Forecast Sensitivity of Lake-effect Snow to Choice of Boundary Layer Parameterization Scheme

This study assesses the forecast sensitivity of lake-effect snow to various boundary layer parameterization schemes using the WRF-ARW model. Six boundary layer schemes are tested on a case-study of lake-effect snow over Lake Erie in Dec 2009. The experiments reveal significant precipitation differences (as much as 20 mm over 6 h) between the schemes. Consideration of the heat and moisture fluxes shows that schemes producing more precipitation have higher fluxes over the lake. Forcing all schemes to use the same over-water heat and moisture fluxes causes the precipitation forecasts to be in closer agreement. The heat and moisture fluxes are found to be strongly dependent on the similarity-stability functions for heat, momentum, and moisture (Ψ_H, Ψ_M, and Ψ_Q). When the over-water values for Ψ_H, Ψ_M, and Ψ_Q are set to be the same in all schemes, precipitation forecasts are similar in all experiments, thus indicating that the parameterization used to determine Ψ_H, Ψ_M, and Ψ_Q can have profound impacts on forecasts of this type of weather. Comparison of the forecast accumulated precipitation to observations shows that most schemes over predict the precipitation. The scheme in closest agreement is the Mellor-Yamada-Nakanishi-Niino scheme.