区域气候变化对美国火灾天气的潜在影响

Ying Tang, S. Zhong, L. Luo, X. Bian, W. Heilman, J. Winkler
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引用次数: 47

摘要

预计气候变化将改变有利于野火发生的大气条件的频率和严重程度。在本研究中,我们使用海恩斯指数(HI)评估了美国相邻地区火灾天气条件的潜在变化,海恩斯指数是一种火灾天气指数,已被用于探测有利于大规模和不稳定火灾行为的大气条件。该指数将较低的大气稳定性和干燥度总结为一个整数值,数值越高表示火灾易发条件。我们利用北美区域气候变化评估计划(NARCCAP)从多个一般环流模式(GCMs)驱动的多个区域气候模式(RCMs)中产生的模拟,研究了本世纪中叶美国季节性日数百分比和高HI(值≥5)连续日数的变化。尽管六个RCM-GCM组合在预估变化的幅度和位置上存在差异,但结果一致表明,夏季美国大部分地区高HI值的日数增加,其中HI的干燥因子比稳定性参数对预估变化的贡献更大。此外,预计夏季高HI的连续日数将增加。总之,这些结果表明,未来的夏天可能更容易发生大型危险火灾。不同模式组合对其他季节的预估不一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Potential Impact of Regional Climate Change on Fire Weather in the United States
Climate change is expected to alter the frequency and severity of atmospheric conditions conducive for wildfires. In this study, we assess potential changes in fire weather conditions for the contiguous United States using the Haines Index (HI), a fire weather index that has been employed operationally to detect atmospheric conditions favorable for large and erratic fire behavior. The index summarizes lower atmosphere stability and dryness into an integer value with higher values indicting more fire-prone conditions. We use simulations produced by the North American Regional Climate Change Assessment Program (NARCCAP) from multiple regional climate models (RCMs) driven by multiple general circulation models (GCMs) to examine changes by midcentury in the seasonal percentage of days and the consecutive number of days with high (values ≥ 5) HI across the United States. Despite differences among the six RCM–GCM combinations in the magnitude and location of the projected changes, the results consistently suggest an increase in the number of days with high HI values over most of the United States during the summer season, with the dryness factor of the HI contributing more than the stability parameter to the projected changes. In addition, the consecutive number of days with high HI is projected to increase in summer. Together, these results suggest that future summers might be more conducive to large and dangerous fires. The projections for other seasons are inconsistent among the model combinations.
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