中尺度空气运动和热力学预测美国每小时的暴雨量很大
Mark T Richardson1, Brian H Kahn1, Peter M Kalmus1,2,3
1Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA USA.
概括
预测大量降水是很困难的. 这项研究使用卫星数据和天气风来预测有利于强降雨的条件,表明中等层次向导是重降雨事件的关键.
科学领域:
- 大气科学 大气科学
- 气象学 天气学
- 遥感 遥感 遥感 遥感
背景情况:
- 预测大量降雨是一个重大的科学挑战.
- 准确预测极端天气事件对于公共安全和资源管理至关重要.
研究的目的:
- 开发一种方法来预测卫星越过后对对流有利的热力学条件.
- 为了评估中等层面的向导对大雨形成的贡献.
主要方法:
- 综合大气红外探测器 (AIRS) 温度和湿度数据与天气预报风.
- 处理 AIRS 检索作为附带移动的空中包裹,以产生时间变化的字段.
- 计算的对流可用潜在能量 (CAPE) 来预测强度降水.
主要成果:
- 由CAPE衍生出来的单独有效地预测了2019-2020年非冬季月份在美国中东部地区的强烈降雨.
- 该方法对极端降水的性能 (第99.9百分位数) 与ERA5再分析相当,并且优于原始的AIRS测量.
- 介面层向被确定为产生大量降水的主要因素.
结论:
- 增强的AIRS数据处理方法为预测大量降水提供了有价值的工具.
- 这种方法为量化大量降雨风险的多十年趋势提供了一个替代方案.
- 了解 mesoscale 偏向作用对于改善恶劣天气预报至关重要.
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