Intelligent Tornado Prediction Engine
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The most common type of tornado in the Southeast region of the United States, known as a quasi-linear convective system tornado, is historically difficult to warn for, with lead times hovering under 7 minutes and a false alarm rate of over 75 percent.
The Intelligent Tornado Prediction Engine (ITORPE) combines meteorological and machine learning expertise from MIT Lincoln Laboratory researches and the Lincoln Laboratory Supercomputing Center to perform extremely large-scale data fusion spanning several years’ worth of radar, satellite, model, and in situ observation platforms, to provide enhanced situational awareness to forecasters using a graphical interface to focus forecasters’ attention on the storms of highest importance.
Date issued
2022-11-09Series/Report no.
The Bulletin;
Keywords
LLSC, MIT Lincoln Laboratory, Deep Learning
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