The January 2022 Hunga Tonga–Hunga Ha’apai eruption was one of the most explosive volcanic events of the modern era1,2, producing a vertical plume that peaked more than 50 km above the Earth3. The initial explosion and subsequent plume triggered atmospheric waves that propagated around the world multiple times4. A global-scale wave response of this magnitude from a single source has not previously been observed. Here we show the details of this response, using a comprehensive set of satellite and ground-based observations to quantify it from surface to ionosphere. A broad spectrum of waves was triggered by the initial explosion, including Lamb waves5,6 propagating at phase speeds of 318.2 ± 6 m s−1 at surface level and between 308 ± 5 to 319 ± 4 m s−1 in the stratosphere, and gravity waves7 propagating at 238 ± 3 to 269 ± 3 m s−1 in the stratosphere. Gravity waves at sub-ionospheric heights have not previously been observed propagating at this speed or over the whole Earth from a single source8,9. Latent heat release from the plume remained the most significant individual gravity wave source worldwide for more than 12 h, producing circular wavefronts visible across the Pacific basin in satellite observations. A single source dominating such a large region is also unique in the observational record. The Hunga Tonga eruption represents a key natural experiment in how the atmosphere responds to a sudden point-source-driven state change, which will be of use for improving weather and climate models.

With the current data availability from both ground‐ and space‐based sources, the network of ground‐based Global Positioning System (GPS) receivers, GPS occultation receivers, in situ electron density sensors, and dual‐frequency beacon transmitters, the time is right for a comprehensive review of the history, current state, and future directions of ionospheric imaging. A brief introduction and history of ionospheric imaging is presented, beginning with computerized ionospheric tomography. Then, a comprehensive review of the current state of ionospheric imaging is presented. The ability of imaging algorithms to ingest multiple types of data and use advanced inverse techniques borrowed from meteorological data assimilation to produce four‐dimensional images of electron density is discussed. Particular emphasis is given to the mathematical basis for the different methods. The science that ionospheric imaging addresses is discussed, and the scientific contributions that ionospheric imaging has made are described. Finally, future directions for this research area are outlined.

Severe ionospheric storms occurred at the end of October 2003. During the evening of 30 October a narrow stream of high electron concentration plasma crossed the polar cap in the antisunward ionospheric convection. A GPS scintillation receiver in the European high arctic, operating at 1.575 GHz, experienced both phase and amplitude scintillation on several satellite‐to‐ground links during this period. Close examination of the GPS signals revealed the scintillation to be co‐located with strong gradients in Total Electron Content (TEC) at the edge of the plasma stream. The gradient‐drift instability is a likely mechanism for the generation of the irregularities causing some of the scintillation at L band frequencies during this storm. The origin of the high TEC is explored and the possible implications of the work for scintillation forecasting are noted. The results indicate that the GPS scintillation over Svalbard can originate from traceable ionospheric plasma structures convecting from the American sector.

[1] High-rate sampling data of Global Navigation Satellite Systems ionospheric scintillation acquired by a network of GPS Ionospheric Scintillation and TEC Monitor receivers located in the Svalbard Islands, in Norway and in Antarctica have been analyzed. The aim is to describe the "scintillation climatology" of the high-latitude ionosphere over both the poles under quiet conditions of the near-Earth environment. For climatology we mean to assess the general recurrent features of the ionospheric irregularities dynamics and temporal evolution on long data series, trying to catch eventual correspondences with scintillation occurrence. In spite of the fact that the sites are not geomagnetically conjugate, long series of data recorded by the same kind of receivers provide a rare opportunity to draw a picture of the ionospheric features characterizing the scintillation conditions over high latitudes. The method adopted is the Ground Based Scintillation Climatology, which produces maps of scintillation occurrence and of total electron content relative variation to investigate ionospheric scintillations scenario in terms of geomagnetic and geographic coordinates, interplanetary magnetic field conditions and seasonal variability. By means of such a novel and original description of the ionospheric irregularities, our work provides insights to speculate on the cause-effect mechanisms producing scintillations, suggesting the roles of the high-latitude ionospheric trough, of the auroral boundaries and of the polar cap ionosphere in hosting those irregularities causing scintillations over both the hemispheres at high latitude. The method can constitute a first step toward the development of new algorithms to forecast the scintillations during space weather events.

Ionospheric storms can have important effects on radio communications and navigation systems.Storm time ionospheric predictions have the potential to form part of effective mitigation strategies to these problems. Ionospheric storms are caused by strong forcing from the solar wind. Electron density enhancements are driven by penetration electric fields, as well as by thermosphere-ionosphere behavior including Traveling Atmospheric Disturbances and Traveling Ionospheric Disturbances and changes to the neutral composition. This study assesses the effect on 1 h predictions of specifying initial ionospheric and thermospheric conditions using total electron content (TEC) observations under a fixed set of solar and high-latitude drivers. Prediction performance is assessed against TEC observations, incoherent scatter radar, and in situ electron density observations. Corotated TEC data provide a benchmark of forecast accuracy. The primary case study is the storm of 10 September 2005, while the anomalous storm of 21 January 2005 provides a secondary comparison. The study uses an ensemble Kalman filter constructed with the Data Assimilation Research Testbed and the Thermosphere Ionosphere Electrodynamics General Circulation Model. Maps of preprocessed, verticalized GPS TEC are assimilated, while high-latitude specifications from the Assimilative Mapping of Ionospheric Electrodynamics and solar flux observations from the Solar Extreme Ultraviolet Experiment are used to drive the model. The filter adjusts ionospheric and thermospheric parameters, making use of time-evolving covariance estimates. The approach is effective in correcting model biases but does not capture all the behavior of the storms. In particular, a ridge-like enhancement over the continental USA is not predicted, indicating the importance of predicting storm time electric field behavior to the problem of ionospheric forecasting.