澳大利亚周边不同强对流风类型的长期观测特征

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Andrew Brown, A. Dowdy, T. Lane, S. Hitchcock
{"title":"澳大利亚周边不同强对流风类型的长期观测特征","authors":"Andrew Brown, A. Dowdy, T. Lane, S. Hitchcock","doi":"10.1175/waf-d-23-0069.1","DOIUrl":null,"url":null,"abstract":"\nRegional understanding of severe surface winds produced by convective processes (severe convective winds: SCWs) is important for decision making in several areas of society, including weather forecasting and engineering design. Meteorological studies have demonstrated that SCWs can occur due to a number of different mesoscale and microscale processes, in a range of large-scale atmospheric environments. However, long-term observational studies of SCW characteristics often have not considered this diversity in physical processes, particularly in Australia. Here, a statistical clustering method is used to separate a large dataset of SCW events, measured by automatic weather stations around Australia, into three types, associated with strong background wind, steep lapse rate, and high moisture environments. These different types of SCWs are shown to have different seasonal and spatial variations in their occurrence, as well as different measured wind gust, lightning, and parent-storm characteristics. In addition, various convective diagnostics are tested in their ability to discriminate between measured SCW events and non-severe events, with significant variations in skill between event types. Differences in environmental conditions and wind gust characteristics between clusters suggests potentially different physical processes for SCW production. These findings are intended to improve regional understanding of severe wind characteristics, as well as environmental prediction of SCWs in weather and climate applications, by considering different event types.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"1 1","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Long-term observational characteristics of different severe convective wind types around Australia\",\"authors\":\"Andrew Brown, A. Dowdy, T. Lane, S. Hitchcock\",\"doi\":\"10.1175/waf-d-23-0069.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nRegional understanding of severe surface winds produced by convective processes (severe convective winds: SCWs) is important for decision making in several areas of society, including weather forecasting and engineering design. Meteorological studies have demonstrated that SCWs can occur due to a number of different mesoscale and microscale processes, in a range of large-scale atmospheric environments. However, long-term observational studies of SCW characteristics often have not considered this diversity in physical processes, particularly in Australia. Here, a statistical clustering method is used to separate a large dataset of SCW events, measured by automatic weather stations around Australia, into three types, associated with strong background wind, steep lapse rate, and high moisture environments. These different types of SCWs are shown to have different seasonal and spatial variations in their occurrence, as well as different measured wind gust, lightning, and parent-storm characteristics. In addition, various convective diagnostics are tested in their ability to discriminate between measured SCW events and non-severe events, with significant variations in skill between event types. Differences in environmental conditions and wind gust characteristics between clusters suggests potentially different physical processes for SCW production. These findings are intended to improve regional understanding of severe wind characteristics, as well as environmental prediction of SCWs in weather and climate applications, by considering different event types.\",\"PeriodicalId\":49369,\"journal\":{\"name\":\"Weather and Forecasting\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2023-08-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Weather and Forecasting\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1175/waf-d-23-0069.1\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Weather and Forecasting","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/waf-d-23-0069.1","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

对由对流过程产生的强地面风(强对流风:SCWs)的区域理解对于包括天气预报和工程设计在内的几个社会领域的决策至关重要。气象研究表明,在一系列大尺度大气环境中,SCWs可由许多不同的中尺度和微尺度过程引起。然而,SCW特征的长期观察研究往往没有考虑到物理过程中的这种多样性,特别是在澳大利亚。本文采用统计聚类方法将澳大利亚各地自动气象站测量的大型SCW事件数据集划分为三种类型,分别与强背景风、陡递减率和高湿度环境相关。这些不同类型的SCWs在发生上有不同的季节和空间变化,以及测量到的阵风、闪电和母暴特征也不同。此外,还测试了各种对流诊断方法区分测量的SCW事件和非严重事件的能力,这些事件类型之间的技能存在显著差异。不同集群之间的环境条件和阵风特征的差异表明,产生水雾的物理过程可能不同。这些发现旨在通过考虑不同事件类型,提高区域对强风特征的理解,以及在天气和气候应用中对SCWs的环境预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Long-term observational characteristics of different severe convective wind types around Australia
Regional understanding of severe surface winds produced by convective processes (severe convective winds: SCWs) is important for decision making in several areas of society, including weather forecasting and engineering design. Meteorological studies have demonstrated that SCWs can occur due to a number of different mesoscale and microscale processes, in a range of large-scale atmospheric environments. However, long-term observational studies of SCW characteristics often have not considered this diversity in physical processes, particularly in Australia. Here, a statistical clustering method is used to separate a large dataset of SCW events, measured by automatic weather stations around Australia, into three types, associated with strong background wind, steep lapse rate, and high moisture environments. These different types of SCWs are shown to have different seasonal and spatial variations in their occurrence, as well as different measured wind gust, lightning, and parent-storm characteristics. In addition, various convective diagnostics are tested in their ability to discriminate between measured SCW events and non-severe events, with significant variations in skill between event types. Differences in environmental conditions and wind gust characteristics between clusters suggests potentially different physical processes for SCW production. These findings are intended to improve regional understanding of severe wind characteristics, as well as environmental prediction of SCWs in weather and climate applications, by considering different event types.
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
Weather and Forecasting
Weather and Forecasting 地学-气象与大气科学
CiteScore
5.20
自引率
17.20%
发文量
131
审稿时长
6-12 weeks
期刊介绍: Weather and Forecasting (WAF) (ISSN: 0882-8156; eISSN: 1520-0434) publishes research that is relevant to operational forecasting. This includes papers on significant weather events, forecasting techniques, forecast verification, model parameterizations, data assimilation, model ensembles, statistical postprocessing techniques, the transfer of research results to the forecasting community, and the societal use and value of forecasts. The scope of WAF includes research relevant to forecast lead times ranging from short-term “nowcasts” through seasonal time scales out to approximately two years.
×
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