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The isotopic compositions of oxygen and hydrogen in ice cores are invaluable tools for the reconstruction of past climate variations. Used alone, they give insights into the variations of the local temperature, whereas taken together they can provide information on the climatic conditions at the point of origin of the moisture. However, recent analyses of snow from shallow pits indicate that the climatic signal can become erased in very low accumulation regions, due to local processes of snow reworking. The signal-to-noise ratio decreases and the climatic signal can then only be retrieved using stacks of several snow pits. Obviously, the signal is not completely lost at this stage, otherwise it would be impossible to extract valuable climate information from ice cores as has been done, for instance, for the last glaciation. To better understand how the climatic signal is passed from the precipitation to the snow, we present here results from varied snow samples from East Antarctica. First, we look at the relationship between isotopes and temperature from a geographical point of view, using results from three traverses across Antarctica, to see how the relationship is built up through the distillation process. We also take advantage of these measures to see how second-order parameters (d-excess and 17O-excess) are related to δ18O and how they are controlled. d-excess increases in the interior of the continent (i.e., when δ18O decreases), due to the distillation process, whereas 17O-excess decreases in remote areas, due to kinetic fractionation at low temperature. In both cases, these changes are associated with the loss of original information regarding the source. Then, we look at the same relationships in precipitation samples collected over 1 year at Dome C and Vostok, as well as in surface snow at Dome C. We note that the slope of the δ18O vs. temperature (T) relationship decreases in these samples compared to those from the traverses, and thus caution is advocated when using spatial slopes for past climate reconstruction. The second-order parameters behave in the same way in the precipitation as in the surface snow from traverses, indicating that similar processes are active and that their interpretation in terms of source climatic parameters is strongly complicated by local temperature effects in East Antarctica. Finally we check if the same relationships between δ18O and second-order parameters are also found in the snow from four snow pits. While the d-excess remains opposed to δ18O in most snow pits, the 17O-excess is no longer positively correlated to δ18O and even shows anti-correlation to δ18O at Vostok. This may be due to a stratospheric influence at this site and/or to post-deposition processes.

With dense SAR satellite data time series it is possible to map surface and subsurface glacier properties that vary in time. On Sentinel-1A and RADARSAT-2 backscatter time series images over mainland Norway and Svalbard, we outline how to map glaciers using descriptive methods. We present five application scenarios. The first shows potential for tracking transient snow lines with SAR backscatter time series and correlates with both optical satellite images (Sentinel-2A and Landsat 8) and equilibrium line altitudes derived from in situ surface mass balance data. In the second application scenario, time series representation of glacier facies corresponding to SAR glacier zones shows potential for a more accurate delineation of the zones and how they change in time. The third application scenario investigates the firn evolution using dense SAR backscatter time series together with a coupled energy balance and multilayer firn model. We find strong correlation between backscatter signals with both the modeled firn air content and modeled wetness in the firn. In the fourth application scenario, we highlight how winter rain events can be detected in SAR time series, revealing important information about the area extent of internal accumulation. In the last application scenario, averaged summer SAR images were found to have potential in assisting the process of mapping glaciers outlines, especially in the presence of seasonal snow. Altogether we present examples of how to map glaciers and to further understand glaciological processes using the existing and future massive amount of multi-sensor time series data.

Variability and trends in seasonal and interannual ice area export out of the Laptev Sea between 1992 and 2011 are investigated using satellite-based sea ice drift and concentration data. We found an average total winter (October to May) ice area transport across the northern and eastern Laptev Sea boundaries (NB and EB) of 3.48 × 105 km2. The average transport across the NB (2.87 × 105 km2) is thereby higher than across the EB (0.61 × 105 km2), with a less pronounced seasonal cycle. The total Laptev Sea ice area flux significantly increased over the last decades (0.85 × 105 km2 decade−1, p > 0.95), dominated by increasing export through the EB (0.55 × 105 km2 decade−1, p > 0.90), while the increase in export across the NB is smaller (0.3 × 105 km2 decade−1) and statistically not significant. The strong coupling between across-boundary SLP gradient and ice drift velocity indicates that monthly variations in ice area flux are primarily controlled by changes in geostrophic wind velocities, although the Laptev Sea ice circulation shows no clear relationship with large-scale atmospheric indices. Also there is no evidence of increasing wind velocities that could explain the overall positive trends in ice export. The increased transport rates are rather the consequence of a changing ice cover such as thinning and/or a decrease in concentration. The use of a back-propagation method revealed that most of the ice that is incorporated into the Transpolar Drift is formed during freeze-up and originates from the central and western part of the Laptev Sea, while the exchange with the East Siberian Sea is dominated by ice coming from the central and southeastern Laptev Sea. Furthermore, our results imply that years of high ice export in late winter (February to May) have a thinning effect on the ice cover, which in turn preconditions the occurence of negative sea ice extent anomalies in summer.

