Drifting snow is a widespread feature over the Antarctic ice sheet whose climatological and hydrological significances at the continental scale have been consequently investigated through modelling and satellite approaches. While field measurements are needed to evaluate and interpret model and punctual satellite products, most drifting snow observation campaigns in Antarctica involved data collected at a single location and over short time periods. With the aim of acquiring new data relevant to the observations and modelling of 10 drifting snow in Antarctic conditions, two remote locations in coastal Adelie Land (East Antarctica) 100 km apart were instrumented in January 2010 with meteorological and second-generation IAV Engineering acoustic FlowCapt TM sensors. The data provided nearly continuously so far constitutes the longest dataset of autonomous near-surface (i.e., below 2 m) measurements of drifting snow currently available over the Antarctic continent.This paper presents an assessment of drifting snow occurrences and snow mass transport from up to 9 years 15 (2010-2018) of half-hourly observational records collected in one of the Antarctic regions most prone to snow transport by wind. The dataset is freely available to the scientific community and can be used to complement satellite products and evaluate snow-transport models close to the surface and at high temporal frequency. Wessem et al., 2018; Agosta et al., 2019). A consensus emerging from these efforts that has persisted for more than two decades suggests that, although significant locally, mass loss through wind redistribution and export into the ocean is of minor importance while sublimation during transport remains the dominant sink of mass when evaluated over the whole ice sheet. Conversely, contrasted results are to be found from one study to 35 65 that cannot be sensed remotely nor determined visually. This includes, among others, particle size distributions and related dimensionless shape parameters, total particle numbers and snow mass fluxes at different heights.
2017; vanAlthough the data collected are also relative to the instrument used and can hardly compare to each other, they are eventually useful for modelling experiments. The dimensionless shape parameter and particle number are, for instance, either predicted or prescribed quantities in snow-transport models that compute sublimation rates and 70 snow mass fluxes assuming a gamma distribution of particles (e.g., Déry et al.snow mass fluxes can be directly used to assess the ability of models to reproduce wind-driven snow conditions at a specific location in a qualitative Gallée et al., 2013) or a quantitative (Nishimura and