The Potential Field Source Surface (PFSS) extrapolation is a method for estimating the large scale coronal magnetic field from photospheric magnetograms. The source surface serves as the outer boundary of its solution domain, and is typically a spherical surface. An appropriate source surface radius (R_ss) enables more accurate identification of the coronal magnetic field topology and estimation of the open flux, thereby potentially enhancing the accuracy of space weather modeling. We prove the well-posedness of the PFSS forward problem and establish the existence and uniqueness of the optimal source surface by combining compactness of the admissible set with continuity of the objective functional. The objective functional is the mean squared error (MSE) between PFSS extrapolation and Parker Solar Probe (PSP) radial magnetic field measurements after Parker spiral backmapping and radial scaling for Encounters 1-19. The optimization algorithm is validated with an analytical solution, and Advanced Composition Explorer (ACE) in situ measurements are used as an independent cross-validation dataset. Additional evaluation metrics and Pareto analysis are used to identify the dominant metrics between open flux and polarity prediction accuracy. Our results show that the optimal R_ss derived from the algorithm generally increase from solar minimum into the ascending phase of solar cycle 25. The optimized solution improves open flux agreement while preserving or improving polarity prediction accuracy relative to 2.5R_s. The Pareto frontiers show a transition for dominant metrics from open flux during solar minimum to polarity prediction accuracy during the ascending phase.

Solar eruptions are driven by the rapid release of free magnetic energy accumulated in the corona. While a recent simulation by Jiang et al. established a fundamental mechanism for eruption initiation, it was limited by unrealistically weak magnetic fields and the absence of flux emergence. We overcome these limitations by developing a hybrid boundary driven magnetohydrodynamic (MHD) simulation that couples flux emergence with shear injection under realistic magnetic field strengths. The Boris correction to the MHD equations is employed to enable the magnetic field to reach observational values (similar to 2000 G) in the plasma with typical coronal density. A hybrid electric field driving strategy is designed: the variation of the magnetic flux is controlled by an inductive electric field component, while shear and free energy are injected via a non-inductive part caused by photospheric rotational flows. The simulation encompasses the complete sequence from flux emergence to eruption, showing that the photospheric rotational flow progressively shears the emerging arcade, forming a sigmoidal structure above the polarity inversion line. Ultimately, a thin current sheet forms, where reconnection sets in, creating a rapidly expanding flux rope. This consistency with previous simulations confirms the robustness of the eruption mechanism under more realistic parameters.

The deployment of deep learning models directly onboard satellites is emerging as a promising approach to real-time space-weather monitoring. However, applying this paradigm to solar flare forecasting introduces three challenges: limited computational resources, the susceptibility of onboard weight storage to radiation-induced multiple-bit upsets (MBUs), and variations in power availability across orbital phases. In this work, we propose N-Slim, a network slimming framework that addresses all three challenges through a novel N-balanced structured channel pruning method. N-Slim proceeds through three phases: baseline pretraining, sparsity learning, and iterative slimming. The core idea of N-balanced pruning is to partition each layer’s output channels into non-overlapping groups of width N and distribute retained channels approximately uniformly across groups, preventing retained channels from clustering together and limiting the number of active channels that a single MBU event can simultaneously corrupt. By applying this method across a geometric sequence of group sizes, N-Slim generates a portfolio of subnets spanning a range of channel pruning rates and inference costs, providing a set of candidate models that could, in principle, support power-adaptive inference during different orbital phases. N-Slim was evaluated on VGG, ResNet, and DenseNet using solar active-region magnetogram images from the Solar Dynamics Observatory (SDO). Experiments demonstrate that N-Slim achieves competitive or improved forecasting accuracy across a range of channel pruning rates, with substantial MBU robustness gains on ResNet and DenseNet and comparable robustness to standard pruning on VGG.

