This paper focuses on unique aspects of the ionospheric response at conjugate locations over Europe and South Africa during the 7–8 September 2017 geomagnetic storm including the role of the bottomside and topside ionosphere and plasmasphere in influencing electron density changes. Analysis of total electron content (TEC) on 7 September 2017 shows that for a pair of geomagnetically conjugate locations, positive storm effect was observed reaching about 65% when benchmarked on the monthly median TEC variability in the Northern Hemisphere, while the Southern Hemisphere remained within the quiet time variability threshold of ±40%. Over the investigated locations, the Southern Hemisphere midlatitudes showed positive TEC deviations that were in most cases twice the comparative response level in the Northern Hemisphere on the 8 September 2017. During the storm main phase on 8 September 2017, we have obtained an interesting result of ionosonde maximum electron density of the F2 layer and TEC derived from Global Navigation Satellite System (GNSS) observations showing different ionospheric responses over the same midlatitude location in the Northern Hemisphere. In situ electron density measurements from SWARM satellite aided by bottomside ionosonde‐derived TEC up to the maximum height of the F2 layer (hmF2) revealed that the bottomside and topside ionosphere as well as plasmasphere electron content contributions to overall GNSS‐derived TEC were different in both hemispheres especially for 8 September 2017 during the storm main phase. The differences in hemispheric response at conjugate locations and on a regional scale have been explained in terms of seasonal influence on the background electron density coupled with the presence of large‐scale traveling ionospheric disturbances and low‐latitude‐associated processes. The major highlight of this study is the simultaneous confirmation of most of the previously observed features and their underlying physical mechanisms during geomagnetic storms through a multi–data set examination of hemispheric differences.

Measurement of the effect of ionospheric irregularities on Global Navigation Satellite Services has drawn great interest due to the adverse effects of such irregularities on precise position estimation. Specialized receivers are currently being used to measure the effects of ionospheric irregularities on the satellite signals. These effects are characterized by the amplitude scintillation index S₄ and the phase scintillation index σ_Φ (sigma phi). In order to compute these scintillation indices, one requires a receiver that measures data at a high sampling rate. The intensity of ionospheric scintillation is an important parameter in the modeling of ionospheric scintillation. Therefore, an index is required that accurately reflects the amplitude scintillation as conventionally measured by means of the S₄ index. To infer the characteristics of ionospheric irregularities from ionospheric scintillation related to geophysical processes, the choice of sampling rate is very important, especially for small‐scale phenomena. In this work, we used a Global Positioning System receiver with high sampling rate, sampling at 20 Hz to compute both the amplitude scintillation index S₄ and the rate of change of total electron content index (ROTI) based on relative total electron content. The results show that by scaling the ROTI values using an appropriate scaling factor, a scintillation index can be calculated that correlates well with the amplitude scintillation index S₄, for values of S₄ < 0.4. For strong scintillation events S₄ > 0.5, the scaled ROTI values are more sensitive for events that lead to loss‐of‐lock (as evidenced by jumps in the L1‐phase values) than the S₄ index. It is also shown that the choice of sampling interval may affect the computed ROTI at a particular location.

Geomagnetically induced currents (GICs) in conductors connected to the Earth are driven by an electric field produced by a time‐varying magnetic field linked to magnetospheric‐ionospheric current perturbations during geomagnetic storms. The GIC measurements are traditionally done on the neutral‐to‐ground connections of power transformers. A method of inferring the characteristics of GIC in power lines using differential magnetic field measurements is presented. Measurements of the GIC in the power lines connected to a particular power transformer are valuable in the verification of the modeling of GIC in the power transmission network. The differential magnetometer method (DMM) is an indirect method used to estimate the GIC in a power line. With the DMM, low‐frequency GIC in the power line is estimated from the difference between magnetic field recordings made directly underneath the power line and at some distance away, where the magnetic field of the GIC in the transmission line has negligible effect. Results of the first application of the DMM to two selected sites of the Southern African power transmission network are presented. The results show that good quality GIC measurements are achieved through the DMM using Commercially‐Off‐The‐Shelf magnetometers.

In this paper, an empirical total electron content (TEC) model and trends in the TEC over the African low-latitude region are presented. GPS-derived TEC data from Malindi, Kenya (geographic coordinates 40.194^∘ E, 2.996^∘ S), and global ionospheric maps (GIMs) were used. We employed an empirical orthogonal function (EOF) analysis method together with least-squares regression to model the TEC. The EOF-based TEC model was validated through comparisons with GIMs, the GPS-derived TEC and the TEC derived from the International Reference Ionosphere 2016 (IRI-2016) model for selected quiet and storm conditions. The single-station EOF-based TEC model over Malindi satisfactorily reproduced the known diurnal, semiannual and annual variations in the TEC. Comparison of the EOF-based TEC model results with the TEC derived from the IRI-2016 model showed that the EOF-based model predicted the TEC over Malindi with fewer errors than the IRI-2016. For the selected storms, the EOF-based TEC model simulated the storm time TEC response over Malindi better than the IRI-2016. In the case of the regional model, the EOF-based TEC model was able to reproduce the TEC characteristics in the equatorial ionization anomaly region. The EOF-based TEC model was then used as a background for estimating TEC trends. A latitudinal dependence in the trends was observed over the African low-latitude region.

The Antarctic and Arctic regions are Earth's open windows to outer space. They provide unique opportunities for investigating the troposphere–thermosphere–ionosphere–plasmasphere system at high latitudes, which is not as well understood as the mid- and low-latitude regions mainly due to the paucity of experimental observations. In addition, different neutral and ionised atmospheric layers at high latitudes are much more variable compared to lower latitudes, and their variability is due to mechanisms not yet fully understood. Fortunately, in this new millennium the observing infrastructure in Antarctica and the Arctic has been growing, thus providing scientists with new opportunities to advance our knowledge on the polar atmosphere and geospace. This review shows that it is of paramount importance to perform integrated, multi-disciplinary research, making use of long-term multi-instrument observations combined with ad hoc measurement campaigns to improve our capability of investigating atmospheric dynamics in the polar regions from the troposphere up to the plasmasphere, as well as the coupling between atmospheric layers. Starting from the state of the art of understanding the polar atmosphere, our survey outlines the roadmap for enhancing scientific investigation of its physical mechanisms and dynamics through the full exploitation of the available infrastructures for radio-based environmental monitoring.