Search Results (1,462)

The China Seismo Electromagnetic Satellite (CSES) mission provides in situ measurements of the electromagnetic field, plasma, and charged particles in the topside ionosphere. Each CSES spacecraft carries several different scientific payloads delivering a wealth of information about the ionospheric plasma dynamics and properties, as well as measurement about energetic particles precipitating in the ionosphere. In this work, we introduce CSESpy, a Python package designed to provide an interface to CSES data products, with the aim of easing the pathway for scientists to carry out analyses of CSES data. Beyond simply being an interface to the data, CSESpy aims to provide higher-level analysis and visualization tools, as well as methods for combining concurrent measurements from different instruments, so as to allow multipayload studies in a unified framework. Moreover, CSESpy is designed to be highly flexible as such, it can be extended to interface with datasets from other sources and can be embedded in wider software ecosystems. We highlight some applications, also demonstrating that CSESpy is a powerful visualization tool for investigating complex events involving variations across multiple physical observables. Full article

The binary anomaly detection (classification) of ionospheric data related to Very Low Frequency (VLF) signal amplitude in prior research demonstrated the potential for development and further advancement. Further data quality improvement is integral for advancing the development of machine learning (ML)-based ionospheric data (VLF signal amplitude) anomaly detection. This paper presents the transition from binary to multi-class classification of ionospheric signal amplitude datasets. The dataset comprises 19 transmitter–receiver pairs and 383,041 manually labeled amplitude instances. The target variable was reclassified from a binary classification (normal and anomalous data points) to a six-class classification that distinguishes between daytime undisturbed signals, nighttime signals, solar flare effects, instrument errors, instrumental noise, and outlier data points. Furthermore, in addition to the dataset, we developed a freely accessible web-based tool designed to facilitate the conversion of MATLAB data files to TRAINSET-compatible formats, thereby establishing a completely free and open data pipeline from the WALDO world data repository to data labeling software. This novel dataset facilitates further research in ionospheric signal amplitude anomaly detection, concentrating on effective and efficient anomaly detection in ionospheric signal amplitude data. The potential outcomes of employing anomaly detection techniques on ionospheric signal amplitude data may be extended to other space weather parameters in the future, such as ELF/LF datasets and other relevant datasets. Full article

We present three dimensional particle-in-cell simulations of current-voltage characteristics of the hemispherical Langmuir probe (LAP), onboard the China Seismo-Electromagnetic Satellite (CSES). Using realistic plasma parameters and background magnetic fields obtained from the International Reference Ionosphere (IRI) and International Geomagnetic Reference Field (IGRF) models, we simulate probe–plasma interactions at three locations: the equatorial region and two magnetically conjugate mid-latitude sites: Millstone Hill (Northern Hemisphere) and Rothera (Southern Hemisphere). The simulations, performed using the PTetra PIC code, incorporate realistic LAP geometry and spacecraft motion in the ionospheric plasma. Simulated current voltage characteristics or I–V curves are compared against in-situ LAP measurements from CSES Orbit-026610, with Pearson’s correlation coefficients used to assess agreement. Our findings indicate how plasma temperature, density, and magnetization affect sheath structure and probe floating potential. The study highlights the significance of kinetic modeling in enhancing diagnostic accuracy, particularly in variable sheath regimes where classic analytical models such as the Orbital-Motion-Limited (OML) theory may be inadequate. Full article

