Evaluation of a Lightning Jump Algorithm with High Resolution Storm Reports

Numerous studies have shown a correlation between rapid increases in lightning activity and the occurrence of severe weather at the surface. The skill of an automated algorithm that detects these rapid increases in lightning, or lightning jumps, was evaluated for 8 different cases in this study using high-resolution storm reports. A completely automated algorithm was used to identify and track storm cells in three domains: central Oklahoma, northern Alabama, and Washington D.C. Multiple storm attributes including total lightning were attributed to each tracked storm in 1-minute intervals. Lightning jumps with each of the 8 cases were then verified using high resolution storm reports collected during the Severe Hazards Analysis and Verification Experiment (SHAVE). These reports offered much better spatial resolution than NCDC Storm Data, and produced a more accurate view of hail and wind evolution or “severe storm periods” at the surface. For the 8 cases examined the algorithm produced an average lead time of 0 minutes when using SHAVE data for verification. Verification statistics were slightly better when using NWS storm reports though not nearly as good as that noted in previous studies.