Snow disappearance date (SDD) has a substantial impact on the ecohydrological dynamics of montane forests, by affecting soil moisture, ecosystem water availability, and fire risk. The forest canopy modulates SDD through competing processes, such as intercepting snowfall and enhancing longwave radiation (LWR) versus reducing near surface shortwave radiation (SWR) and wind speed. Limited ground-based observations of snow presence and absence have restricted our ability to unravel the dominant processes affecting SDD over mountains with complex forest structure. We apply a lidar-derived method to estimate fractional snow cover area (fSCA) at two relatively warm sites in the Sierra Nevada and two colder sites in the Rocky Mountain. Our analyses show that warm sites and lower elevations are characterized by higher LWR and canopy snow interception leading to less snow retention under dense forest canopy. In contrast, snow retention in colder forests can be longer in open or under canopy depending on interactions between vegetation structure and topography. These colder climates have greater under canopy snow retention on north-facing slopes and under low vegetation density areas, but greater snow retention in open areas at lower elevations and south-facing slopes. We develop a new conceptual model to incorporate the role of topography and vegetation structure into existing climate-based frameworks. The inferences into the interacting energy and mass controls, derived from our lidar datasets give opportunities to improve hydrological modeling and provide targeted forest management recommendations.