Abstract: Spectral albedo of the snow surface in the visible/near-infrared range has been measured for 3 years by an automatic spectral radiometer installed at Dome C (75° S, 123° E) in Antarctica in order to retrieve the specific surface area (SSA) of superficial snow. This study focuses on the uncertainties of the SSA retrieval due to instrumental and data processing limitations. We find that when the solar zenith angle is high, the main source of uncertainties is the imperfect angular response of the light collectors. This imperfection introduces a small spurious wavelength-dependent trend in the albedo spectra which greatly affects the SSA retrieval. By modeling this effect, we show that for typical snow and illumination conditions encountered at Dome C, retrieving SSA with an accuracy better than 15 % (our target) requires the difference of response between 400 and 1100 nm to not exceed 2 %. Such a small difference can be achieved only by (i) a careful design of the collectors, (ii) an ad hoc correction of the spectra using the actual measured angular response of the collectors, and (iii) for solar zenith angles less than 75°. The 3-year time series of retrieved SSA features a 3-fold decrease every summer which is significantly larger than the estimated uncertainties. This highlights the high dynamics of near-surface SSA at Dome C.

Abstract: A 22.4 m-long shallow firn core was extracted during the 2006/2007 field season from coastal Adélie Land. Annual layer counting based on subannual analyses of δ18O and major chemical components was combined with 5 reference years associated with nuclear tests and non-retreat of summer sea ice to build the initial ice-core chronology (1946–2006), stressing uncertain counting for 8 years. We focus here on the resulting δ18O and accumulation records. With an average value of 21.8 ± 6.9 cm w.e. yr−1, local accumulation shows multi-decadal variations peaking in the 1980s, but no long-term trend. Similar results are obtained for δ18O, also characterised by a remarkably low and variable amplitude of the seasonal cycle. The ice-core records are compared with regional records of temperature, stake area accumulation measurements and variations in sea-ice extent, and outputs from two models nudged to ERA (European Reanalysis) atmospheric reanalyses: the high-resolution atmospheric general circulation model (AGCM), including stable water isotopes ECHAM5-wiso (European Centre Hamburg model), and the regional atmospheric model Modèle Atmosphérique Régional (AR). A significant linear correlation is identified between decadal variations in δ18O and regional temperature. No significant relationship appears with regional sea-ice extent. A weak and significant correlation appears with Dumont d'Urville wind speed, increasing after 1979. The model-data comparison highlights the inadequacy of ECHAM5-wiso simulations prior to 1979, possibly due to the lack of data assimilation to constrain atmospheric reanalyses. Systematic biases are identified in the ECHAM5-wiso simulation, such as an overestimation of the mean accumulation rate and its interannual variability, a strong cold bias and an underestimation of the mean δ18O value and its interannual variability. As a result, relationships between simulated δ18O and temperature are weaker than observed. Such systematic precipitation and temperature biases are not displayed by MAR, suggesting that the model resolution plays a key role along the Antarctic ice sheet coastal topography. Interannual variations in ECHAM5-wiso temperature and precipitation accurately capture signals from meteorological data and stake observations and are used to refine the initial ice-core chronology within 2 years. After this adjustment, remarkable positive (negative) δ18O anomalies are identified in the ice-core record and the ECHAM5-wiso simulation in 1986 and 2002 (1998–1999), respectively. Despite uncertainties associated with post-deposition processes and signal-to-noise issues, in one single coastal ice-core record, we conclude that the S1C1 core can correctly capture major annual anomalies in δ18O as well as multi-decadal variations. These findings highlight the importance of improving the network of coastal high-resolution ice-core records, and stress the skills and limitations of atmospheric models for accumulation and δ18O in coastal Antarctic areas. This is particularly important for the overall East Antarctic ice sheet mass balance.

