The Importance of Understanding Mesoscale Model Parameterization Schemes for Weather Forecasting

Abstract

A severe weather outbreak that occurred on 21?23 November 1992 in the southern United States is used to illustrate how an understanding of model parameterization schemes can help in the evaluation and utilization of mesoscale model output. Results from a mesoscale model simulation show that although the model accurately simulated many of the observed mesoscale features, there are several aspects of the model simulation that are not perfect. Through an understanding of the model parameterization schemes, these model imperfections are analyzed and found to have little effect on the overall skill of the model forecast in this case. Mesoscale model output also is used to provide guidance to evaluate the severe weather threat. By using the model output to produce hourly calculations of convective available potential energy (CAPE) and storm relative environmental helicity (SREH), it is found that regions with positive CAPE, SREH greater than 150 m2 s?2, and model-produced convective rainfall correspond well with areas in which supercell thunderstorms developed. In addition, these parameters are highly variable in both space and time, accentuating the need for continuous monitoring in an operational environment and frequent model output times.