Assimilation of high-resolution GNSS tropospheric delays and its effects on a severe convective event nowcasting

IF 4.5 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES
Yuxin Zheng , Cuixian Lu , Zhilu Wu , Zhenyu Guan , Jiafeng Li , Zhuo Wang , Chengbo Liu
{"title":"Assimilation of high-resolution GNSS tropospheric delays and its effects on a severe convective event nowcasting","authors":"Yuxin Zheng ,&nbsp;Cuixian Lu ,&nbsp;Zhilu Wu ,&nbsp;Zhenyu Guan ,&nbsp;Jiafeng Li ,&nbsp;Zhuo Wang ,&nbsp;Chengbo Liu","doi":"10.1016/j.atmosres.2024.107785","DOIUrl":null,"url":null,"abstract":"<div><div>A crucial factor limiting convective weather nowcasting is the lack of timely updated and accurate atmospheric water vapor observations. The Global Navigation Satellite System (GNSS) can accurately sense water vapor with high temporal resolutions, which is adequate to observe many meso- and small-scale variations associated with convective weather. In this contribution, an hourly cycling data assimilation system is established to investigate the influence of assimilating GNSS zenith total delays (ZTD) on severe convective weather nowcasting. The contributions of assimilating ZTD with different temporal resolutions are discussed in detail by validating with the radiosonde observations. The results demonstrate that the assimilation of ZTD significantly improves the moisture distribution of the middle and lower troposphere. Furthermore, model simulations become wetter or drier as the frequency of ZTD assimilation increases. Verification of the precipitation forecasts is performed by comparing them with the radar-estimated precipitation. The results indicate that assimilation of GNSS ZTD improves the accuracy of precipitation forecast in the nowcasting range of 0–6 h. Compared to the control experiment, the hourly ZTD assimilation experiment reveals the highest precipitation forecast skill scores, followed by the experiments of assimilating ZTD every three and six hours, indicating that the rapid update of water vapor information could contribute to improving the precipitation nowcasting in a rapidly developing convective system.</div></div>","PeriodicalId":8600,"journal":{"name":"Atmospheric Research","volume":"314 ","pages":"Article 107785"},"PeriodicalIF":4.5000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Research","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169809524005672","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

A crucial factor limiting convective weather nowcasting is the lack of timely updated and accurate atmospheric water vapor observations. The Global Navigation Satellite System (GNSS) can accurately sense water vapor with high temporal resolutions, which is adequate to observe many meso- and small-scale variations associated with convective weather. In this contribution, an hourly cycling data assimilation system is established to investigate the influence of assimilating GNSS zenith total delays (ZTD) on severe convective weather nowcasting. The contributions of assimilating ZTD with different temporal resolutions are discussed in detail by validating with the radiosonde observations. The results demonstrate that the assimilation of ZTD significantly improves the moisture distribution of the middle and lower troposphere. Furthermore, model simulations become wetter or drier as the frequency of ZTD assimilation increases. Verification of the precipitation forecasts is performed by comparing them with the radar-estimated precipitation. The results indicate that assimilation of GNSS ZTD improves the accuracy of precipitation forecast in the nowcasting range of 0–6 h. Compared to the control experiment, the hourly ZTD assimilation experiment reveals the highest precipitation forecast skill scores, followed by the experiments of assimilating ZTD every three and six hours, indicating that the rapid update of water vapor information could contribute to improving the precipitation nowcasting in a rapidly developing convective system.
高分辨率全球导航卫星系统对流层延迟的同化及其对严重对流事件预报的影响
限制对流天气预报的一个关键因素是缺乏及时更新和准确的大气水汽观测。全球导航卫星系统(GNSS)能够以较高的时间分辨率精确感知水汽,足以观测到与对流天气相关的许多中尺度和小尺度变化。本文建立了一个每小时循环数据同化系统,以研究同化全球导航卫星系统天顶总延迟(ZTD)对强对流天气预报的影响。通过与无线电探空仪观测数据进行验证,详细讨论了不同时间分辨率的天顶总延迟同化的贡献。结果表明,ZTD 同化显著改善了对流层中下层的湿度分布。此外,随着 ZTD 同化频率的增加,模式模拟会变得更湿润或更干燥。通过与雷达估算的降水量进行比较,对降水预报进行了验证。结果表明,GNSS ZTD 同化提高了 0-6 小时降水预报的准确性。与对照实验相比,每小时 ZTD 同化实验的降水预报技能得分最高,其次是每 3 小时和每 6 小时同化 ZTD 的实验,表明水汽信息的快速更新有助于改善快速发展的对流系统中的降水预报。
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 求助全文
来源期刊
Atmospheric Research
Atmospheric Research 地学-气象与大气科学
CiteScore
9.40
自引率
10.90%
发文量
460
审稿时长
47 days
期刊介绍: The journal publishes scientific papers (research papers, review articles, letters and notes) dealing with the part of the atmosphere where meteorological events occur. Attention is given to all processes extending from the earth surface to the tropopause, but special emphasis continues to be devoted to the physics of clouds, mesoscale meteorology and air pollution, i.e. atmospheric aerosols; microphysical processes; cloud dynamics and thermodynamics; numerical simulation, climatology, climate change and weather modification.
×
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