Development of a Classification Method for Geostationary Lightning Mapper (GLM) Data Using Simultaneous Lightning Observations from Ground and Geostationary Orbit

To better understand the spectral content of lightning, and to support future validation efforts for space-based lightning sensors, Sandia National Laboratories (SNL) has deployed six radiometers and a contextual camera at Texas Tech University’s (TTU) field site to capture optical spectral data alongside the other established sensors at the TTU. Based on their timestamps, we matched 8 of 13 signals collected on May 28, 2024 to group data from the Geostationary Lightning Mapper (GLM) sensors hosted on GOES 16 and 18 satellites. Based on the contextual camera imagery, these events are primarily Cloud to Ground (CG) strokes. Using this feature of the data, one goal in this project is to develop a classification method for GLM data to distinguish between CG and In Cloud (IC) flashes.

_{SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525}