Snow’s thermal and radiative properties strongly impact the land surface energy balance and thus the atmosphere above it. Land surface snow information is poorly known in mountainous regions. Few studies have examined the impact of initial land surface snow conditions in high resolution, convection permitting numerical weather prediction models during the mid-latitude cool season. The extent to which land surface snow influences atmospheric energy transport and subsequent surface meteorological states is tested using a high resolution (1km) configuration of the Weather Research and Forecasting (WRF) model, for both calm conditions and weather characteristic of a warm late March Atmospheric River. A set of synthetic but realistic snow states are used as initial conditions for the model runs and the resulting differences are compared. We find that snow reduces/increases two meter air temperatures by as much as 4K during both periods, and that the atmosphere responds to snow perturbations through advection of moist static energy from neighboring regions. Snow mass and snow covered area are both important variables that influence two meter air temperature. Finally, the meteorological states produced from the WRF experiments are used to force an offline hydrologic model, demonstrating that snow melt rates can increase/decrease by factor of two depending on the initial snow conditions used in the parent weather model. We propose that more realistic representations of land surface snow properties in mesoscale models may be a source of hydrometeorological predictability

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