Snow modeling within a multi-layer soil-vegetation-atmosphere model

Abstract:

Estimates of snow depth, extent, and melt in the Sierra Nevada Mountain Range are critical to estimating the amount of water that will be available for crops during the growing season within California's Central Valley. Numerical simulations utilizing a fourth order turbulent closure transport scheme in a multi-layer soil-vegetation-atmosphere model, Advanced Canopy-Atmosphere-Soil algorithm (ACASA), were used to explore snow model improvements in the physics-based parameterization for the Sierra Nevada Range. A set of alterations were made separately to the existing snowpack model within ACASA focusing on improvements to snow cover simulations on complex terrain slopes and over varying canopy cover. Three winter seasons were simulated; a climatological average, dry, and wet winter. The simulated output from the models are compared to observations to determine which model alterations made the largest improvements to snow simulations.