ИСТИНА

Flooding of the snowpack on sea ice is a common phenomenon in the Antarctic, driven by the combination of high snowfall rates and relatively thin sea ice. When the weight of the snow forces the ice surface to be depressed below sea level, seawater infiltrates the snowpack, creating a slush layer. This layer can refreeze, forming snow-ice, which can contribute significantly to total ice thickness. Snow-ice formation plays an important role in the Antarctic sea ice mass balance, including compensating for basal ice loss and maintaining the ice cover in regions with high ocean heat fluxes. However, the process of snow-ice formation introduces complexities to the interpretation of remote sensing data, impeding the accurate retrieval of key sea ice parameters, such as thickness, at large scales. Despite its importance, the spatial and temporal variability of snow-ice formation remains not well constrained on a pan-Antarctic scale. This study aims to address this gap by (1) quantifying slush and snow-ice formation across the Southern Ocean, (2) assessing its role in the sea ice mass balance, and (3) evaluating its impact on altimeter-based retrievals of snow depth and sea ice thickness. We employ a Lagrangian framework to track individual virtual ice parcels using satellite-derived sea ice drift vectors. The evolution of each floe and its overlying snowpack is simulated throughout its lifetime using the physics-based SNOWPACK model, driven by meteorological inputs from ERA5 reanalysis and oceanic data from the Global Ice-Ocean Modeling and Assimilation System (GIOMAS). This approach provides high-resolution simulations of snowpack dynamics, including flooding, slush formation, and snow-ice development. By delivering daily spatial distributions of these formations across the Southern Ocean, we enhance our understanding of their contributions to the regional and pan-Antarctic sea ice mass balance, helping to address knowledge gaps in snow-to-ice conversion and its influence on ice thickness variability and resilience. The presence of liquid water and salt in the snowpack significantly alters its dielectric properties, introducing biases in satellite-derived products when these effects are not accounted for. In particular, snow flooding shifts the dominant scattering horizon in Ku-band altimetry, leading to errors in snow depth and sea ice freeboard estimates that propagate into inaccuracies in derived ice thickness and volume. By integrating SNOWPACK results into the Snow Microwave Radiative Transfer Model (SMRT), we simulate satellite-based observations of the surface. This allows us to quantitatively explain the origins of these biases and propose solutions to mitigate them. This work is particularly relevant to the upcoming mission CRISTAL, which will feature a dual-frequency altimeter, including Ku-band, designed to measure and monitor sea ice thickness and snow depth in both the Arctic and Southern Oceans. Our findings provide insights to improve the interpretation and accuracy of data from these missions, ultimately enhancing polar climate monitoring efforts.