This paper investigates the dynamics of the main parameters of the solar wind and the interplanetary magnetic field based on satellite observations during the extreme geospace storm of May 10–11, 2024. It was found that there was a significant increase in the number density, velocity, temperature, and dynamic pressure of solar wind particles and a sharp increase in the variability of the interplanetary magnetic field components during the storm. These changes contributed to the development of powerful disturbances in the Earth’s magnetosphere. A systems spectral analysis revealed that the spectra of the solar wind and interplanetary magnetic field parameters were dominated by components with periods of 150–190 min.
Reliable estimation of ionospheric Total Electron Content (TEC) is essential for mitigating signal delays and positioning errors in satellite-based communication and navigation systems. In low-latitude regions such as East Africa, TEC variability is strongly influenced by equatorial electrodynamics, seasonal asymmetry, and solar-cycle evolution, posing persistent challenges for both global and regional ionospheric models. This study presents a regional assessment of the IRI-2016, IRI-2020, and AfriTEC models in reproducing TEC variability over East Africa during the ascending phase of Solar Cycle 25 (2021–2022), a period marked by increasing solar and geomagnetic activity. Model outputs are systematically evaluated against GNSS-derived vertical TEC observations from selected International GNSS Service (IGS) stations, with analyses conducted across four representative seasons corresponding to the March and September equinoxes and the June and December solstices. Model performance is quantified using root mean square error (RMSE), Pearson correlation coefficients, and residual distribution analysis to examine error magnitude and bias under varying geophysical conditions. Results reveal pronounced seasonal dependence, with all models showing larger errors during solstice periods, particularly December. AfriTEC demonstrates improved agreement during equinoxes, with reduced variance and near-zero mean residuals, indicating balanced performance under moderate geomagnetic activity. However, its tendency to overestimate TEC during solstices and underestimate peak values during disturbed intervals highlights limitations in representing thermospheric winds and pre-reversal enhancement variability. IRI-2020 shows modest improvements over IRI-2016 in stability and correlation, yet both global models struggle to capture equinoctial and storm-time TEC extremes during the ascending solar cycle. These findings confirm that model performance over East Africa is strongly modulated by seasonal forcing and solar-cycle phase, underscoring the importance of region-specific validation. Integrating regional GNSS observations with enhanced electrodynamic parameterizations is crucial for improving ionospheric predictions and supporting reliable GNSS-based applications across the African sector.
The main types of energy losses experienced by ultrarelativistic electron-positron pulsar plasma in the upper atmosphere of a companion star are considered. These energy-loss mechanisms include ionization losses due to interactions with atoms of the medium, excitation losses associated with the energy transferred to plasma particles, losses resulting from the production of δ electrons, Cherenkov radiation losses, bremsstrahlung losses, synchrotron radiation losses, and inverse Compton losses. It is shown that the fastest component of the pulsar plasma can reach the top of the convection zone of the nearby companion star. The kinetic energy range of the plasma particles reaching the upper boundary of the convection zone corresponds to the energy range of the giant dipole resonance (GDR). As a result of the interaction between the pulsar plasma and the upper atmosphere of the companion star, localized regions of the photosphere and of the photosphere-convection zone boundary at different depths undergo nonuniform (spot-like) heating. This interaction may also produce neutron-rich isotopes, which are subsequently transported into the upper layers of the photosphere.
The ionosphere, a vital layer of Earth’s atmosphere, undergoes dynamic changes influenced by solar and geomagnetic activities. This study evaluates the Multi-Instrument Data Analysis System (MIDAS) for estimating ionospheric total electron content (TEC) in the data-scarce East African longitude sector, focusing on the 2015 St. Patrick’s Day geomagnetic storm. TEC maps from MIDAS are compared with those from the Global Ionospheric Map (GIM) and the AfriTEC neural network-based model, revealing temporal and spatial TEC variations during both quiet and storm conditions. Validation is performed using ground GPS station data. MIDAS and GIM successfully captured TEC enhancements during the storm, while AfriTEC, relying on quiet-condition data, showed limited responsiveness. GIM showed a high correlation coefficient (R = 0.99) with observational data, while MIDAS (R = 0.97) better captured transient diurnal variations. MIDAS outperformed AfriTEC in capturing transient TEC fluctuations, such as diurnal variations and storm-induced enhancements, though it showed occasional variability compared to GIM. The results demonstrate the potential of tomographic techniques in regional ionospheric studies, especially in data-scarce regions, and underscore the importance of model adaptability to geomagnetic variations.
The Earth’s magnetosphere acts as an energy- and direction-selective filter for high-energy charged particles and, thus, modifies the nonthermal radiation spectrum observed at the ground. The authors developed a physically motivated description of geomagnetic shielding in terms of an effective phase-space potential barrier, introduced the magnetospheric transmission function T(R, t), and formulated a criterion for the transition to the spectral-modulation regime by the magnetic field. To quantify T(R, t) and the temporal evolution of the cutoff rigidity Rc(t), Monte Carlo trajectory tracing in realistic magnetic-field configurations (IGRF internal field plus external current systems) is employed. Using the June 7–8, 2024, event, we compared the model with neutron monitor data (Apatity, Oulu, South Pole) and calibrated the linear parameterization Rc(t) = Rc,0 + αDst(t). It was found that α = (4 ± 0.6) × 10−5 GV/nT within the event window, implying very small cutoff variations (≲1.5 × 10−3 GV) under modest Dst changes (tens of nT). This separation of magnetospheric filtering from source-driven processes (acceleration/transport) suggests that the observed spectral evolution in this event is predominantly of solar/heliospheric origin.
