Quantifying the Relationship between Southern-End Supercells and Tornado Production

For decades, there has been a common practice among tornado chasers of targeting the southernmost supercell (colloquially known as the “Tail-end Charlie) when there are multiple supercells aligned in a north-south manner. It is thought that this practice is based off of the belief that the southernmost storm has the greatest likelihood of producing a tornado due to its relatively uncontaminated inflow and its tendency to remain isolated longer than cells farther north. This work aims to statistically evaluate the distribution of tornado-producing supercells in the U.S., when multiple (2 or more) supercells are linearly oriented along a north-south axis, to determine if the southern-end storm is indeed favored for tornado production over the others. All cases from 2016 with lines of multiple north-south oriented supercells, as well as specific selected cases from other years, were gathered using data from the SPC SeverePlot 3.0 online database and Level II NEXRAD data. A total of 324 supercells and 123 tornadoes were sampled. The c² statistic was used to analyze sources of dependency between the events individually and collectively, the total number of supercells in the line, month of occurrence, geographic region, type of surface boundary initiating the storms, and EF scale tornado ratings. It was found that in the month of April, fewer southernmost supercells produced tornadoes than expected; more north-south oriented lines occurred in the Southern Plains, but there was no statistical dependency between southern-end storm tornado production and geographic location; the dryline produced more lines of discrete supercells than other frontal boundaries; warm fronts and the dryline produced more southernmost tornadoes than expected, but it was not statistically significant. Ultimately, there were no statistically significant trends to indicate that southernmost supercells are more prolific tornado producers than other supercells in the line, although some groupings had stronger dependence than others. Specific events and other parameters are observed in detail to examine any other possible correlations.