Open AccessDeveloping empirical lightning cessation forecast guidance for the Cape Canaveral Air Force Station and Kennedy Space Center
Author(s) -
Stano Geoffrey T.,
Fuelberg Henry E.,
Roeder William P.
Publication year - 2010
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2009jd013034
Subject(s) - meteorology , percentile , lightning (connector) , storm , environmental science , lightning detection , confidence interval , statistics , geography , thunderstorm , mathematics , power (physics) , physics , quantum mechanics
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.