIS) surface albedo are essential, given the crucial role of surface albedo in modulating the amount of absorbed solar radiation and meltwater production. In this study, we assess the spatio-temporal variability of GrIS albedo (during June, July, and August) for the period 2000–2013. We use two remote sensing products derived from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS), as well as outputs from the Modèle Atmosphérique Régionale (MAR) regional climate model (RCM) and data from in situ automatic weather stations. Our results point to an overall consistency in spatiotemporal variability between remote sensing and RCM albedo, but reveal a difference in mean albedo of up to ~0.08 between the two remote sensing products north of 70° N. At low elevations, albedo values simulated by the RCM are positively biased with respect to remote sensing products and in situ measurements by up to ~0.1 and exhibit low variability compared with observations. We infer that these differences are the result of a positive bias in simulated bare-ice albedo. MODIS albedo, RCM outputs and in situ observations consistently point to a~decrease in albedo of −0.03 to −0.06 per decade over the period 2003–2013 for the GrIS ablation zone (where there is a net loss of mass at the GrIS surface). Nevertheless, satellite products show a~decline in albedo of −0.03 to −0.04 per decade for regions within the accumulation zone (where there is a net gain of mass at the surface) that is not confirmed by either the model or in situ observations.
Map of the high Dudh Koshi basin (in grey in the inset map of Nepal and with limits represented by the dashed black line in the main map) where Mera and Pokalde glaciers are located (inside the red squares). Meteorological stations and summits are indicated by dots and triangles respectively. Glaciarized areas from the Randolph Glacier Inventory v2.0 (Arendt et al., 2012) are represented in blue. Maps with red contours are enlargements for Pokalde and Mera glaciers, showing the ablation stake network (grey circles), the accumulation measurement sites (blue squares) and the Mera automatic weather station (AWS-black star). The backgrounds are a SPOT5 image of 4 January 2011 and a Pleiades-1A image of 25 November 2012 for Pokalde and Mera glaciers respectively (CNES 2011-2012/Distribution Astrium). From the Mera central summit (red triangle), Mera glacier flows toward the north and splits into two main branches, referred as Mera and Naulek branches respectively. 
In the Everest region, Nepal, ground-based monitoring programs were started on the debris-free Mera Glacier (27.7° N, 86.9° E; 5.1 km2, 6420 to 4940 m a.s.l.) in 2007 and on the small Pokalde Glacier (27.9° N, 86.8° E; 0.1 km2, 5690 to 5430 m a.s.l., ∼ 25 km North of Mera Glacier) in 2009. These glaciers lie on the southern flank of the central Himalaya under the direct influence of the Indian monsoon and receive more than 80% of their annual precipitation in summer (June to September). Despite a large inter-annual variability with glacier-wide mass balances ranging from −0.77± 0.40 m w.e. in 2011–2012 (Equilibrium-line altitude (ELA) at ∼ 6055 m a.s.l.) to + 0.46 ± 0.40 m w.e. in 2010–2011 (ELA at ∼ 5340 m a.s.l.), Mera Glacier has been shrinking at a moderate mass balance rate of −0.10± 0.40 m w.e. yr−1 since 2007. Ice fluxes measured at two distinct transverse cross sections at ∼ 5350 m a.s.l. and ∼ 5520 m a.s.l. confirm that the mean state of this glacier over the last one or two decades corresponds to a limited mass loss, in agreement with remotely-sensed region-wide mass balances of the Everest area. Seasonal mass balance measurements show that ablation and accumulation are concomitant in summer which in turn is the key season controlling the annual glacier-wide mass balance. Unexpectedly, ablation occurs at all elevations in winter due to wind erosion and sublimation, with remobilized snow likely being sublimated in the atmosphere. Between 2009 and 2012, the small Pokalde Glacier lost mass more rapidly than Mera Glacier with respective mean glacier-wide mass balances of −0.72 and −0.26 ± 0.40 m w.e. yr−1. Low-elevation glaciers, such as Pokalde Glacier, have been usually preferred for in-situ observations in Nepal and more generally in the Himalayas, which may explain why compilations of ground-based mass balances are biased toward negative values compared with the regional mean under the present-day climate.
Monthly averages of U i /U g in % and difference angle α i − α g in four regions of the transpolar ice drift based on data from the D07 array and the PAWS buoys G and I.
During the EU research project DAMOCLES 18 ice buoys were deployed in the region of the Arctic transpolar drift (TPD). Sixteen of them formed a square with 400 km side-length. The measurements lasted from 2007 to 2009. The properties of the TPD and the impact of synoptic weather systems on the ice drift are analysed. Compared to Nansen's drift with the vessel Fram the measured speed of the TPD is here almost twice as fast. Within the TPD, the speed increases by a factor of almost three from the North Pole to the Fram Strait region. The hourly buoy position fixes show that the speed is underestimated by 10–20% if positions were taken at only 1–3 days intervals as it is usually done for satellite drift estimates. The geostrophic wind factor Ui/Ug, i.e. the ratio of ice speed Ui and geostrophic wind speed Ug, in the TPD amounts to 0.012 on average, but with regional and seasonal differences. The constant Ui/Ug relation breaks down for Ug < 5 m s−1. The impact of synoptic weather systems is studied applying a composite method. Cyclones (anticyclones) cause cyclonic (anticyclonic) vorticity and divergence (convergence) of the ice drift. The amplitudes are twice as large for cyclones as for anticyclones. The divergence caused by cyclones corresponds to a 0.1–0.5%/6 h open water area increase based on the composite averages, but reached almost 4% within one day during a strong August 2007 storm. This storm also caused a~long-lasting (over several weeks) rise of Ui and Ui/Ug and changed the ice conditions in a way allowing ocean tidal motion to directly affect ice motion. The consequences of an increasing Arctic storm activity for the ice cover are discussed.
Average melt onset date (day of year) by elevation bands from passive microwave data using the algorithm in Mote and Anderson (1995).  
Cumulative mass anomaly from GRACE updated through September 2012 (Gt).  
Same as Fig. 6d but for the daily bare ice extent (where the snow density is higher then 900 kg m −3 ) in percentage of the GrIS area.  
700 mb geopotential height (m) and wind anomaly for June, July and August 2012 from the NCEP/NCAR Reanalysis data.  
North Atlantic Oscillation (NAO) index from NOAA climate prediction center for June (blue), July (red), and August (green) for the period 1950–2012.  
A combined analysis of remote sensing observations, regional climate model (RCM) outputs and reanalysis data over the Greenland ice sheet provides evidence that multiple records were set during summer 2012. Melt extent was the largest in the satellite era (extending up to ~ 97% of the ice sheet) and melting lasted up to ~ two months longer than the 1979–2011 mean. Model results indicate that near surface temperature was ~ 3 standard deviations (σ) above the 1958–2011 mean, while surface mass balance was ~ 3σ below the mean and runoff was 3.9σ above the mean over the same period. Albedo, exposure of bare ice and surface mass balance also set new records, as did the total mass balance with summer and annual mass changes of, respectively, −627 Gt and −574 Gt, 2σ below the 2003–2012 mean. We identify persistent anticyclonic conditions over Greenland associated with anomalies in the North Atlantic Oscillation (NAO), changes in surface conditions (e.g. albedo) and pre-conditioning of surface properties from recent extreme melting as major driving mechanisms for the 2012 records. Because of self-amplifying positive feedbacks, less positive if not increasingly negative SMB will likely occur should large-scale atmospheric circulation and induced surface characteristics observed over the past decade persist. Since the general circulation models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) do not simulate the abnormal anticyclonic circulation resulting from extremely negative NAO conditions as observed over recent years, contribution to sea level rise projected under different warming scenarios will be underestimated should the trend in NAO summer values continue.
