2023年9月7-8日香港历史暴雨:诊断、预报及临近预报

IF 2 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
Hiu Ching Tam, Yu-Heng He, Pak Wai Chan, Shiwei Yu, Huisi Mo, Hui Su, Ling-Feng Hsiao, Yangzhao Gong
{"title":"2023年9月7-8日香港历史暴雨:诊断、预报及临近预报","authors":"Hiu Ching Tam,&nbsp;Yu-Heng He,&nbsp;Pak Wai Chan,&nbsp;Shiwei Yu,&nbsp;Huisi Mo,&nbsp;Hui Su,&nbsp;Ling-Feng Hsiao,&nbsp;Yangzhao Gong","doi":"10.1002/asl.1284","DOIUrl":null,"url":null,"abstract":"<p>On 7–8 September 2023, Hong Kong was hit by a historical and record-breaking rainstorm associated with the remnant of Tropical Cyclone Haikui (2311). The hourly rainfall recorded at the Hong Kong Observatory Headquarters once reached 158.1 mm, the highest since record began in 1884. The 24-h rainfall even exceeded 600 mm in some parts of the territory. The historical rainstorm resulted in heavy flooding and landslides, bringing significant societal impact to Hong Kong. This paper aims to review this unprecedented heavy rain event from the aspects of diagnosis, forecasting and nowcasting. Early indicators of such events over Hong Kong with substantial lead time are limited from the dynamics and thermodynamics consideration, the numerical weather prediction models, given the present technology. The only indication may come from the climatologically extreme total precipitable water. While recent research of developing a regional risk-based alerting system on the higher impact event of flooding associated with heavy rain might have potential to enhance the weather service, and emerging AI model showed some promising post-simulations, predicting historical and record-breaking rainstorms remains a challenge for operational weather forecasting and warning services.</p>","PeriodicalId":50734,"journal":{"name":"Atmospheric Science Letters","volume":"26 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl.1284","citationCount":"0","resultStr":"{\"title\":\"Historical rainstorm in Hong Kong on 7–8 September 2023: Diagnosis, forecasting and nowcasting\",\"authors\":\"Hiu Ching Tam,&nbsp;Yu-Heng He,&nbsp;Pak Wai Chan,&nbsp;Shiwei Yu,&nbsp;Huisi Mo,&nbsp;Hui Su,&nbsp;Ling-Feng Hsiao,&nbsp;Yangzhao Gong\",\"doi\":\"10.1002/asl.1284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>On 7–8 September 2023, Hong Kong was hit by a historical and record-breaking rainstorm associated with the remnant of Tropical Cyclone Haikui (2311). The hourly rainfall recorded at the Hong Kong Observatory Headquarters once reached 158.1 mm, the highest since record began in 1884. The 24-h rainfall even exceeded 600 mm in some parts of the territory. The historical rainstorm resulted in heavy flooding and landslides, bringing significant societal impact to Hong Kong. This paper aims to review this unprecedented heavy rain event from the aspects of diagnosis, forecasting and nowcasting. Early indicators of such events over Hong Kong with substantial lead time are limited from the dynamics and thermodynamics consideration, the numerical weather prediction models, given the present technology. The only indication may come from the climatologically extreme total precipitable water. While recent research of developing a regional risk-based alerting system on the higher impact event of flooding associated with heavy rain might have potential to enhance the weather service, and emerging AI model showed some promising post-simulations, predicting historical and record-breaking rainstorms remains a challenge for operational weather forecasting and warning services.</p>\",\"PeriodicalId\":50734,\"journal\":{\"name\":\"Atmospheric Science Letters\",\"volume\":\"26 1\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asl.1284\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Science Letters\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/asl.1284\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Science Letters","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/asl.1284","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

2023年9月7日至8日,香港遭受由热带气旋“海葵”(2311)残余影响的一场历史上破纪录的暴雨袭击。天文台总部录得的每小时雨量一度达到158.1毫米,是自1884年有记录以来的最高纪录。部分地区的24小时雨量甚至超过600毫米。这次历史性的暴雨造成严重的水浸和山泥倾泻,对香港社会造成重大影响。本文拟从诊断、预报和临近预报等方面对此次特大暴雨进行回顾。在目前的技术条件下,从动力学和热力学的角度考虑,数值天气预报模式对香港的天气预报的早期指标是有限的。唯一的指示可能来自气候极端的总可降水量。虽然最近研究开发一种基于区域风险的预警系统,以应对与暴雨相关的洪水的高影响事件,可能有可能增强气象服务,而且新兴的人工智能模型显示了一些有希望的后期模拟,但预测历史和破纪录的暴雨仍然是业务天气预报和预警服务的一个挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Historical rainstorm in Hong Kong on 7–8 September 2023: Diagnosis, forecasting and nowcasting

Historical rainstorm in Hong Kong on 7–8 September 2023: Diagnosis, forecasting and nowcasting

On 7–8 September 2023, Hong Kong was hit by a historical and record-breaking rainstorm associated with the remnant of Tropical Cyclone Haikui (2311). The hourly rainfall recorded at the Hong Kong Observatory Headquarters once reached 158.1 mm, the highest since record began in 1884. The 24-h rainfall even exceeded 600 mm in some parts of the territory. The historical rainstorm resulted in heavy flooding and landslides, bringing significant societal impact to Hong Kong. This paper aims to review this unprecedented heavy rain event from the aspects of diagnosis, forecasting and nowcasting. Early indicators of such events over Hong Kong with substantial lead time are limited from the dynamics and thermodynamics consideration, the numerical weather prediction models, given the present technology. The only indication may come from the climatologically extreme total precipitable water. While recent research of developing a regional risk-based alerting system on the higher impact event of flooding associated with heavy rain might have potential to enhance the weather service, and emerging AI model showed some promising post-simulations, predicting historical and record-breaking rainstorms remains a challenge for operational weather forecasting and warning services.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Atmospheric Science Letters
Atmospheric Science Letters METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
4.90
自引率
3.30%
发文量
73
审稿时长
>12 weeks
期刊介绍: Atmospheric Science Letters (ASL) is a wholly Open Access electronic journal. Its aim is to provide a fully peer reviewed publication route for new shorter contributions in the field of atmospheric and closely related sciences. Through its ability to publish shorter contributions more rapidly than conventional journals, ASL offers a framework that promotes new understanding and creates scientific debate - providing a platform for discussing scientific issues and techniques. We encourage the presentation of multi-disciplinary work and contributions that utilise ideas and techniques from parallel areas. We particularly welcome contributions that maximise the visualisation capabilities offered by a purely on-line journal. ASL welcomes papers in the fields of: Dynamical meteorology; Ocean-atmosphere systems; Climate change, variability and impacts; New or improved observations from instrumentation; Hydrometeorology; Numerical weather prediction; Data assimilation and ensemble forecasting; Physical processes of the atmosphere; Land surface-atmosphere systems.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信