In this presentation, we will introduce supplemental analytics that assess the quality of TORs on a scale of 0 to 100 throughout the lifetimes of associated tornadoes by considering lead times and tornado damage ratings along their tracks. Such a “feature scaling” approach emphasizes the importance of lead time for the strongest stage of the tornado (based on the damage it produced), when casualties and damage to property are most likely to occur. This quantitative approach is more consistent with both a meteorologist’s qualitative considerations during severe weather operations and the practical impacts to NWS end users. This presentation will also demonstrate an automated method for calculating these supplemental analytics for past events, which could be valuable as a training tool for Science and Operations Officers at local weather forecast offices.

