Summertime evolution of snow specific surface area close to the surface on the Antarctic Plateau

Abstract

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 2-to-3-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 characterized by significant daily to weekly variations due to the deposition of small crystals with SSA up to 100 m 2 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 interannual variability of summer SSA decrease and summer precipitation amount. To this end, some Crocus parameterizations have been adapted to Dome C conditions, and the model was forced by ERAInterim reanalysis. It successfully matches the observations at daily to seasonal timescales, except for the few cases when snowfalls are not captured by the reanalysis. On the contrary, the interannual variability of summer SSA decrease is poorly simulated when compared to 14 years of microwave satellite data sensitive 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 snow compaction by the wind might be overestimated in the model.

Development and calibration of an automatic spectral albedometer to estimate near-surface snow SSA time series

“…In contrast, Gallet et al (2011) measured SSA vertical profiles at Dome C and obtained radiative transfer calculations in agreement with Hudson et al (2006) observations without adding such a layer. Using snowpack numerical modeling, Libois et al (2015) obtained SSA profiles at Dome C with such a significant gradient near the surface. This is particularly remarkable as their simulations do not consider some processes susceptible to bring small grains on the surface such as shrinking of airborne particles by sublimation or clear-sky precipitation (a.k.a.…”

“…This accuracy is sufficient to achieve a 1 % accuracy of broadband albedo (Gardner and Sharp, 2010) which is considered to be adequate for climate study (Bogren et al, 2016). Intensive campaigns of SSA measurements have provided new insight of the snow metamorphism in the Alps and in Antarctica over seasons and have allowed refined evaluation of detailed snow model predictions (Picard et al, 2012;Morin et al, 2013;Roy et al, 2013;Libois et al, 2015). However, these techniques still require an operator which is often a limitation, particularly in Antarctica.…”

“…Simulations are also used to explore the representativeness of the retrieved SSA. The geophysical interpretation of the 3-year SSA time series obtained with our instrument and its comparison to snow model simulations are addressed in Libois et al (2015). Section 2 describes the retrieval of SSA from spectral albedo and uncertainties induced by instrumental artifacts.…”

Archival processes of the water stable isotope signal in East Antarctic ice cores

“…3) whose seasonal isotopic variations appear more regular and in phase with temperature. (Picard et al, 2012;Libois et al, 2015); the rise usually starts during the first week of December. Rapid falls of the grain index result from important precipitation events and the input of small snow grains from precipitation.…”

“…Picard et al (2012) argue that the grain index is an indicator of the coarsening of snow grains and show its increase in summer to be anti-correlated with the integrated summer precipitation amount. When available, we include Surface Specific Area (SSA) measurements also as an indicator of metamorphism (Libois et al, 2015). These optical methods are completed with snow observations.…”