The snow surface morphology is shaped throughout a winter season by atmospheric conditions, like precipitation, wind, solar irradiance, air temperature or relative humidity. Changes in morphology affect the snow surface roughness which influences the turbulent fluxes of sensible and latent heat, and thus the surface energy balance. The aerodynamic roughness length (z0) is an important parameter to calculate the turbulent fluxes and to characterise the interaction between the atmosphere and the snow surface. However, z0 values used to characterize snow surfaces are rare and often generalized. Moreover, direct measurements are often difficult to achieved and associated with large uncertainty. This study used a fixed automated high-resolution 3D laser scanner to continuously map the snow surface on an hourly basis. The methods of processing point clouds allow to derive surface roughness height maps. These maps were applied to several models to estimate z0 values for each scan, based on the microtopographic approach. To validate the geometric z0 values derived from the scanner, a sonic anemometer is used to directly measure the anemometric z0 values on the study area. The results first highlight the robustness of the laser scanner and the methods used to derive snow height maps and snow roughness maps. The Lettau model for the derivation of z0 from the scans was found to agree best with the measured z0 values from the sonic during stable wind conditions. This point out that the z0 values over the snow season range from 0.1 mm to 4 mm. Furthermore, the chosen interpolation cell size for the methods based on Lettau’s equation and the window moving filter size for the detrending process turned out to have a large impact on the z0 values, presenting a range up to 1 order of magnitude each or more. Snow surface reflectance values from the scanner were found to be representative of the surface snow grain size and shape under certain atmospheric conditions.