It is notoriously difficult to couple surface mass balance (SMB) results from climate models to the changing geometry of an ice sheet model. This problem is traditionally avoided by using only accumulation from a climate model, and parameterizing the meltwater run-off as a function of temperature, which is often related to surface elevation (Hs). In this study, we propose a new strategy to calculate SMB, to allow a direct adjustment of SMB to a change in ice sheet topography and/or a change in climate forcing. This method is based on elevational gradients in the SMB field as computed by a regional climate model. Separate linear relations are derived for ablation and accumulation, using pairs of Hs and SMB within a minimum search radius. The continuously adjusting SMB forcing is consistent with climate model forcing fields, also for initially non-glaciated areas in the peripheral areas of an ice sheet. When applied to an asynchronous coupled ice sheet – climate model setup, this method circumvents traditional temperature lapse rate assumptions. Here we apply it to the Greenland Ice Sheet (GrIS). Experiments using both steady-state forcing and glacial-interglacial forcing result in realistic ice sheet reconstructions.

In this study, snowpack scenarios are modelled across the French Alps using dynamically downscaled variables from the ALADIN Regional Climate Model (RCM) for the control period (1961–1990) and three emission scenarios (SRES B1, A1B and A2) for the mid- and late 21st century (2021–2050 and 2071–2100). These variables are statistically adapted to the different elevations, aspects and slopes of the Alpine massifs. For this purpose, we use a simple analogue criterion with ERA40 series as well as an existing detailed climatology of the French Alps (Durand et al., 2009a) that provides complete meteorological fields from the SAFRAN analysis model. The resulting scenarios of precipitation, temperature, wind, cloudiness, longwave and shortwave radiation, and humidity are used to run the physical snow model CROCUS and simulate snowpack evolution over the massifs studied. The seasonal and regional characteristics of the simulated climate and snow cover changes are explored, as is the influence of the scenarios on these changes. Preliminary results suggest that the snow water equivalent (SWE) of the snowpack will decrease dramatically in the next century, especially in the Southern and Extreme Southern parts of the Alps. This decrease seems to result primarily from a general warming throughout the year, and possibly a deficit of precipitation in the autumn. The magnitude of the snow cover decline follows a marked altitudinal gradient, with the highest altitudes being less exposed to climate change. Scenario A2, with its high concentrations of greenhouse gases, results in a SWE reduction roughly twice as large as in the low-emission scenario B1 by the end of the century. This study needs to be completed using simulations from other RCMs, since a multi-model approach is essential for uncertainty analysis.

To estimate the sea level rise (SLR) originating from changes in surface mass balance (SMB) of the Greenland ice sheet (GrIS), we present 21st century climate projections obtained with the regional climate model MAR (Modèle Atmosphérique Régional), forced by output of three CMIP5 (Coupled Model Intercomparison Project Phase 5) general circulation models (GCMs). Our results indicate that in a warmer climate, mass gain from increased winter snowfall over the GrIS does not compensate mass loss through increased meltwater run-off in summer. Despite the large spread in the projected near-surface warming, all the MAR projections show similar non-linear increase of GrIS surface melt volume because no change is projected in the general atmospheric circulation over Greenland. By coarsely estimating the GrIS SMB changes from GCM output, we show that the uncertainty from the GCM-based forcing represents about half of the projected SMB changes. In 2100, the CMIP5 ensemble mean projects a GrIS SMB decrease equivalent to a mean SLR of +4 ± 2 cm and +9 ± 4 cm for the RCP (Representative Concentration Pathways) 4.5 and RCP 8.5 scenarios respectively. These estimates do not consider the positive melt–elevation feedback, although sensitivity experiments using perturbed ice sheet topographies consistent with the projected SMB changes demonstrate that this is a significant feedback, and highlight the importance of coupling regional climate models to an ice sheet model. Such a coupling will allow the assessment of future response of both surface processes and ice-dynamic changes to rising temperatures, as well as their mutual feedbacks.

Predicting the climate for the future and how it will impact ice sheet evolution requires coupling ice sheet models with climate models. However, before we attempt to develop a realistic coupled setup, we propose, in this study, to first analyse the impact of a model simulated climate on an ice sheet. We undertake this exercise for a set of regional and global climate models. Modelled near surface air temperature and precipitation are provided as upper boundary conditions to the GRISLI (GRenoble Ice Shelf and Land Ice model) hybrid ice sheet model (ISM) in its Greenland configuration. After 20 kyrs of simulation, the resulting ice sheets highlight the differences between the climate models. While modelled ice sheet sizes are generally comparable to the observed one, there are considerable deviations among the ice sheets on regional scales. These deviations can be explained by biases in temperature and precipitation near the coast. This is especially true in the case of global models. But the deviations between the climate models are also due to the differences in the atmospheric general circulation. To account for these differences in the context of coupling ice sheet models with climate models, we conclude that appropriate downscaling methods will be needed. In some cases, systematic corrections of the climatic variables at the interface may be required to obtain realistic results for the Greenland ice sheet (GIS).

