Ionosphere and Space Weather Based on Satellite Remote Sensing Observation

Dear Colleagues,

The ionosphere is a dynamic region of Earth's upper atmosphere that plays a vital role in space weather processes, influencing satellite communications, GNSS positioning, and radar systems. Space weather events such as solar flares, coronal mass ejections, and geomagnetic storms can cause significant ionospheric disturbances, leading to communication blackouts, signal degradation, and navigation errors. Understanding and forecasting these disturbances is essential for the resilience of modern technological infrastructure. Satellite remote sensing has become an indispensable tool for observing the ionosphere, offering global coverage, high temporal resolution, and the ability to monitor real-time ionospheric variability. When integrated with ground-based observations—such as GNSS networks, ionosondes, and incoherent scatter radars—these datasets enable a multi-scale view of ionospheric dynamics. Recent advances in remote sensing technologies, data fusion techniques, and physics-informed models, including those based on machine learning, are driving innovation in ionospheric and space weather research. This research area is critically important for enhancing our scientific understanding and operational capability in space weather monitoring and prediction. As the dependency on satellite-based systems grows, so does the urgency for accurate, timely, and global-scale assessments of ionospheric behavior.

This Special Issue aims to highlight cutting-edge developments in remote sensing technologies and methodologies for ionospheric and space weather research. A particular focus will be placed on innovative approaches that leverage the synergy between satellite and ground-based observations, and on modeling and forecasting techniques—including those utilizing machine learning—that contribute to space weather resilience. In line with Remote Sensing's mission, this Issue seeks contributions that address atmospheric and environmental challenges using advanced remote sensing techniques. We especially welcome studies that push the boundaries of observational capabilities or predictive modeling in the context of ionospheric disturbances and space weather impacts.

We invite original research articles, technical notes, and comprehensive reviews in the following areas:

1. Innovative satellite-based techniques for ionospheric monitoring and their integration with ground-based systems.
2. Detection and characterization of ionospheric disturbances (e.g., TIDs, scintillation, storm-time effects) via remote sensing.
3. Data assimilation and space weather forecasting models, including AI/ML-based approaches, using multi-source observations.
4. Impact assessment of ionospheric disturbances on GNSS, satellite communications, and radar operations.
5. New satellite missions, sensor technologies, or data fusion frameworks for improved space weather resilience.
6. Cross-disciplinary approaches combining remote sensing, geophysics, and atmospheric modeling to address space environment challenges.

This Special Issue encourages both technological innovations and modeling advancements, particularly those with practical applications in forecasting and early warning systems.

Prof. Dr. Xudong Gu
Guest Editor

Manuscript Submission Information

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