Ice edge based on a 70 % threshold value of the SSM/I-ASI ice concentration during days with cold air outbreaks: 26 March (a) and 4 March (b) 2013. The arrows denote the vertically averaged wind in the boundary layer at the positions of the dropsondes. The lines are HYSPLIT backward trajectories at 10 m height and the dots mark 10 h. Background of (a): MODIS visible image at 12:45 UTC ( realtime.cgi).  
An analysis of SSM/I satellite data reveals that the Whaler's Bay Polynya north of Svalbard was considerably larger in the last three winters from 2012 to 2014 compared to the previous 20 years. This increased polynya size leads to strong atmospheric convection during cold air outbreaks in a region north of Svalbard that typically was ice covered in the last decades. The change in ice cover can strongly influence local temperature conditions. Dropsonde measurements from March 2013 show that the unusual ice conditions generate extreme convective boundary layer heights that are larger than the regional values reported in previous studies.
Histogram of processor time per simulation of the 5000 Monte Carlo simulations. The dashed line denotes the ensemble mean (58 s). The bimodal distribution is due to the greater computational requirements of simulations selected to carry forward into transient forcing following spin-up (B) in comparison to those that were not selected (i.e. discarded following spinup; A).
Modeled (grey lines with ensemble mean in black) and observed (points; Meier et al., 723
Observed (McNabb et al., 2012) and modeled ensemble mean change in ice thickness (∆H) along the Columbia Glacier main flowline (x) between 1957 and 2007, and modeled ensemble mean change in ice thickness between 1957 and 2100.
Due to the abundance of observational datasets collected since the onset of its retreat (c. 1983), Columbia Glacier, Alaska, provides an exciting modeling target. We perform Monte Carlo simulations of the form and flow of Columbia Glacier, using a 1-D (depth-integrated) flowline model, over a wide range of parameter values and forcings. An ensemble filter is imposed following spin-up to ensure that only simulations which accurately reproduce observed pre-retreat glacier geometry are retained; all other simulations are discarded. The selected ensemble of simulations reasonably reproduces numerous highly transient post-retreat observed datasets with a minimum of parameterizations. The selected ensemble mean projection suggests that Columbia Glacier will achieve a new dynamic equilibrium (i.e. "stable") ice geometry c. 2020, by which time iceberg calving rate will have returned to approximately pre-retreat values. Comparison of the observed 1957 and 2007 glacier geometries with the projected 2100 glacier geometry suggests that, by 2007, Columbia Glacier had already discharged ∼83 % of its total sea level rise contribution expected by 2100. This case study therefore highlights the difficulties associated with the future extrapolation of observed glacier mass loss rates that are dominated by iceberg calving.
A transient heat flow model was used to simulate both past and future ground temperatures of mountain permafrost and associated active layer thickness in Southern Norway. The model was forced by reconstructed air temperature starting from 1860, approximately coinciding with the Little Ice Age in the region. The impact of climate warming on mountain permafrost until 2100 is assessed by using downscaled air temperatures from a multi-model ensemble for the A1B scenario. For 13 borehole locations, records over three consecutive years of ground temperatures, air temperatures and snow cover data are available for model calibration and validation. The boreholes are located at different elevations and in substrates with different thermal properties. With an increase of air temperature of ~+1.5 °C over 1860–2010 and an additional warming of +2.8 °C until 2100, we simulate the evolution of ground temperatures for the borehole locations. According to model results, the active-layer thickness has increased since 1860 by 0.5–5 m and >10 m for the sites Juvvasshøe and Tron, respectively. The simulations also suggest that at an elevation of about 1900 m a.s.l. permafrost will degrade until the end of this century with a probability of 55–75% given the chosen A1B scenario.
Changes in map area of 498 glaciers located in the Main Caucasus Ridge (MCR) and on Mt. Elbrus in the Greater Caucasus Mountains (Russia and Georgia) were assessed using multispectral ASTER and panchromatic Landsat imagery with 15 m spatial resolution from 1999–2001 and 2010–2012. Changes in recession rates of glacier snouts between 1987–2001 and 2001–2010 were investigated using aerial photography and ASTER imagery for a sub-sample of glaciers. In total, glacier area declined by 4.7 ± 1.6% or 19.24 km2. Glaciers located in the central and western MCR lost 13.4 km2 (4.6 ± 1.8%) in total or 8.56 km2 (5.0 ± 1.8%) and 4.87 km2 (4.1 ± 1.9%) respectively. Glaciers on Mt. Elbrus, although located at higher elevations, lost 5.8 km2 (4.9 ± 0.7%) of their total area. The recession rates of valley glacier termini increased between 1987–2000/01 and 2010 from 3.8 ± 0.8 m a−1, 3.2 ± 0.9 m a−1 and 8.3 ± 0.8 m a−1 to 11.9 ± 1.1 m a−1, 8.7 ± 1.1 m a−1 and 14.1 ± 1.1 m a−1 in the central and western MCR and on Mt. Elbrus respectively. The highest rate of increase in glacier termini retreat was registered on the southern slope of the central MCR where it has tripled. A positive trend in summer temperatures forced glacier recession and strong positive temperature anomalies of 1998, 2006, and 2010 contributed to the enhanced loss of ice. An increase in accumulation season precipitation observed in the northern MCR since the mid-1980s has not compensated for the effects of summer warming while the negative precipitation anomalies, observed on the southern slope of the central MCR in the 1990s, resulted in stronger glacier wastage.
Permafrost and related thermo-hydro-mechanical processes are thought to influence high alpine rock wall stability, but a lack of field measurements means that the characteristics and processes of rock wall permafrost are poorly understood. To help remedy this situation, in 2005 work began to install a monitoring system at the Aiguille du Midi (3842 m a.s.l). This paper presents temperature records from nine surface sensors (eight years of records) and three 10 m deep boreholes (4 years of records), installed at locations with different surface and bedrock characteristics. In line with previous studies, our temperature data analyses showed that: micro-meteorology controls the surface temperature, active layer thicknesses are directly related to aspect and ranged from
Ikonos satellite sensor specifications. 
Horizontally projected area of the melt relevant surface types on the Koxkar glacier derived from satellite imagery mapping. 
To quantify the ablation processes on a debris covered glacier, a simple distributed ablation model has been developed and applied to a selected glacier. For this purpose, a bundle of field measurements was carried out to collect empirical data. A morphometric analysis of the glacier surface enables us to statistically capture the areal distribution of topographic features that influence debris thickness and consequently ablation. Remote sensing techniques, using high resolution satellite imagery, were used to extrapolate the ground truth results to the whole ablation area and to map and classify melt-relevant surface types. As a result, a practically applicable method is presented, that allows the estimation of ablation on a debris covered glacier by combining field data and remote sensing information. The sub-debris ice ablation accounts for about 19% of the entire ice ablation, while the percentage of the moraine covered area accounts for approximately 32% of the entire glacerized area. Although the ice cliffs occupy only 1.7% of the debris covered area the melt amount accounts for approximately 15% of the total sub-debris ablation and 2.7% of the total ablation respectively. Our study highlights the influence of debris cover on the response of the glacier terminus to climate warming. Due to the fact that melt rates beyond 0.1m of moraine cover are highly restricted the shielding effect of the debris cover dominates over the temperature- and elevation dependence of the ablation in the bare ice case.
