Snow in mountain catchments serves as a constant water release during the melting season, supporting many human activities downstream. However, it also poses threats to human life and infrastructures, e.g. with wet-or glide-snow avalanches. These avalanches are likely to occur more frequently with a warming climate but are hard to predict due to the spatio-temporal complexity of the involved processes. The snow liquid water content is a key parameter to monitor to address both potentialities and challenges of a melting snowpack. Synthetic Aperture Radar products like Sentinel-1 are valid tools for detecting wet snow, as liquid water increases dielectric losses absorption coefficients, resulting in low backscattering values. Although energy-balance snow models can simulate liquid water distribution as well as other scattering properties, continuous ground truth measurements are needed for validation. However, such datasets are rare, because they are very demanding as of resources and expertise. We present part of a comprehensive dataset of full snow profiles covering one snow season at the Weissfluhjoch field site (Switzerland). This dataset includes detailed manual measurements of important snow microwave properties: temperature, density, specific surface area, liquid water content, and surface roughness. The high temporal and vertical resolution of the dataset allowed us to track the evolution of the wetting front in detail. Moreover, making use of the Snow Microwave Radiative Transfer model (SMRT), we were able to use ground data to successfully reproduce the Sentinel-1 backscattering. Finally, we could give a detailed explanation of the physical processes driving Sentinel-1 backscattering trends and explore the potential of interpreting these trends to track the melting snow process.