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Picard G, Royer A, Arnaud L, Fily M, . (2014). Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica
. TC, 8(3), 1105–1119.
Abstract: based on BIPOL and CALVA-snow
Programme: 1110
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Berthier E, Vincent C, Magnússon E, Gunnlaugsson Á Þ, Pitte P, Le Meur E, Masiokas M, Ruiz L, Pálsson F, Belart J M C, Wagnon P, . (2014). Glacier topography and elevation changes derived from Pléiades sub-meter stereo images
. 1994-0416, 8(6), 2275–2291.
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.
Programme: 1053
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Barral H, Genthon C, Trouvilliez A, Brun C, Amory C, . (2014). Blowing snow in coastal Adélie Land, Antarctica: three atmospheric-moisture issues
. TC, 8(5), 1905–1919.
Abstract: Three years of blowing snow observations and associated meteorology along a 7-m mast at site D17 in coastal Adelie Land are presented. The observations are used to address 3 atmospheric moisture issues related to the occurrence of blowing snow, a feature which largely affects many regions of Antarctica: 1) Blowing snow sublimation raises close to saturation the moisture content of the surface atmosphere, and atmospheric models and meteorological analyzes that do not carry blowing snow parameterizations areaffected by a systematic dry bias; 2) While snowpack modeling with a parameterization of surface snow erosion by wind can reproduce the variability of snow accumulation and ablation, ignoring the high levels of atmospheric moisture content associated with blowing snow results in overestimating surface sublimation affecting the energy budget of the snow-pack; 3) the well-known profile method to calculate turbulent moisture fluxes is not applicable when blowing snow occurs, because moisture gradients are weak due to blowing snow sublimation, and the impact of measurement uncertainties are strongly amplified in case of strong winds.
Keywords: Antarctica, Snowpack, Surface Mass Balance, Katabatic flow, Blowing snow, Sublimation, Latent Heat Fluxes, Moisture, Observation, Modelling, Profile method,Monin and Obukhov similarity theory, Uncertainty propagation
Programme: 1013
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Domine F, Barrere M, Sarrazin D, Morin S, Arnaud L, . (2015). Automatic monitoring of the effective thermal conductivity of snow in a low-Arctic shrub tundra
. TC, 9(3), 1265–1276.
Abstract: The effective thermal conductivity of snow, keff, is a critical variable which determines the temperature gradient in the snowpack and heat exchanges between the ground and the atmosphere through the snow. Its accurate knowledge is therefore required to simulate snow metamorphism, the ground thermal regime, permafrost stability, nutrient recycling and vegetation growth. Yet, few data are available on the seasonal evolution of snow thermal conductivity in the Arctic. We have deployed heated needle probes on low-Arctic shrub tundra near Umiujaq, Quebec, (N56340; W76290) and monitored automatically the evolution of keff for two consecutive winters, 2012–2013 and 2013–2014, at four heights in the snowpack. Shrubs are 20 cm high dwarf birch. Here, we develop an algorithm for the automatic determination of keff from the heating curves and obtain 404 keff values. We evaluate possible errors and biases associated with the use of the heated needles. The time evolution of keff is very different for both winters. This is explained by comparing the meteorological conditions in both winters, which induced different conditions for snow metamorphism. In particular, important melting events in the second year increased snow hardness, impeding subsequent densification and increase in thermal conductivity.We conclude that shrubs have very important impacts on snow physical evolution: (1) shrubs absorb light and facilitate snow melt under intense radiation; (2) the dense twig network of dwarf birch prevent snow compaction, and therefore keff increase; (3) the low density depth hoar that forms within shrubs collapsed in late winter, leaving a void that was not filled by snow.
Programme: 1042
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Libois Q, Picard G, Arnaud L, Dumont M, Lafaysse M, Morin S, Lefebvre E, . (2015). Summertime evolution of snow specific surface area close to the surface on the Antarctic Plateau
. The Cryosphere, 9(4). Retrieved July 3, 2024, from http://dx.doi.org/10.5194/tc-9-2383-2015
Abstract: On the Antarctic Plateau, snow specific surface area (SSA) close to the surface shows complex variations at daily to seasonal scales which affect the surface albedo and in turn the surface energy budget of the ice sheet. While snow metamorphism, precipitation and strong wind events are known to drive SSA variations, usually in opposite ways, their relative contributions remain unclear. Here, a comprehensive set of SSA observations at Dome C is analysed with respect to meteorological conditions to assess the respective roles of these factors. The results show an average two-to-three-fold SSA decrease from October to February in the topmost 10 cm, in response to the increase of air temperature and absorption of solar radiation in the snowpack during spring and summer. Surface SSA is also characterised by significant daily to weekly variations, due to the deposition of small crystals with SSA up to 100 m2 kg−1 onto the surface during snowfall and blowing snow events. To complement these field observations, the detailed snowpack model Crocus is used to simulate SSA, with the intent to further investigate the previously found correlation between inter-annual variability of summer SSA decrease and summer precipitation amount. To this end, Crocus parameterizations have been adapted to Dome C conditions, and the model was forced by ERA-Interim reanalysis. It successfully matches the observations at daily to seasonal time scales, except for few cases when snowfalls are not captured by the reanalysis. On the contrary, the inter-annual variability of summer SSA decrease is poorly simulated when compared to 14 years of microwave satellite data sensititve to the near surface SSA. A simulation with disabled summer precipitation confirms the weak influence in the model of the precipitation on metamorphism, with only 6 % enhancement. However we found that disabling strong wind events in the model is sufficient to reconciliate the simulations with the observations. This suggests that Crocus reproduces well the contributions of metamorphism and precipitation on surface SSA, but that snow compaction by the wind might be overestimated in the model.
