@article{ref1,
title="Skilful forecasting of global fire activity using seasonal climate predictions",
journal="Nature communications",
year="2018",
author="Turco, Marco and Jerez, Sonia and Doblas-Reyes, Francisco J. and AghaKouchak, Amir and Llasat, Maria Carmen and Provenzale, Antonello",
volume="9",
number="1",
pages="e2718-e2718",
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.<p /> <p>Language: en</p>",
language="en",
issn="2041-1723",
doi="10.1038/s41467-018-05250-0",
url="http://dx.doi.org/10.1038/s41467-018-05250-0"
}