Global Navigation Satellite System (GNSS) spoofing, which manipulates PVT solutions through false measurements, increasingly threatens GNSS reliability and user safety. However, most existing simulator-based spoofers, constrained by their inability to access real-time ionospheric information (e.g., Global Ionosphere Maps, GIMs) from external sources, struggle to replicate authentic total electron content (TEC) along each signal propagation path accurately and in a timely manner. In contrast, widespread dual-frequency (DF) receivers with access to the internet can validate local TEC measurements against external references, establishing a pivotal spoofing detection distinction. Here, we propose an Ionospheric Information-Assisted Spoofing Detection Technique (IIA-SDT), exploiting the inherent consistency between TEC values derived from DF pseudo-range measurements and external references in spoofing-free scenarios. Spoofing probably disrupts this consistency: in simulator-based full-channel spoofing where all channels are spoofed, the inaccuracies of the offline ionospheric model used by the spoofer inevitably cause TEC mismatches; in partial-channel spoofing where the spoofer fails to control all channels, an unintended PVT deviation is induced, which also causes TEC deviations due to the spatial variation of the ionosphere. Basic principles and theoretical analysis of the proposed IIA-SDT are elaborated in the paper. Simulations using ionospheric data collected from 2023 to 2024 at a typical mid-latitude location are conducted to evaluate IIA-SDT performance under various parameter configurations. With a window length of 5 s and satellite number of 8, the annual average detection probability approximates 75% at a false alarm rate of $1\times {10}^{-3}$, with observable temporal variations. Field experiments across multiple scenarios further validate the spoofing detection capability of the proposed method. Full article

Rocket launches constitute a major anthropogenic source of disturbance in the near-Earth space environment, inducing significant ionospheric perturbations through both chemical and dynamic mechanisms. This study presents a systematic analysis of ionospheric disturbances—specifically, electron density depletion and traveling ionospheric disturbances (TIDs)—triggered by four rocket launches from China’s Jiuquan Satellite Launch Center between 2023 and 2025. Using high-rate, multi-constellation GNSS data from 370 ground stations and BeiDou GEO satellites, we extracted total electron content (TEC) signals and applied advanced detection methods, including the Multi-Rolling-Multi-Image-Tracking (MRMIT) algorithm for depletion identification and a parametric integration framework for quantitative comparison. Our results reveal that all launches produced rapid TEC depletions, evolving along the rocket trajectory and peaking within approximately 30 min. Launch mass was the dominant factor controlling depletion intensity, while propellant chemistry (UDMH-based vs. liquid oxygen/methane) and local time/background TEC levels modulated the recovery rate and spatial extent. Additionally, distinct TIDs exhibiting wave-like and V-shaped structures were observed, propagating outward from the trajectory with latitudinal variations in amplitude and waveform. These findings highlight the critical roles of rocket attributes and ambient ionospheric conditions in shaping disturbance characteristics. The study underscores the value of multi-source GNSS networks and novel methodologies in monitoring anthropogenic space weather effects, with implications for GNSS performance and sustainable space operations. Full article

The Denoising Wavelet Transform Convolutional Long Short-Term Memory Network (DWTConvLSTM) is a novel ionospheric total electron content (TEC) spatiotemporal prediction model proposed in 2025 that can simultaneously consider high-frequency and low-frequency features while suppressing noise. However, it also has flaws as it only considers unidirectional temporal features in spatiotemporal prediction. To address this issue, this paper adopts a bidirectional structure and designs a bidirectional DWTConvLSTM model that can simultaneously extract bidirectional spatiotemporal features from TEC maps. Furthermore, we integrate a lightweight attention mechanism called Convolutional Additive Self-Attention (CASA) to enhance important features and attenuate unimportant ones. The final model was named CASA-BiDWTConvLSTM. We validated the effectiveness of each improvement through ablation experiments. Then, a comprehensive comparison was performed on the 11-year Global Ionospheric Maps (GIMs) dataset, involving the proposed CASA-BiDWTConvLSTM model and several other state-of-the-art models such as C1PG, ConvGRU, ConvLSTM, and PredRNN. In this experiment, the dataset was partitioned into 7 years for training, 2 years for validation, and the final 2 years for testing. The experimental results indicate that the RMSE of CASA-BiDWTConvLSTM is lower than those of C1PG, ConvGRU, ConvLSTM, and PredRNN. Specifically, the decreases in RMSE during high solar activity years are 24.84%, 16.57%, 13.50%, and 10.29%, respectively, while the decreases during low solar activity years are 26.11%, 16.83%, 11.68%, and 7.04%, respectively. In addition, this article also verified the effectiveness of CASA-BiDWTConvLSTM from spatial and temporal perspectives, as well as on four geomagnetic storms. Full article