Programme: 1110
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Amory C, Trouvilliez A, Gallée H, Favier V, Naaim-Bouvet F, Genthon C, Agosta C, Piard L, Bellot H, . (2015). Comparison between observed and simulated aeolian snow mass fluxes in Adélie Land, East Antarctica
. TC, 9(4), 1373–1383.
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Gorodetskaya I V, Kneifel S, Maahn M, Thiery W, Schween J H, Mangold A, Crewell S, Van Lipzig N P M, . (2015). Cloud and precipitation properties from ground-based remote-sensing instruments in East Antarctica
. The Cryosphere, 9(1), 285–304.
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Amory C, Trouvilliez A, Gallée H, Favier V, Naaim-Bouvet F, Genthon C, Agosta C, Piard L, Bellot H, . (2015). Comparison between observed and simulated aeolian snow mass fluxes in Adélie Land, East Antarctica
. The Cryosphere, 9(4), 1373–1383.
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Champollion N, Picard G, Arnaud L, Lefebvre E, Fily M, . (2013). Hoar crystal development and disappearance at Dome C, Antarctica: observation by near-infrared photography and passive microwave satellite . TC, 7(4), 1247–1262.
Abstract: Hoar crystals episodically cover the snow surface in Antarctica and affect the roughness and reflective properties of the airsnow interface. However, little is known about their evolution and the processes responsible for their development and disappearance despite a probable influence on the surface mass balance and energy budget. To investigate hoar evolution, we use continuous observations of the surface by in situ near-infrared photography and by passive microwave remote sensing at Dome C in Antarctica. From the photography data, we retrieved a daily indicator of the presence/absence of hoar crystals using a texture analysis algorithm. The analysis of this 2 yr long time series shows that Dome C surface is covered almost half of the time by hoar. The development of hoar crystals takes a few days and seems to occur whatever the meteorological conditions. In contrast, the disappearance of hoar is rapid (a few hours) and coincident with either strong winds or with moderate winds associated with a change in wind direction from southwest (the prevailing direction) to southeast. From the microwave satellite data, we computed the polarisation ratio (i.e. horizontal over vertical polarised brightness temperatures), an indicator known to be sensitive to hoar in Greenland. Photography data and microwave polarisation ratio are correlated, i.e. high values of polarisation ratio which theoretically correspond to low snow density values near the surface are associated with the presence of hoar crystals in the photography data. Satellite data over nearly ten years (20022011) confirm that a strong decrease of the polarisation ratio (i.e. signature of hoar disappearance) is associated with an increase of wind speed or a change in wind direction from the prevailing direction. The photography data provides, in addition, evidence of interactions between hoar and snowfall. Further adding the combined influence of wind speed and wind direction results in a complex picture of the snowatmosphere interactions in Antarctica which deserves further quantification and modelling.
Programme: 1110
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Amory, C., A. Trouvilliez, H. Gallée, F. Naaim-Bouvet, C. Genthon, V. favier, C. Agosta, L. Piard, and H. bellot. (2015). Comparison of aeolian snow transport events and snow mass fluxes between observations and simulations made by the regional climate model MAR in Adélie Land, East Antarctica. TC, 9, 1373–1383.
Abstract: Using the original setup described in Gallée et al. (2013), the MAR regional climate model including a coupled snowpack/aeolian snow transport parameterization, was run at a fine spatial (5 km horizontal and 2 m vertical) resolution over 1 summer month in coastal Adélie Land. Different types of feedback were taken into account in MAR including drag partitioning caused by surface roughness elements. Model outputs are compared with observations made at two coastal locations, D17 and D47, situated respectively 10 and 100 km inland. Wind speed was correctly simulated with positive values of the Nash test (0.60 for D17 and 0.37 for D47) but wind velocities above 10 m s−1 were underestimated at both D17 and D47; at D47, the model consistently underestimated wind velocity by 2 m s−1. Aeolian snow transport events were correctly reproduced with the right timing and a good temporal resolution at both locations except when the maximum particle height was less than 1 m. The threshold friction velocity, evaluated only at D17 for a 7-day period without snowfall, was overestimated. The simulated aeolian snow mass fluxes between 0 and 2 m at D47 displayed the same variations but were underestimated compared to the second-generation FlowCaptTM values, as was the simulated relative humidity at 2 m above the surface. As a result, MAR underestimated the total aeolian horizontal snow transport for the first 2 m above the ground by a factor of 10 compared to estimations by the second-generation FlowCaptTM. The simulation was significantly improved at D47 if a 1-order decrease in the magnitude of z0 was accounted for, but agreement with observations was reduced at D17. Our results suggest that z0 may vary regionally depending on snowpack properties, which are involved in different types of feedback between aeolian transport of snow and z0.
Programme: 1013
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