The wind and temperature information of AMDAR data applying to the analysis of severe weather nowcasting of airport

Yuan Zhou, Ming Wei, Zhoujie Cheng, Yinghui Ning, Linlin Qi
{"title":"The wind and temperature information of AMDAR data applying to the analysis of severe weather nowcasting of airport","authors":"Yuan Zhou, Ming Wei, Zhoujie Cheng, Yinghui Ning, Linlin Qi","doi":"10.1109/ICIST.2013.6747706","DOIUrl":null,"url":null,"abstract":"Strong convection is the important weather phenomenon impacting the flight safety, always causes sudden changes of meteorological elements. AMDAR data is of high resolution on spatial and temporal, which can provide vital information for the short-term forecast of strong convection weather in the airport terminal area. This paper extracts the three-dimensional vertical wind profiles and temperature profiles, and produces the wind shear warning analysis diagram in the horizontal and vertical direction. The case studied in this paper is a strong convection at April 2011 in Guangdong Province, AMDAR data, together with multi-source information such as radar, satellite and air sounding is analyzed. The study has found that with high resolution spatial and temporal AMDAR data, wind and temperature disturbance information could reveal the motion of wind shear and turbulence in the airport, so that the unique observational basis for protecting the aircraft's take-off and landing safety is provided.","PeriodicalId":415759,"journal":{"name":"2013 IEEE Third International Conference on Information Science and Technology (ICIST)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Third International Conference on Information Science and Technology (ICIST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIST.2013.6747706","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Strong convection is the important weather phenomenon impacting the flight safety, always causes sudden changes of meteorological elements. AMDAR data is of high resolution on spatial and temporal, which can provide vital information for the short-term forecast of strong convection weather in the airport terminal area. This paper extracts the three-dimensional vertical wind profiles and temperature profiles, and produces the wind shear warning analysis diagram in the horizontal and vertical direction. The case studied in this paper is a strong convection at April 2011 in Guangdong Province, AMDAR data, together with multi-source information such as radar, satellite and air sounding is analyzed. The study has found that with high resolution spatial and temporal AMDAR data, wind and temperature disturbance information could reveal the motion of wind shear and turbulence in the airport, so that the unique observational basis for protecting the aircraft's take-off and landing safety is provided.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
AMDAR数据的风和温度信息在机场恶劣天气临近预报分析中的应用
强对流是影响飞行安全的重要天气现象,常引起气象要素的突变。AMDAR数据具有高时空分辨率,可为机场候机区强对流天气的短期预报提供重要信息。提取了三维垂直风廓线和温度廓线,生成了水平和垂直方向的风切变预警分析图。本文以2011年4月广东省的一次强对流为例,结合雷达、卫星、空探等多源资料对AMDAR资料进行了分析。研究发现,利用高分辨率时空AMDAR数据,风和温度扰动信息可以揭示机场内风切变和湍流的运动,为保障飞机的起降安全提供了独特的观测依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Session 20: Ubi/cloud computing Localization based on active learning for cognitive radio networks A dual operating frequency band periodic half-width microstrip leaky-wave antenna End-to-end flow inference of encrypted MANET SER performance of opportunistic relaying with direct link using antenna selection
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1