Enhancing seasonal fire predictions with hybrid dynamical and random forest models
Source
This study presents an innovative approach to forecasting seasonal anomalies in burned areas (BA) by integrating process-based seasonal prediction and a random forest climate-fire model. The Standardized Precipitation Index (SPI), derived from observed precipitation, allows us to predict burned area anomalies a month before the start of the target fire season in ~68% of the burnable area.
When utilizing seasonal predictions, the system maintains skilful results in ~46% of the burnable area. Given the availability of observational and forecast data in near-real-time, a prototype operational forecast for burned areas could be provided to enhance climate services.
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Hazards
Wildfire
Themes
Early warning
ISBN/ISSN/DOI
10.1038/s44304-025-00069-4 (DOI)
Number of pages
10 p.
Publication year
2025