CanCPLD:对流参数和闪电数据用于支持北美未来雷暴预测
Alex J Cannon1, Kathleen S Ramsey2,3, Alessio C Spassiani4
1Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada. alex.cannon@ec.gc.ca.
Scientific data
|October 10, 2025
概括
本研究汇编了北美数据集,以使用环境参数统计模型雷暴活动. 气候模型预测在各种全球变暖情景下评估未来雷暴风险.
科学领域:
- 大气科学 大气科学
- 气候建模气候模型
- 气象学 天气学
背景情况:
- 雷暴带来了严重的自然危险,如冰,洪水,强风和闪电.
- 在气候模型中准确模拟雷暴是很困难的,因为它们的规模很小,物理驱动因素很复杂.
- 使用环境参数的统计模型可以推断雷暴活动并预测未来的趋势.
研究的目的:
- 创建一个全面的闪电和对流参数数据集,用于北美 (北方40度).
- 使用此数据集与气候模型输出来评估不同升温水平下的未来雷暴活动.
- 改善对气候变化对恶劣天气事件的影响的理解.
主要方法:
- 编制了数十年来闪电总和201个对流参数的数据集.
- 利用欧洲中期天气预报中心在0.25°网格和3小时间隔重新分析数据 (ERA5).
- 计算了HighResMIP气候模型模拟的相同变量,用于历史和未来变暖场景 (1°C至4°C) 的6小时间隔的气候模型模拟.
主要成果:
- 为北美建立了一个数据集,将历史闪电数据与关键环境参数联系起来.
- 该方法允许将统计雷暴模型应用于气候模型输出.
- 未来雷暴活动的预测可以根据模拟的环境条件得出.
结论:
- 开发的数据集和方法提供了一个评估气候变化对雷暴活动影响的框架.
- 这种方法可以使用气候模型预测来了解与严重的对流风暴相关的未来风险.
- 进一步的研究可以完善这些统计模型,并探索雷暴对变暖反应的区域差异.
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