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

N. E. Theeuwes,A. A. M. Holtslag,F. Krikken,G. J. Steeneveld

doi:10.5194/asr-4-15-2010

N. E. Theeuwes, A. A. M. Holtslag + Show 2 more

Open Access

https://doi.org/10.5194/asr-4-15-2010

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Abstract

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.

Highlights

Forecasting the timing, location and intensity of lake effect snow (LES) is one of the most challenging problems concerning weather forecasting in the Great Lakes region of the U.S.A. and Canada
The atmospheric boundary layer (ABL) scheme used for this research is the computationally efficient Medium Range Forecast (MRF) model (Hong and Pan, 1996), since it has shown superior skill over other ABL schemes for convective conditions (e.g. Holtslag and Boville, 1993)
The modeled wind direction at the surface was southwest, as observed at the Buffalo weather station. This means the air traveled over a large part of Lake Erie

Summary

Introduction

Forecasting the timing, location and intensity of lake effect snow (LES) is one of the most challenging problems concerning weather forecasting in the Great Lakes region of the U.S.A. and Canada. LES is a mesoscale convective precipitation event that occurs when stably stratified arctic air is destabilized over a relatively warm lake These storms can result in extreme precipitation with snowfall of 150–250 cm over a multiday period (Niziol et al, 1995). This has significant impacts on the regional infrastructure and transportation Since this type of event cannot be well forecasted using synoptic data (Niziol et al, 1995), a mesoscale meteorological model may provide better results. Ballentine et al (1998) examined whether a LES storm over Lake Ontario was well represented in a mesoscale model They managed to forecast the location and intensity of lake effect with MM5 successfully, there were errors in the timing of a few hours. WRF has not often been used to study LES, except in Maesaka et al (2006) who found that WRF was able to model LES belts fairly well

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