Detection of Ionosphere Anomalies (DIA) for detection, identification, and analysis of ionosphere anomalies from satellite spectrograms and time series row data from instruments onboard the DEMETER satellite was designed. Using this software, the analyses of ionosphere parameter variations caused by various factors are provided. The scientific data processing and visualization technologies used in the development of DIA can be used in the creation of software for other scientific space missions.

The 30 August–2 September 2019 geospace storm and its influence on the characteristics of high frequency radio waves over the People's Republic of China have been analyzed. The geospace storm was weak, the magnetic storm was moderate, and the ionospheric storm was moderate to strongly negative, which manifested itself by the reduction in the ionospheric F-region electron density. Appreciable disturbances were also observed to occur in the ionospheric E-region and possibly in the E_s layer.

Travelling ionospheric disturbances behave like waves in the ionosphere, the ionised upper part of the atmosphere. In this study, we use an ionospheric tomography technique to map the electron content as affected by the passage of a large-scale travelling ionospheric disturbance launched during the largest geomagnetic storm observed by modern instruments. This is the first such imaging using this software and to the authors' knowledge the first study of this travelling ionospheric disturbance.

The analysis of unexpected ionospheric phases before large earthquakes is one of the cutting-edge issues in earthquake prediction studies. Ionospheric TEC data were analyzed by short-time Fourier transform and a classic running median to detect abnormalities before the M_w 7.3 Iran–Iraq earthquake on November 12, 2017. The results showed clear positive anomalies 8–9 d before the earthquake as an earthquake precursor due to quiet space weather, local dispersion, and proximity to the epicenter.

The paper analytically and numerically treats the new theoretical basis for ground-based and satellite monitoring of the most powerful processes in the lower atmosphere and Earth (hurricanes, earthquakes, etc.), solar-wind magnetosphere (magnetic storms) and ionosphere (lightning discharges, thunderstorms, etc.). This can be provided by the determination of phases and amplitudes of radio waves in the Earth and ionosphere. In perspective, damage from the natural disasters can be decreased.

Underground nuclear explosion (UNE) can produce ionospheric disturbances through a lithosphere–atmosphere–ionosphere coupling mechanism, which is very similar with earthquakes. By using the total electron content observations and Swarm ionospheric current data, we have investigated the geomagnetic conjugate ionospheric disturbances. We proposed that the electric field generated during the UNE test can be an important mechanism for ionospheric disturbance.

A localized total electron content enhancement (LTE) was observed as a product of the geomagnetic storm that happened on 8 September 2017. This result was unexpected because it was located south of the equatorial ionization anomaly (EIA). The origin of the enhancement of the TEC in the EIA is very likely due to the super-fountain effect. On the other hand, the LTE is suggested to be produced by the contribution of the super-fountain effect along with traveling ionospheric disturbances.

In this contribution, we analyse the performance of the Swarm onboard GPS receiver and present the approach for determination of the IfE Swarm kinematic orbit with PPP. The differences between our kinematic orbits and ESA reduced-dynamic orbits are at 1.5 cm, 1.5 cm and 2.5 cm level in along-track, cross-track and radial directions, respectively. A comparison with SLR underlines an accuracy of the kinematic orbits of 3–4 cm.