Interplanetary scintillation (IPS) tomography is a key technique for probing the three-dimensional structures of the inner heliosphere and for space weather forecasting. In this paper, we quantify how the performance of an IPS-driven magnetohydrodynamic computer-assisted tomography model depends on the coverage of the input IPS observations. Using the ISEE IPS data during Carrington rotation 2075 in 2008 as the sole IPS constraint, we reconstruct the density and speed of the ambient solar wind. Comparison with OMNI in situ data at 1 au shows that three corotating interaction regions (CIRs I–III) are reasonably reproduced. While the CIRs II and III agree well with observations, CIR I arrives nearly 4 days earlier and exhibits a much stronger density compression than measured. Tracing the 3D CIR structures back toward the Sun reveals that the discrepancy arises from sparse IPS data coverage over the southern hemisphere. The lack of IPS observational constraints for the source region of the CIR I causes the southern fast solar wind to artificially protrude into the heliospheric equator, producing an overly wide and strong CIR. Our results indicate the critical role of observation coverage in IPS tomography and highlight the benefits of coordinated IPS observations within the Worldwide IPS Stations (WIPSS) network.

Coronal mass ejections (CMEs), one of the most significant and intense solar eruptive activities, exert profound impacts on Earth and the interplanetary space environment. Consequently, automatic detection and tracking of CMEs have become crucial tasks for mitigating their impacts. Considering the complexity of manually annotating regions of CME on coronagraph images and the presence of anomalous data, we have developed a new automatic CME tracking system that does not rely on pixel-level annotations and can handle obvious data errors. The proposed system consists of three stages: error area segmentation and inpainting, CME segmentation, and CME tracking. First, we apply a weakly supervised semantic segmentation framework, Token Contrast, to the tasks of CME and error area segmentation. Subsequently, we propose a CME inpainting model, Mask-Aware Recurrent Feature Reasoning, to restore erroneous regions in running-difference coronagraph images. Then, we employ Kalman filters to track the evolution of CMEs and extract their kinematic parameters. All deep learning models in our system are trained on the dataset without pixel-level labels, which can be easily constructed from publicly available CME catalogs. Moreover, by comparison with existing catalogs and methods, we demonstrate that the proposed system is reliable in providing CME initial kinematics, facilitating studies on the origin and propagation of CMEs.

Identifying universal, topology-independent thresholds in the coronal magnetic fields at the onset of solar eruptions is crucial for physics-based prediction of eruptions. To this end, we systematically analyze the evolution of magnetic energy and helicity in 12 high-fidelity 3D magnetohydrodynamic simulations where eruptions are triggered by magnetic reconnection. The simulations encompass a comprehensive parameter space, including bipolar and quadrupolar configurations, sheared arcades, preexisting flux ropes, and various photospheric driving motions. We find that the ratio of current-carrying helicity to total relative helicity (Hj/Hr) exhibits a remarkably consistent threshold of 0.38 +/- 0.04 at eruption onset across all cases, with a coefficient of variation of only similar to 10%. This threshold specifically characterizes the critical conditions at eruption onset and is largely independent of the subsequent temporal evolution, making it the most robust eruptivity indicator identified. In contrast, other normalized helicity and energy metrics show greater scatter. Crucially, we further find that Hj/Hr does not necessarily achieve its peak at the eruption onset time and its posteruption evolution diverges based on the magnetic topology. It continues to increase in bipolar configurations due to tether-cutting reconnection, which transforms sheared arcades into erupting current-carrying magnetic flux, but decreases in quadrupolar configurations as breakout reconnection peels off the erupting flux. These results highlight the helicity ratio as a promising and consistent eruptivity indicator and provide new insights into its dynamic evolution due to different reconnections.

Unmanned Aerial Vehicles (UAVs) are becoming integral to the emerging low-altitude economy, operating primarily below 3,000 m for applications such as logistics, inspection, precision agriculture, and urban air mobility. The safe and reliable operation of UAVs depends critically on communication, navigation, and surveillance (CNS) systems, which provide command and control, precise positioning, and situational awareness. Although UAV hardware is largely protected from direct radiation hazards by the Earth's atmosphere and magnetosphere, space weather can still indirectly disrupt operations by affecting CNS performance. Solar flares, geomagnetic storms, and ionospheric irregularities can degrade communication links, induce navigation errors, and compromise surveillance reliability, posing risks to flight safety and operational continuity. This commentary highlights these vulnerabilities, reviews mechanisms through which space weather impacts UAV systems, and emphasizes the importance of integrating space weather awareness into UAV traffic management and system design to support a resilient low-altitude economy.