MODIS daily reflectance (band 620-670 nm) indicated by the colour bar on the right hand side from 21 August 2012 including the sites of the K-transect relative to the ice margin, the dark zone with lower surface albedo and supraglacial lakes. Flow direction is from East to West. The region is characterised by a lack of lakes at the end of the summer season. 
Velocity records from the 8 sites on the K-transect with 7 years of data. Data are plotted with respect to their mean values (grey line) and sorted from the ice margin (top) to the accumulation area (bottom), 150 km from the margin. Note some similar patterns, increase in winter velocity encircled blue, and dip in autumn velocity encircled red. For S5, S6 and S9 melt based on AWS data is shown for reference on the right axis. 
The progression of the early spring event upglacier. Data are averaged over the period 2005-2012. 
Seasonal cycle of water pressure, melt and velocity at SHR starting in January 2011. Note how the onset of significant melt leads to high magnitude acceleration and a short period of water pressure in excess of the overburden pressure (horizontal grey line), which infers floatation. Later in the ablation season variability in the water pressure remains visible, but the amplitude is diminished. During the ablation season the hydraulic system of channels develops, phase 1, and closes once the melt decreases, phase 3 in the figure. Note that even in autumn and early winter, single melt events affect water pressure and ice velocity. Ablation rates are linearly from zero to 8.5 cm w.e. day −1. The percentages indicate the pressure scaled by the overburden pressure. 
Decadal trends in SMB and velocity from 1990-2012. Data (Van de Wal et al., 2012) suggest a gradual decrease in SMB with superimposed large interannual variability and a decrease in velocity over time. Data for SMB and velocity are weighted mean values over the entire ablation area (19), where the individual sites are weighted proportional to the area they cover along the transect. 
The concept of a positive feedback between ice flow and enhanced melt rates in a warmer climate fuelled the debate regarding the temporal and spatial controls on seasonal ice acceleration. Here we combine melt, basal water pressure, and ice velocity data. We show using twenty years of data covering the whole ablation area that there is no strong feedback between annual ice velocities and melt rates. Annual velocities even slightly decreased with increasing melt. Results also indicate that melt variations are most important for velocity variations in the upper ablation zone up to the equilibrium line altitude. During the extreme melt in 2012 a large velocity response near the equilibrium line was observed, highlighting the possibility of rapidly changing bed conditions in this part of the ice sheet that may lead to a doubling of the annual ice velocity.
Seasonal early and late season distributions of snow-covered area as functions of along-valley distance shown with a late October 2009 image corresponding to the above alongvalley distance.
Seasonal distributions of snow-covered area with respect to elevation in the Fryxell region.
Seasonal comparison of modeled snow water equivalent for each region using an initial depth of 0.25 m. Solid lines represent the 2009-2010 season and dashed lines represent the 2010-2011 season.
Accumulated snow in the McMurdo Dry Valleys, while limited, has great ecological significance to subnivian soil environments. Though sublimation dominates the ablation process in this region, measurable increases in soil moisture and insulation from temperature extremes provide more favorable conditions with respect to subnivian soil communities. While precipitation is not substantial, significant amounts of snow can accumulate, via aeolian redistribution, in topographic lees along the valley bottoms, forming thousands of discontinuous snow patches. These patches have the potential to act as significant sources of local melt water, controlling biogeochemical cycling and the landscape distribution of microbial communities. Therefore, determining the spatial and temporal dynamics of snow at multiple scales is imperative to understanding the broader ecological role of snow in this region. High-resolution satellite imagery acquired during the 2009–2010 and 2010–2011 austral summers was used to quantify the distribution of snow across Taylor and Wright Valleys. Extracted snow-covered area from the imagery was used as the basis for assessing seasonal variability and seasonal controls on accumulation and ablation of snow at multiple scales. In addition, fifteen 1 km2 plots (3 in each of 5 study regions) were selected to assess the prevalence of snow cover at finer spatial scales. Results confirm that snow patches tend to form in the same locations each year with some minor deviations observed. At the snow-patch scale, neighboring patches often exhibit considerable differences in aerial ablation rates, and particular snow patches do not reflect trends for snow-covered area observed at the landscape scale. These differences are presumably related to microtopographic influences over snow depth and exposure. This highlights the importance of both the landscape and snow-patch scales in assessing the effects of snow cover on biogeochemical cycling and microbial communities.
(a) Observed (blue line) versus modelled (red line) cumulative ice ablation at S5 and S6. Cumulative ice melt from annual stake measurements are indicated by triangles. (b) Observed versus modelled 10-day average ice melt rates at S5 (red dots) and S6 (blue dots). The dashed lines are linear regressions on the data.
Average seasonal cycle of melt frequency at S5 (red line), S6 (blue line) and S9 (green line). Error bars indicate standard deviation for the 7-year period.
Average seasonal cycle of albedo (a) (error bars indicate standard deviation for the 7-year period) and average seasonal cycle of the albedo standard deviation (SD) (b).
Cumulative energy fluxes (10 3 MJ m −2 ) during melt for S5 (a), S6 (b) and S9 (c).
Variation with distance from ice margin of (a): fraction of total melt energy provided by SEB components (error bar indicate standard deviation from year to year) and (b): regression slope of anomalies of cumulative monthly SEB energy components with anomalies of cumulative monthly melt (error bar represents standard deviation from regression performed on subsets of the data).  
We present the seasonal cycle and interannual variability of the surface energy balance (SEB) in the ablation zone of the west Greenland ice sheet, using seven years (September 2003–August 2010) of hourly observations from three automatic weather stations (AWS). The AWS are situated along the 67° N latitude circle at elevations of 490 m a.s.l. (S5), 1020 m a.s.l. (S6) and 1520 m a.s.l. (S9) at distances of 6, 38 and 88 km from the ice sheet margin. The hourly AWS data are fed into a model that calculates all SEB components and melt rate; the model allows for shortwave radiation penetration in ice and time-varying surface momentum roughness. Snow depth is prescribed from albedo and sonic height ranger observations. Modelled and observed surface temperatures for non-melting conditions agree very well, with RMSE's of 0.97–1.26 K. Modelled and observed ice melt rates at the two lowest sites also show very good agreement, both for total cumulative and 10-day cumulated amounts. Melt frequencies and melt rates at the AWS sites are discussed. Although absorbed shortwave radiation is the most important energy source for melt at all three sites, interannual melt variability at the lowest site is driven mainly by variability in the turbulent flux of sensible heat. This is explained by the quasi-constant summer albedo in the lower ablation zone, limiting the influence of the melt-albedo feedback, and the proximity of the snow free tundra, which heats up considerably in summer.
