Predicting propagating convective systems using operational forecast models

Mesoscale convective systems (MCSs) produce a considerable amount of significant severe weather during the warm season. Yet these systems can be notoriously difficult to predict, especially their direction of movement. System movement is determined by a combination of larger-scale forcing mechanisms and convective propagation. When the propagation component is large, predicting system movement becomes particularly challenging.

Recent studies have suggested that this challenge is magnified by poor forecasts of convective propagation in mesoscale NWP models. These poor forecasts have been attributed to parameterized convection. However, detailed analyses of forecasts from the operational Eta model indicate that its convective parameterization scheme can induce strongly propagating MCSs under the right conditions. For example, a large, bowing MCS occurred on 11 June 2001. On this day the Eta model produced a bowing, propagating convective line, similar to observations of this event.

In this study, the physical mechanisms of propagation are identified and linked to specific characteristics of the environment and the convective parameterization. We have determined that the certain types of feedback from the convective scheme induce gravity wave-like features that resonate with the parameterized convection, promoting propagation of the larger system. Now that this propagation mechanism is understood, there is promise that it can be harnessed to provide more realistic propagating MCSs in mesoscale NWP models and more accurate operational forecasts of severe convective episodes associated with MCSs. Detailed analyses and the implications of these results will be discussed at the conference.