. (2014). Using MODIS land surface temperatures and the Crocus snow model to understand the warm bias of ERA-Interim reanalyses at the surface in Antarctica
. TC, 8(4), 1361–1373.
Abstract: based on CALVA-snow activities
Programme: 1110
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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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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 29, 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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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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J. C. Stroeve, S. Jenouvrier, G. G. Campbell, C. Barbraud, K. Delord. (2016). Mapping and assessing variability in the Antarctic marginal ice zone, pack ice and coastal polynyas in two sea ice algorithms with implications on breeding success of snow petrels (Vol. 10).
Abstract: Sea ice variability within the marginal ice zone (MIZ) and polynyas plays an important role for phytoplankton productivity and krill abundance. Therefore, mapping their spatial extent as well as seasonal and interannual variability is essential for understanding how current and future changes in these biologically active regions may impact the Antarctic marine ecosystem. Knowledge of the distribution of MIZ, consolidated pack ice and coastal polynyas in the total Antarctic sea ice cover may also help to shed light on the factors contributing towards recent expansion of the Antarctic ice cover in some regions and contraction in others. The long-term passive microwave satellite data record provides the longest and most consistent record for assessing the proportion of the sea ice cover that is covered by each of these ice categories. However, estimates of the amount of MIZ, consolidated pack ice and polynyas depend strongly on which sea ice algorithm is used. This study uses two popular passive microwave sea ice algorithms, the NASA Team and Bootstrap, and applies the same thresholds to the sea ice concentrations to evaluate the distribution and variability in the MIZ, the consolidated pack ice and coastal polynyas. Results reveal that the seasonal cycle in the MIZ and pack ice is generally similar between both algorithms, yet the NASA Team algorithm has on average twice the MIZ and half the consolidated pack ice area as the Bootstrap algorithm. Trends also differ, with the Bootstrap algorithm suggesting statistically significant trends towards increased pack ice area and no statistically significant trends in the MIZ. The NASA Team algorithm on the other hand indicates statistically significant positive trends in the MIZ during spring. Potential coastal polynya area and amount of broken ice within the consolidated ice pack are also larger in the NASA Team algorithm. The timing of maximum polynya area may differ by as much as 5 months between algorithms. These differences lead to different relationships between sea ice characteristics and biological processes, as illustrated here with the breeding success of an Antarctic seabird.
Programme: 109
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. (2017). (Vol. 11). Bachelor's thesis, , .
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J. Grazioli, C. Genthon, B. Boudevillain, C. Duran-Alarcon, M. Del Guasta, J.-B. Madeleine, A. Berne. (2017). (Vol. 11).
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. (2014). (Vol. 8).
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F. Domine, M. Barrere, D. Sarrazin. (2016). Seasonal evolution of the effective thermal conductivity of the snow and the soil in high Arctic herb tundra at Bylot Island, Canada (Vol. 10).
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. (2014). 1994-0416, 8(6), 2275–2291.
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