Modeling study demonstrates improved snowpack density and thermal profiles across polar ice sheets, indicating enhanced capability to project sea level rise.
Accurate modeling of the snowpack over ice sheets is essential for quantifying their surface mass balance contribution and their resulting impact on sea level rise. The snowpack evolution is largely governed by surface climate but also by internal processes such as densification. In land surface models, such processes are often represented using formulations developed for seasonal snow, limiting their realism in polar environments. To improve the representation of polar snow in the land surface model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems), the surface component of the IPSL-CM climate model, we implement a series of developments over Greenland and Antarctica. These developments include (1) a new snowpack initialization procedure that generates deep, physically consistent density profiles based solely on latitude and elevation aimed to be included in other snowpack models, (2) a wind-based surface snow density parameterization applicable to both Greenland and Antarctica, and (3) a recalibrated dry-snow densification scheme for snowpack compaction, using observations and 1D and 2D offline simulations. These developments improve the simulation of surface snow density as well as the internal snowpack structure, including both density and temperature, with good agreement with dry-snow observations. Discrepancies still persist in representing the Greenland ablation zones, suggesting that further improvements in surface energy balance processes are needed, with specific attention to snow albedo.
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A 2026 study studied this question.