Mesoscale modeling of lake effect snow over Lake Erie – sensitivity to convection, microphysics and the water temperature

Abstract. Lake effect snow is a shallow convection phenomenon during cold air advection over a relatively warm lake. A severe case of lake effect snow over Lake Erie on 24 December 2001 was studied with the MM5 and WRF mesoscale models. This particular case provided over 200 cm of snow in Buffalo (NY), caused three casualties and $10 million of material damage. Hence, the need for a reliable forecast of the lake effect snow phenomenon is evident. MM5 and WRF simulate lake effect snow successfully, although the intensity of the snowbelt is underestimated. It appears that significant differences occur between using a simple and a complex microphysics scheme. In MM5, the use of the simple-ice microphysics scheme results in the triggering of the convection much earlier in time than with the more sophisticated Reisner-Graupel-scheme. Furthermore, we find a large difference in the maximum precipitation between the different nested domains: Reisner-Graupel produces larger differences in precipitation between the domains than "simple ice". In WRF, the sophisticated Thompson microphysics scheme simulates less precipitation than the simple WSM3 scheme. Increased temperature of Lake Erie results in an exponential growth in the 24-h precipitation. Regarding the convection scheme, the updated Kain-Fritsch scheme (especially designed for shallow convection during lake effect snow), gives only slight differences in precipitation between the updated and the original scheme.