Ionospheric Observations and Modeling for Enhanced Space Weather Prediction and GNSS Accuracy

The ionosphere is a dynamic, partially ionized region that directly affects satellite communications, Global Navigation Satellite System (GNSS) positioning, HF radio communications and broadcasting, and a growing number of low-Earth-orbit satellite services. Solar Cycle 25 reached a higher level of solar activity than Solar Cycle 24. During its solar maximum, geomagnetic storms, magnetospheric substorms, sudden ionospheric disturbances, equatorial plasma bubbles, and large-scale traveling ionospheric disturbances (LSTIDs) occurred more frequently, posing significant challenges for operational space weather prediction and GNSS positioning accuracy across a wide range of latitudes.Recent satellite missions and constellations, including FengYun-3E, COSMIC-2, Swarm, ICON, GOLD, Spire, together with GNSS radio occultation observations, now provide overlapping coverage of key ionospheric parameters: Total Electron Content (TEC), F2-layer peak height (hmF2) and density (NmF2), electron density profiles, and topside scale heights. The main challenge now is integration of multiple types of ionospheric observations. Measurements from space-borne and ground-based GNSS, ionosondes, and incoherent scatter radars are sometimes inconsistent with each other, and large observational gaps remain over oceans where the ground-based observations are sparse. These issues limit our ability to construct a consistent and accurate representation of the ionosphere for space weather prediction and high-precision GNSS applications.This Research Topic invites contributions addressing, but not limited to, the following themes:• Satellite and ground-based ionospheric observations.• Empirical and physics-based modeling.• Data assimilation.• Machine learning and artificial intelligence (AI) methods for developing and improving global and regional ionospheric models using multi-source ionospheric observations.• Model validation and applications in ionospheric specification, nowcasting, forecasting, and GNSS positioning.Particular emphasis is placed on interdisciplinary studies that bridge observations, models, and advanced computational methods to improve our understanding of ionospheric variability and its impacts on space weather prediction and GNSS performance. Topic editors: Yuichi OTSUKA, Libo Liu, Sanjay Kumar Source: https://www.frontiersin.org/research-topics/83677/ionospheric-observations-and-modeling-for-enhanced-space-weather-prediction-and-gnss-accuracy