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.
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 (Vsw, Nsw), as well as the southward component of the interplanetary magnetic field (IMF). We analyzed solar wind parameters such as Vsw and Nsw together with variable IMF parameters and storm-time Dst index values during Solar Cycles 24 and 25 (2008–2023). Our dataset includes all intense geomagnetic storms (Dst < –99 nT). For each event, we considered the solar wind and IMF conditions during the 3 days before and after the peak Dst value. Regression and correlation analyses showed that a sustained southward orientation of the IMF Bz component can trigger an intense geomagnetic storm even when the total IMF magnitude Bt 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 Vsw values. This finding indicates that elevated Vsw 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 Vsw 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 (Nsw, Vsw) and the IMF Bz component contribute to the potential intensity of geomagnetic storms. Furthermore, intervals of high Vsw values combined with a southward IMF Bz 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.
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 Rc were parameterized using the Dst 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.
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 (εA ≈ 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 Dst index recovered from –50 to –20 nT.
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 δ_2 = 3.098 1ptrad . 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.
The temporal and spatial evolution and flare activity of the active region (AR) NOAA 13 664 and its impact on space weather have been analyzed. This AR was one of the largest and most active solar regions observed in the current, 25th solar cycle. The region appeared in the southern hemisphere of the solar disk on May 1, 2024. Its structure changed very rapidly: the number of sunspots was growing and the AR area increased. On May 6, a new small AR NOAA 13 668 formed on the eastern side of the AR. During the day, these two regions merged, resulting in the formation of a large-scale sunspot group 13 664/13 668 with a unique complexity structure. Starting on May 7, it had a multipolar magnetic field configuration Hale class βγδ. On May 8, solar flares of magnitude X1.0, M8.7, and M9.9 occurred in the AR, triggering coronal mass ejections (CMEs). Several large CMEs reached Earth on May 10, causing an extreme geomagnetic storm with bright auroras observed up to 18.1° north latitude. The storm lasted from May 10 to 12, causing a variety of space weather effects, and was given the highest category of G5. On May 11, it peaked with –412 nT Dst index, making it the strongest storm since 2003. In total, during the active region’s first pass across the Sun’s disk from May 1 to 15, it produced 48 C-class, 55 M-class, and 12 X-class flares. On May 14, AR13664 passed beyond the solar disk edge, and it appeared on the side of the Sun facing Earth and was renumbered as NOAA 13 697 on May 29. It was smaller in size and consisted of fewer spots, but its magnetic component remained Hale class βγδ. From May 31 to June 1, the AR produced three X-flares: X1.1, X1.4, and X1.0. Each of them was accompanied by CMEs that reduced the power of shortwave transmissions on all frequencies below 30 MHz. On June 8, radiation from the M9.8 flare ionized the Earth’s upper atmosphere, causing a deep shortwave radio blackout in the western Pacific Ocean. The flare also produced a moderate S2 radiation storm. During its second pass across the Sun’s disk from May 27 to June 10, AR produced 127 C-class flares, 30 M-class flares, and six X-class flares. On June 24, AR13 664/13 697 returned to view for the third time. It was renumbered NOAA 13 723. AR had already fragmented to a fraction of its former size, but its magnetic field remained Hale class βγδ. On June 23, the AR produced an M9.3 flare, the CME from which caused a moderate shortwave radio blackout in Western Europe and Africa. On June 25, the AR produced another M1.0 flare. The number of sunspots in AR gradually decreased and, starting on June 29, it had a Hale class of β. In total, AR13 723 produced 23 C-class flares and two M-class flares during its third pass across the Sun’s disk from June 24 to July 6. On May 9, 2024, spectrograms of the X2.3 class flare were recorded with the Ernest Gurtovenko Horizontal Solar Telescope of the Main Astronomical Observatory in Kyiv. The motion direction features and changes in the line-of-sight velocities of chromospheric and photospheric matter in one of nodes flare were analyzed. It was concluded that they were associated with the passage of chromospheric condensation and waves that were formed during the pulsed release of energy as a result of magnetic reconnections in the upper layers of the AR atmosphere. By studying the evolution of this hyperactive region NOAA 13 664/13 697/13 723 and its impact on Earth in detail, the authors are improving the ability to predict abrupt changes in solar activity and warn of the extreme space weather events they cause, such as extreme geomagnetic storms that affect people’s life quality.