Since the original formulation of the positive-degree-day (PDD) method, different PDD calibrations have been proposed in the literature in response to the increasing number of observations. Although these formulations provide a satisfactory description of the present-day Greenland geometry, they have not all been tested for paleo ice sheets. Using the climate-ice sheet model CLIMBER-GRISLI coupled with different PDD models, we evaluate how the parameterization of the ablation may affect the evolution of Northern Hemisphere ice sheets in the transient simulations of the last glacial cycle. Results from fully coupled simulations are compared to time-slice experiments carried out at different key periods of the last glacial period. We find large differences in the simulated ice sheets according to the chosen PDD model. These differences occur as soon as the onset of glaciation, therefore affecting the subsequent evolution of the ice system. To further investigate how the PDD method controls this evolution, special attention is given to the role of each PDD parameter. We show that glacial inception is critically dependent on the representation of the impact of the temperature variability from the daily to the inter-annual time scale, whose effect is modulated by the refreezing scheme. Finally, an additional set of sensitivity experiments has been carried out to assess the relative importance of melt processes with respect to initial ice sheet configuration in the construction and the evolution of past Northern Hemisphere ice sheets. Our analysis reveals that the impacts of the initial ice sheet condition may range from quite negligible to explaining about half of the LGM ice volume depending on the representation of stochastic temperature variations which remain the main driver of the evolution of the ice system.
Mountain snow covers typically become patchy over the course of a melting season. The snow pattern during melt is mainly governed by the end of winter snow depth distribution and the local energy balance. The objective of this study is to investigate micrometeorological processes driving snow ablation in an Alpine catchment. For this purpose we combine a meteorological model (ARPS) with a fully distributed energy balance model (Alpine3D). Turbulent fluxes above melting snow are further investigated by using data from eddy-correlation systems. We compare modelled snow ablation to measured ablation rates as obtained from a series of Terrestrial Laser Scanning campaigns covering a complete ablation season. The measured ablation rates indicate that the advection of sensible heat causes locally increased ablation rates at the upwind edges of the snow patches. The effect, however, appears to be active over rather short distances except for very strong wind conditions. Neglecting this effect, the model is able to capture the mean ablation rates for early ablation periods but strongly overestimates snow ablation once the fraction of snow coverage is below a critical value. While radiation dominates snow ablation early in the season, the turbulent flux contribution becomes important late in the season. Simulation results indicate that the air temperatures appear to overestimate the local air temperature above snow patches once the snow coverage is below a critical value. Measured turbulent fluxes support these findings by suggesting a stable internal boundary layer close to the snow surface causing a strong decrease of the sensible heat flux towards the snow cover. Thus, the existence of a stable internal boundary layer above a patchy snow cover exerts a dominant control on the timing and magnitude of snow ablation for patchy snow covers.
Meteorological and surface change measurements collected during a 2.5 yr period are used to calculate surface mass and energy balances at 5324 m a.s.l. on Guanaco Glacier, a cold-based glacier in the semi-arid Andes of Chile. Meteorological conditions are marked by extremely low vapour pressures (annual mean of 1.1 hPa), strong winds (annual mean of 10 m s−1), high shortwave radiation receipt (mean annual 295 W m−2) and low precipitation rates (mean annual 45 mm w.e.). Net shortwave radiation provides the greatest source of energy to the glacier surface, and net longwave radiation dominates energy losses. The turbulent latent heat flux is always negative, which means that the surface is always losing mass via sublimation, which is the main form of ablation at the site. Sublimation rates are most strongly correlated with net shortwave radiation, incoming shortwave radiation, albedo and vapour pressure. Low glacier surface temperatures restrict melting for much of the period, however episodic melting occurs during the austral summer, when warm, humid, calm and high pressure conditions restrict sublimation and make more energy available for melting. Low accumulation (131 mm w.e. over the period) and relatively high ablation (1435 mm w.e.) means that mass change over the period was negative (−1304 mm w.e.), which continued the negative trend recorded in the region over the last few decades.
A dark region of tens of kilometres width is present on the western ablation zone of the Greenland ice sheet. The dark appearance is caused by higher amounts of dust. This dust has either been deposited recently or was brought to the surface by outcropping ice. Because the resulting lower albedos may have a significant effect on melt rates, we analysed surface dust, also called cryoconite, from locations in the dark region as well as locations from the brighter surrounding reference ice with microscopic and geochemical techniques to unravel the composition and origin. We find that (part of) the material indeed crops out from the ice, and that there is little difference between dust from the dark region and from the reference ice. Although, the dust from the dark region seems enriched in trace and minor elements that are mainly present in the current atmosphere because of anthropogenic activity. This enrichment is probably caused by higher precipitation and lower melt rates in the dark region relative to the ice marginal zone. The rare earth elemental ratios of the investigated material are approximately the same for all sites and resemble Earths average crust composition. Therefore, the cryoconite does probably not contain volcanic material. The mineralogical composition of the dust excludes Asian deserts, which are often found as provenance for glacial dust in ice cores, as source regions. Consequently, the outcropping dust likely has a more regional origin. Finally, we find cyanobacteria and algae in the cryoconite. Total Organic Carbon accounts for up to 5 weight percentage of the cryoconite from the dark region, whereas dust samples from the reference ice contain only 1% or less. This organic material is likely formed in situ. Because of their high light absorbency, cyanobacteria and the organic material they produce, contribute significantly to the low albedo of the dark region.
The climate sensitivity of Abrahamsenbreen, a 20 km long surge-type glacier in northern Spitsbergen, is studied with a simple glacier model. A scheme to describe the surges is included, which makes it possible to account for the effect of surges on the total mass budget of the glacier. A climate reconstruction back to AD 1300, based on ice-core data from Lomonosovfonna and climate records from Longyearbyen, is used to drive the model. The model is calibrated by requesting that it produces the correct Little Ice Age maximum glacier length and simulates the observed magnitude of the 1978-surge. Abrahamsenbreen is strongly out of balance with the current climate. If climatic conditions will remain as they were for the period 1989–2010, the glacier will ultimately shrink to a length of about 4 km (but this will take hundreds of years). For a climate change scenario involving a 2 m yr−1 rise of the equilibrium line from now onwards, we predict that in the year 2100 Abrahamsenbreen will be about 12 km long. The main effect of a surge is to lower the mean surface elevation and to increase the ablation area, thereby causing a negative perturbation of the mass budget. We found that the occurrence of surges leads to a somewhat stronger retreat of the glacier in a warming climate. Because of the very small bed slope, Abrahamsenbreen is sensitive to small perturbations in the equilibrium-line altitude E. For a decrease of E of only 160 m, the glacier would steadily grow into the Woodfjorddalen until after 2000 years it would reach the Woodfjord and calving could slow down the advance.
(a) Twelve temperature profiles measured for filters with 10 micrograms of fullerene soot. Profiles are from three different filters measured four times each. (b) Mean temperature profile and SD of data 12 temperature profiles. (c) Temperature increases after ten seconds for five masses of fullerene soot. Error bars are SDs for each measurement and bold line is fit to data. 
Plot showing the relationship between eBC as determined from the LAHM analysis and refractory black carbon as determined by the SP2 instrument (r 2 = 0.92). The values near 0.0 rBC are from Pisco mountain in region 2 while the higher values are from Vallunaraju in region 4. The 1 to 1 line is plotted to guide the eye. 
Google map image of the Cordillera Blanca mountain range. The five regions as well as the city of Huaraz are indicated on the map by black arrows. Average eBC values as determined from the LAHM analysis are shown in the plot for each of the three years. The thin lines indicate ±1 SD of the measurements. Note that in 2013, region 2, SP2 samples averaged 0.65 ng g −1 rBC indicating that most of the 5 ng g −1 of the eBC estimate could be due to light absorption by dust. 
LAHM determined eBC values averaged by altitude bins plotted with ±1 SD (lines) by altitude for the northern (regions 1 and 2) mountains and the southern (regions 3-5) mountains in the Cordillera Blanca. Absorbing particulates in snow in regions 1 and 2 are likely primarily dust while regions 3-5 are strongly influenced by pollution from the city of Huaraz. 
