Scientists are using artificial intelligence to predict where GLM will observe lightning in the future. To accomplish this, a sophisticated machine-learning algorithm was trained, using GLM data, to recognize complex patterns in GOES-R Advanced Baseline Imager imagery that often precede lightning activity detected by GLM. This AI model skillfully and reliably predicts where lightning is most likely to occur even before precipitation forms.
The AI tool can accurately predict lightning up to 60 minutes before the first observation of lightning flashes. Clear predictive signals often emerge before rain forms, ahead of weather radar signals. An example from Washington, D.C. on July 7, 2021, shows a lightning probability signal occurring 50 minutes before the first instance of lightning.
At 1:56 p.m. EST, the AI lightning prediction tool indicated a greater than 25% chance of lightning occurring in the next hour. No rain was present at that time. At 2:21 p.m. EST, the lightning prediction tool indicated a greater than 75% chance of lightning occurring in the next hour. It was still not raining in the area.
The advanced data provided by GOES-16 and GOES-17 allow for new and innovative applications. Not only is the satellite data useful for depicting current weather conditions, but it is also critical for predicting hazardous conditions in the future. This lightning prediction AI tool demonstrates a new way to use satellite data to help keep us informed and stay safe.
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