WELCOME TO THE GEOSTATIONARY LIGHTNING MAPPER VIRTUAL COMMUNITY

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/

Example GLM Imagery - Click the drop down menu on the top right for many more options!

 

 

Full-Disk Archive

Archived AWIPS-compatible full-disk GLM grids are available at... 

https://lightningdev.umd.edu/feng_data_sharing/

What's New

GLM Training Resources

ArcGIS Story Maps (2022)     Quickly Diagnosing GLM Noise ...

Other Featured Training

WOC Severe Lessons (WDTD) Satellite Lightning Products and Best Practices Ground Based Lightning Products and Best Practices   FDTD Satellite Applications Webinars ...

Full-Disk Archive

Archived AWIPS-compatible full-disk GLM grids are available at...  https://lightningdev.umd.edu/feng_data_sharing/

WELCOME TO THE GEOSTATIONARY LIGHTNING MAPPER VIRTUAL COMMUNITY

This forum supports Geostationary Lightning Mapper (GLM) implementation and training, providing tools for learning about the GLM capabilities and limitations, exploring applications, understanding...

Most recent image

Imagery available for every 12 hour period since Sept 2019 at ( https://lightning.umd.edu/glm/imagery/autovideos/ ) Your browser does not support the video tag.

Blog Post Entry

Forecasters are invited to submit blog posts using either the "+Add Blog Entry" button below or a simplified google submission form available here ( https://forms.gle/6wpcHdrfGrwBx91G9 )

Highlighted Papers

Reference / Link Plain Language Summary Goss, H. 2020:  Lightning research flashes forward , Eos , 101, Published on 24 April...