Journal of Geophysical Research: Space Physics最新文献

The formation process of the F3 layer at sunrise in the middle latitudes is newly investigated using data from the Mother's Day geomagnetic storm of 10–11 May 2024. Ionosonde, Fabry-Perot Interferometer (FPI), satellite data, and model simulations of Equatorial Electric Field for India, South-East Asia-Australia, and Japanese sectors are utilized. The F3 layer was recorded by Ionosondes at Japanese mid-latitude stations during 19 UT–21 UT, which coincided with the local Sunrise time. Over Perth (Australia), Wuhan (China), and Ahmedabad (India), formations were delayed at 22 UT–23 UT. The COSMIC vertical profiles showed enhanced F2 layer altitude after 19 UT, and confirmed the formation of additional ionospheric stratifications above the F2 layer. The thermospheric winds measured by FPI at northern mid-latitude and southern low-latitudes indicated strong equatorward winds in both hemispheres starting around 18:30 UT. The analysis revealed that dawn-time F3 layer stratifications in middle latitude were manifestations of residual nighttime F layer, which was raised to higher altitude by the equatorward winds, even as a new weak F2 layer was formed below by photo-ionization. The reduction in thermospheric O/N₂ caused the F3 layer at higher altitudes to survive and remain stronger than the F2 layer for a considerable time after sunrise. In contrast, the low-latitude F3 layer was formed by vertical drift induced by the electric field, when an IMF-Bz transition resulted in an eastward penetration electric field pulse in the dawn sector. At Perth in the southern hemisphere, both mechanisms were effective in the formation (wind) and sustenance (electric field) of the F3 layer.

The F10.7 and F30 solar indices are the solar radio fluxes measured at wavelengths of 10.7 and 30 cm, respectively, which are key indicators of solar activity. F10.7 is valuable for explaining the impact of solar ultraviolet (UV) radiation on the upper atmosphere of Earth, while F30 is more sensitive and could improve the reaction of thermospheric density to solar stimulation. In this study, we present a new deep learning model, named the Solar Index Network, or SINet for short, to predict daily values of the F10.7 and F30 solar indices. The SINet model is designed to make medium-term predictions of the index values (1–60 days in advance). The observed data used for SINet training were taken from the National Oceanic and Atmospheric Administration as well as Toyokawa and Nobeyama facilities. Our experimental results show that SINet performs better than five closely related statistical and deep learning methods for the prediction of F10.7. Furthermore, to our knowledge, this is the first time deep learning has been used to predict the F30 solar index.

We investigate the injection and transport of energetic particles from the Earth's plasma sheet into the inner magnetosphere during the three consecutive substorms that occuurred on 7 September 2017. Using coordinated observations from the MMS, LANL, and Van Allen Probes spacecraft, we track the evolution of ion and electron fluxes from the mid-tail to the inner magnetosphere. Using the dipole field approximation to trace particle drift orbits from LANL satellites at geosynchronous orbit, we identified the equatorial injection region to extend from ∼2000 to ∼0400 MLT. Subsequently, the injected particles were detected further earthward at Van Allen Probes (L ∼ 4), particularly on the dayside. The multi-point data reveal that stronger substorms injected ions over a wide energy range (1–200 keV) with significant dayside penetration, while weaker substorms resulted in narrower energy injections (5–30 keV). Back-tracing the proton drift paths further, calculated using the electric and magnetic fields from the MHD simulation, indicates that convection and adiabatic drifts alone are insufficient to account for the ion injections observed at the Van Allen Probe locations. This suggests that non-adiabatic processes, such as substorm-driven impulsive electric fields, are required for particles to reach the same regions. In contrast, electrons at Van Allen Probes lacked clear injection signatures, suggesting the influence of localized electric fields. These results highlight the spatiotemporal complexity of substorm injections and emphasize the value of multi-point observations and simulations to understand particle transport in the inner magnetosphere.

