Physics

Meteorology

Flash (photography)

Mathematics

Geostationary Operational Environmental Satellite

Optics

Storm

Statistics

Astronomy

Satellite

Power (physics)

Geostationary orbit

Geography

Lightning detection

Quantum mechanics

Lightning (connector)

Environmental science

Remote sensing

Thunderstorm

Journal of Geophysical Research Atmospheres

The GOES‐16 Geostationary Lightning Mapper (GLM) detection efficiency (DE) is studied over a full year (2018/19) in central Florida using the Kennedy Space Center Lightning Mapping Array (KSC LMA). Mean daily flash DE was 73.8%, and detection was highest during nighttime hours. GLM reported 86.5% of the LMA flashes that had coincident cloud‐to‐ground return strokes reported by the U.S. National Lightning Detection Network. Results also reveal that flash size and duration are critical parameters influencing GLM detection, regardless of the storm type, with 20–40% detection for small and short‐duration flashes and greater than 95% detection for very large and long‐duration flashes. These findings can be explained by examining the time‐evolution of cloud‐top optical emissions observed by the Lightning Imaging Sensor (LIS). Statistical simulations based on long‐term LIS group area observations indicate that about half of the above‐threshold light sources are smaller than a LIS pixel (~ 4 × 4 km) and are smallest during and just after an initial breakdown in IC flashes. This work also demonstrates that for sources smaller than a GLM pixel, the cloud‐top energy detection threshold for GLM is double that for LIS despite GLM's lower energy density threshold. Overall, these findings provide a framework for interpreting GLM performance under varying meteorological conditions, and help explain reports of low flash detection efficiency for storms associated with severe weather, as they typically exhibit high flash rates and resulting small and short‐duration flashes.

Time Evolution of Satellite‐Based Optical Properties in Lightning Flashes, and its Impact on GLM Flash Detection