The performance of Advanced Driver Assistance Systems can degrade in the case of adverse weather conditions, reducing their effectiveness. Snow accumulation on the secondary surface of the sensors is a primary contributor to this loss of performance. Modelling this phenomenon in the early stages of vehicle design is crucial for enhancing the passive performance of the deicing systems and minimizing the need for extensive road testing. This work presents a comparison of the results of an Ahmed body simulated through two distinct CFD methodologies: Lagrangian Multi-Phase (LMP) and Smoothed Particle Hydrodynamics (SPH). Both methodologies are compared to the environmental wind tunnel measurements of the same geometry under similar snow type conditions. In both simulations, the flow field of the Ahmed body is obtained through a transient RANS-LES approach, i.e., Improved Delayed Detached Eddy Simulation (IDDES), which is standard practice in the automotive industry. The particle model in the LMP solver employs a one-way coupling with the flow, and an energetic threshold for deposition and re-suspension. In contrast, the SPH method models the snow as a continuous elastoplastic material and treats interactions with the rigid boundaries as viscous phenomena. Additionally, the SPH method has been calibrated against the environmental wind tunnel measurements and snow characterization tests. Finally, we highlighted the limitations of each method regarding how they handle snowflake impacts with the boundary surface and particle re-suspension phenomenon by graphically comparing the snowflakes deposition pattern on the Ahmed body. Next, we propose considerations for overcoming these limitations. In summary, the original contribution proposed by this research consists in the graphical comparison of two different simulation methods, elucidating their strengths and weaknesses. Engineers can leverage these tools to accelerate and reduce costs in the early development phase.