Abstract. Estimates of snow and firn density are required for satellite altimetry based retrievals of ice sheet mass balance that rely on volume to mass conversions. Therefore, biases and errors in presently used density models confound assessments of ice sheet mass balance, and by extension, ice sheet contribution to sea level rise. Despite this importance, most contemporary firn densification models rely on simplified semi-empirical methods, which are partially reflected by significant modeled density errors when compared to observations. In this study, we present a new, wind-driven, drifting snow compaction scheme that we have implemented into SNOWPACK, a physics-based land surface snow model. We demonstrate high-quality simulation of near-surface Antarctic snow firn density at 122 observed density profiles across the Antarctic ice sheet, as indicated by reduced model biases throughout most of the near-surface firn column when compared to two semi-empirical firn densification models. Because SNOWPACK is physics-based, its performance does not degrade when applied to sites without observations used in the calibration of semi-empirical models, and could therefore better represent firn properties in locations without extensive observations and under future climate scenarios, in which firn properties are expected to diverge from their present state.;