We propose an approach to simulate ultra-wideband (UWB) electromagnetic pulse (EMP) propagation in the ionosphere with magnetic field-aligned irregularities of plasma density based on Monte Carlo technique. This approach considers propagation of a nanosecond EMP by ray trajectories in the frequency domain, which allows one to analyze the role of scattering effects for lower and higher harmonics of the pulse. Parameters of the irregularities used in the simulations are chosen close to those of artificial ionospheric turbulence (AIT) density striations stimulated by high-frequency (HF) heating facilities. The employed technique provides a possibility to compare the effects of dispersion and scattering on the waveform of bipolar nanosecond EMP for various parameters of ionospheric plasma and its disturbances. In the presence of 10-m scale, 10-percent level density striations, we show that lower frequencies are most responsible for the EMP waveform transformation due to the plasma dispersion, and are scattered away from the initial propagation direction, while higher frequencies experience minor dispersion and are less scattered. The influence of AIT-type striations on the straightforward EMP delay and its broadening in the time domain is analyzed compared to the EMP propagation in uniform plasma. Preliminarily, the effects of AIT-type striations on EMP characteristics seem to be weak in the main part of its frequency spectrum, even for strong (non-realistic) plasma density depletions of up to 50%.

State parameter profiles in the equatorial topside ionosphere were measured in June, 2023, and late July and early August, 2025, at the Jicamarca Radio Observatory. The measurements combined multiple radar pulsing schemes and analysis methods. In 2025, for the first time, plasma drifts were measured concurrently with electron densities, electron and ion temperatures, and ion composition by exploiting a new electronic beam steering capability. Significant quiet-time day-to-day variability is evident across all measurements. In this study, variability in the vertical drifts is considered as a source of variability in the other plasma state parameters. Topside temperatures and the midday temperature depression in particular are examined for sensitivity to vertical drifts. While predictions obtained from the SAMI2-PE model, which includes energetic electron transport, exhibit reasonable agreement with observations overall, they do not account for topside variability. Some limitations of the measurements and the model along with strategies for improvement and further study are discussed.

Geomagnetic indices can be used to quantify variations in geomagnetic activity caused by Sun-Earth interactions across the magnetosphere and ionosphere. The global Kp index is widely used as a global geomagnetic indicator, but it is based mostly on the Northern Hemisphere with no contributions from South American observatories. As a result, regional features such as the South American Magnetic Anomaly (SAMA) are not represented. To address this limitation, the regional Ksa index was developed using magnetometer data collected from the Embrace Magnetometer Network (Embrace MagNet), which consists exclusively of South American stations. This study analyzes data from Ksa and Kp and introduces two additional hybrid indices, Kp* and Ksa*. The Kp* index uses global data from the International Real-time Magnetic Observatory Network processed with the Embrace MagNet algorithm, while the Ksa* index applies the Finnish Meteorological Institute algorithm to South American data. The analysis was conducted over the year 2020, a period characterized by low solar activity, to investigate the behavior of the indices under quiet conditions during three seasonal periods: December solstice, Equinoxes, and June solstice. Pearson correlation coefficients were computed to evaluate the relationships between the indices. The results revealed significant discrepancies between indices derived from different data sets, even when processed with the same algorithm. These differences emphasize the impact of regional geomagnetic phenomena such as the SAMA and Sq current variability.

