Rapid increases in lightning activity in severe thunderstorms, also known as lightning jumps, have been shown to occur well in advance of the manifestation of severe weather at the ground. However, not all thunderstorms that exhibit this "jump signature" produce severe weather, and not all severe thunderstorms demonstrate a significant lightning jump. Based on the aforementioned positive result (lightning-severe weather), it is hypothesized that trends in lightning activity can be used as a tool for severe weather warning decision support. Accordingly, recent lightning tool development has focused on the development of lightning jump algorithms with anticipated application to both ground and spaceborne total lightning detection. If designed properly, these algorithms should result in increased warning lead times and/or reduced false alarm rates. This study examines the jump signature algorithm advanced by Gatlin (2006), with the specific goals of a) increasing the case data base; and b) further testing and refining the jump signature algorithm. Ultimately we are supporting the development of a lightning jump algorithm that will be used operationally for the Global Lightning Mapper, to be flown on the future GOES-R platform.