Glaciers in the tropical Andes have been rapidly losing mass since the 1970s. In addition to the documented increase in air temperature, increases in light absorbing particulates deposited on glaciers could be contributing to the observed glacier loss. Here we report on measurements of light absorbing particulates sampled from glaciers during three surveys in the Cordillera Blanca in Peru. During three research expeditions in the dry seasons (May–August) of 2011, 2012 and 2013, two hundred and forty snow samples were collected from fifteen mountain peaks over altitudes ranging from 4800 to nearly 6800 m. Several mountains were sampled each of the three expeditions and some mountains were sampled multiple times during the same expedition. Collected snow samples were melted and filtered in the field then later analyzed using the Light Absorption Heating Method (LAHM), a new technique that measures the ability of particulates on filters to absorb visible light. LAHM results have been calibrated using filters with known amounts of fullerene soot, a common industrial surrogate for black carbon (BC). As sample filters often contain dust in addition to BC, results are presented in terms of effective Black Carbon (eBC). During the 2013 survey, snow samples were collected and kept frozen for analysis with a Single Particle Soot Photometer (SP2). Calculated eBC mass from the filter analysis and the SP2 refractory Black Carbon (rBC) results were well correlated (r2 = 0.92). These results indicate that a substantial portion of the light absorbing particulates in the more polluted areas were likely BC. The three years of data show that glaciers in the Cordillera Blanca Mountains close to human population centers have substantially higher levels of eBC (as high as 70 ng g−1) than remote glaciers (as low as 2.0 ng g−1 eBC), indicating that population centers can influence local glaciers by sourcing BC.
The SoS-2013 experiment. a) Top. The experimental field with the seasonal snow 3 pack; b) Bottom left. The gravel surface under the snow; c) Bottom right. Artificially added 4 impurities were visible on the surface of the melting snow. 5 6
The Black Carbon (BC) content [ppb] vs. density [kg m −3 ] for the natural seasonal snow cover in Sodankylä, north of the Arctic Circle. (a) Cold snowpack. In natural snow (within the circle) BC concentrations were 8-126 ppb and snow densities were 200-264 kg m −3. When soot was artificially deposited, the snow density decreased to 168 kg m −3 for a BC concentration of 1465 ppb. For the reference spot, the snow density was 210 kg m −3 with a soot concentration of 126 ppb. The line is the least squares linear fit through all the points. (b) Melting snow. SoS2013 data for reference spots (within the circle), and spots with artificially added impurities. The densities and corresponding carbon contents were measured separately for the specified surface layers, not for the whole snow pack. The line is the least squares linear fit through all the points.
The origin of our Sodankylä snow density data coupled with BC analysis results. The campaigns are explained in the text. 
Climatic effects of Black Carbon (BC) deposition on snow have been proposed to result from reduced snow albedo and increased melt due to light-absorbing particles. In this study, we hypothesize that BC may decrease the liquid water retention capacity of melting snow, and present our first data, where both the snow density and elemental carbon content were measured. In our experiments, artificially added light-absorbing impurities decreased the density of seasonally melting natural snow. We also suggest three possible processes that might lead to the lower snow density.
There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally-based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice los has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead-lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants, and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.
Inlay: surface topography in the area of SLE, indicated with the red circle. Contours are 200 m apart. Main figure: solidus line (solid) and line of maximum density (LoMD, dashed) (Jackett et al., 2006) as well as the parameter space where SLE is located (red). The ice thickness refers to a density of 917 kg m −3. The four possible temperature regimes are indicated by red letters. The dotted line indicates the critical depth (3050 m) and pressure (2790 dbar) where the LoMD and the solidus line intersect. Waters within regions B and C indicate fluids with supercooled conditions (hence why they appear above the solidus line). The region of the convective ocean case and the stratified lake case are separated by the LoMD. Orange lines indicate the corresponding results for a salinity of 1‰.
Temperature cross section along the path shown in Fig. 2. Different temperature regimes are indicated by black-dashed ovals, Approximate lake access points locations (see text) along this cross section are indicated on top.  
We present results from new geophysical data allowing 3-D modelling of the water flow within Subglacial Lake Ellsworth (SLE), West Antarctica. Our simulations indicate that this lake has a novel temperature distribution due to significantly thinner ice than other surveyed subglacial lakes. The critical pressure boundary (tipping depth), established from the semi-empirical Equation of State, defines whether the lake's flow regime is convective or stratified. It passes through SLE and separates different temperature (and flow) regimes on either side of the lake. Our results have implications for the location of proposed access holes into SLE, the choice of which will depend on scientific or operational priorities. If an understanding of subglacial lake water properties and dynamics is the priority, holes are required in a basal freezing area at the North end of the lake. This would be the preferred priority suggested by this paper, requiring temperature and salinity profiles in the water column. A location near the Southern end, where bottom currents are lowest, is optimum for detecting the record of life in the bed sediments; to minimise operational risk and maximise the time span of a bed sediment core, a location close to the middle of the lake, where the basal interface is melting and the lake bed is at its deepest, remains the best choice. Considering potential lake-water salinity and ice-density variations, we estimate the critical tipping depth , separating different temperature regimes within subglacial lakes, to be in about 2900 to 3045 m depth.
Comparison for each experiment of mean observed (thin solid lines) and mean exponentially fitted thickness (thick dashed lines). Panel (a) corresponds to tank A, panel (b) to tank B.
Histograms for all experiment observations for (a) ice salinity centred in 0.6 g kg −1 bins and (b) frazil ice solid fraction, centred in 0.02 bins. Light gray distributions show data from E2 and E4 only.
Variation of derived Q s and Q i with mean temperature difference between water and air for each experiment and tank. Upper and lower (95 % confidence interval) limits are given with vertical black lines: tank A (dotted) and tank B (dash dot). Tank B points for the cooling period, E3 and E4, have been displaced in the x-axis by +0.06 units, for visibility.
Histogram of ice thickness normalized against initial wave height for all data. Data for E1 in dark grey, E2 in white, E3 in light gray and E4 in brown. Bins set at 0.1.  
Ice growth in turbulent seawater is often accompanied by the accumulation of frazil ice crystals at its surface. The thickness and volume fraction of this ice layer play an important role in shaping the gradual transition from a loose to a solid ice cover, however, observations are very sparse. Here we analyse an extensive set of observations of frazil ice, grown in two parallel tanks with controlled wave conditions and thermal forcing, focusing on the first one to two days of grease ice accumulation. The following unresolved issues are addressed: (i) at which volume fraction the frazil crystal rising process starts and how densely they accumulate at the surface, (ii) how the grease ice solid fraction evolves with time until solid ice starts to form and (iii) how do these conditions affect, and are affected by, waves and heat loss from the ice. We obtained estimates of the initial frazil ice solid fraction (0.04–0.05), the maximum solid fraction to which it accumulates (0.24–0.28), as well as the time-scale of packing, at which 95 % of the frazil reaches the maximum solid fraction (12–18 h). Comparison of ice thickness and wave observations also indicates that grease ice first begins to affect the wave field significantly when its thickness exceeds the initial wave amplitude. These results are relevant for modelling frazil ice accumulation and freeze-up of leads, polynyas and the seasonal ice zone.
Cross section through an ice sheet: four different mechanisms of aerosol transport to the ablation zone. ELA stands for equilibrium line altitude.  
