A Mesoseale Numerical Model of Lake-Fffect Storms

Abstract

The atmospheric structure upwind of the Great takes during arctic air outbreaks is represented by three layers: a lower constant flux layer in contact with the ground, a well-mixed planetary boundary layer surmounted by an inversion, and a deep stratum of overlying stable air. The set of primitive equations is averaged through the depth of the mixed layer to yield predictive equations for the horizontal components of velocity, potential temperature and specific humidity in the layer, and the height of the inversion. Interactions between the well-mixed convective layer and both the underlying and overlying layers are parameterized so that time-dependent calculations can be limited to a single layer. Precipitation from cumulus clouds within the layer is represented in terms of the mesoscale variables and latent heat is included. The equation set has been solved numerically for a 2000-point grid mesh centered on Lake Erie. Grid separation was 6 km in the cross-lake direction and 12 km along the lake axis. Initial conditions were specified to be balanced and everywhere uniform. Terrain influences, surface roughness and temperature variations, and moisture fluxes were then allowed to perturb the mixed layer until the resulting mesoscale disturbance approached a steady state. Experiments revealed that each of the surface forcing factors contributed significantly and tended to complement each other in shaping the lake-effect storm. Alterations in prevailing flow produced realistic changes in storm morphology. Patterns of disturbance in the height of the inversion appear to be well correlated with observed radar and snowfall patterns. A case study of the 1–2 December 1966 storm demonstrated quite good simulators of precipitation patterns and amounts but data are insufficient to test many other aspects of the model results. It is concluded that a single layer can be used to represent many of the significant aspects of lake-effect storms and that the mesoseale disturbance provides effective control over the location and intensity of convective activity.