Low-temperature oxidation of titanomagnetite in oceanic basalts distorts the primary thermoremanent magnetization (TRM) signal essential for reconstructing Earth’s magnetic field history, though the specific impact of magma intrusion-induced oxidation on paleointensity preservation remains poorly constrained. This investigation simulates such oxidation processes using a novel experimental design involving isothermal annealing (260 $°$C; 50 µT field; durations 12.5–1300 h) of Red Sea rift basalts (P72/4), employing the Thellier-Coe method to quantify how chemical remanent magnetization (CRM) overprinting affects TRM fidelity under controlled field orientations aligned either parallel or perpendicular to the initial TRM. Results demonstrate two-sloped Arai-Nagata diagrams with reliable TRM preservation below 360 $°$C but significant alteration artifacts above this threshold. Crucially, field orientation during oxidation critically influences accuracy: parallel configurations maintain fidelity (±3% deviation at $Z=0.48$), while perpendicular fields introduce systematic biases (38% overestimation at $Z=0.15$; 20% underestimation at $Z>0.48$), which is attributable to magnetostatic interactions in core-shell grain structures. These findings establish that paleointensity reliability in basalt prone to low-temperature oxidation depends fundamentally on the alignment between oxidation-era magnetic fields and primary TRM direction, necessitating stringent sample selection and directional constraints in marine paleomagnetic research to mitigate CRM-TRM interference. Full article

A practical methodology for estimating regionally optimized Klobuchar coefficients using only International GNSS Service (IGS) Global Ionosphere Map (GIM) data is proposed. The method preserves computational simplicity, enabling near-real-time corrections suitable for accurate GNSS positioning. Utilizing both slant and vertical total electron content (STEC and VTEC) values extracted from GIM as inputs to estimate eight Klobuchar coefficients, robust parameter sets were obtained. Root mean square error (RMSE) analysis was used to compare these models to the standard Klobuchar model. Comprehensive performance evaluations using STEC-derived parameters, encompassing both seasonal and spatial analyses across South Korea, demonstrated significant reductions in ionospheric delay errors, with improvements reaching up to 57% compared to the conventional Klobuchar model. The far less computationally intensive VTEC-based model was applied over a wider region with 120 grid points. Continuous testing of this model over an entire year confirmed consistent enhancements in correction accuracy every day, demonstrating stable performance throughout the period. The developed regional Klobuchar models were further validated indirectly through satellite positioning performance, demonstrating daily RMSE improvements over the standard Klobuchar model ranging from 17.3% to 44.6%. Full article

In the paper we consider the pulsed disturbances caused in the ionosphere by an extreme G5-level geomagnetic superstorm on 10 May 2024, and by the X1.0 and M-class solar flares on 8 May 2024, which preceded the storm. Particular attention is paid to the short-term delays and the sequence of disturbance appearance in the ionosphere and geomagnetic field during these extreme events. The results of a continuous Doppler sounding of the ionosphere on an inclined radio path with a sampling frequency of 25 Hz were used, as well as the data of a ground-based mid-latitude fluxgate magnetometer LEMI-008, and an induction magnetometer IMS-008, which operated with a sampling frequency of 66.6 Hz. Ionization of the ionosphere by the intense X-ray and extreme ultraviolet radiation of solar flares was accompanied by the equally sudden and similarly timed disturbances in the Doppler frequency shift (DFS) of the ionospheric signal, which had an amplitude of 2.0–5.8 Hz. The largest pulsed burst in DFS was registered 68 s after an X1.0 flare on 8 May 2024 at the time when the change of the X-ray flux was at its maximum. Following onto the effect in the ionosphere, a disturbance in the geomagnetic field appeared with a time delay of 35 s. This disturbance is a secondary one that arose as a consequence of the ionosphere response to the solar flare. It was likely driven by the contribution of ionospheric currents and electric fields, which modified the Earth’s magnetic field. On 10 May 2024, a G5-level geomagnetic superstorm with a sudden commencement triggered an impulsive reaction in the ionosphere. A response in DFS at the calculated reflection altitude of the sounding radio wave of 267.5 km was detected 58 s after the commencement of the storm. The sudden impulsive changes in Doppler frequencies showed a bipolar character, reflecting complex dynamic transformations in the ionosphere at the geomagnetic storm. Consequently, the DFS amplitude initially rose to 5.5 Hz over 86 s, and then its sharp drop to $-3.2$ Hz followed. Using the instruments that operated in a mode with a high temporal resolution allowed us to identify for the first time the impulsive nature of the ionospheric reaction, the time delays, and the sequence of disturbance appearances in the ionosphere and geomagnetic field in response to the X1.0 solar flare on 8 May 2024 as well as to the sudden commencement of the extreme G5-level geomagnetic storm on 10 May 2024. Full article

