The Emergence of Lightning in Severe Thunderstorm Prediction and the Possible Contributions from Spatial Science

Abstract

Thunderstorms capable of producing dangerous weather are common in different regions throughout the world. Identifying particular thunderstorms that will become hazardous is a considerable forecasting challenge for meteorologists making warning decisions. The goal of more accurate and earlier severe thunderstorm warning has led to the idea of using a storm's lightning behavior – a reflection of storm intensity to predict imminent storm severity. Researchers have found that storms producing severe weather are often preceded by a rapid increase in lightning frequency, or a “jump”, prompting attempts to develop a quantitative lightning-based indicator of storm severity as a forecasting aid. Although recent studies have produced promising results, this initiative is rife with opportunities for geographers as lightning continues to evolve into a reliable operational tool. Technological advances in lightning detection have enabled the research, but the inherent volume of lightning data and their time-space nature represent an obstacle and an opportunity for spatial scientists. Increasingly robust lightning-jump algorithms will require extensive thunderstorm databases, the development of which involves identification of time-space clusters of lightning that represent discrete thunderstorms of varying types, which need to be aligned with geo-referenced severe weather reports. The spatial analytical tools and techniques inherent to geography can facilitate the meteorological analyses that are needed to advance the lightning jump concept toward an operational tool. Forecasters within the USA are particularly hopeful, as they look to capitalize on data generated by the Geostationary Lightning Mapper sensor mounted aboard a key satellite for weather and climate monitoring expected to be launched in 2016.