Kinematics and Physics of Celestial Bodies最新文献

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 R_c(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 R_c(t) = R_c,0 + αD_st(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 D_st 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.

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.

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.

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.

Understanding the complex interplay between solar wind parameters and geomagnetic storm dynamics remains a major challenge in space weather research. Our strategy applies a more comprehensive statistical analysis of the occurrence and intensity of geomagnetic storms than earlier studies. It examines both the individual and combined effects of solar wind velocity and density (V_sw, N_sw), as well as the southward component of the interplanetary magnetic field (IMF). We analyzed solar wind parameters such as V_sw and N_sw together with variable IMF parameters and storm-time D_st index values during Solar Cycles 24 and 25 (2008–2023). Our dataset includes all intense geomagnetic storms (D_st < –99 nT). For each event, we considered the solar wind and IMF conditions during the 3 days before and after the peak D_st value. Regression and correlation analyses showed that a sustained southward orientation of the IMF B_z component can trigger an intense geomagnetic storm even when the total IMF magnitude B_t remains relatively low. During the declining phase of Solar Cycle 24, the number of geomagnetic storms exceeded that observed during the cycle’s maximum phase, indicating that geomagnetic storm frequency does not always increase at solar maximum. During the minimum phase of Solar Cycle 24, no intense storms occurred despite high V_sw values. This finding indicates that elevated V_sw values do not necessarily produce intense geomagnetic storms. In addition, case studies of the April 24, 2023, and June 23, 2015, storms demonstrated that higher V_sw values do not always correspond to more intense storms, as compared with the event on March 17, 2015. These results suggest that numerous combinations of solar wind parameter behavior (N_sw, V_sw) and the IMF B_z component contribute to the potential intensity of geomagnetic storms. Furthermore, intervals of high V_sw values combined with a southward IMF B_z orientation can produce substantial magnetospheric disturbances that lead to intense geomagnetic storms. The obtained results emphasize the need to investigate multiple solar wind parameters in order to understand the drivers underlying geomagnetic storm activity.

The ionosphere, as a medium for radio wave propagation, remains highly sensitive to disturbances in geospace and largely governs the accuracy and reliability of communication, navigation, and radar systems. The most powerful drivers of disturbances in the Earth–atmosphere–ionosphere–magnetosphere (EAIM) and Sun–interplanetary medium–magnetosphere–ionosphere–atmosphere–Earth (SIMMIAE) systems are coronal mass ejections. These events restructure the coupling strength and interaction dynamics across the coupled system, generating spatiotemporal ionospheric disturbances that degrade the performance of satellite- and ground-based technologies. This study addresses the need to better understand both global and local ionospheric responses to intense, nonstationary energy inputs. We investigate ionospheric disturbances during a unique multistage magnetic storm by analyzing maps of the rate of total electron content index (ROTI) and the temporal evolution of global electron content (GEC). We identify three consecutive GEC maxima: approximately 2.20 GECU on November 4 at 22:00 UTC, followed by 2.22–2.25 GECU during the second half of November 5, as well as a deep minimum of 1.63 GECU on November 6. The resulting ionospheric plasma “saturation–depletion” cycle had an amplitude of 0.62 GECU. We observe the highest ROTI values (3.8–4.3 TECU/min) in the polar region (60°–75° N) at 04:00 UTC on November 4, while the strongest equatorial enhancement (3.6 TECU/min) occurred at 00:00 UTC the same day over South America. Strong disturbances (ROTI ≥ 0.9 TECU/min) expanded to geomagnetic latitudes up to ±40° between 18:00 UTC on November 5 and 06:00 UTC on November 6, coinciding with a sharp decline in GEC and a peak in the Akasofu parameter (ε_A ≈ 6.6 TJ/s). During the second day of the storm main phase, electrodynamic processes, including SAPS and substorms, dominated and produced a pronounced anticorrelation between reduced GEC values and enhanced ROTI activity. ROTI ≥ 1 TECU/min disturbances persisted for approximately 1 day after the D_st index recovered from –50 to –20 nT.

A comparative analysis of three ground level enhancement (GLE) events—GLE69 (January 20, 2005), GLE71 (May 17, 2012), and GLE72 (September 10–11, 2017)—using hourly integral proton fluxes from GOES (>10, >30, >60 MeV) and 5-min data from high-latitude neutron monitors (Apatity, Oulu, South Pole) is presented. Assuming a power-law integral spectrum, we reconstructed the temporal evolution of the effective spectral index and event amplitude, and extrapolated the spectra to GeV energies. The 2005 event is characterized by a very hard spectrum (γ ≈ 1.5) and a dominant GeV component, whereas the 2012 and 2017 events exhibit softer spectra (γ = 2.0–2.3) and significantly smaller ground-level amplitudes. To quantify the role of the magnetospheric state, variations of the geomagnetic cutoff rigidity R_c were parameterized using the D_st index. We find that cutoff modulation plays a minor role in GLE69, becomes comparable to the intrinsic event amplitude in GLE71, and approaches a controlling factor under near-threshold conditions in GLE72. Using the analytical scaling, it is demonstrated that the Earth’s magnetosphere may act as a nonlinear amplifier of transient particle fluxes, with the efficiency of this mechanism increasing for softer spectra. The results define a physical framework describing the transition between acceleration-dominated, mixed, and cutoff-modulated regimes, providing a basis for the classification and interpretation of GLE events.

This paper presents a detailed study of four eclipsing binary systems—TIC 142154041, TIC 1400824435, TIC 237278994, and TIC 140638648—using photometric data from the TESS space telescope. The authors classified the stars using a modern classification system based on the concepts of Roche lobes and Lagrange points. Their orbital periods and initial epochs were computed and corrected through O–C diagram analysis. For better understanding of their variability, the phase curves and light curves are also presented in the article. No significant period variations were observed for TIC 142154041 and TIC 1400824435. An O–C diagram for TIC 237278994 was constructed and quasi-periodic variability was found, with the primary and secondary extrema showing antiphase behavior. This pattern is consistent with the O’Connell effect. Using a Lomb-Scargle periodogram, a rough period of the O–C variability was estimated for each type of extrema and it was suggested that it may be related to star spots on the surface of one of the components. In addition, cases of the O’Connell effect for TIC 140638648 were identified. For TIC 140638648, the primary and secondary minima (using Fourier decomposition) were found to be in antiphase, confirmed by the dominance of the second harmonic (0.0751 mag) over the first (0.021 mag) with a phase shift of ({{delta }_{2}} = 3.098,{kern 1pt} {text{rad}}). These results show that O–C analysis of high-quality photometry can reveal effects like the O’Connell variability and harmonic patterns that are hard to notice based only on the light curve; this gives new data and clues about how star spots and surface activity shape the light curve of eclipsing binary systems.