An Observational Examination of Supercell and Squall Line Thunderstorm Interactions

Widespread severe weather outbreaks often contain multiple storm organizations, with supercells and squall lines generally producing most of the severe weather hazards (large hail, damaging winds, and tornadoes). Recent research has focused on cases where squall lines and supercells merged into a single system and noted some changes to storm structure in advance of the merger. This included changes in low-level rotation in supercells and anecdotal evidence that supercells in close proximity to a squall line produced longer-tracked tornadoes than other supercells in the same environment. The goal of this study is to further document changes in the storm structure and intensity of supercell and squall line storms when they are in close proximity to each other. Past research has shown that supercells and squall lines can both modify their local environments, including changes to the wind and thermodynamic profiles. The present study will use radar data from observed cases to determine if the two storms evolve consistently with expected changes to their local environments. This will be accomplished using archived WSR-88D data analyzed with the Warning Decision Support System -- Integrated Information (WDSS-II) software for multiple cases over a range of environments. By analyzing the evolution of radar parameters including reflectivity factor, velocity, azimuthal shear, vertically integrated liquid (VIL), hail detection algorithms (HDA), and echo tops, we plan to document any common changes to squall line and supercell intensity when the two are in close proximity. The results of this analysis will help to better define a conceptual model of how these two storm types interact when in close proximity, and provide observation-based “ground truth” with which to evaluate on-going numerical model simulations of similar interactions. Ultimately, the combined results of these projects are intended to aid in the development of future forecasting techniques to help enhance severe weather warnings during these types of complex weather events.