arXiv:2109.09791

Prediction of severe thunderstorm events with ensemble deep learning and radar data

Sabrina Guastavino, Michele Piana, Marco Tizzi, Federico Cassola, Antonio Iengo, Davide Sacchetti, Enrico Solazzo, Federico Benvenuto

제출 2021-09-20

원문 초록

The problem of nowcasting extreme weather events can be addressed by applying either numerical methods for the solution of dynamic model equations or data-driven artificial intelligence algorithms. Within this latter framework, the present paper illustrates how a deep learning method, exploiting videos of radar reflectivity frames as input, can be used to realize a warning machine able to sound timely alarms of possible severe thunderstorm events. From a technical viewpoint, the computational core of this approach is the use of a value-weighted skill score for both transforming the probabilistic outcomes of the deep neural network into binary classification and assessing the forecasting performances. The warning machine has been validated against weather radar data recorded in the Liguria region, in Italy,

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arXiv:2506.21002공통 태그 Binary Classification공식 코드 · Papers with Code

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