Abstract The May 2024 geomagnetic storm, one of the most intense events of Solar Cycle 25 to date, caused widespread disruptions in aviation operations, particularly for polar and high‐latitude routes. This study quantifies the operational and economic impacts of the storm on 12 selected transatlantic flights between North America and Europe. Using Automatic Dependent Surveillance‐Broadcast data and atmospheric reanalysis products, we identify significant rerouting to lower‐latitude corridors to mitigate risks of high‐frequency communication outages and satellite navigation degradation. Results indicate the storm increased average flight distance by 5.2%, cruise‐phase fuel consumption by 5.1%, and airborne time by 1.5%. Average departure delays rose by 15.1 min, while average arrival delays increased by 14.6 min. The estimated economic loss, accounting for additional fuel costs, time delays, and environmental impacts, was approximately USD 8,582 per flight. These findings highlight the operational vulnerabilities of high‐latitude flight corridors during space weather events and stress the importance of proactive space weather risk mitigation strategies for global aviation.

Understanding the propagation of coronal mass ejections (CMEs) through interplanetary space is essential for space weather forecasting. Due to observational limitations, measurements of the photospheric polar magnetic fields remain highly uncertain, and their influence on CME propagation in the heliosphere is still poorly quantified. In this study, we systematically investigate how variations in the photospheric polar magnetic fields affect the Sun-Mars propagation of the 2021 December 4 CME using numerical simulations. The results show that stronger polar fields modify the background solar wind, producing higher plasma density, enhanced magnetic field strength, a flattened heliospheric current sheet, and weakened high-speed streams in the ecliptic plane. These changes markedly slow the CME's radial propagation and inhibit its lateral and radial expansion, leading to notably delayed arrivals at BepiColombo and MAVEN/Tianwen-1. Quantitatively, an enhancement of the polar magnetic fields with a peak value of 6 G at the pole decreases the mean propagation and expansion speeds by roughly 200 km s-1 and halves the CME volume. Force analysis reveals that strengthening the polar fields produces only minor changes in the internal force balance of the CME, where the thermal pressure gradient force dominates over the Lorentz force, while it strongly affects the forces acting on the CME surface. At large heliocentric distances, the magnetic pressure of the background solar wind becomes comparable to or even exceeds the aerodynamic drag force, producing a strong confining effect that hinders the CME's motion.

Interplanetary scintillation (IPS) phenomenon behaves as twinkling of a compact radio source due to scattering in the solar wind. Here we report the first identification of IPS signal by a new parabolic dish antenna with its diameter of 30 m, observed on 2024 March 1. The radio source of 3C446 at solar elongation of 6.4° was targeted during its 5 minute transit across our antenna beam at ArQi (115.13°E, 44.73°N). Our receiver is characterized as simultaneous measurements of dual polarizations from 3C446 emission, integrated over a 40 MHz bandwidth around its central frequency of 1.4 GHz. The horizontally and vertically polarized components, though independently and simultaneously measured, show a strong correlation in terms of both time-series and power spectral analyses. Using a spectra-fitting method on basis of the classic IPS theory, the solar wind speed in our observation case is inferred to be 283 km s ^−1 . Such a solar wind speed inferred at the piercing point of 24 solar radii along our IPS ray-path reaffirms the interplanetary diagnostic capability of ground-based IPS technique. Our first-light IPS observation at ArQi represents a significant advance in the ongoing commissioning phase of our IPS-dedicated telescope facility within the Chinese Meridian Project–Phase II.

