Meteorological Imagery for the Geostationary Lightning Mapper. Issue 24 (28th December 2019)

• Record Type: Journal Article
• Authors: Bruning, Eric C.; Tillier, Clemens E.; Edgington, Samantha F.; Rudlosky, Scott D.; Zajic, Joe; Gravelle, Chad; Foster, Matt; Calhoun, Kristin M.; Campbell, P. Adrian; Stano, Geoffrey T.; Schultz, Christopher J.; Meyer, Tiffany C.
• Is Part Of: Journal of geophysical research. Volume 124:Issue 24(2019)
• Page Start: 14285
• Page End: 14309
• Publication Date: 2019-12-28
• Subjects: Lightning -- Satellite -- Imagery -- Open source -- GOES‐R -- Geostationary; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2019JD030874
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: The Geostationary Lightning Mapper (GLM) on the Geostationary Operational Environmental Satellite‐R series of weather satellites provides point geolocations of lightning flashes that are further comprised of a hierarchy of geolocated groups and events. This study describes an open‐source method for reconstruction of imagery from those point detections that retains the quantitative physical measurements made by GLM, restores the spatial footprint of the events, and connects that spatial footprint to the groups and flashes. Meteorological signals are demonstrated to be more apparent in the gridded imagery than in the point detections, leading to their adoption by the United States National Weather Service as the first GLM product available in their real‐time displays. Analysis of a mesoscale convective system over Argentina confirms that there is a class of propagating lightning observed by GLM (distinct from that in storm cores) that can be visualized and quantified using our imagery‐based approach. Plain Language Summary: This paper describes a method for creating imagery from the Geostationary Lightning Mapper instrument on the new geostationary weather satellites launched by the United States. The imagery overlays directly on and can be animated like other weather satellite images, making it more suitable for diagnosing thunderstorm behavior than the simple lightning location plots easily made from the publicly available data. The imagery can be summed to create analyses of lightning on climate time scales. The imagery illustrates that extensive lightning discharges exist in some storm systems and that distant ground strike points are joined by a single extensive lightning channel in the cloud. Key Points: An algorithm restores the shapes of Geostationary Lightning Mapper event detections and resamples them on a target grid to make imagery Imagery capitalizes on GLM's improved sensitivity, resulting in improved display of meteorological processes compared to point displays Statistics from imagery support prior work distinguishing a second class of extensive, propagating lightning