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Simulating the effects of weather and climate on large wildfires in France

机译:模拟天气和气候对法国大型野火的影响

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Large wildfires across parts of France can cause devastating damage whichputs lives, infrastructure, and the natural ecosystem at risk. In the climatechange context, it is essential to better understand how these largewildfires relate to weather and climate and how they might change in a warmerworld. Such projections rely on the development of a robust modelingframework linking large wildfires to present-day atmospheric variability.Drawing from a MODIS product and a gridded meteorological dataset, we deriveda suite of biophysical and fire danger indices and developed generalizedlinear models simulating the probability of large wildfires (>100ha) at8km spatial and daily temporal resolutions across the entire country overthe last two decades. The models were able to reproduce large-wildfireactivity across a range of spatial and temporal scales. Differentsensitivities to weather and climate were detected across differentenvironmental regions. Long-term drought was found to be a significantpredictor of large wildfires in flammability-limited systems such as theAlpine and southwestern regions. In the Mediterranean, large wildfires werefound to be associated with both short-term fire weather conditions andlonger-term soil moisture deficits, collectively facilitating the occurrenceof large wildfires. Simulated probabilities on days with large wildfires wereon average 2–3?times higher than normal with respect to the mean seasonalcycle, highlighting the key role of atmospheric variability in wildfirespread. The model has wide applications, including improving ourunderstanding of the drivers of large wildfires over the historical periodand providing a basis on which to estimate future changes to large wildfiresfrom climate scenarios.
机译:法国各地的大火可能造成毁灭性破坏,危及生命,基础设施和自然生态系统。在气候变化的背景下,有必要更好地了解这些大火如何与天气和气候联系起来,以及在温暖的世界中它们如何变化。这些预测依赖于将大型野火与当今大气变化联系在一起的健壮建模框架的发展。从MODIS产品和栅格化的气象数据集中,我们得出了一套生物物理和火灾危险指数,并开发了模拟大型野火概率的广义线性模型。 (20公顷以上)在过去二十年中,整个国家/地区在8 km的时空分辨率。这些模型能够在一系列时空尺度上再现大型野火活动。在不同的环境区域中检测到对天气和气候的不同敏感性。在诸如阿尔卑斯山和西南地区等可燃性受限的系统中,长期干旱被认为是大型野火的重要预测因素。在地中海,发现大火与短期火灾天气条件和长期土壤湿度不足有关,共同促进了大火的发生。就平均季节周期而言,大火天的模拟概率平均比正常水平高2–3倍,突显了大气变化在野火蔓延中的关键作用。该模型具有广泛的应用,包括改善我们对历史时期大火的驱动力的理解,并为从气候情景中估计未来大火的变化提供基础。

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