Aerosol and Clouds
Developing empirical lightning cessation forecast guidance for the Cape Canaveral Air Force Station and Kennedy Space Center
Article first published online: 14 MAY 2010
Copyright 2010 by the American Geophysical Union.
Journal of Geophysical Research: Atmospheres (1984–2012)
Volume 115, Issue D9, 16 May 2010
How to Cite
2010), Developing empirical lightning cessation forecast guidance for the Cape Canaveral Air Force Station and Kennedy Space Center, J. Geophys. Res., 115, D09205, doi:10.1029/2009JD013034., , and (
- Issue published online: 14 MAY 2010
- Article first published online: 14 MAY 2010
- Manuscript Accepted: 4 DEC 2009
- Manuscript Revised: 5 NOV 2009
- Manuscript Received: 19 AUG 2009
 This research addresses the 45th Weather Squadron's (45WS) need for improved guidance regarding lightning cessation at Cape Canaveral Air Force Station and Kennedy Space Center (KSC). KSC's Lightning Detection and Ranging (LDAR) network was the primary observational tool to investigate both cloud-to-ground and intracloud lightning. Five statistical and empirical schemes were created from LDAR, sounding, and radar parameters derived from 116 storms. Four of the five schemes were unsuitable for operational use since lightning advisories would be canceled prematurely, leading to safety risks to personnel. These include a correlation and regression tree analysis, three variants of multiple linear regression, event time trending, and the time delay between the greatest height of the maximum dBZ value to the last flash. These schemes failed to adequately forecast the maximum interval, the greatest time between any two flashes in the storm. The majority of storms had a maximum interval less than 10 min, which biased the schemes toward small values. Success was achieved with the percentile method (PM) by separating the maximum interval into percentiles for the 100 dependent storms. PM provides additional confidence to the 45WS forecasters, and a modified version was incorporated into their forecast procedures starting in the summer of 2008. This inclusion has resulted in ∼5–10 min time savings. Last, an experimental regression variant scheme using non-real-time predictors produced precise results but prematurely ended advisories. This precision suggests that obtaining these parameters in real time may provide useful added information to the PM scheme.