An evaluation of high-resolution regional climate model simulations of snow cover and albedo over the Rocky Mountains, with implications for the simulated snow-albedo feedback

The snow-albedo feedback (SAF) strongly influences climate over midlatitude mountainous regions. However, over these regions the skill of regional climate models (RCMs) at simulating properties such as snow cover and surface albedo is poorly characterized. These properties are evaluated in a pair of 7year long high-resolution RCM simulations with the Weather Research and Forecasting model over the central Rocky Mountains. Key differences between the simulations include the computational domain (regional versus continental) and land surface model used (Noah versus Noah-MP). Simulations are evaluated against high-resolution satellite estimates of snow cover and albedo from the Moderate Resolution Imaging Spectroradiometer. Both simulations generally reproduce the observed seasonal and spatial variability of snow cover and also exhibit important biases. One simulation substantially overpredicts subpixel fractional snow cover over snowy pixels (by up to 0.4) causing large positive biases in surface albedo, likely due in part to inadequate representation of canopy effects. The other simulation exhibits a negative bias in areal snow extent (as much as 19% of the analysis domain). Surface measurements reveal large positive biases in snow albedo (exceeding 0.2) during late spring caused by neglecting radiative effects of impurities deposited onto snow. Semi-idealized climate change experiments show substantially different magnitudes of SAF-enhanced warming in the two simulations that can be tied to the differences in snow cover in their control climates. More confident projections of regional climate change over mountains will require further work to evaluate and improve representation of snow cover and albedo in RCMs.