The Value of Probabilistic Prediction for Lightning Ignited Fires
Abstract In 2021, the availability of a physical model for lightning density prediction at ECMWF led to the development of data driven models to identify episodes conducive of fires. The machine‐learning classifiers worked remarkably well reaching an overall accuracy up to 78%. Still, errors in the...
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Wiley
2022-09-01
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| coleção: | Geophysical Research Letters |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1029/2022GL099669 |
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