Space weather disturbances can degrade satellite navigation accuracy, posing operational challenges for Unmanned Aerial Vehicle (UAV) missions that require precise path planning. This study investigates the impact of space weather-induced horizontal navigation errors on UAV flight distance and energy consumption through a simulation-based analysis. Sixteen scenarios are evaluated by combining four flight altitudes (30, 60, 90, and 120 m) with four levels of satellite navigation errors (5, 10, 30, and 50 m). Simulation results indicate that larger satellite navigation errors increase flight distance through cumulative route deviations. In contrast, higher flight altitudes reduce flight distance by enabling more direct routes, though at the cost of increased energy consumption during ascending and descending phases. Total energy consumption, comprising ascent, descent, and horizontal phases, reflects a trade-off. Specifically, higher altitudes increase ascending and descending energy but reduce horizontal energy due to shorter flight distances. These findings highlight the dual influences of navigation accuracy and altitude on UAV operational efficiency under disturbed space weather conditions. This study provides critical insights for urban air mobility and low-altitude traffic management systems, emphasizing the need for adaptive altitude selection and resilient navigation strategies to maintain safety and efficiency during space weather events.

Solar flares, coronal mass ejections (CMEs) and enegertic particles, etc., are the driving sources that may cause catastrophic space weathers. It is desirable to obtain information of solar eruptions like flares and CMEs, etc., propagating from the Sun to the near-Earth space. The Chinese Meridian Project includes the interplanetary scintillation (IPS) telescopes to investigate the structures and properties of the solar wind throughout the inner heliosphere. From IPS observations one can obtain disturbance information on CME speeds and thus on CME arrival times well off the Sun-Earth line. When combined with modeling techniques and/or in situ data, other parameters such as CME masses can also be obtained, along with CME propagation directions and arrival times. Therefore, a radio telescope array with three 140 m 40 m parabolic cylinder antennas at the main site and two 30 m antennas at two subsites about 200 km away from each other, featuring a multi-site array with the highest sensitivity dedicated to IPS observations in the world, has been supported as a major facility of the Chinese Meridian Project. The detailed description of the final optimized design and implementation of this IPS radio telescope array is introduced. The antennas and array configuration, the analog and digital receiving systems for the main site and subsites, the calibration of the IPS telescope array and data processing are described. Finally the overall performance of the IPS telescope array is provided. The detailed information on the IPS radio telescope array will facilitate the use of its data serving space weather research and applications.

Simulating coronal mass ejections (CMEs) from their origin in active regions (ARs) to their propagation to Earth remains challenging, particularly when aiming to resolve AR scales and employ realistic magnetic field strengths without compromising computational efficiency. Here we present a methodology for end-to-end CME modeling that addresses these challenges. Three nested magnetohydrodynamic simulations are coupled to jointly cover the heliosphere from the solar surface to beyond 1.5 au. A block-structured adaptive mesh refinement scheme is employed to achieve similar to 700 km resolution in the low corona, allowing AR scales to be resolved while maintaining the total grid count below 108 across the entire computational domain. A semirelativistic Boris correction combined with a relativistic mass-density factor is used to handle magnetic field strengths up to 103 G without prohibitively small time steps. Using this model, we simulate the emergence of a bipolar AR into the corona, the initiation of a CME by shearing of the AR core field, and the subsequent evolution. Our simulation captures its pre-eruption energy buildup, triggered by magnetic reconnection, rapid acceleration, and propagation to 1 au and beyond. The simulated CME exhibits a three-part structure in synthetic coronagraph images and a torus-shaped flux rope in the heliosphere, with synthetic in situ observations showing shock formation, density compression, and a prolonged southward Bz component at 1 au. The entire simulation requires about 1 day on a moderately sized cluster (e.g., 600 processors), while the simulated CME takes 3 days to arrive at 1 au, offering a lead time of 2 days if used for forecasting.

