The hydrology of alpine areas is highly snow-dependent. Snowmelt, as a major component of the hydrologic cycle, influences the streams hydrology and biogeochemistry and is important to take into account in water resources management. Modeling snow distribution and snow melt in mountainous regions is challenging due to the complexity of the topography and its influence on meteorological parameters. Topographic shadows, for example lead to a high variability of Incoming ShortWave Radiation (ISWR) on short spatial and time scales. Therefore the influence of shadows needs to be considered in the spatial interpolation of point measurements over an area. Simple distance based interpolation algorithms like Inverse Distance Weighting (IDW) usually do not take into account the intrinsic variability of the studied phenomenon. A modified IDW method accounting for shadows is therefore introduced. Mountain shading is computed with an algorithm based on an irregular triangulated representation of the topography. The shadow information is then used as an a priori information in the interpolation process. The modified IDW accounting for shadows leads to a significant improvement of the agreement between measured and interpolated ISWR. A maximum and median RMSE improvement of 75% and 26% were achieved when switching from the classical IDW to the modified one. Such differences in the interpolated ISWR lead to significant shifts of simulated snow free dates and melting patterns especially in the regions strongly shadowed during the melting season. This study emphasizes the importance of accounting for shadows in solar radiation interpolation. However, proper modeling of snowmelt also requires to put efforts in the correction and interpolation of other meteorological parameters.