WELCOME TO THE GEOSTATIONARY LIGHTNING MAPPER VIRTUAL COMMUNITY - Geostationary Lightning Mapper
WELCOME TO THE GEOSTATIONARY LIGHTNING MAPPER VIRTUAL COMMUNITY
This forum supports Geostationary Lightning Mapper (GLM) implementation and training. The page provides a vehicle for learning about the GLM capabilities and limitations, exploring GLM applications, understanding data quality, and addressing GLM inquiries.
The first Geostationary Lightning Mapper (GLM) launched into orbit aboard the first Geostationary Operational Environmental Satellite R-series (GOES-R), becoming GOES-16 after reaching geostationary orbit on 29 November 2016. The GLM on GOES-16 is the first of four instruments that will provide lightning mapping over most of the western hemisphere through 2036.
The GLM performance meets or exceeds all program specifications, but the data quality will continue to improve. Simultaneous development and implementation efforts aim to improve the operational utility of the GLM data. New visualizations have been developed for the NWS Advanced Weather Interactive Processing System (AWIPS) software.
Sample desktop backgrounds... Maria, Irma, Harvey, Three Hurricanes, or Lake Maracaibo
Near real time imagery is available at http://lightning.umd.edu, http://col.st/haYgj, and http://col.st/WtVLp
Example GLM Imagery
What's New
This forum supports Geostationary Lightning Mapper (GLM) implementation and training, providing tools for learning about the GLM capabilities and limitations, exploring applications, understanding data quality, discovering new research, and addressing inquiries.
The GLM continuously observes lightning throughout a near hemispheric field of view, capturing spatiotemporal variability on unprecedented scales (Rudlosky et al. 2019). As a high-frame-rate camera that detects light pulses at cloud tops, the GLM differs from the ground-based lightning detection networks most familiar to NWS forecasters. Thus, focused research, development, and training efforts are required to guide the operational application of these data. A gridded product suite (Bruning et al. 2019) and associated AWIPS configurations were implemented to provide GLM information to forecasters (Sima 2020).
Please follow the navigation tabs above to explore training documents, product descriptions, imagery examples, refereed literature, and additional commentary. Near real time imagery is available at http://col.st/haYgj, and http://col.st/WtVLp, https://www.weathernerds.org/satellite/, https://weather.cod.edu/satrad/, and https://www.star.nesdis.noaa.gov/goes/index.php. Additional information available at https://lightning.umd.edu/glm/.