Snow presents unique characteristics that pose challenges to conventional modeling approaches. Its nonlinear behaviour, intrinsic large deformations, and time- and rate-dependent response to mechanical actions make it a material for which is difficult to use conventional constitutive laws and numerical algorithms. Moreover, temperature variations induce metamorphisms that modify the original shape of snow crystals. Sintering, occurring at low thermal gradients, transforms snow particles into denser structures with enhanced mechanical properties. Conversely, high gradients yield low-density, brittle snow patterns. Having a constitutive model capable of accurately representing these unique features of snow behaviour and, at the same time, reproducing different snow types is of paramount importance. Furthermore, understanding these phenomena is crucial for various applications, including avalanche modeling, risk assessment, vehicle safety on snowy roads, and design of structures in cold environments. Here, we apply a novel constitutive model based on the elasto-viscoplastic theory, implemented in the finite element software Abaqus/Standard by means of a nonlinear implicit numerical algorithm. We highlight the role of sintering and validate the model against experimental data, emphasizing its performance in non-homogeneous strain conditions. Furthermore, we explore the influence of deformation rates on the mechanical response of snow. With reference to the latter topic, we present the findings from simulations of confined compression experiments, documented in the literature, revealing certain patterns of strain rate localization.