Skilful Forecasting of Global Fire Activity Using Seasonal Climate Predictions

Skilful Forecasting of Global Fire Activity Using Seasonal Climate Predictions. Turco, M., Jerez, S., Doblas-Reyes, F. J., AghaKouchak, A., Llasat, M. C., & Provenzale, A.

Paper doi abstract bibtex

Societal exposure to large fires has been increasing in recent years. Estimating the expected fire activity a few months in advance would allow reducing environmental and socio-economic impacts through short-term adaptation and response to climate variability and change. However, seasonal prediction of climate-driven fires is still in its infancy. Here, we discuss a strategy for seasonally forecasting burned area anomalies linking seasonal climate predictions with parsimonious empirical climate-fire models using the standardized precipitation index as the climate predictor for burned area. Assuming near-perfect climate predictions, we obtained skilful predictions of fire activity over a substantial portion of the global burnable area (̃60\,%). Using currently available operational seasonal climate predictions, the skill of fire seasonal forecasts remains high and significant in a large fraction of the burnable area (̃40\,%). These findings reveal an untapped and useful burned area predictive ability using seasonal climate forecasts, which can play a crucial role in fire management strategies and minimise the impact of adverse climate conditions.

@article{turcoSkilfulForecastingGlobal2018,
  title = {Skilful Forecasting of Global Fire Activity Using Seasonal Climate Predictions},
  author = {Turco, Marco and Jerez, Sonia and Doblas-Reyes, Francisco J. and AghaKouchak, Amir and Llasat, Maria C. and Provenzale, Antonello},
  date = {2018-07},
  journaltitle = {Nature Communications},
  volume = {9},
  issn = {2041-1723},
  doi = {10.1038/s41467-018-05250-0},
  url = {https://doi.org/10.1038/s41467-018-05250-0},
  abstract = {Societal exposure to large fires has been increasing in recent years. Estimating the expected fire activity a few months in advance would allow reducing environmental and socio-economic impacts through short-term adaptation and response to climate variability and change. However, seasonal prediction of climate-driven fires is still in its infancy. Here, we discuss a strategy for seasonally forecasting burned area anomalies linking seasonal climate predictions with parsimonious empirical climate-fire models using the standardized precipitation index as the climate predictor for burned area. Assuming near-perfect climate predictions, we obtained skilful predictions of fire activity over a substantial portion of the global burnable area (̃60\,\%). Using currently available operational seasonal climate predictions, the skill of fire seasonal forecasts remains high and significant in a large fraction of the burnable area (̃40\,\%). These findings reveal an untapped and useful burned area predictive ability using seasonal climate forecasts, which can play a crucial role in fire management strategies and minimise the impact of adverse climate conditions.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14640555,climate-change,fire-season,forecast,global-scale,long-term,standardized-precipitation-index,wildfires},
  number = {1}
}

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