Recent developments in snow stability modeling demonstrated the great potential of numerical snow cover modeling for avalanche forecasting. The recently developed metrics provided promising results, possibly even superseding traditional stability indices. To further validate these results, we compared the temporal evolution of various stability metrics to a unique data set of measurements including snow stratigraphy, snow microstructure and stability at the Steintälli site (Davos, Switzerland). From January to March 2016, we measured the shear strength of a prominent weak layer of depth hoar crystals with the shear frame and the critical crack length in propagation saw tests. Concurrently, we characterized snow microstructure with the snow micro-penetrometer (SMP) and ran the numerical snow cover model SNOWPACK with the data from the automatic weather station at the site. Our results show that initially, strength and toughness were low, but increased with time; they were correlated. Also, load increased with time, and strength and toughness were correlated with load. While in the field we monitored the most prominent weak layer in the snowpack, the modelled stability metrics indicated that different weak layers, closer to the snow surface, were more prone to fail later in the season. The three stability metrics we compared showed similar temporal trends and performance with regard to avalanche activity in the region of Davos and forecast danger levels. Our detailed site-specific validation indicates that numerical stability metrics provide valuable data for avalanche forecasting though different indices show different behavior at times calling for specific interpretation.