Albedo evolution of the KAN_M station over the years 2009 until the end of 2012. Panels (a, b) show AWS data in blue and different simulations. The parameters are optimised for different yeas and then used to simulate the entire period. In (a) the precipitation comes from MAR model output and the temperature from AWS data and in (b) those are parameterised. Panel (c) shows the range of settings for each year and for Station S5 in brown on the right side of the scales.  
Ice loss due to surface melt of the Greenland ice sheet has increased in recent years. Surface melt in the ablation zone is controlled by atmospheric temperature and surface albedo. Impurities such as mineral dust and black carbon darken the snow and ice surfaces and therefore reduce the surface albedo which leads to more absorbed solar energy and ultimately amplifying melt. These impurities accumulate on the ice surface both from atmospheric fallout and by melt-out of material which was enclosed in the snowpack or the ice compound. A general impurity accumulation model is developed and applied to calculate the surface albedo evolution at two locations in western Greenland. The model is forced either by regional climate model output or by a parameterisation for temperature and precipitation. Simulations identify mineral dust as the main contributor to impurity mass on ice where the dominating part originates from melt out of englacial dust. Daily reduction of impurities is in the range of one per-mille which leads to a residence time of decades on the ice surface. Therefore the impurities have a prolonged effect on surface melt once they are located on the ice surface. The currently englacially stored mineral dust and black carbon will effect future melt and sea level rise and can be studied with the presented model.
Standard physical parameters and constants.
Global annual mean surface air temperature anomalies for different representative concentration pathways (IPCC, 2013; Table 12.2). After 2300 the temperature anomalies are kept constant.
Cross-section of the spin-up ice sheet at the year 2000: (a) englacial black carbon concentration, (b) dust concentration, (c) depositional-x (provenance) and (d) depositional time.
Time series of the surface values of (a) englacial dust, (b) englacial BC, (c) surface mass balance and (d) time of deposition. The vertical axis shows time, with the start of simulation at the top.
Time series of the RCP 4.5 scenario including aerosols: (a) englacial dust, (b) BC concentrations, (c and d) respective surface amount on 1 August, (e) surface mass balance, (f) depositional time of ice at the surface.
Albedo is the dominating factor governing surface melt variability in the ablation area of ice sheets and glaciers. Aerosols such as mineral dust and black carbon (soot) accumulate on the ice surface and cause a darker surface and therefore a lower albedo. The dominant source of these aerosols in the ablation area is melt-out of englacial material which has been transported via ice flow. The darkening effect on the ice surface is currently not included in sea level projections, and the effect is unknown. We present a model framework which includes ice dynamics, aerosol transport, aerosol accumulation and the darkening effect on ice albedo and its consequences for surface melt. The model is applied to a simplified geometry resembling the conditions of the Greenland ice sheet, and it is forced by several temperature scenarios to quantify the darkening effect of aerosols on future mass loss. The effect of aerosols depends non-linearly on the temperature rise due to the feedback between aerosol accumulation and surface melt. The effect of aerosols in the year 3000 is up to 12% of additional ice sheet volume loss in the warmest scenario.
We present a new method of using ground penetrating radar (GPR) for estimating snow accumulation and compaction rates in Antarctica. We process 500 MHz data to produce radargrams with unambiguous reflection horizons that can be observed and tracked in repeat GPR measurements made one year apart. Our processing methodology is a deterministic deconvolution via the Fourier domain using an estimate of the emitted waveform from direct measurement. At two measurement sites near Scott Base, Antarctica, point measurements of average accumulation from snow pits and firn cores are extrapolated to a larger area by identifying a dateable dust layer in the radargrams. Over an 800 m×800 m area on the McMurdo Ice Shelf (77°45´ S, 167°17´ E) the average accumulation is found to be 269 ± 9 kg m<sup>−2</sup> a<sup>−1</sup>. The accumulation over an area of 400 m×400 m in the dry snow zone on Ross Island (77°40´ S, 167°11´ E, 350 m a.s.l.) is found to be higher (404 ± 22 kg m<sup>−2</sup> a<sup>−1</sup>) and shows increased variability related to undulating terrain. Compaction of snow between 2 m and 13 m depth is estimated at both sites by tracking several internal reflection horizons along the radar profiles and calculating the average change in separation of horizon pairs from one year to the next. The derived compaction rates range from 7 cm m<sup>−1</sup> at a depth of two metres, down to no measurable compaction at 13 m depth, and are similar to published values from point measurements.
This study explores an approach that simultaneously estimates Antarctic mass balance and glacial isostatic adjustment (GIA) through the combination of satellite gravity and altimetry data sets. The results improve upon previous efforts by incorporating reprocessed data sets over a longer period of time, and now include a firn densification model to account for firn compaction and surface processes. A range of different GRACE gravity models were evaluated, as well as a new ICESat surface height trend map computed using an overlapping footprint approach. When the GIA models created from the combination approach were compared to in-situ GPS ground station displacements, the vertical rates estimated showed consistently better agreement than existing GIA models. In addition, the new empirically derived GIA rates suggest the presence of strong uplift in the Amundsen Sea and Philippi/Denman sectors, as well as subsidence in large parts of East Antarctica. The total GIA mass change estimates for the entire Antarctic ice sheet ranged from 53 to 100 Gt yr−1, depending on the GRACE solution used, and with an estimated uncertainty of ±40 Gt yr−1. Over the time frame February 2003–October 2009, the corresponding ice mass change showed an average value of −100 ± 44 Gt yr−1 (EA: 5 ± 38, WA: −105 ± 22), consistent with other recent estimates in the literature, with the mass loss mostly concentrated in West Antarctica. The refined approach presented in this study shows the contribution that such data combinations can make towards improving estimates of present day GIA and ice mass change, particularly with respect to determining more reliable uncertainties.
(a) Location of site on Bylot Island, (b) Landsat 7 image of Fountain Glacier, (c) carrying out pre-flight checks for the Outlander UAV.  
Orthomosaic images of the glacier terminus from (a) 2010 (UAV) and (b) 2011 (piloted helicopter). Contour interval is 10 m.  
(a) Changes in glacier margins from 2010 to 2011 (image shown is from 2011). Areas where significant changes have occurred are shown in white and denoted by A, B and C; (b) change in ice thickness measured from 1 July 2010 to 2 July 2011. Increases in thickness to the east of the terminus reflect changes to the proglacial icing; (c) horizontal flow speed and flow direction between 1 July 2010 and 2 July 2011.  
Remotely-sensed glaciological measurements can be expensive, and often involve a trade-off between resolution, scale, and frequency. In an attempt to overcome these issues we report on a case study in which two low-cost techniques were used to generate orthomosaic images and digital elevation models (DEMs) of an arctic glacier in two consecutive ablation seasons. In the first aerial survey we used an unmanned aerial vehicle (UAV) and acquired images autonomously, while in the second we used a piloted helicopter and acquired images manually. We present a preliminary assessment of accuracy and apply these data to measure glacier thinning and motion.
