Abstract
The Earth Networks Total Lightning Network (ENTLN) is comprised of wideband sensors to detect both the intra-cloud (IC) and cloud-to-ground (CG) flash signals efficiently. Since 2009, ENTLN has been used to track the properties of storms cells, such as the lightning flash rate, cell direction, and speed as a basis for issuing alerts for thunderstorms that could have the potential for severe weather. A storm cell is a cluster of flashes with a boundary as a polygon determined by the flash density value for a given period. From this storm cell data, Earth Networks produces the Dangerous Thunderstorm Alert (DTA). Most severe convective storms can generate high IC flash rate and high IC/CG flash-rate ratios. When rates exceed critical thresholds, DTAs are issued. DTA helps in predicting the storm ahead by generating an alert with significant lead time before the ground-level severe weather. Through DTA, the storm cells are monitored continuously, which enhances the situational awareness. In this study, we analyze the efficiency and accuracy of these automated DTAs by comparing with National Weather Service alert in relation to local storm reports, which are used as ground truth.
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