Comparing Thunderstorm Characteristics Derived from ENTLN Versus GLM Data

As the climate changes we enter an ever more intense and dynamic atmosphere. As such, it is important to leverage all the tools available to best predict these changes so that we are prepared. As an essential climate variable, lightning data is recognized as a crucial tool for improving thunderstorm safety and awareness. There are currently several operational lightning location systems available, some of which observe lightning in different frequencies. Furthermore, lightning location data can be used to effectively estimate various characteristics of thunderclouds (both in real-time and historically) and have the added benefit of allowing for long-term and large-scale analyses. In this study, we cluster lightning location data into thunderstorms using a custom-built algorithm. We apply this to both Earth Networks Total Lightning Network (ENTLN) and Geostationary Lightning Mapper (GLM) data and compare how both systems ultimately estimate their characteristics. The ENTLN is a radio-frequency ground-based system, while the GLM is an optical space-based system. We will showcase some case studies to highlight differences as well as take a statistical approach to discuss overall trends. Assessing how these two different systems represent thunderstorms will help with applications related to storm dynamics and microphysics as well as operational forecasting.