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Morphological features of severe ionospheric weather associated with typhoon Doksuri in 2023

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posted on 2025-03-25, 15:56 authored by Wang Li, Fangsong Yang, Jiayi Yang, Renzhong Zhang, Juan Lin, Dongsheng Zhao, Craig HancockCraig Hancock
The atmospheric gravity waves (AGWs) generated by severe typhoons can facilitate the transfer of energy from the troposphere to the ionosphere, resulting in medium-scale traveling ionospheric disturbances (MSTIDs). However, the complex three-dimensional nature of MSTIDs over oceanic regions presents challenges for detection using ground-based Global Navigation Satellite System (GNSS) networks. This study employs a hybrid approach combining space-based and ground-based techniques to investigate the spatiotemporal characteristics of ionospheric perturbations during Typhoon Doksuri. Plane maps depict significant plasma fluctuations extending outward from the typhoon’s gale wind zone on 24 July, reaching distances of up to 1800 km from the typhoon’s center, while space weather conditions remained relatively calm. These ionospheric perturbations propagated at velocities between 173 m/s and 337 m/s, consistent with AGW features and associated propagation speeds. Vertical mapping reveals that energy originating from Typhoon Doksuri propagated upward through a 500 km layer, resulting in substantial enhancements of plasma density and temperature in the topside ionosphere. Notably, the topside horizontal density gradient was 1.5 to 2 times greater than that observed in the bottom-side ionosphere. Both modeling and observational data convincingly demonstrate that the weak background winds favored the generation of AGWs associated with Typhoon Doksuri, influencing the development of distinct MSTIDs.

Funding

National Natural Science Foundation of China (Grants 42204030 and 42204037)

Yunnan Fundamental Research Projects (Grants 202201BE070001-035 and 202301AU070062)

Support Programme for Developing Yunnan Talents

History

School

  • Architecture, Building and Civil Engineering

Published in

Remote Sensing

Volume

16

Issue

18

Publisher

MDPI

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Acceptance date

2024-09-09

Publication date

2024-09-11

Copyright date

2024

eISSN

2072-4292

Language

  • en

Depositor

Dr Craig Hancock. Deposit date: 17 October 2024

Article number

3375

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