Dataset to accompany manuscript "Gradient Ionosphere Index Estimation Using Ground-Based GEO Observations for Multi-scale Ionospheric Dynamics Monitoring"

This dailaset accompanies the manuscipt "Gradient Ionosphere Index Estimation Using Ground-Based GEO Observations for Multi-scale Ionospheric Dynamics Monitoring". The dala can beused to reproduce figures 3-11 in the main text. All files are in .mat fomat and are easlly readable.The abstract for the associated paper is as follows: High-resolution and real-time monitoring of ionospheric dynamics is critical for advancing space weather research and ensuring the reliability of satellite-based communication and navigation systems. 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, referred to as GIX-GEO, which utilizes gradient ionosphere index (GIX) estimations 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 seconds), without requiring satellite motion corrections. This capability enables real-time, multi-scale analysis of ionospheric disturbances. Case studies demonstrate the framework’s ability in (1) resolving sub-minute electron density variations during the diurnal development of equatorial ionization anomalies (EIA), (2) tracking the evolution of plasma irregularities associated with equatorial plasma bubbles (EPBs), and (3) characterizing the propagation of large-scale traveling ionospheric disturbances (LSTIDs). The GIX-GEO framework provides a geometry-consistent, scalable tool that bridges the gap between sparse satellite observations and high-resolution ionospheric diagnostics, offering significant value for both scientific investigation and operational space weather monitoring.