测绘学报 ›› 2026, Vol. 55 ›› Issue (8): 1331-1342.doi: 10.11947/j.AGCS.2026.20260305

• 快报论文 •    

基于多源GNSS-R观测的2026台风“巴威”海面风场及洪涝过程快速监测分析

郭斐1(), 郭沁雨1(), 胡国骥1, 张小红1,2, 唐琪3   

  1. 1.武汉大学测绘学院,湖北 武汉 430079
    2.武汉大学中国南极测绘研究中心,湖北 武汉 430079
    3.航天天目(重庆)卫星科技有限公司,重庆 401332
  • 收稿日期:2026-07-29 修回日期:2026-08-14 发布日期:2026-09-09
  • 通讯作者: 郭沁雨 E-mail:fguo@whu.edu.cn;qinyuguo@whu.edu.cn
  • 作者简介:郭斐(1984—),男,博士,教授,研究方向为GNSS反射测量。E-mail:fguo@whu.edu.cn
  • 基金资助:
    国家重点研发计划(2024YFB3910000);中央高校青年教师科研创新能力支持项目(SRICSPYF-ZY2025002)

Rapid monitoring and analysis of sea surface wind fields and flooding processes associated with Typhoon Bavi (2026) based on multi-source GNSS-R observations

Fei Guo1(), Qinyu Guo1(), Guoji Hu1, Xiaohong Zhang1,2, Qi Tang3   

  1. 1.School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
    2.Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China
    3.Aerospace Tianmu (Chongqing) Satellite Technology Co., Ltd., Chongqing 401332, China
  • Received:2026-07-29 Revised:2026-08-14 Published:2026-09-09
  • Contact: Qinyu Guo E-mail:fguo@whu.edu.cn;qinyuguo@whu.edu.cn
  • About author:Guo Fei (1984—), male, professor, majors in GNSS reflectometry. E-mail: fguo@whu.edu.cn
  • Supported by:
    The National Key Research and Development Program of China(2024YFB3910000);The Fundamental Research Funds for the Central Universities(SRICSPYF-ZY2025002)

摘要:

近年来,台风及其引发的暴雨及洪涝灾害严重威胁沿海安全,亟须高时空分辨率遥感数据支撑全过程监测。2026年第9号台风“巴威”风力强、影响范围广,并伴随持续强降水,对沿海及内陆地区造成严重影响。星载全球导航卫星反射技术(global navigation satellite systems-reflectometry,GNSS-R)因观测平台数量多、重访周期短、采样密度高等优势,为台风风场连续监测及灾害响应提供了有效途径。本文利用Cyclone GNSS(CYGNSS)、风云三号和天目一号星座多源GNSS-R数据,对台风发展期间海面风场演变特征及其引发的城市内涝进行分析。结果表明,GNSS-R风速可准确跟踪台风路径与强度变化,监测到的最高风速可达80 m/s。在高风速条件下,相较再分析风速数据,能够更有效地恢复风速分布厚尾特征,且基于GNSS-R的洪涝监测结果与降水过程及SMAP参考数据一致。此外,多源GNSS-R联合观测可显著提升覆盖率和采样频次,较单一GNSS-R数据源提高约30%,能够更连续地刻画台风发展过程。本文研究证实多源GNSS-R可支撑“海上风场—陆地灾害”全过程快速监测,为其业务化应用提供了参考。

关键词: 星载GNSS-R, 海面风场, 洪涝监测, 风云三号, 台风“巴威”

Abstract:

In recent years, typhoons and the associated torrential rainfall and flooding have posed severe threats to coastal safety, necessitating high spatiotemporal resolution remote sensing data to support full-process monitoring. The 9th typhoon of 2026, “Bavi”, characterized by intense wind strength, extensive influence, and persistent heavy precipitation, has caused significant impacts on both coastal and inland regions. Spaceborne global navigation satellite systems-reflectometry (GNSS-R), benefiting from advantages such as a large number of observation platforms, short revisit cycles, and high sampling density, offers a novel approach for the continuous monitoring of typhoon wind fields and disaster response. This study utilizes multi-source GNSS-R data from Cyclone GNSS (CYGNSS), Fengyun-3, and Tianmu-1 to analyze the evolutionary characteristics of sea surface wind fields during typhoon development and the associated urban waterlogging. The results demonstrate that GNSS-R-derived wind speeds can accurately track typhoon track and intensity variations, with the maximum monitored wind speed reaching 80m/s. Under high-wind conditions, GNSS-R data are more effective than reanalysis wind data in recovering the heavy-tailed characteristics of wind speed distributions. Furthermore, the flood monitoring results based on GNSS-R are consistent with both the rainfall processes and the reference data from SMAP. In addition, the combined observations from multi-source GNSS-R significantly enhance coverage and sampling frequency, improving by approximately 30% compared to a single GNSS-R data source, thereby enabling a more continuous depiction of the typhoon evolution process. This study confirms that multi-source GNSS-R can support rapid, full-process monitoring spanning “offshore wind fields to on-land disasters”, providing a reference for its operational application.

Key words: spaceborne GNSS-R, sea surface wind field, flood monitoring, Fengyun-3, Typhoon Bavi

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