The radio spectra of pulsars are generally the power-law spectra shapes with a spectral index of approximately –1.6. But people have found that the spectra of some pulsars exhibit flat or steep spectra. Flat spectra refer to radio spectra with spectral indices ranging from –1 to 1, while steep spectra refer to radio spectra with spectral indices less than –2.5. We used the ATNF pulsar catalog and other literature to identify 239 flat-spectrum pulsars and 159 steep-spectrum pulsars, and conducted statistical analysis on the spatial position, magnetic field, spectral index, dispersion measure, and radio luminosity of these pulsars. The research results indicate that flat-spectrum and steep-spectrum pulsars are mainly concentrated near the galactic plane. The average spectral index of flat-spectrum pulsars is –0.62, with an average dispersion measure of 195.7 pc cm−3, while the average spectral index of steep-spectrum pulsars is –2.88, with an average dispersion measure of 96.5 pc cm−3. The characteristic age of flat-spectrum pulsars is also smaller than that of steepspectrum pulsars. There is a certain correlation between the dispersion measure of these two types of pulsars and their ages, rotation period changing rates, and surface magnetic fields, with the stronger correlations observed in flat-spectrum pulsars. In addition, there is a strong correlation between the dispersion measure of flat-spectrum pulsars and their rotational energy loss rates, while no such correlation has been found between the dispersion measure of steep-spectrum pulsars and their rotational energy loss rates. These correlations may indicate that the interstellar medium has a significant impact on the evolution process of flat-spectrum and steep-spectrum pulsars.
The ionosphere serves as the primary natural medium for radio-wave propagation over wavelengths ranging from millimeters to tens of thousands of kilometers. Understanding regular and irregular ionospheric processes, therefore, remains a critical scientific objective. At present, empirical models of wave disturbances that capture diurnal, seasonal, and longer-term global variations in their parameters do not exist. Developing such models requires consistent, continuous observations worldwide; however, because such coverage is unattainable, researchers typically focus on measurements obtained during characteristic geophysical periods, including the spring and autumn equinoxes and the summer and winter solstices. The present study follows this approach. This work reports the results of an analysis of diurnal and seasonal variations in electron density and associated wave disturbances in the ionospheric F2 layer during the 24th solar activity cycle. To monitor ionospheric conditions, we employed a custom-built digital ionosonde developed at the V. N. Karazin Kharkiv National University. After constructing time series of critical frequencies, the trend and the difference between the original series and the trend were calculated. We determined the electron density and its increment from the critical frequency of the ordinary component of the reflected signal. Across all seasons, a dominant oscillation with a period of 140–250 min, an amplitude of (3.8–11.4) × 1010 m–3, and a relative amplitude of 0.09–0.23 appeared in the F2 layer of the ionosphere. Depending on the season, this oscillation persisted for up to 12 h, whereas oscillations at other periods showed substantially smaller amplitudes. Through a comparative analysis of diurnal and seasonal variations in F2-layer electron density and its quasi-periodic disturbances, we established quantitative parameters that characterize these variations.
In this study, we examine the convergence behavior of the Newton–Raphson basins of convergence in relation to the equilibrium points serving as attractors within the framework of the pseudo-Newtonian planar circular restricted four-body problem. This model accounts for the effects of both radiation pressure and the presence of a circular asteroid belt. Our focus lies on determining the positions and assessing the stability of these equilibrium points as the transition parameter, denoted by ϵ , is varied across the range [0, 1]. By employing a multivariate form of the Newton–Raphson iterative algorithm, we draw the basins of convergence across selected two-dimensional planes. A thorough numerical analysis is carried out to illustrate how changes in the transition parameter influence the structure and geometry of these convergence regions. Furthermore, we examine the relationship between the spatial extent of the attraction basins and the number of iterations needed to reach convergence. The results suggest that the behavior of these regions is complex yet deeply engaging, offering rich insights into the dynamics of the system.
Quasi-periodic oscillations (QPOs) in the X-ray light curves of accreting black holes provide a powerful, albeit complex, probe into the strong-field regime of General Relativity. Traditionally, constraints on black hole spin from QPOs have relied on phenomenological or relativistic precession models, each burdened by systematic uncertainties and observational limitations. In this work, we explore a complementary approach grounded in data-driven inference: using synthetic QPO datasets generated from theoretically motivated spin-frequency relations, we apply Gaussian Process Regression (GPR) to recover the underlying spin parameter of a stellar-mass black hole. Our method is tailored for computational accessibility, requiring minimal training data, no large-scale simulations, and modest hardware while retaining physical interpretability. The GPR model successfully reconstructs the spin parameter from noisy QPO signals with high confidence, highlighting the potential of non-parametric machine learning in extracting astrophysical parameters where traditional likelihoods fail or become intractable. We discuss the implications for future observations from next-generation X-ray observatories, and advocate for broader use of Bayesian non-parametric techniques in theoretical astrophysics. Our work serves as a prototype for applying modern statistical tools to long-standing theoretical questions in black hole physics, even in resource-constrained research settings.