The formation of international networks of magnetic observatories has provided new opportunities for monitoring geomagnetic disturbances and solving problems related to space weather. On the other hand, collective processing of data from numerous observatories revealed problems with the quality of data provided by some of them. Sometimes, the reason for the decrease in data quality is associated with faulty measuring instruments. However, every year, industrial interference also increases its influence on measurement quality. INTERMAGNET suggests carrying out a mutual comparison between the values of neighboring magnetic observatories as one of the methods for solving the problem of maintaining data quality. This paper proposes a method to improve the quality of magnetograms, which makes it possible to eliminate the results of interference of local origin through the use of four spatially separated magnetic observatories located in Kazakhstan. This method is suitable for automating the magnetograms’ quality control process. Full article

Accurate ionospheric channel estimation is of great significance for acquisition of ionospheric structure, error correction of remote sensing data, high-precision Synthetic Aperture Radar (SAR) imaging, over-the-horizon (OTH) detection, and the establishment of stable communication links. Traditional super-resolution channel estimation algorithms face challenges in terms of multipath correlation and noise interference when estimating ionospheric channel information. Meanwhile, some super-resolution algorithms struggle to meet the requirements of real-time measurement due to their high computational complexity. In this paper, we propose the Cross-correlation Oblique Projection Pursuit (CC-OPMP) algorithm, which constructs an atom selection strategy for anti-interference correlation metric and a dual-space multipath separation mechanism based on a greedy framework to effectively suppress noise and separate neighboring multipath components. Simulations demonstrate that the CC-OPMP algorithm outperforms other algorithms in both channel estimation accuracy and computational efficiency. Full article

As the peak of Solar Cycle 25 approaches, space weather events such as Equatorial Plasma Bubble (EPBs) and geomagnetic storms are expected to become more frequent. While EPBs are a primary source of scintillation, geomagnetic storms can either enhance or suppress this activity depending on storm timing, intensity, and induced electric field effects, thereby causing significant ionospheric disturbances that degrade Global Navigation Satellite System (GNSS) signal reception performance. This study presents a novel, systematic evaluation of GPS + Galileo Precise Point Positioning (PPP) performance under intense ionospheric scintillation during the rising phase of Solar Cycle 25 using datasets from globally distributed stations. More than twenty months of data have been systematically analysed, with a focus on stations located in equatorial regions, which are the most affected by strong scintillation. PPP processing was performed using final products from the European Space Agency (ESA) with Multi-GNSS Experiment (MGEX) products employed as backups when ESA data were unavailable. It is shown that under severe scintillation the accuracy of the final PPP solution is severely reduced, with errors more than doubled with respect to calm days. In this respect, frequent cycle slips and anomalies in the input observations are detected. A comparative analysis of GPS-only and GPS + Galileo PPP solutions confirms that integrating Galileo not only mitigates the impact of scintillation but also improves the reliability and accuracy of positioning in challenging space weather conditions. Full article

