The storms produced wind gusts up to 30 mph and dropped a quarter-inch of rain. The FOX Forecast Center said thunderstorms moved through the Fort Worth area between about 2:30 p.m. This lightning prediction AI tool demonstrates a new way to use satellite data to help keep us informed and stay safe.Ĭheck out the experimental near real-time probability of lightning data. The fire was quickly brought under control, and no injuries were reported. Not only is the satellite data useful for depicting current weather conditions, but it is also critical for predicting hazardous conditions in the future. The advanced data provided by GOES-16 (GOES East) and GOES-17 (GOES West) allow for new and innovative applications. “As John’s work shows, machine learning is opening the door to new satellite applications that directly address major societal challenges in ways that were not previously possible,” said Pavolonis. Mike Pavolonis, the NOAA scientist who leads the ProbSevere project, praised the new application. This tool was developed by John Cintineo at the University of Wisconsin/Cooperative Institute for Meteorological Satellite Studies (CIMSS), as part of ProbSevere, a statistical model that predicts the probability that a storm will produce severe weather in the near-term. Probability of lightning occurring in the next 60 minutes plotted for the coast of South Carolina on July 14, 2021, along with GLM flash-extent density data when lightning was detected. EST, the AI lightning prediction tool indicated a greater than 25% chance of lightning occurring in the next hour. on July 7, 2021, shows a lightning probability signal occurring 50 minutes before the first instance of lightning.Īt 1:56 p.m. Clear predictive signals often emerge before rain forms, ahead of weather radar signals.

The AI tool can accurately predict lightning up to 60 minutes before the first observation of lightning flashes. It also indicates where lightning remains a threat in storms with intermittent lightning activity and helps determine when the threat from lightning is diminishing. About Farmonline Weather Radar Distance and latitude/longitude coordinates are displayed when you mouse over the map.

This AI model skillfully and reliably predicts where lightning is most likely to occur even before precipitation forms. To accomplish this, a sophisticated machine-learning algorithm was trained, using GLM data, to recognize complex patterns in GOES-R Advanced Baseline Imager (ABI) imagery that often precede lightning activity detected by GLM. Scientists are using artificial intelligence (AI) to predict where GLM will observe lightning in the future. Lightning captured in Temescal Valley, California.

Weather radar lightning tracker