A tomography-based methodology for the mass transport characterization of snow is presented. Five samples, characteristic for a wide range of seasonal snow, are considered. Their three-dimensional (3-D) geometrical representations are obtained by micro-computed tomography and used in direct pore-level simulations to numerically solve the governing mass and momentum conservation equations, allowing for the determination of their effective permeability and Dupuit-Forchheimer coefficient. The extension to the Dupuit-Forchheimer coefficient is useful near the snow surface, where Reynolds numbers higher than unity can appear. Simplified semi-empirical models of porous media are also examined. The methodology presented allows for the determination of snow's effective mass transport properties, which are strongly dependent on the snow microstructure and morphology. These effective properties can, in turn, readily be used in snowpack volume-averaged (continuum) models such as strongly layered samples with macroscopically anisotropic properties.