Lightning Detection

Lightning Detection

NWA Remote Sensing Committee

Lightning is the second highest cause of weather-related deaths in the United States annually, and produces considerable damage by initiating fires and disrupting communications and power transmission systems. Remote sensing technology is becoming increasingly important in the detection of lightning-producing convective storms.

The National Lightning Data Network (NLDN), operated by Vaisala, Inc., provides continuous cloud-to-ground lightning strike data to a variety of government, commercial, and public users. Other ground-based time of arrival type networks include the U. S. Precision Lightning Network, Inc., operated by WSI, Inc., and the Earth Networks Total Lightning Network, which observes both in-cloud and cloud-to-ground strikes.

A space-based Lightning Imaging Sensor (LIS), developed by NASA Marshall Space Flight Center, is flown on the Tropical Rainfall Measuring Mission (TRMM) satellite. A Geostationary Lightning Mapper (GLM) was implemented on GOES-R/16, launched in November, 2016, as recommended by the NWA.

Listed below are some resources that provide useful information on lightning, including remote sensing capabilities:

 General Information

 Lightning Research

 Realtime Lightning Strike Information

 Lightning Forecasts

 Lightning Safety

 Papers of Note

Commercial Lightning Systems and Services (For information only; not an        endorsement by the NWA)

 Top of Page

The National Weather Association (NWA) provides this information for the benefit of members and guests. Reference in this Web site to any specific information, commercial products, process, service, manufacturer, or company does not constitute its endorsement or recommendation by the NWA. The NWA is not responsible for the contents of any "off-site" Web page referenced from this Web site. To provide feedback to the NWA staff and volunteers who maintain this page or to ask for further information on this topic, please contact the NWA Remote Sensing Committee

Last modified - 13 December 2017