The solar flare is the primary source of eruptions that generate space weather. Its high-speed jet is believed to produce the potential termination shock (TS) at the apex of the magnetic flux loop. Within the solar atmosphere, it becomes particularly intriguing to explore the fundamental mechanisms responsible for the initial acceleration of particles and their role in the generation of solar energetic particles (SEPs), extending to the phenomenon known as ground level enhancement (GLE). This study focuses on uncovering the relationship between GLE events and the flare-TS. To achieve this, we employ a Dynamic Monte Carlo (DMC) simulation technique to model the behavior of the flare-TS. In this theoretical framework, thermal particles that are part of the high-speed outflow from magnetic reconnection events penetrate the shock front at the loop top. Through numerous cycles of interaction with the TS, these particles undergo successive energy gains. Consequently, our simulation reveals details of the energy spectral structure. Besides the standard power-law with a hard index below 2 MeV, the emergence of a "bump-on-tail" structure between 2 and 20 MeV is observed in the simulated accelerated protons. Additionally, the efficiency of the TS acceleration dependent on the speed of the input bulk flow suggests a potential SEPs source for boosting GLEs. Based on these findings, we suggest that the termination shock acceleration mechanism serves as an initial source of energetic particles, which would lead to GLEs directly or seed the subsequent interplanetary processes for GLEs indirectly.

Solar energetic particles (SEPs), which originate from the eruptive activities of the solar corona, are accompanied by a significant amount of high-energy charged particles, can cause damage to spacecraft systems and affect human activities in space.Describing the propagation of SEPs in interplanetary space constitutes an indispensable component in the construction of SEP physical model. In this work, we developed a coupled Physics-based model composed of a data-driven analytical background model and a particle transport model represented by the focused transport equation (FTE). By using the coupled model, we try to simulate the energetic particle propagation in different interplanetary structures, such as the stream interaction region (SIR) and the coronal mass ejection (CME), with specific cases observed by WIND, STEREO A/B and SOHO, and to explore the physical nature behind the spacecraft observations.

Abstract The internal charging effects triggered by energetic (>100 keV) electrons in the Earth's radiation belts can cause anomalies and failures of electronic components aboard spacecraft. Given the critical importance of safeguarding space assets, it is essential to estimate internal charging risks, which depend highly on the distribution of radiation belt electron fluxes. In this study, we reconstruct the distribution of electron fluxes using a 3‐D data assimilative model, which integrates a radiation belt numerical model with multi‐satellite observations using the Ensemble Kalman Filter. We then estimate the spatial and temporal evolution of internal charging currents and risks across the entire outer radiation belt under specific shielding/dielectric layers and configurations. Furthermore, we analyze the impacts of shielding thickness on charging currents for different characteristic energy spectra. Our results reveal that for both power‐law and exponential energy spectra, the charging current decreases monotonically with increasing shielding thickness. However, there exists a “critical shielding thickness” for the bump‐on‐tail (BOT) energy spectrum. Below this critical value, the charging current increases with shielding thickness, whereas beyond it the current decreases. For the BOT energy spectrum, both higher electron energies corresponding to peak flux and thinner dielectric thicknesses can result in an increase in the “critical shielding thickness.” Our results shed important light on the prediction of satellite internal charging risk under the exposure to Earth's highly dynamic outer radiation belt.

In this study, we identified 51 dayside diffuse auroral patches and examined their two‐dimensional evolutions by using the Time History of Events and Macroscale Interactions during Substorms probes and the ground‐based all‐sky imager at the South Pole. Two typical events show diffuse auroral patches associated with upstream dynamic pressure enhancements of the bow shock and magnetospheric compressions, followed by their east–west propagations. The statistical results suggest that most conjunction events were associated with foreshock activities, while the remaining events were associated with dynamic pressure enhancements in the pristine solar wind. These azimuthal motions can be either eastward or westward, with initial locations at ∼12–13 and ∼9–10 Magnetic Local Time, respectively, exhibiting a dawn‐dusk asymmetry. Additionally, poleward motions were found in all events. Larger dynamic pressure enhancements correspond to faster poleward motions and could push the initial diffuse auroral brightening toward lower latitudes. These characteristics of their poleward motions were consistent with the Tamao path.

