Department of Applied Physics, University of Barcelona, 08028, Barcelona, Spain.
Regional Atmospheric Modeling Group, Department of Physics, University of Murcia, 30100, Murcia, Spain.
Nat Commun. 2018 Jul 13;9(1):2718. doi: 10.1038/s41467-018-05250-0.
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.
近年来,社会面临的大火越来越多。提前几个月预估预期的火灾活动,可以通过短期适应和应对气候变异性和变化来减少环境和社会经济影响。然而,气候驱动火灾的季节性预测仍处于起步阶段。在这里,我们讨论了一种将季节性气候预测与简约经验气候火灾模型联系起来的方法,以标准化降水指数作为气候预测指标来预测燃烧面积异常。假设气候预测近乎完美,我们获得了全球可燃烧区域的火灾活动的高超预测能力(约 60%)。利用目前可用的业务性季节性气候预测,火灾季节性预测的技能在可燃烧区域的很大一部分(约 40%)仍然很高且具有显著意义。这些发现揭示了利用季节性气候预测进行燃烧面积预测的一种未被充分利用但有用的能力,这在火灾管理策略中可以发挥关键作用,并最大限度地减少不利气候条件的影响。