Ionospheric Dynamics: Total Electron Content Variations from Natural and Human-Induced Disturbances

The study of ionospheric dynamics, focusing on Total Electron Content (TEC) and electron density variations, is vital in space weather and atmospheric sciences as it relates to the impacts of the Ionosphere and Middle-Upper Atmosphere (IMUA) on space-based communication and navigation systems.

Advances in Global Navigation Satellite System (GNSS) technology have enabled detailed analyses of ionospheric responses to a variety of natural and human-induced disturbances. Recent progress in multi-instrument observation networks, data availability, and AI-driven modeling capabilities makes this an especially timely area of investigation. Natural disturbances include solar eclipses, volcanic eruptions, atmospheric waves, geomagnetic storms, and secular variations of the geomagnetic field. Human-induced disturbances include chemical releases, high-power radiowave heating, exhaust from rocket launches, and long-term changes in the IMUA induced by climate change in the lower atmosphere. Despite progress, challenges remain in fully understanding and modeling the impact of these perturbations on the ionosphere. Current models provide insights, yet further comprehensive studies and critical data to feed the models are needed.

This Research Topic explores upper atmosphere and ionospheric dynamics, emphasizing TEC variations associated with the large range of external ionospheric drivers, with the aim of enhancing prediction accuracy. Beyond its geophysical core, the topic carries cross-disciplinary relevance for satellite operations, telecommunications, and climate science. Contributions addressing both regional and global scales, as well as transient events and long-term secular trends, are equally encouraged.

The Editors invite Original Research, Review, Mini Review, and Methods articles addressing, but not limited to, the following:

• Data analysis: We welcome articles reporting TEC and electron density variations associated with external drivers, including solar eclipses, geomagnetic storms, volcanic eruptions, chemical release experiments, and climate change, and their potential impact on systems locally and globally. We also encourage studies that develop synergies between TEC single and network observations and other ionosphere and thermosphere measurement techniques to characterize more fully their state and temporal evolution in 3-D, and that address the role of TEC data and networks in multi-instrument, space-based, and ground-based monitoring systems.

• Theoretical and modeling studies: We welcome articles providing insight into the physical processes that control the ionospheric response to the aforementioned external drivers, as well as modeling studies that couple natural and human-induced atmospheric perturbations to the ionosphere both regionally and globally.

• Machine Learning and AI: We welcome articles addressing the emerging role of Machine Learning and other AI techniques in bridging the gaps between TEC observations, other data, and modeling studies.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Study Protocol
• Technology and Code

Keywords: Total Electron Content (TEC), Ionospheric dynamics, Space weather, GNSS, Ionospheric disturbances, Magnetosphere-ionosphere coupling, Machine learning, Upper atmosphere, Vertical coupling in the atmosphere

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.