The development of reliable models of near surface snow-atmosphere interactions from small to large scale is motivated by the need for a better understanding of the fluid- and morpho-dynamic processes in Polar environments. These interactions drive observed spatial patterns of snow distribution, ice deformation, travel and distribution of sea ice, among many others. However, challenges arise when representing the detailed sequence of processes involved, such as aerodynamic entrainment, particle dynamics, feedback on fluid momentum and particle impact on the surface. Here, we test a Lagrangian Stochastic Model of snow particle transport coupled to a Large Eddy Simulation to represent particle dynamics in turbulent flows and momentum extraction caused by suspended particles. An Immersed Boundary Method is adopted to effectively reproduce surface erosion and deposition, both of which influence surface drag and turbulence statistics. The model is implemented to represent snow redistribution over an Antarctic sea ice floe over which pre- and post- storm snow distribution patterns were successfully quantified using a terrestrial laser scanner. The dataset collected in October 2012 as part of the SIPEX-2 indicates marked changes in the snow distribution as a result of particle transport processes, providing valuable testing grounds for the model. The modeled snow surface pattern and the spatially variable shear stress evolve and reciprocally interact, generating areas of preferential deposition and erosion consistent with the observations. Model results and future improvements are discussed.