Abstract. The isotopic compositions of oxygen and hydrogen in ice cores are invaluable tools for the reconstruction of past climate variations. Used alone, they give insights into the variations of the local temperature, whereas taken together they can provide information on the climatic conditions at the point of origin of the moisture. However, recent analyses of snow from shallow pits indicate that the climatic signal can become erased in very low accumulation regions, due to local processes of snow reworking. The signal-to-noise ratio decreases and the climatic signal can then only be retrieved using stacks of several snow pits. Obviously, the signal is not completely lost at this stage, otherwise it would be impossible to extract valuable climate information from ice cores as has been done, for instance, for the last glaciation. To better understand how the climatic signal is passed from the precipitation to the snow, we present here results from varied snow samples from East Antarctica. First, we look at the relationship between isotopes and temperature from a geographical point of view, using results from three traverses across Antarctica, to see how the relationship is built up through the distillation process. We also take advantage of these measures to see how second-order parameters (d-excess and ¹⁷O-excess) are related to δ¹⁸O and how they are controlled. d-excess increases in the interior of the continent (i.e., when δ¹⁸O decreases), due to the distillation process, whereas ¹⁷O-excess decreases in remote areas, due to kinetic fractionation at low temperature. In both cases, these changes are associated with the loss of original information regarding the source. Then, we look at the same relationships in precipitation samples collected over 1 year at Dome C and Vostok, as well as in surface snow at Dome C. We note that the slope of the δ¹⁸O vs. temperature (T) relationship decreases in these samples compared to those from the traverses, and thus caution is advocated when using spatial slopes for past climate reconstruction. The second-order parameters behave in the same way in the precipitation as in the surface snow from traverses, indicating that similar processes are active and that their interpretation in terms of source climatic parameters is strongly complicated by local temperature effects in East Antarctica. Finally we check if the same relationships between δ¹⁸O and second-order parameters are also found in the snow from four snow pits. While the d-excess remains opposed to δ¹⁸O in most snow pits, the ¹⁷O-excess is no longer positively correlated to δ¹⁸O and even shows anti-correlation to δ¹⁸O at Vostok. This may be due to a stratospheric influence at this site and/or to post-deposition processes.

Abstract. In polar regions, sastrugi are a direct manifestation of drifting snow and form the main surface roughness elements. In turn, sastrugi alter the generation of atmospheric turbulence and thus modify the wind field and the aeolian snow mass fluxes. Little attention has been paid to these feedback processes, mainly because of experimental difficulties. As a result, most polar atmospheric models currently ignore sastrugi over snow-covered regions. This paper aims at quantifying the potential influence of sastrugi on the local wind field and on snow erosion over a sastrugi-covered snowfield in coastal Adélie Land, East Antarctica. We focus on two erosion events during which sastrugi responses to shifts in wind direction have been interpreted from temporal variations in drag and aeolian snow mass flux measurements during austral winter 2013. Using this data set, it is shown that (i) neutral stability, 10 m drag coefficient (C_DN10) values are in the range of 1.3–1.5 × 10⁻³ when the wind is well aligned with the sastrugi, (ii) as the wind shifts by only 20–30° away from the streamlined direction, C_DN10 increases (by 30–120 %) and the aeolian snow mass flux decreases (by 30–80 %), thereby reflecting the growing contribution of the sastrugi form drag to the total surface drag and its inhibiting effect on snow erosion, (iii) the timescale of sastrugi aerodynamic adjustment can be as short as 3 h for friction velocities greater than 1 m s⁻¹ and during strong drifting snow conditions and (iv) knowing C_DN10 is not sufficient to estimate the snow erosion flux that results from drag partitioning at the surface because C_DN10 includes the contribution of the sastrugi form drag.

Abstract. This study aims to better understand and quantify the uncertainties in microwave snow emission models using the Dense Media Radiative Theory Multi-Layer model (DMRT-ML) with in situ measurements of snow properties. We use surface-based radiometric measurements at 10.67, 19 and 37 GHz in boreal forest and subarctic environments and a new in situ data set of measurements of snow properties (profiles of density, snow grain size and temperature, soil characterization and ice lens detection) acquired in the James Bay and Umiujaq regions of Northern Québec, Canada. A snow excavation experiment – where snow was removed from the ground to measure the microwave emission of bare frozen ground – shows that small-scale spatial variability (less than 1 km) in the emission of frozen soil is small. Hence, in our case of boreal organic soil, variability in the emission of frozen soil has a small effect on snow-covered brightness temperature (T_B). Grain size and density measurement errors can explain the errors at 37 GHz, while the sensitivity of T_B at 19 GHz to snow increases during the winter because of the snow grain growth that leads to scattering. Furthermore, the inclusion of observed ice lenses in DMRT-ML leads to significant improvements in the simulations at horizontal polarization (H-pol) for the three frequencies (up to 20 K of root mean square error). However, representation of the spatial variability of T_B remains poor at 10.67 and 19 GHz at H-pol given the spatial variability of ice lens characteristics and the difficulty in simulating snowpack stratigraphy related to the snow crust. The results also show that, in our study with the given forest characteristics, forest emission reflected by the snow-covered surface can increase the T_B up to 40 K. The forest contribution varies with vegetation characteristics and a relationship between the downwelling contribution of vegetation and the proportion of pixels occupied by vegetation (trees) in fisheye pictures was found. We perform a comprehensive analysis of the components that contribute to the snow-covered microwave signal, which will help to develop DMRT-ML and to improve the required field measurements. The analysis shows that a better consideration of ice lenses and snow crusts is essential to improve T_B simulations in boreal forest and subarctic environments.

Abstract. Although both the temporal and spatial variations of the snow depth are usually of interest for numerous applications, available measurement techniques are either space-oriented (e.g. terrestrial laser scans) or time-oriented (e.g. ultrasonic ranging probe). Because of snow heterogeneity, measuring depth in a single point is insufficient to provide accurate and representative estimates. We present a cost-effective automatic instrument to acquire spatio-temporal variations of snow depth. The device comprises a laser meter mounted on a 2-axis stage and can scan ≈ 200 000 points over an area of 100–200 m² in 4 h. Two instruments, installed in Antarctica (Dome C) and the French Alps (Col de Porte), have been operating continuously and unattended over 2015 with a success rate of 65 and 90 % respectively. The precision of single point measurements and long-term stability were evaluated to be about 1 cm and the accuracy to be 5 cm or better. The spatial variability in the scanned area reached 7–10 cm (root mean square) at both sites, which means that the number of measurements is sufficient to average out the spatial variability and yield precise mean snow depth. With such high precision, it was possible for the first time at Dome C to (1) observe a 3-month period of regular and slow increase of snow depth without apparent link to snowfalls and (2) highlight that most of the annual accumulation stems from a single event although several snowfall and strong wind events were predicted by the ERA-Interim reanalysis. Finally the paper discusses the benefit of laser scanning compared to multiplying single-point sensors in the context of monitoring snow depth.