The influence of spatial surface temperature changes over the Arctic Ocean on the 2-m air temperature variability is estimated using backward trajectories based on ERA-Interim and the JRA25 wind fields. They are initiated at Alert, Barrow and at the Tara drifting station. Three different methods are used. The first one compares mean ice surface temperatures along the trajectories to the observed 2-m air temperatures at the stations. The second one correlates the observed temperatures to air temperatures obtained using a simple Lagrangian box model which only includes the effect of sensible heat fluxes. For the third method, mean sensible heat fluxes from the model are correlated with the difference of the air temperatures at the model starting point and the observed temperatures at the stations. The calculations are based on MODIS ice surface temperatures and four different sets of ice concentration derived from SSM/I and AMSR-E data. Under nearly cloud free conditions, up to 90% of the 2-m air temperature variance can be explained for Alert, and 60% for Barrow using these methods. The differences are attributed to the different ice conditions, which are characterized by high ice concentration around Alert and lower ice concentration near Barrow. These results are robust for the different sets of reanalyses and ice concentration data. Near-surface winds of both reanalyses show a large inconsistency in the Central Arctic, which leads to a large difference in the correlations between modeled and observed 2-m air temperatures at Tara. Explained variances amount to 70% using JRA and only 45% using ERA. The results also suggest that near-surface temperatures at a given site are influenced by the variability of surface temperatures in a domain of about 150 to 350 km radius around the site.
Geographic setting of Alta Val de La Mare and location of the automatic weather stations.
Descriptive statistics for air temperature data recorded by the weather stations. On- glacier sites are in bold type. 
Mean temperature vs. altitude: (a) from 3 July to 23 September 2010, and (b) from 7 July to 12 September 2011. Lines indicate linear regressions of temperature vs. altitude for subsets of weather stations. LR = vertical lapse rates.
Transfer functions for the coefficients K 1 , K 2 and T * of the Shea and Moore (2010) method. CMBC = S&M study area; AVDM = our study area. Outliers due to under-sampling at freezing temperatures have been removed (as in the S&M work). β 3 to β 7 are coefficients from S&M (J. M. Shea, personal communication, 2014), while the transfer function and coefficients for T * are new results from the present work.
On-glacier temperature calculated with the Shea and Moore (2010) method vs. observed temperature.
Glacier mass balance models rely on accurate spatial calculation of input data, in particular air temperature. Lower temperatures (the so-called glacier cooling effect), and lower temperature variability (the so-called glacier damping effect) generally occur over glaciers, compared to ambient conditions. These effects, which depend on the geometric characteristics of glaciers and display a high spatial and temporal variability, have been mostly investigated on medium- to large-size glaciers so far, while observations on smaller ice bodies are scarce. Using a dataset from 8 on-glacier and 4 off-glacier weather stations, collected in summer 2010 and 2011, we analyzed the air temperature variability and wind regime over three different glaciers in the Ortles-Cevedale. The magnitude of the cooling effect and the occurrence of katabatic boundary layer (KBL) processes showed remarkable differences among the three ice bodies, suggesting the likely existence of important reinforcing mechanisms during glacier decay and disintegration. None of the methods proposed in the literature for calculating on-glacier temperature from off-glacier data fully reproduced our observations. Among them, the more physically-based procedure of Greuell and Böhm (1998) provided the best overall results where the KBL prevail, but it was not effective elsewhere (i.e. on smaller ice bodies and close to the glacier margins). The accuracy of air temperature estimations strongly impacted the results from a mass balance model which was applied to the three investigated glaciers. Most importantly, even small temperature deviations caused distortions in parameter calibration, thus compromising the model generalizability.
A combined interpretation of synthetic aperture radar (SAR) satellite images and helicopter electromagnetic (HEM) sea-ice thickness data has provided an estimate of sea-ice volume formed in Laptev Sea polynyas during the winter of 2007/08. The evolution of the surveyed sea-ice areas, which were formed between late December 2007 and middle April 2008, was tracked using a series of SAR images with a sampling interval of 2–3 days. Approximately 160 km of HEM data recorded in April 2008 provided sea-ice thicknesses along profiles that transected sea-ice varying in age from 1–116 days. For the volume estimates, thickness information along the HEM profiles was extrapolated to zones of the same age. The error of areal mean thickness information was estimated to be between 0.2 m for younger ice and up to 1.55 m for older ice, with the primary error source being the spatially limited HEM coverage. Our results have demonstrated that the modal thicknesses and mean thicknesses of level ice correlated with the sea-ice age, but that varying dynamic and thermodynamic sea-ice growth conditions resulted in a rather heterogeneous sea-ice thickness distribution on scales of tens of kilometers. Taking all uncertainties into account, total sea-ice area and volume produced within the entire surveyed area were 52 650 km<sup>2</sup> and 93.6 ± 26.6 km<sup>3</sup>. The surveyed polynya contributed 2.0 ± 0.5% of the sea-ice produced throughout the Arctic during the 2007/08 winter. The SAR-HEM volume estimate compares well with the 112 km<sup>3</sup> ice production calculated with a high resolution ocean sea-ice model. Measured modal and mean-level ice thicknesses correlate with calculated freezing-degree-day thicknesses with a factor of 0.87–0.89, which was too low to justify the assumption of homogeneous thermodynamic growth conditions in the area, or indicates a strong dynamic thickening of level ice by rafting of even thicker ice.
Observational data sets. 
Annual mean ice thickness in the SCICEX Box. The dots show the observations, red are from the submarines. The orange line is the third-order polynomial from RPW08 for which the draft was converted to thickness with a factor of 1.107. The green line is a third-order polynomial from this study. 
Coefficients of the ITRP indicator variables for a fit for the Arctic Ocean for 20002013. Grey bars show the coefficients for a fit that includes all of the observations. Bars in other colors indicate which source has been left out in fits that leave one data source out at a time. The legend for the bar colors is given by the color of the diagonal labels. ICESat-G is always the reference. 
Sea ice thickness is a fundamental climate state variable that provides an integrated measure of changes in the high-latitude energy balance. However, observations of ice thickness have been sparse in time and space making the construction of observation-based time series difficult. Moreover, different groups use a variety of methods and processing procedures to measure ice thickness and each observational source likely has different and poorly characterized measurement and sampling biases. Observational sources include upward looking sonars mounted on submarines or moorings, electromagnetic sensors on helicopters or aircraft, and lidar or radar altimeters on airplanes or satellites. Here we use a curve-fitting approach to evaluate the systematic differences between eight different observation systems in the Arctic Basin. The approach determines the large-scale spatial and temporal variability of the ice thickness as well as the mean differences between the observation systems using over 3000 estimates of the ice thickness. The thickness estimates are measured over spatial scales of approximately 50 km or time scales of 1 month and the primary time period analyzed is 2000–2013 when the modern mix of observations is available. Good agreement is found between five of the systems, within 0.15 m, while systematic differences of up to 0.5 m are found for three others compared to the five. The trend in annual mean ice thickness over the Arctic Basin is −0.58 ± 0.07 m decade−1 over the period 2000–2013, while the annual mean ice thickness for the central Arctic Basin alone (the SCICEX Box) has decreased from 3.45 m in 1975 to 1.11 m in 2013, a 68% reduction. This is nearly double the 36% decline reported by an earlier study. These results provide additional direct observational confirmation of substantial sea ice losses found in model analyses.
(a-c) The distribution of observed ship speeds under various ice related factors. As in Fig. 2 the respective distribution of ship speeds is depicted by box plots. Panel (a) refers to convergent and non-convergent ice motion, panel (b) explores various classes of ice drift speed and panel (c) refers to the specific situation where the ice is drifting very slow (< 10 cm s −1 ) and additionally the ice drift angle is close to 90 • relative to the ship course. (Naturally, only data sets with ship and ice speeds > 0 could be considered.)
