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时间复合增加加利福尼亚州大气河流的经济影响
Corinne Bowers1, Katherine A Serafin2, Jack W Baker1
1Civil and Environmental Engineering Department, Stanford University, Stanford, CA 94304, USA.
Science advances
|January 19, 2024
概括
加利福尼亚州的大气河流 (ARs) 的序列显著增加了洪水风险和损失. 了解这些复合事件对于预测ARs的全部影响至关重要.
科学领域:
- 气候学 气候学 气候学
- 水文学的水文学
- 极端天气事件 极端天气事件
背景情况:
- 大气河流 (ARs) 是加利福尼亚降雨和洪水的主要驱动因素.
- 时间复合的AR事件可以加剧水文危险和损害.
- 量化时间复合对AR诱导损失的贡献至关重要.
研究的目的:
- 系统量化时间复合对加利福尼亚州大气河流引起的损失的贡献.
- 调查AR序列的强度和频率以及相关的洪水影响之间的关系.
- 评估先前的AR事件的特征如何影响后续事件的损失.
主要方法:
- 对历史大气河流事件序列的分析.
- 统计评估与洪水相关的影响和与AR序列相关的损失.
- 从序列内的AR损失与序列之外的AR损失的比较.
主要成果:
- 最强大的大气河更有可能发生在暂时聚集的序列中.
- 在AR日,AR序列增加了洪水影响的可能性8.3%,在非AR日增加了5.4%.
- 与孤立的AR相比,序列内的AR显示出预期损失的三倍以上,损失随着先前事件的强度和事件间时间的缩短而升级.
结论:
- 大气河流的时间复合是加利福尼亚州洪水风险的关键因素.
- 对AR后果的预测模型必须纳入时间聚类的影响.
- 了解AR序列对于有效的洪水减缓和管理策略至关重要.
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