成都市2024年秋初暴雨初生预报分析
Analysis and Forecasting of Rainstorm Onset in Early Autumn 2024 in Chengdu
DOI: 10.12677/ojns.2025.134083, PDF,   
作者: 袁 振*, 刘晓达:民航西南空管局气象中心,四川 成都;赖 明#:民航西南空管局航空气象技术研究及应用实验室,四川 成都;龙佳雨:安远县气象局,江西 赣州
关键词: 成都初秋暴雨葵花9号卫星产品初生云团Early Autumn in Chengdu Rainstorm Himawari-9 Satellite Product Initial Cloud Cluster
摘要: 为提升暴雨预警准确率,本研究利用中国气象局观测数据和日本的葵花9号卫星资料,采用单通道阈值法和多通道分析法,对2024年成都秋初两次暴雨过程进行分析。结果表明:(1) 暴雨发展迅速,天气尺度小,小时雨量多超20 mm,极端达55 mm。(2) 单通道阈值法显示初生云团亮温为200~240 K,低于235 K时暴雨发生。(3) 多通道分析中,红外–分裂窗亮温差(0.5~5 K)与暴雨发生密切相关。(4) 云有效半径 > 30 μm、光学厚度 < 28及云顶高度升至9~13 km时,暴雨概率显著增加。通过研究暴雨云团初生阶段的对流云发展规律及其演变特征,对于提高成都地区及全国范围的气象预警准确性具有重要价值。这不仅有助于减少极端天气对公共安全和工农业生产的影响,还能为防灾减灾工作提供科学依据。
Abstract: To improve the accuracy of heavy rainfall warnings, this study utilized observational data from the China Meteorological Administration and Japan’s Himawari-9 satellite data, employing single-channel threshold and multi-channel analysis methods to analyze two heavy rainfall events in early autumn 2024 in Chengdu. The results show that: (1) Heavy rainfall develops rapidly, with small synoptic scales and hourly precipitation often exceeding 20 mm, reaching up to 55 mm in extreme cases. (2) The single-channel threshold method revealed that the brightness temperature of nascent cloud clusters ranged from 200 K to 240 K, with rainfall occurring when it dropped below 235 K. (3) In multi-channel analysis, the brightness temperature difference (BTD) between infrared and split-window channels (0.5~5 K) was closely associated with heavy rainfall. (4) The probability of heavy rainfall significantly increased when the cloud effective radius exceeded 30 μm, the optical thickness was below 28, and the cloud-top height rose to 9~13 km. By investigating the development patterns and evolutionary characteristics of convective clouds during the nascent stage of heavy rainfall cloud clusters, this study provides valuable insights for improving meteorological warning accuracy in Chengdu and nationwide. This not only helps mitigate the impact of extreme weather on public safety and industrial/agricultural production but also offers scientific support for disaster prevention and reduction efforts.
文章引用:袁振, 赖明, 刘晓达, 龙佳雨. 成都市2024年秋初暴雨初生预报分析[J]. 自然科学, 2025, 13(4): 789-798. https://doi.org/10.12677/ojns.2025.134083

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