The detachment of large parts of low-angle mountain glaciers resulting in massive ice–rock avalanches have so far been believed to be a unique type of event, made known to the global scientific community first for the 2002 Kolka Glacier detachment, Caucasus Mountains, and then for the 2016 collapses of two glaciers in the Aru range, Tibet. Since 2016, several so-far unrecognized low-angle glacier detachments have been recognized and described, and new ones have occurred. In the current contribution, we compile, compare, and discuss 20 actual or suspected large-volume detachments of low-angle mountain glaciers at 10 different sites in the Caucasus, the Pamirs, Tibet, Altai, the North American Cordillera, and the Southern Andes. Many of the detachments reached volumes in the order of 10–100 million m3. The similarities and differences between the presented cases indicate that glacier detachments often involve a coincidental combination of factors related to the lowering of basal friction, high or increasing driving stresses, concentration of shear stress, or low resistance to exceed stability thresholds. Particularly soft glacier beds seem to be a common condition among the observed events as they offer smooth contact areas between the glacier and the underlying substrate and are prone to till-strength weakening and eventually basal failure under high pore-water pressure. Partially or fully thawed glacier bed conditions and the presence of liquid water could thus play an important role in the detachments. Surface slopes of the detached glaciers range between around 10∘ and 20∘. This may be low enough to enable the development of thick and thus large-volume glaciers while also being steep enough to allow critical driving stresses to build up. We construct a simple slab model to estimate ranges of glacier slope and width above which a glacier may be able to detach when extensively losing basal resistance. From this model we estimate that all the detachments described in this study occurred due to a basal shear stress reduction of more than 50 %. Most of the ice–rock avalanches resulting from the detachments in this study have a particularly low angle of reach, down to around 5∘, likely due to their high ice content and connected liquefaction potential, the availability of soft basal slurries, and large amounts of basal water, as well as the smooth topographic setting typical for glacial valleys. Low-angle glacier detachments combine elements and likely also physical processes of glacier surges and ice break-offs from steep glaciers. The surge-like temporal evolution ahead of several detachments and their geographic proximity to other surge-type glaciers indicate the glacier detachments investigated can be interpreted as endmembers of the continuum of surge-like glacier instabilities. Though rare, glacier detachments appear to be more frequent than commonly thought and disclose, despite local differences in conditions and precursory evolutions, the fundamental and critical potential of low-angle soft glacier beds to fail catastrophically.

Soils in the northern high latitudes are a key component in the global carbon cycle, with potential feedback on climate. This study aims to improve the previous soil organic carbon (SOC) and total nitrogen (TN) storage estimates for the Zackenberg area (NE Greenland) that were based on a land cover classification (LCC) approach, by using geomorphological upscaling. In addition, novel organic carbon (OC) estimates for deeper alluvial and deltaic deposits (down to 300 cm depth) are presented. We hypothesise that landforms will better represent the long-term slope and depositional processes that result in deep SOC burial in this type of mountain permafrost environments. The updated mean SOC storage for the 0–100 cm soil depth is 4.8 kg C m−2, which is 42 % lower than the previous estimate of 8.3 kg C m−2 based on land cover upscaling. Similarly, the mean soil TN storage in the 0–100 cm depth decreased with 44 % from 0.50 kg (± 0.1 CI) to 0.28 (±0.1 CI) kg TN m−2. We ascribe the differences to a previous areal overestimate of SOC- and TN-rich vegetated land cover classes. The landform-based approach more correctly constrains the depositional areas in alluvial fans and deltas with high SOC and TN storage. These are also areas of deep carbon storage with an additional 2.4 kg C m−2 in the 100–300 cm depth interval. This research emphasises the need to consider geomorphology when assessing SOC pools in mountain permafrost landscapes.

Landsat imagery was applied to elucidate glacier fluctuations of land- and marine-terminating outlet glaciers from the Greenland Ice Sheet (GrIS) and local land-terminating glaciers and ice caps (GIC) peripheral to the GrIS in the Ammassalik region, Southeast Greenland, during the period 1972–2011. Data from 21 marine-terminating glaciers (including the glaciers Helheim, Midgaard, and Fenris), the GrIS land-terminating margin, and 35 GIC were examined and compared to observed atmospheric air temperatures, precipitation, and reconstructed ocean water temperatures (at 400 m depth in the Irminger Sea). Here, we document that net glacier recession has occurred since 1972 in the Ammassalik region for all glacier types and sizes, except for three GIC. The land-terminating GrIS and GIC reflect lower marginal and areal changes than the marine-terminating outlet glaciers. The mean annual land-terminating GrIS and GIC margin recessions were about three to five times lower than the GrIS marine-terminating recession. The marine-terminating outlet glaciers had an average net frontal retreat for 1999–2011 of 0.098 km yr−1, which was significantly higher than in previous sub-periods 1972–1986 and 1986–1999. For the marine-terminating GrIS, the annual areal recession rate has been decreasing since 1972, while increasing for the land-terminating GrIS since 1986. On average for all the observed GIC, a mean net frontal retreat for 1986–2011 of 0.010 ± 0.006 km yr−1 and a mean areal recession of around 1% per year occurred; overall for all observed GIC, a mean recession rate of 27 ± 24% occurred based on the 1986 GIC area. Since 1986, five GIC melted away in the Ammassalik area.