Evaluating the Three-Ingredients Method for Nowcasting QLCS Tornadoes

Quasi-linear convective system (QLCS) tornadoes pose a significant challenge for forecasters across the United States. These tornadoes, which are often smaller and weaker compared to their supercell counterparts, have worse tornado warning skill scores. This may be due to knowledge gaps surrounding processes that lead to QLCS tornadogenesis, or how those processes are linked to the QLCS near-storm environment. This is an issue when you consider many of these tornadoes occur in regions that can be disproportionately affected by severe weather due to socioeconomic factors. Improving tornado warning skill scores for these tornadoes are critical to advancing to the National Weather Service (NWS) core mission of protecting life and property.

NWS forecasters commonly use the “Three Ingredients Method” (3IM) to anticipate QLCS mesovortex- and tornadogenesis. This includes finding balanced or slightly shear dominant regimes of the QLCS, coincident with line normal 0-3 km bulk shear ≥ 30 kts, and surges or bowing segments in the QLCS. Locations that meet all three ingredients are often favored locations for severe storm reports, either through damaging wind and/or tornadoes. Using six years of historical case data, RUC/RAP 0-hour environmental data, and Doppler radar data, this presentation will provide results evaluating both the QLCS tornadic environment and the 3IM. Over 1000 QLCS cases have been analyzed. Preliminary results indicate that lowering the 3IM shear threshold to ≥ 20 kts improves the 3IM tornadic “probability of detection” by approximately 20%, but also increases the number of false positive cases by 9%. Additional analysis shows the 3IM has different verification statistics across the different regions, suggesting the 3IM is not a one size fits all model for nowcasting QLCS tornadoes. This presentation will also discuss other environmental parameters, and suggestions for utilizing these results in the operational environment.