Mountain snowpacks are a source of freshwater for billions of people globally. However, these snowpacks are under profound threat due to climate change as patterns of snowfall and ablation change. There is a significant and timely need to diagnose how these snowpacks are currently changing and how they will change under future climates to better provide estimates of freshwater availability. Mountain snowpacks are influenced by a set of cascading emergent behaviours, where periods of snowfall, wind redistribution events and avalanches shape the snowpacks before spring and summer ablation via spatially distributed energy fluxes. The complex spatial pattern of snowpack ablation impacts freshwater inputs to local ecology, stream flows, and groundwater recharge. Contextualizing the current and predicted snowpack changes against historical trends motivates using global and continental reanalysis products to provide historical forcing data for snowpack simulations. However, these reanalyses are spatially coarse (~10 to 25 km), and it has not been well established if key forcing variables, such as wind speed and direction, are sufficient to drive snowdrift permitting scale snow models. In this work, the multiscale Canadian Hydrological Model (CHM) is driven with ERA5-land (global) and the Canadian Surface reanalysis (CaSR; North America) reanalysis at a snowdrift permitting resolution to evaluate their capacity to be used to produce historical estimates of high-resolution mountain snowpacks. The INARCH COPE Kananaskis region of the Canadian Rockies is used to evaluate downscaled windfields and simulated snowpack against in situ observations and lidar snow depth.