TY  - JOUR
PY  - 2018//
TI  - Skilful forecasting of global fire activity using seasonal climate predictions
JO  - Nature communications
A1  - Turco, Marco
A1  - Jerez, Sonia
A1  - Doblas-Reyes, Francisco J.
A1  - AghaKouchak, Amir
A1  - Llasat, Maria Carmen
A1  - Provenzale, Antonello
SP  - e2718
EP  - e2718
VL  - 9
IS  - 1
N2  - 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>
LA  - en
SN  - 2041-1723
UR  - http://dx.doi.org/10.1038/s41467-018-05250-0
ID  - ref1
ER  -