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<h1>Home</h1>
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ProbSevere LightningCast is a part of the ProbSevere portfolio of machine-learning algorithms for convective hazards. The main LightningCast model predicts the probability of any lightning (as observed by GLM) in the next 60 minutes. It uses GOES-R ABI channels as predictors and utilizes a U-Net convolutional neural network architecture. The model was trained with TensorFlow and uses Python. It can be run in near-real time or on archived cases.
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Building LightningCast
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Running LightningCast in near-real time
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[Near-real time LightningCast output matrix](https://docs.google.com/spreadsheets/d/1IyVLCFpxcnn1mpnppbZZZ6qF-jmKNVH5tj2hf5vDZCc/edit?usp=sharing)
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[Running LightningCast offline](https://gitlab.ssec.wisc.edu/jcintineo/lightningcast/-/wikis/Running-LightningCast-offline)
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[LightningCast meteograms](https://gitlab.ssec.wisc.edu/jcintineo/lightningcast/-/wikis/LightningCast-meteograms) |
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