We report the exceptional observations of amplified eastward subauroral polarization streams (SAPS) made by the F15 spacecraft at ~840 km altitude near magnetic midnight during 2015–2016 in 17 events. The results show the dawn-cell-associated amplified eastward SAPS flows streaming alongside the duskward-extending dawn cell. The amplified eastward SAPS flows maximized at ~3200 m/s within their respective deep plasma density troughs, mimicking the SAPS flows and thus implying positive feedback mechanisms in action, where the electron temperature reached ~7000 K. One set of correlated magnetosphere–ionosphere conjugate observations is also presented. This illustrates the magnetotail-reconnection-related inward-directed cross-tail convection electric field (E_C) reaching the near-earth plasmasheet’s tailward end, while the inward-directed SAPS E field was absent on the inner-magnetosphere plasmapause, and the emerging eastward SAPS flow in the conjugate ionosphere. These results provide observational evidence that the earthward-propagating inward-directed dawn–dusk cross-tail E field (1) mapped down to auroral latitudes with an equatorward direction, (2) propagated to subauroral latitudes, and (3) played a key role in the development of the emerging eastward SAPS flow and in the amplification of the fully-developed eastward SAPS flows near magnetic midnight, while positive feedback mechanisms supported further SAPS growth. Full article

In LEO constellation–augmented navigation, the transmitting antenna phase center offset (PCO) and the equipment delay associated with the downlink signals of LEO satellites constitute major error sources that must be precisely characterized. Previous studies primarily focused on single or small-scale satellite scenarios, lacking comprehensive evaluations regarding the influence of constellation scale, orbital altitude, ground station configuration, and various error sources. To address this gap, we propose a joint estimation method utilizing observations from a limited number of regional ground stations in China that simultaneously track GNSS and LEO satellites. The method is specifically designed to accommodate practical constraints on ground station distribution within China. Initially, a batch least-squares estimation strategy is employed to simultaneously determine the ionosphere-free PCO and initial equipment delays for all LEO satellites in a constellation-wide solution. Subsequently, the estimated PCO parameters are fixed, and the equipment delays are further refined using a precise point positioning (PPP) approach. To systematically evaluate the method’s performance under realistic conditions, we analyze the impact of orbital altitude, constellation size, ground station number, data processing duration, and orbit/clock biases through comprehensive simulations. The results indicate: (1) the Z-direction component of the PCO (pointing toward the Earth’s center) and equipment delay is more sensitive to orbit and clock errors; (2) Increasing the number of LEO satellites generally improves the estimation accuracy of equipment delays, but the marginal gain diminishes as the constellation size expands; (3) sub-centimeter PCO accuracy and equipment delay accuracies better than 3 cm can still be achieved using only 3–4 regionally distributed ground stations over an observation period of 5–7 days. Full article

The Hunga-Tonga volcanic eruption on 15 January 2022, produced significant atmospheric and ionospheric disturbances that may degrade global navigation satellite system (GNSS) and precise point positioning (PPP) accuracy. Using data from the GEONET GNSS network and Soratena barometric pressure sensors across Japan, we analyzed the eruption’s effects through the gradient ionospheric index (GIX) and the rate of TEC index (ROTI) to characterize the propagation and effects of these disturbances on ionospheric total electron content (TEC) gradients. Our analysis identified two separate ionospheric disturbance events. The first event, coinciding with the arrival of atmospheric Lamb waves, was characterized by wave-like pressure anomalies, differential TEC (dTEC) fluctuations, and modest horizontal gradients of vertical TEC (VTEC). In contrast, the second, more pronounced disturbance was driven by equatorial plasma bubbles (EPBs), which generated severe ionospheric irregularities and large TEC gradients. Further analysis revealed that these two disturbances had markedly different impacts on GNSS positioning accuracy. The Lamb wave–induced disturbance mainly caused moderate TEC fluctuations with limited effects on positioning accuracy, and mid-latitude stations maintained both average and 95th percentile positioning ($\mathrm{p}\mathrm{p}\mathrm{p},{\mathrm{P}}_{95}$) errors below 0.1 m throughout the event. In contrast, the EPB-driven disturbance had a substantial impact on low-latitude regions, where the average horizontal PPP error peaked at 0.5 m and the horizontal and vertical $\mathrm{p}\mathrm{p}\mathrm{p},{\mathrm{P}}_{95}$ errors exceeded 1 m. Our findings reveal two episodes of spatial-gradient enhancement and successfully estimate the propagation speed and direction of the Lamb waves, supporting the potential application of ionospheric gradient monitoring in forecasting GNSS performance degradation. Full article