This study investigates the ionospheric response to the April 2023 geomagnetic superstorm by analyzing Total Electron Content (TEC) variations over equatorial and low-latitude regions. TEC data derived from GNSS were processed and compared with estimates from the NeQuick model. Geomagnetic indices (Dst, AE, Kp), magnetometer data, and thermospheric O/ . -0emN_2 ratios from GUVI/TIMED observations were used to track storm-time ionospheric changes. TEC was computed from dual-frequency GNSS signals, corrected for biases, and validated using statistical metrics such as RMSE and the Pearson correlation coefficient (R), which ranged from 0.66 to 0.96 across stations and storm phases. The study found both positive and negative storm-time ionospheric effects, with significant regional differences. A notable depletion in the O/ . -0emN_2 ratio corresponded with TEC decreases, emphasizing thermosphere-ionosphere coupling during disturbed periods. This integrated observational and model-based approach highlights complex ionospheric dynamics triggered by geomagnetic superstorms and the value of multi-instrument analysis in space weather research.
Solar storms, accompanied by flares, coronal mass ejections, and the generation of high-speed solar wind streams, cause a set of physical processes in the geospace environment and on Earth. The collective manifestation of these processes is referred to as a geospace storm. Geospace storms are associated with intense disturbances of the geomagnetic field, the ionosphere, the upper atmosphere (thermosphere), the geoelectric field of magnetospheric-ionospheric-atmospheric origin, the troposphere, and telluric currents. All these disturbances are closely interconnected. Therefore, a geospace storm can be understood as a synergistically interacting system of magnetic, ionospheric, atmospheric, and electrical storms. Every geospace storm is a unique phenomenon. In addition to general patterns, each storm has its own individual characteristics. For this reason, the study of each new storm remains a relevant scientific task. An interesting event occurred in early January 2015: a recurrent sequence of three geomagnetic storms over the course of 1 week. The purpose of this study is to describe the features of fluctuations in the level and spectral composition of the geomagnetic field during these three successive storms from January 2 to 8, 2015. The core of the magnetometric system located at the magnetometric observatory of the V. N. Karazin Kharkiv National University (geographic coordinates: 49.65° N, 36.93° E) is the IM-II induction magnetometer-fluxmeter. It offers high sensitivity (0.5…500 pT for periods of 1–1000 s, respectively). The signal output from the magnetometer, initially in relative units and accounting for the instrument’s amplitude-frequency characteristics, is first converted into absolute units (in nanoteslas). Time series of the amplitudes of the horizontal components of the geomagnetic field are then constructed. Subsequently, a system spectral analysis is performed across the period range of 1–1000 s. Analysis of the three recurrent geospace and magnetic storms observed near the maximum of the 24th solar activity cycle revealed the following. During January 2/3, 4/5, and 7/8, 2015, severe magnetospheric storms occurred, with corresponding powers of 180, 240, and 530 GJ/s and energies of approximately 1920, 4800, and 10 500 TJ, respectively. The magnetic storms during January 2/3, 4/5, and 7/8, 2015, were classified as rather moderate, moderate, and strong, with associated energies of 2.5, 3.1, and 4.9 PJ, and power P1 of approximately 200, 50, and 600 GW. At the same time, the P2 power reached 32, 12, and 23 GW, respectively. During January 2/3, 4/5, and 7/8, 2015, the fluctuation level of the horizontal components of the geomagnetic field increased from 0.5 nT by factors of approximately 4–5, 2–3, and 8–10, respectively. These increases correlated with the average power of the geomagnetic storm during its main phase. During the magnetic storms, fluctuations in the geomagnetic field were dominated by components with periods of 700–1000 s. Oscillations with periods of 140–200 s had slightly lower amplitudes, and those with periods of 40–50 s were the weakest.
A comparative analysis of two methods for determining electric current density in the near-Earth magnetospheric plasma is presented: the multispacecraft curlometer technique and the particle-based (kinetic) approach relying on plasma moments. The study is based on data from the Magnetospheric Multiscale Mission (MMS) for six magnetic reconnection events in Earth’s magnetotail observed between 2019 and 2024. It is shown that the results of both methods agree well under conditions of stable spacecraft configuration and the absence of radiation contamination in the measurements. The particle-based approach systematically yields overestimated current densities, likely due to locally enhanced ion density near the spacecraft. Spectral analysis reveals that particle-derived data exhibit increased noise levels at frequencies above 1 Hz. The obtained results are important for refining our understanding of energy-dissipation mechanisms and the dynamics of magnetic reconnection processes.
