The objective of this project has been to explore the potential of the wind over complex terrain, as an energy source during wintertime in Switzerland. A wind assessment method is developed based on short-term wind profile measurements with a wind lidar, long-duration meteorological station measurements, which are connected via machine learning to a specific site. Driving a high-resolution numerical weather model (WRF) with COSMO model as an input, we create a map of the spatial pattern of the local wind speed potential for short episodes of predominating weather patterns. We further use Wind-Topo, a very recent machine learning model, which predicts wind potential at high spatial and temporal resolution, to reproduce first the WRF simulations and then yearly averages. The yearly averages are used as a basis of comparison with the Swiss wind atlas. This report provides the local air flow analysis based on two measurement campaigns at La Stadera, near the Lukmanier Pass, GR, and at Cabane, Glacier3000 near Les Diablerets, VD, as examples of 3D wind assessment in complex terrain. Furthermore, a previous assessment in Eastern Switzerland is re-calculated with Wind-Topo. The results show that the Swiss wind atlas provides a good estimate of wind potential at the two measurement sites and that spatial patterns are comparable but not identical to Wind-Topo. The in-depth analysis of spatial patterns from both, Wind-Topo and WRF, suggest that areas of high wind potential may be missed by the wind atlas in particular in slopes and valleys. The spatial analysis presented here has limited validation and we suggest further investigation of these effects and an update of the Swiss wind atlas at higher temporal and spatial resolution. This appears necessary to assist and promote the transition of the Swiss electricity supply system towards renewable energy resources.