The International Space Station (ISS)-hosted Neutron Star Interior Composition Explorer (NICER) aims to observe distant astrophysical sources. As its field-of-view passes through Earth's magnetosphere, NICER detects local magnetospheric X-ray emissions. While monitoring a distant astronomical source, NICER detected an unexpected X-ray signal. This signal contained distinct lines at 0.537 and 0.404 keV, near the K-alpha lines of oxygen and nitrogen, respectively. These emissions have been proposed to be generated locally either by solar wind charge-exchange, auroral X-ray emissions, or photoionization/photoexcitation. To differentiate between these sources, X-ray spectral characteristics were put into the context of particle precipitation, cusp boundary models, solar wind parameters, and geomagnetic activity. To account for variations in the line-of-sight and the magnetospheric conditions, observations from NICER utilized the same astrophysical target on multiple different dates. The findings are most consistent with a combined source composed of auroral emissions and solar wind charge-exchange (SWCX). The prominent nitrogen and oxygen lines support the auroral component, while the line-of-sight's passing through the cusp and the broadness of the oxygen feature suggest a contributing component of SWCX. These emissions are positive detections of local (within Earth's magnetosphere) X-ray generation mechanisms.

The atomic oxygen greenline dayglow emissions in Earth's upper atmosphere exhibit a distinct dual-peak structure, at altitudes in the range of 100–105 km and 130–145 km. These peaks are attributed to different production mechanisms, and their temporal behavior is expected to provide insights into the nature of dynamics prevalent at these altitudes. Ground-based and satellite-based measurements provide integrated information that prevents independent quantification of the contribution of emissions corresponding to these altitude regions. With the availability of a ground-based high-resolution spectrograph, MISE, capable of retrieving the daytime green line airglow emission and a collocated Digisonde operating simultaneously in Ahmedabad, there exists a unique possibility to quantify and characterize the greenline dayglow contribution in lower and upper altitude regions in terms of diurnal, altitudinal, and seasonal behavior. Investigations carried out in the present study reveal that in the lower altitude region, the emissions are strongly dependent on the electron content, underscoring the dominance of photochemical processes. In contrast, the emissions in the upper altitude region are found to be significantly influenced by meridional winds in addition to the electron content. Further, the contribution of emissions in the upper altitude region is found to be larger than that in the lower one at all times of the day and is found to vary in the range of 1.8–2.4, depending on the season. These results reveal the intriguing altitude-varying nature of the upper atmosphere in the range of 90–160 km, the details of which are presented in this work.

This study demonstrates the feasibility of applying Physics-Informed Neural Networks (PINNs) to reconstruct the spatial and temporal evolution of two-dimensional magnetohydrodynamic (MHD) reconnection structures from limited in situ observational data. By embedding the complete set of MHD equations into the loss function, the reconstructed solutions naturally satisfy the governing physical laws. The reconstruction accuracy is systematically evaluated by varying the number, spatial distribution, and sampling interval of observation points. The analysis reveals that placing observation points both upstream and downstream of the plasmoid significantly enhances reconstruction accuracy, highlighting the importance of capturing both the early-time evolution near the $��X�$-point and the well-developed downstream structures. These findings demonstrate the potential of PINNs as a powerful tool for recovering large-scale MHD reconnection structures from sparse data, while also providing practical guidance for the design and operation of future multi-satellite observation missions.

When particles from the radiation belts impinge on the atmosphere, they can be absorbed into the atmosphere or deflected back into the magnetosphere. The deflection of particles back into the magnetosphere is known as backscatter, and it is a key link connecting the atmosphere to the magnetosphere—involving collisions with atmospheric neutrals, magnetic mirroring, the production of secondary emissions, and energy transfer from the particle to the atmosphere. Backscatter is both a feedback mechanism to magnetospheric precipitation drivers and an indirect measure of atmospheric energy absorption, making it an important process to quantify and understand. In this work, we use data from the Electron Fields and Losses INvestigation (ELFIN) satellites to quantify backscatter rates. We find that backscatter rates vary between $��\sim �5�\%�$ during periods of loss cone filling and $��\sim �90�\%�$ during periods without loss cone filling. We then compare the ELFIN backscatter data to the results of an updated and improved Monte Carlo-based simulation and find excellent agreement with ELFIN-measured backscatter rates. Finally, we use our improved Monte Carlo model to characterize the pitch angle and energy dependence of backscatter and the pitch angle distributions of backscattered electrons, finding results consistent with previous modeling efforts.