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In this study, snow particle size variability was investigated along a transect in Dronning Maud Land from the coast to the polar plateau. The aim of the study was to better understand the spatial and temporal variations in surface snow properties. Samples were collected twice daily during a traverse in 2007-08 to capture regional variability. Local variability was assessed by sampling in 10 x 10m grids (5m spacing) at selected locations. The particle size and shape distributions for each site were analysed through digital image analysis. Snow particle size variability is complex at different scales, and shows an internal variability of 0.18-3.31 mm depending on the sample type (surface, grid or pit). Relationships were verified between particle size and both elevation and distance to the coast (moisture source). Regional seasonal changes were also identified, particularly on the lower elevations of the polar plateau. This dataset may be used to quantitatively analyse the optical properties of surface snow for remote sensing. The details of the spatial and temporal variations observed in our data provide a basis for further studies of the complex and coupled processes affecting snow particle size and the interpretation of remote sensing of snow covered areas.

Knowledge of snow properties across Antarctica is important in estimating how climate could potentially influence the mass balance of the Antarctic ice sheet. However, measuring these variables has proven to be challenging because appropriate techniques have not yet been developed and extensive datasets of field estimates are lacking. The goal of this study was to estimate the relationship between field-observed snow particle-size parameters from across the East Antarctic ice sheet and a suite of spatial datasets (i.e. topography, remote-sensing data) using a principal component analysis (PCA). Five snow particle-size parameters were correlated to spatial datasets of the following five groups: (1) relief properties such as elevation and slope; (2) remote-sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) and synthetic aperture radar (SAR) sensors; (3) spatially interpolated data (i.e. 10 m maps of temperature and approximate snow accumulation in kg m(-2) a(-1)); (4) field-retrieved data on surface roughness; and (5) in situ elevation and distance from the coast. The results show that the relief parameter slope correlated best with the snow particle length and area (r=0.76, r=0.80). Further, the PCA indicated that the different remote-sensing parameters correlated differently with the size parameters and that the most common parameter in visual analysis, particle length (grain diameter), is not always the optimal parameter to characterize the snow particle size as, for example, area correlates better to slope and aspect than length., AuthorCount:4

During the Japanese-Swedish Antarctic traverse expedition of 2007/08, we measured the surface snow density at 46 locations along the 2800 km long route from Syowa station to Wasa station in East Antarctica. The mean snow density for the upper 1 (or 0.5) m layer varied from 333 to 439 kg m(-3) over a region spanning an elevation range of 365-3800 m a.s.l. The density variations were associated with the elevation of the sampling sites; the density decreased as the elevation increased, moving from the coastal region inland. However, the density was relatively insensitive to the change in elevation along the ridge on the Antarctic plateau between Dome F and Kohnen stations. Because surface wind is weak in this region, irrespective of elevation, the wind speed was suggested to play a key role in the near-surface densification. The results of multiple regression performed on the density using meteorological variables were significantly improved by the inclusion of wind speed as a predictor. The regression analysis yielded a linear dependence between the density and the wind speed, with a coefficient of 13.5 kg m(-3) (m s(-1))(-1). This relationship is nearly three times stronger than a value previously computed from a dataset available in Antarctica. Our data indicate that the wind speed is more important to estimates of the surface snow density in Antarctica than has been previously assumed., AuthorCount:7

During the Japanese-Swedish Antarctic traverse expedition of 2007/08, we measured the surface snow density at 46 locations along the 2800 km long route from Syowa station to Wasa station in East Antarctica. The mean snow density for the upper 1 (or 0.5) m layer varied from 333 to 439 kg m^[-3] over a region spanning an elevation range of 365-3800 m a.s.l. The density variations were associated with the elevation of the sampling sites; the density decreased as the elevation increased, moving from the coastal region inland. However, the density was relatively insensitive to the change in elevation along the ridge on the Antarctic plateau between Dome F and Kohnen stations. Because surface wind is weak in this region, irrespective of elevation, the wind speed was suggested to play a key role in the near-surface densification. The results of multiple regression performed on the density using meteorological variables were significantly improved by the inclusion of wind speed as a predictor. The regression analysis yielded a linear dependence between the density and the wind speed, with a coefficient of 13.5 kg m^[-3] (m s^[-1])^[-1]. This relationship is nearly three times stronger than a value previously computed from a dataset available in Antarctica. Our data indicate that the wind speed is more important to estimates of the surface snow density in Antarctica than has been previously assumed.

Understanding spatial snow particle size variations are key to help interpretation of remotely sensed data of snow cover. In the case of Antarctica, remote sensing is the only viable option to estimate the surface mass balance of the ice sheet on continental scale. We have investigated snow particle size variability along a transect from the coast onto the polar plateau in Dronning Maud Land, Antarctica, to better understand the spatial and temporal variations in surface snow properties. Two daily samples were collected during a 55 day traverse to capture the regional variability. Local variability was assessed by sampling in grids at selected locations and the particle size and shape distributions for each site was analysed through digital image analysis, which has the benefit of yielding large quantities of reproducible quantitative data without the need for advanced laboratory analysis. The results provide an understanding of the complexity of snow particle size variability at different scales and show a variability range from 0.18–3.31 mm depending on the sample type (surface, grid or pit). We can verify relationships between grain size and both elevation and distance to the coast (moisture source) but have also identified regional seasonal changes, particularly on the lower elevations of the polar plateau. Our data provide possibilities to quantitatively assess the optical properties of the surface snow for remote sensing. The details of the spatial and temporal variations observed in our data provides a basis for further studies of the complex and coupled processes affecting snow particle size and the interpretation of remote sensing of snow covered areas.