A collaborative effort between VA Tech and the NWS Blacksburg office, funded by the GOES-R program, studied the potential utility of total lightning data (from Earth Networks Inc) in weak shear storms over the Central Appalachian region. Recently, a summary of this work was published in the NWA Journal of Operational Meteorology. VT graduate student Paul Miller, now a PhD candidate at the University of Georgia, is the lead author. The title and abstract are below, and you can find the article here:
Essentially, while there is certainly promise in using total flash rates and trends in diagnosing the severe potential for these weak shear (often known as “single cell” or “pulse” storms), a 2-sigma lightning “jump” (as defined in previous research) proved not to be a practical algorithm due mainly to a very high false alarm. Differences in how storms are defined (i.e., radar vs. lightning clusters), the actual detection network, geographic region, as well as environment and storm mode, may all determine the effectiveness of any future algorithm designed to use flash counts and trends to better anticipate severe potential.
Article title and abstract:
Single-cell Thunderstorm Severity: Examples from the Central Appalachians Region
Paul W. Miller1, Andrew W. Ellis2, and Stephen J. Keighton3
1University of Georgia, Athens, Georgia
2Virginia Tech, Blacksburg, Virginia
3NOAA/NWS, Blacksburg, Virginia
The performance of a total lightning jump algorithm for guiding severe thunderstorm warnings within a weakly sheared environment was investigated using data from the Earth Networks Total Lightning Network. Total lightning observations from two summers for a study domain within the central Appalachian Mountains region were clustered into likely thunderstorms using single-linkage clustering. The spatial and temporal characteristics of each flash cluster were evaluated and used to assign a “storm index” (SI) score to each cluster. Small, short-lived, slow-moving, circular clusters—consistent with single-cell thunderstorms—were given large SI scores, and large, long-lived, fast-moving, linear clusters—inconsistent with the single-cell mode—received smaller SI scores. Statistical testing revealed that days with a simple majority of lightning-defined (LD) single-cell storms possessed significantly weaker 0–6-km wind shear than days with a majority of non-single-cell storms. After classifying 470 clusters as either LD single-cell or multicell/supercell, the 2σ lightning jump algorithm was applied to the flashes associated with each cluster. Total lightning jumps identified by the algorithm were aligned with severe weather report data to evaluate the accuracy of the algorithm. Although probability of detection values for both categories compared well to previous studies, false alarm rates were significantly larger than previously documented. The algorithm performed unsatisfactorily among the LD single-cell and multicell/supercell storms studied, and its performance deteriorated further when applied to a subset of storms most clearly defined as single-cell. However, severe LD storms demonstrated greater flash rates, a promising characteristic for future lightning-based warning tools.