(a–c) Observed ship speed distribution under several (binned) ice conditions, described by box plots. The bottom and top of the boxes are the first and third quartiles while the thicker band inside the boxes depicts the median. Lines extending vertically from the boxes (whiskers) depict ship speeds within 1.5 times the interquartile range from the box. Outliers are plotted as individual points. Panel (a) refers to ice concentration, (b) ice thickness and (c) ridge density.  
(a–d) Observed (red lines) and reconstructed (black line) ship speeds for typical vessels in the test region: (a) General Cargo, 120 m (b) Oil Tanker, 140 m, (c) Cargo, 117 m, (d) RoRo, 166 m. The reconstructions are based on a multi-linear regression of forecasted ice concentration , level ice thickness, ridge density, ice speed and an additional factor which is based inter alia on the angle in which the ship is moving relative to the ice movement (parameterized as described in Fig. 3c).  
The Baltic Sea is a seasonally ice covered marginal sea located in a densely populated area in northern Europe. Severe sea ice conditions have the potential to hinder the intense ship traffic considerably. Thus, sea ice fore- and nowcasts are regularly provided by the national weather services. Typically, several ice properties are allocated, but their actual usefulness is difficult to measure and the ship captains must determine their relative importance and relevance for optimal ship speed and safety ad hoc. The present study provides a more objective approach by comparing the ship speeds, obtained by the Automatic Identification System (AIS), with the respective forecasted ice conditions. We find that, despite an unavoidable random component, this information is useful to constrain and rate fore- and nowcasts. More precisely, 62–67% of ship speed variations can be explained by the forecasted ice properties when fitting a mixed effect model. This statistical fit is based on a test region in the Bothnian Bay during the severe winter 2011 and employes 15 to 25 min averages of ship speed.
Area-altitude distribution of the Bering Glacier. The total area of the glacier is 4773 km 2 and there are 49 altitude intervals spaced at 30.6 m, ranging from 150 to 1650 m in elevation. Latitude 60.302 @BULLET N Longitude −143.20 @BULLET W.  
Cumulative balance of the Bering Glacier. Total thinning during this 61-yr period is 39 m or 0.6 m of ice per year. The vertical lines at 1972 and 2003 delineate the period for which the volume loss determined by the PTAA and geodetic methods are compared.  
a. Net, accumulation and ablation balances of the Bering Glacier as a function of elevation, averaged for the 1951-2011 period. The ELA (1300 m) is defined as the point at which the net balance crosses the zero balance line.
b. Net, accumulation and ablation balances of the Bering Glacier as a function of elevation, averaged for the 2004 period. The ELA is 1850 m, 550 m above average. The balance at the terminus (−14 mwe) is nearly 3 times as negative as on a normal year.
b. The 5-yr running mean of daily snow accumulation on the Bering Glacier, and timing of the four observed surges since 1951.  
The historical net, ablation and accumulation daily balances and runoff of the Bering Glacier, Alaska are determined for the 1951–2011 period with the PTAA (precipitation-temperature-area-altitude) model, using daily precipitation and temperature observations collected at the Cordova and Yakutat weather stations, together with the area-altitude distribution of the glacier. The mean annual balance for this 61-yr period is −0.6 mwe, the accumulation balance is +1.4 and the ablation balance is −2.0 mwe. Periodic surges of this glacier transport large volumes of ice to lower elevations where the ablation rate is higher, producing more negative balances and increasing runoff. During the 1993–1995 surge the average ablation balance is −3.3 mwe, over a meter greater than the 1951–2011 average. Runoff from the Bering Glacier (derived from simulated ablation and precipitation as rain) is highly correlated with the four glacier surges that have been observed since 1951. Ice volume loss for the 1972–2003 period measured with the PTAA model is 2.3 km<sup>3</sup> we a<sup>−1</sup> and closely agrees with losses for the same period measured with the geodetic method.
Climate projections for the 21st century indicate that there could be a pronounced warming and permafrost degradation in the Arctic and sub-Arctic regions. Climate warming is likely to cause permafrost thawing with subsequent effects on surface albedo, hydrology, soil organic matter storage and greenhouse gas emissions. To assess possible changes in the permafrost thermal state and active layer thickness, we implemented the GIPL2-MPI transient numerical model for the entire Alaska permafrost domain. Input parameters to the model are spatial datasets of mean monthly air temperature and precipitation, prescribed thermal properties of the multilayered soil column, and water content which are specific for each soil class and geographical location. As a climate forcing we used the composite of five IPCC Global Circulation Models that has been downscaled to 2 by 2 km spatial resolution by Scenarios Network for Alaska Planning (SNAP) group. In this paper we present the preliminary modeling results based on input of five-model composite with A1B carbon emission scenario. The model has been calibrated according to the annual borehole temperature measurements for the State of Alaska. We also performed more detailed calibration for fifteen shallow borehole stations where high quality data are available on daily basis. To validate the model performance we compared simulated active layer thicknesses with observed data from CALM active layer monitoring stations. Calibrated model was used to address possible ground temperature changes for the 21st century. The model simulation results show the widespread permafrost degradation in Alaska could begin in 2040–2099 time frame within the vast area southward from the Brooks Range except for the high altitudes of the Alaska Range and Wrangell Mountains.
Lakes are abundant throughout the pan-Arctic region. For many of these lakes ice cover lasts for up to two thirds of the year. This frozen cover allows human access to these lakes, which are therefore used for many subsistence and recreational activities, including water harvesting, fishing, and skiing. Safe access to these lakes may be compromised, however, when, after significant snowfall, the weight of the snow acts on the ice and causes liquid water to spill through weak spots and overflow at the snow-ice interface. Since visual detection of subsnow liquid overflow (SLO) is almost impossible our understanding on SLO processes is still very limited and geophysical methods that allow SLO detection are desirable. In this study we demonstrate that a commercially available, lightweight 1GHz, ground penetrating radar system can detect and map extent and intensity of SLO. Radar returns from wet snow-ice interfaces are at least twice as much in strength than returns from dry snow-ice interface. The presence of SLO also affects the quality of radar returns from the base of the lake ice. During dry conditions we were able to profile ice thickness of up to 1 m, conversely, we did not retrieve any ice-water returns in areas affected by SLO.
In the present study we describe the retrievals of snow grain size and spectral albedo (plane and spherical albedo) for Western Himalayan snow cover using Hyperion sensor data. The asymptotic radiative transfer (ART) theory was explored for the snow retrievals. To make the methodology operational only five spectral bands (440, 500, 1050, 1240 and 1650 nm) of Hyperion were used for snow parameters retrieval. The bi-spectral method (440 nm in the visible and 1050/1240 nm in the NIR region) was used to retrieve snow grain size. Spectral albedos were retrieved using satellite reflectances and estimated grain size. A good agreement was observed between retrieved snow parameters and ground observed snow-meteorological conditions. The satellite retrieved grain sizes were compared with field spectroradiometer retrieved grain sizes and close results were found for Lower Himalayan snow. The wavelength 1240 nm was found to be more suitable compared to 1050 nm for grain size retrieval along the steep slopes. The methodology was able to retrieve the spatial variations in snow parameters in different parts of Western Himalaya which are due to snow climatic and terrain conditions of Himalaya. This methodology is of importance for operational snow cover and glacier monitoring in Himalayan region using space-borne and air-borne sensors.
Top-cited authors
Michiel Roland Van den Broeke
Xavier Fettweis
  • University of Liège
Jason E. Box
  • Geological Survey of Denmark and Greenland
M. Hofer
  • University of Innsbruck
Matthias Huss
  • Université de Fribourg