We analyse Swarm satellite magnetic field and electron density data one month before and one month after 12 strong earthquakes that have occurred in the first 2.5 years of Swarm satellite mission lifetime in the Mediterranean region (magnitude M6.1+) or in the rest of the world (M6.7+). The search for anomalies was limited to the area centred at each earthquake epicentre and bounded by a circle that scales with magnitude according to the Dobrovolsky’s radius. We define the magnetic and electron density anomalies statistically in terms of specific thresholds with respect to the same statistical quantity along the whole residual satellite track (|geomagnetic latitude| ≤ 50°, quiet geomagnetic conditions). Once normalized by the analysed satellite tracks, the anomalies associated to all earthquakes resemble a linear dependence with earthquake magnitude, so supporting the statistical correlation with earthquakes and excluding a relationship by chance.

The geomagnetic storm occurred on 25 August 2018, i.e. during the minimum of solar cycle 24, is currently the strongest ever probed by the first China Seismo‐Electromagnetic Satellite (CSES‐01). By integrating the in situ measurements provided by CSES‐01 (orbiting at altitude of 507 km) and by Swarm A satellite (orbiting at ca. 470 km) with ground‐based observations (ionosondes, magnetometers and Global Navigation Satellite System receivers), we investigate the ionospheric response at low‐ and mid‐ latitudes over Brazil. Specifically, we investigate the electrodynamic disturbances driven by solar wind changes, by focusing on the disturbances driving modifications of the Equatorial Electrojet (EEJ). Our proposed multi‐sensor technique analysis mainly highlights the variations in the topside and bottomside ionosphere, and the interplay between Prompt Penetrating Electric Fields and Disturbance Dynamo Electric Fields resulting in EEJ variations. Thanks to this approach and leveraging on the newly available CSES‐01 data, we complement and extend what recently investigated in the Western South American sector, by highlighting the significant longitudinal differences, which mainly come from the occurrence of a daytime counter‐EEJ during both 25 and 26 August at Brazilian longitudes and during part of 26 August only in the Peruvian sector. In addition, the increased thermospheric circulation driven by the storm has an impact on the EEJ during the recovery phase of the storm. The observations at the CSES‐01/Swarm altitudes integrated with the ground‐based observation recorded signatures of Equatorial Ionospheric Anomaly (EIA) crests formation and modification during daytime coupled with the positive ionospheric storm effects at mid‐latitude.

Earthquakes are the most energetic phenomena in the lithosphere: their study and comprehension are greatly worth doing because of the obvious importance for society. Geosystemics intends to study the Earth system as a whole, looking at the possible couplings among the different geo-layers, i.e., from the earth’s interior to the above atmosphere. It uses specific universal tools to integrate different methods that can be applied to multi-parameter data, often taken on different platforms (e.g., ground, marine or satellite observations). Its main objective is to understand the particular phenomenon of interest from a holistic point of view. Central is the use of entropy, together with other physical quantities that will be introduced case by case. In this paper, we will deal with earthquakes, as final part of a long-term chain of processes involving, not only the interaction between different components of the Earth’s interior but also the coupling of the solid earth with the above neutral or ionized atmosphere, and finally culminating with the main rupture along the fault of concern. Particular emphasis will be given to some Italian seismic sequences.

Nowadays, the possibility that medium-large earthquakes could produce some electromagnetic ionospheric disturbances during their preparatory phase is controversial in the scientific community. Some previous works using satellite data from DEMETER, Swarm and, recently, CSES provided several pieces of evidence supporting the existence of such precursory phenomena in terms of single case studies and statical analyses. In this work, we applied a Worldwide Statistical Correlation approach to M5.5+ shallow earthquakes using the first 8 years of Swarm (i.e., from November 2013 to November 2021) magnetic field and electron density signals in order to improve the significance of previous statistical studies and provide some new results on how earthquake features could influence ionospheric electromagnetic disturbances. We implemented new methodologies based on the hypothesis that the anticipation time of anomalies of larger earthquakes is usually longer than that of anomalies of smaller magnitude. We also considered the signal’s frequency to introduce a new identification criterion for the anomalies. We find that taking into account the frequency can improve the statistical significance (up to 25% for magnetic data and up to 100% for electron density). Furthermore, we noted that the frequency of the Swarm magnetic field signal of possible precursor anomalies seems to slightly increase as the earthquake is approaching. Finally, we checked a possible relationship between the frequency of the detected anomalies and earthquake features. The earthquake focal mechanism seems to have a low or null influence on the frequency of the detected anomalies, while the epicenter location appears to play an important role. In fact, land earthquakes are more likely to be preceded by slower (lower frequency) magnetic field signals, whereas sea seismic events show a higher probability of being preceded by faster (higher frequency) magnetic field signals.

The first 5.3 years of magnetic data from three Swarm satellites have been systematically analyzed, and possible co-seismic magnetic disturbances in the ionosphere were investigated just a few minutes after the occurrence of large earthquakes. We preferred to limit the investigation to a subset of earthquakes selected in function of depth and magnitude. After a systematic inspection of the available data around (in time and space) the seismic events, we found 12 Swarm satellite tracks with co-seismic disturbances possibly produced by ten earthquakes from Mw5.6 to Mw6.9. The distance of the satellite to the earthquake epicenter corresponds to the measured distance-time arrival of the disturbance from the surface to the ionosphere, confirming that the identified disturbances are most likely produced by the seismic events. Secondly, we found a good agreement with a model that combined a propagation of the disturbance to the F2 ionospheric layer with an acoustic gravity wave at a velocity of about (2.2 ± 0.3) km/s and a second faster phenomenon that transmits the disturbance from F2 layer to the Swarm satellite with a velocity of about (16 ± 3) km/s as an electromagnetic scattering propagation.

On 20 December 2021, after six quiet years, the Hunga Tonga–Hunga Ha’apai volcano erupted abruptly. Then, on 15 January 2022, the largest eruption produced a plume well registered from satellites and destroyed the volcanic cone previously formed in 2015, connecting the two islands. We applied a multi-parametric and multi-layer study to investigate all the possible pre-eruption signals and effects of this volcanic activity in the lithosphere, atmosphere, and ionosphere. We focused our attention on: (a) seismological features considering the eruption in terms of an earthquake with equivalent energy released in the lithosphere; (b) atmospheric parameters, such as skin and air temperature, outgoing longwave radiation (OLR), cloud cover, relative humidity from climatological datasets; (c) varying magnetic field and electron density observed by ground magnetometers and satellites, even if the event was in the recovery phase of an intense geomagnetic storm. We found different precursors of this unique event in the lithosphere, as well as the effects due to the propagation of acoustic gravity and pressure waves and magnetic and electromagnetic coupling in the form of signals detected by ground stations and satellite data. All these parameters and their detailed investigation confirm the lithosphere–atmosphere–ionosphere coupling (LAIC) models introduced for natural hazards such as volcano eruptions and earthquakes.