Solar eclipses (SEs) are accompanied by both regular and a number of irregular effects as well as individual effects inherent in a particular SE. The following questions remain unanswered: can there be effects prior to an SE? How long do they last after the end of an SE? Do they appear on the night side of the planet? What effects occur in the magnetically conjugate region? What is the role of dynamic processes and geophysical fields in the interaction of subsystems in the Earth–atmosphere–ionosphere–magnetosphere system during an SE? These questions need to be addressed. The aim of this paper is to present the results of observations of temporal variations of total electron content (TEC) in the ionosphere over China obtained using Global Navigation Satellite System during the SE and reference days. The low-latitude ionosphere has certain features that could not fail to manifest themselves in the effects of the SE. Estimation of the ionospheric response to the annular SE was performed using recordings of GPS satellite signals obtained on dual-frequency receivers. The error of the TEC calculation technique used in the study does not exceed 0.1 TECU. To obtain acceptable results, the mutual motions of the TEC measurement point, lunar shadow, and Earth’s rotation were taken into account. The ionospheric effect of the SE, which consisted in a significant reduction in TEC, was confidently observed at all five stations and for all seven satellites. It was found that the deficit of TEC clearly followed the maximum magnitude value of the SE. The maximum TEC depletion reached 6–7 TECU at a magnitude of Mmax ≈ 0.976–0.986. In this case, the relative TEC depletion was 35–37
The influence of turbulent mixing on the vertical profile of electric-field intensity in the atmospheric boundary layer is investigated. The effects of meteorological conditions and thermodynamic stratification on the electrical conductivity and structure of the electric field are analyzed. It is shown that the turbulent diffusion coefficient K(z), which determines the vertical transport of electric charge, can vary significantly with altitude depending on atmospheric stratification. Several models for describing K(z) are considered, including empirical and theoretically grounded approaches (the Monin–Obukhov model). Calculations based on radiosonde data from the Norderney station (WMO 10 113) for the winter and summer seasons have made it possible to trace seasonal differences in the distributions of the turbulent diffusion coefficient and electric-field intensity. Additionally, data from station 2TDJJ8J aboard the research vessel Polarstern RV, which operates near the Earth’s poles during polar summer, are analyzed. This makes it possible to compare changes in the electric field and the turbulent diffusion coefficient for high-latitude regions of both hemispheres. The similarity of exponential field decay with altitude is established, and differences indicating regional characteristics of atmospheric stratification are identified.
Modern experimental and theoretical studies of atmospheric gravity waves (AGW) indicate the need for a nonlinear consideration of these processes. First of all, this is due to the exponential growth of the amplitudes of gravity waves with height in the atmosphere, which significantly limits the possibility of applying the linear theory. In the work, analytical solutions of the system of nonlinear equations describing the propagation of atmospheric gravity waves in the isothermal atmosphere were obtained. To find the solutions, nonlinear equations obtained earlier in the model of two-dimensional motion of an ideal atmospheric gas in the Boussinesq approximation were used. The nonlinear components in these equations have the form of Poisson brackets. We found the solutions of the nonlinear equations in the form of plane waves. For this type of solution, the Poisson brackets are converted to zero. This approach allowed us to obtain analytical solutions that describe various types of nonlinear gravity waves in an isothermal atmosphere. In the linear theory of AGW, solutions in the form of plane waves are in the assumption of small amplitudes of perturbations. Unlike the linear consideration, the solutions of the nonlinear equations that were obtained do not have restrictions on the amplitude. Within the framework of the specified simplifying assumptions, solutions were obtained from the system of nonlinear equations for: (1) freely propagating internal gravity waves, (2) horizontal (evanescent) atmospheric gravity waves, and (3) important special cases of evanescent wave modes. The energy conditions for the realization of the obtained types of wave perturbations in an isothermal atmosphere were analyzed. The specified nonlinear solutions (1)–(3) are nondivergent since a system of nonlinear equations was used when obtaining them, written in the assumption of zero velocity divergence. At the same time, in the linear theory, the assumption of zero velocity divergence singles out only one f-mode from the entire AGW spectrum. That is, the application of nonlinear theory when considering gravity waves, even with significant simplifications in the original system of nonlinear equations, significantly expands the class of wave solutions in comparison with the linear theory.