Abstract: In response to climate change, most glaciers are losing mass and hence contribute to sea-level rise. Repeated and accurate mapping of their surface topography is required to estimate their mass balance and to extrapolate/calibrate sparse field glaciological measurements. In this study we evaluate the potential of sub-meter stereo imagery from the recently launched Pléiades satellites to derive digital elevation models (DEMs) of glaciers and their elevation changes. Our five evaluation sites, where nearly simultaneous field measurements were collected, are located in Iceland, the European Alps, the central Andes, Nepal and Antarctica. For Iceland, the Pléiades DEM is also compared to a lidar DEM. The vertical biases of the Pléiades DEMs are less than 1 m if ground control points (GCPs) are used, but reach up to 7 m without GCPs. Even without GCPs, vertical biases can be reduced to a few decimetres by horizontal and vertical co-registration of the DEMs to reference altimetric data on ice-free terrain. Around these biases, the vertical precision of the Pléiades DEMs is ±1 m and even ±0.5 m on the flat glacier tongues (1σ confidence level). Similar precision levels are obtained in the accumulation areas of glaciers and in Antarctica. We also demonstrate the high potential of Pléiades DEMs for measuring seasonal, annual and multi-annual elevation changes with an accuracy of 1 m or better if cloud-free images are available. The negative region-wide mass balances of glaciers in the Mont-Blanc area (−1.04 ± 0.23 m a−1 water equivalent, w.e.) are revealed by differencing Satellite pour l'Observation de la Terre 5 (SPOT 5) and Pléiades DEMs acquired in August 2003 and 2012, confirming the accelerated glacial wastage in the European Alps.

Abstract: The values of the snow and soil thermal conductivity, ksnow and ksoil, strongly impact the thermal regime of the ground in the Arctic, but very few data are available to test model predictions for these variables. We have monitored ksnow and ksoil using heated needle probes at Bylot Island in the Canadian High Arctic (73° N, 80° W) between July 2013 and July 2015. Few ksnow data were obtained during the 2013–2014 winter, because little snow was present. During the 2014–2015 winter ksnow monitoring at 2, 12 and 22 cm heights and field observations show that a depth hoar layer with ksnow around 0.02 W m−1 K−1 rapidly formed. At 12 and 22 cm, wind slabs with ksnow around 0.2 to 0.3 W m−1 K−1 formed. The monitoring of ksoil at 10 cm depth shows that in thawed soil ksoil was around 0.7 W m−1 K−1, while in frozen soil it was around 1.9 W m−1 K−1. The transition between both values took place within a few days, with faster thawing than freezing and a hysteresis effect evidenced in the thermal conductivity–liquid water content relationship. The fast transitions suggest that the use of a bimodal distribution of ksoil for modelling may be an interesting option that deserves further testing. Simulations of ksnow using the snow physics model Crocus were performed. Contrary to observations, Crocus predicts high ksnow values at the base of the snowpack (0.12–0.27 W m−1 K−1) and low ones in its upper parts (0.02–0.12 W m−1 K−1). We diagnose that this is because Crocus does not describe the large upward water vapour fluxes caused by the temperature gradient in the snow and soil. These fluxes produce mass transfer between the soil and lower snow layers to the upper snow layers and the atmosphere. Finally, we discuss the importance of the structure and properties of the Arctic snowpack on subnivean life, as species such as lemmings live under the snow most of the year and must travel in the lower snow layer in search of food.

Abstract: In the 2019/2020 austral summer, the surface melt duration and extent on the northern George VI Ice Shelf (GVIIS) was exceptional compared to the 31 previous summers of distinctly lower melt. This finding is based on analysis of near-continuous 41-year satellite microwave radiometer and scatterometer data, which are sensitive to meltwater on the ice shelf surface and in the near-surface snow. Using optical satellite imagery from Landsat 8 (2013 to 2020) and Sentinel-2 (2017 to 2020), record volumes of surface meltwater ponding were also observed on the northern GVIIS in 2019/2020, with 23 % of the surface area covered by 0.62 km³ of ponded meltwater on 19 January. These exceptional melt and surface ponding conditions in 2019/2020 were driven by sustained air temperatures ≥0 ^∘C for anomalously long periods (55 to 90 h) from late November onwards, which limited meltwater refreezing. The sustained warm periods were likely driven by warm, low-speed (≤7.5 m s⁻¹) northwesterly and northeasterly winds and not by foehn wind conditions, which were only present for 9 h total in the 2019/2020 melt season. Increased surface ponding on ice shelves may threaten their stability through increased potential for hydrofracture initiation; a risk that may increase due to firn air content depletion in response to near-surface melting.