The interaction between the solar wind and Earth's magnetosphere is a critical area of research in space weather and space physics. Accurate determination of the magnetopause position is essential for understanding magnetospheric dynamics. While numerous magnetopause models have been developed over past decades, most are time-independent, limiting their ability to elucidate the dynamic movement of the magnetopause under varying solar wind conditions. This study introduces the first time-dependent three-dimensional magnetopause model based on quasi-elastodynamic theory, named the POS (Position–Oscillation–Surface wave) model. Unlike existing time-independent models, the POS model physically reflects the dynamic responses of magnetopause position and shape to time-varying solar wind conditions. The predictive accuracy of the POS model was evaluated using 38 887 observed magnetopause-crossing events. The model achieved a root-mean-square error of 0.774 Earth radii (RE, representing a 17.9 % improvement over five widely used magnetopause models. Notably, the POS model demonstrated superior accuracy under highly disturbed solar wind conditions (22.1 % better) and in higher-latitude regions (27.0 % better) and flank regions (33.3 % better) of the magnetopause. The POS model's remarkable accuracy, concise formulation, and fast computational speed enhance our ability to predict magnetopause position and shape in real time. This advancement is significant for understanding the physical mechanisms of space weather phenomena and improving the accuracy of space weather forecasts. Furthermore, this model may provide new insights and methodologies for constructing magnetopause models for other planets.

The long-chain effects of eruptive solar activities on Earth's magnetosphere, ionosphere, and the mid-to-lower atmospheric circulation are an important theoretical research topic in the fields of space weather and atmospheric science. Understanding the impact of space weather on aviation holds substantial economic value. It is well-known that flight times for polar routes may increase during solar proton events (SPEs) due to the necessity of avoiding high-energy particles. However, changes in atmospheric circulation due to SPEs and their impact on flight times have not been reported yet. This study systematically analyzed 15 pairs of representative international air routes, comprising a total of 16,037 flight records affected by the polar jet stream between 2015 and 2019. An unpaired two-sample two-tailed t-test revealed that 86.67% of westbound flights had shorter durations, while 86.67% of eastbound flights had longer durations during SPEs compared to quiet periods, with an average change of approximately 7 min. Further investigation into 42 SPEs during an entire solar cycle (11 years) indicates that the poleward shift of the polar jet stream, associated with high-energy particle precipitation, is the fundamental reason for the asymmetrical changes in flight times. This is the first report detailing the impact of SPEs on atmospheric circulation and flight times. Our findings reveal the long-chain mechanism by which SPEs directly influence the circulation of Earth's lower atmosphere. These results are also crucial for aviation, as they can help airlines optimize routes, reduce fuel costs, and contribute to climate change mitigation efforts.

Coronal mass ejections (CMEs) are phenomena in which the Sun suddenly releases a mass of energy and magnetized plasma, potentially leading to adverse space weather. Numerical simulation provides an important avenue for comprehensively understanding the structure and mechanism of CMEs. Here we present a global-corona MHD simulation of a CME originating from sheared magnetic arcade and its interaction with the near-Sun solar wind. Our simulation encompasses the pre-CME phase with gradual accumulation of free magnetic energy (and building up of a current sheet within the sheared arcade) as driven by the photospheric shearing motion, the initiation of CME as magnetic reconnection commences at the current sheet, and its subsequent evolution and propagation to around 0.1 AU. A twisted magnetic flux rope (MFR), as the main body of the CME, is created by the continuous reconnection during the eruption. By interacting with the ambient field, the MFR experiences both rotation and deflection during the evolution. The CME exhibits a typical three-part structure, namely a bright core, a dark cavity and a bright front. The bright core is mainly located at the lower part of the MFR, where plasma is rapidly pumped in by the high-speed reconnection outflow. The dark cavity contains both outer layer of the MFR and its overlying field that expands rapidly as the whole magnetic structure moves out. The bright front is formed due to compression of plasma ahead of the fast-moving magnetic structure. Future data-driven modeling of CME will be built upon this simulation with real observations used for the bottom boundary conditions.