Ionospheric gradient estimation using ground-based GEO observations for monitoring multi-scale ionospheric dynamics

Abstract High-resolution and real-time monitoring of ionospheric dynamics is important for space weather research and satellite-based communication and navigation. However, the existing observational frameworks often face trade-offs between spatial coverage, temporal continuity, and resolution. This study presents a novel fixed-geometry observation framework, which utilizes the ionospheric gradients derived from a network of Geostationary Earth Orbit (GEO) satellites and ground-based Global Navigation Satellite System (GNSS) receivers. The stationary geometry between GEO satellites and ground receivers enables the formation of dense, fixed Ionospheric Pierce Points (IPPs), and geometry-invariant inter-IPP baselines, which serve as fundamental sensing units. Leveraging this configuration, the proposed framework produces high-resolution ionospheric Total Electron Content (TEC) gradient fields (spatially < 0.25°, temporally 30 s), without requiring satellite motion corrections. This enables multi-scale analysis of ionospheric disturbances in real time. Case studies demonstrate the framework can resolve sub-minute electron density variations during the diurnal development of Equatorial Ionization Anomalies (EIA), track the evolution of plasma irregularities associated with Equatorial Plasma Bubbles (EPBs), and characterize the propagation of Large-scale Traveling Ionospheric Disturbances (LSTIDs). The GEO-based framework provides a geometry-consistent and scalable tool that bridges the gap between sparse satellite observations and high-resolution ionospheric diagnostics, which is significant for both scientific investigation and operational space weather monitoring.

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Publication Details

Journal
Satellite Navigation
Published
2025-12-01
DOI
https://doi.org/10.1186/s43020-025-00187-4
Citations
1
Primary Topic
Ionosphere and magnetosphere dynamics
Type
article
Field-Weighted Citation Impact
1.15

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Ionospheric gradient estimation using ground-based GEO observations for monitoring multi-scale ionospheric dynamics

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article

Ionospheric gradient estimation using ground-based GEO observations for monitoring multi-scale ionospheric dynamics

Runqing Liu, Zishen Li, Grzegorz Nykiel, Xin Wan, Yongqiang Hao, Mainul Hoque, Jiahao Zhong, Ningbo Wang, N. Jakowski, Ang Liu, Zhiyao Li
article en
1 citations

Abstract

Abstract High-resolution and real-time monitoring of ionospheric dynamics is important for space weather research and satellite-based communication and navigation. However, the existing observational frameworks often face trade-offs between spatial coverage, temporal continuity, and resolution. This study presents a novel fixed-geometry observation framework, which utilizes the ionospheric gradients derived from a network of Geostationary Earth Orbit (GEO) satellites and ground-based Global Navigation Satellite System (GNSS) receivers. The stationary geometry between GEO satellites and ground receivers enables the formation of dense, fixed Ionospheric Pierce Points (IPPs), and geometry-invariant inter-IPP baselines, which serve as fundamental sensing units. Leveraging this configuration, the proposed framework produces high-resolution ionospheric Total Electron Content (TEC) gradient fields (spatially < 0.25°, temporally 30 s), without requiring satellite motion corrections. This enables multi-scale analysis of ionospheric disturbances in real time. Case studies demonstrate the framework can resolve sub-minute electron density variations during the diurnal development of Equatorial Ionization Anomalies (EIA), track the evolution of plasma irregularities associated with Equatorial Plasma Bubbles (EPBs), and characterize the propagation of Large-scale Traveling Ionospheric Disturbances (LSTIDs). The GEO-based framework provides a geometry-consistent and scalable tool that bridges the gap between sparse satellite observations and high-resolution ionospheric diagnostics, which is significant for both scientific investigation and operational space weather monitoring.

Satellite NavigationVol. 6(1)
Ministry of Education of the People's Republic of China (CN), Sun Yat-sen University (CN), Chinese Academy of Sciences (CN), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Aerospace Information Research Institute (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, China Meteorological Administration
Openalex Percentile: Top 14%
Ionosphere and magnetosphere dynamics
1.15
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