Analysis of and Ways to Improve Tornado Warning False Alarms at NWS Louisville (107)
Ryan Sharp, National Weather Service, Louisville, KY
Zack Taylor, National Weather Service
Theodore Funk, National Weather Service
In 2017, National Weather Service (NWS) Louisville (LMK) took a detailed look at our tornado warning statistics over the past ten years, centered on false alarm rate (FAR). Our FAR has been high for many years, in part due to the more tenuous quasi-linear convective system (QLCS) tornadoes that frequent the Ohio Valley. We assessed county-by-county statistics as well as larger geographical zones to determine where FAR needs the most improvement across the forecast area. We also studied the effect of human factors on the warning decision process as determined from a local forecaster survey. Potential ways to improve statistics and overall warning decision support were discussed, including recommendations on warning polygon vs. county shape.
The study also stressed the importance of a mesoscale analyst to assess hourly near storm environmental data and to consider whether certain parts of our forecast area were more prone to tornado development. Previous research at LMK correlated Storm Prediction Center mesoscale data sets (e.g., Effective Storm Relative Helicity, etc.) with tornado warnings in the Ohio Valley. A tool was developed at LMK to integrate this research into real-time events. Given the multitude of existing and new data sets (e.g., GOES-16 and MRMS), we recommended employing 2-person warning teams to monitor mesoanalysis data and issue warnings.
This presentation will highlight the procedures outlined above, including lessons learned from our office's severe weather roundtable discussion in October 2017 and case studies since then.