Search Results (174)

The ionospheric response to a geomagnetic storm depends on several factors, including the strength of a storm, commencement type, solar origin of a geomagnetic storm (as, coronal mass ejections or high-speed solar wind streams), and observational site location. In this work, we present the results of a statistical analysis of 80 moderate to major geomagnetic storms that took place during the declining phase of the 24th solar cycle from 2015 to 2019. We performed an analysis of the ionospheric response to these storms using the total electron content (TEC) data obtained from three geodetic receivers located in Portugal: Lisbon (Continental Portugal), Furnas (Azores), and Funchal (Madeira). Statistical analysis of the observed TEC variations allowed detection of specific patterns in the ionospheric response to storms with different characteristics. We found that the type of geomagnetic storm commencement (gradual or sudden) is a statistically significant predictor of the ionospheric response amplitude and duration. Also, specific patterns in the ionospheric response to geomagnetic storms were found for the most southern location (Madeira), which are likely related to its proximity to the northern boundary of the equatorial ionization anomaly. Full article

Global Navigation Satellite Systems (GNSSs) have become a fundamental technology supporting modern civilisation, industry, and society, including a vast number of applications in urban science. Degradations and disruptions in GNSS Positioning, Navigation, and Timing (PNT) service performance caused by both natural and adversarial sources degrade the quality and robustness of GNSS-based applications. Ionospheric effects form the principal single source of GNSS PNT performance degradation. Traditional GNSS ionospheric delay correction models cannot resolve the ionospheric effect mitigation problem due to their global nature and an intrinsic lack of agility and flexibility. Here, we contribute to the problem resolution by proposing a geomagnetic ambient-aware GNSS ionospheric delay correction model based on near-real-time measurements of geomagnetic field components as descriptors of the GNSS positioning environment immediately surrounding a GNSS receiver. The proposed geomagnetic ambient-aware GNSS ionospheric delay correction model is developed using statistical/machine learning model-development methods applied to a massive database of related experimental observations. The model may be implemented in traditional single-unit and distributed architectures, such as the previously introduced Ambient-Aware Application-Aligned (AA)² GNSS PNT framework. It improves GNSS PNT performance for urban science applications, thus increasing their Quality of Service. The proposed approach and the resulting bespoke geomagnetic ambient-aware GNSS ionospheric delay correction model are successfully demonstrated using the R environment for statistical computing for the case of a single-frequency commercial-grade GNSS receiver operating in a sub-equatorial region. Full article

Equatorial plasma bubbles (EPBs) are ionospheric plasma depletions that can disrupt Global Navigation Satellite System (GNSS) signals and degrade positioning at equatorial and low latitudes. Evaluating total electron content (TEC)-based EPB detection using observations is challenging because GNSS links provide sparse, geometry-dependent sampling, and the three-dimensional structure of EPBs is generally unknown. This study develops a controlled forward modeling framework for simulating and detecting EPB signatures in GNSS slant TEC (sTEC). Global-scale Observations of the Limb and Disk (GOLD)-derived parameterised depletions were embedded in a three-dimensional Neustrelitz electron density model (NEDM-2020) background ionosphere, and sTEC was integrated along simulated receiver and satellite ray paths. Depletion events were identified from detrended sTEC, mapped to ionospheric pierce point coordinates, and combined across multiple satellite links using a declination-guided clustering and grouping procedure. The prescribed signatures were detected under static and uniformly drifting conditions. The tested horizontal-geometry and drift-speed cases remained detectable, whereas no event satisfied the detection criteria at the lowest depletion-amplitude scaling factor of 0.50 applied to the GOLD-derived depletion amplitude. In 30 Gaussian noise realisations at each non-zero noise level, the nominal PRN 23 depletion was recovered in 17, 6, and 1 runs at noise standard deviations of 0.10, 0.25, and 0.50 TECU, respectively. An adapted slope-and-variance-based method identified the PRN 10 depletion in the static case but did not retain a valid depletion event in the drifting case. The framework provides a controlled testbed for evaluating EPB detection and localisation under known simulated conditions. Evaluation using real GNSS observations and independent measurements is required to assess its performance under observational conditions. Full article

Reliable short-term prediction of thermospheric states is important for satellite drag applications but remains difficult because of nonlinear, multiscale variability. We developed a multivariable Adaptive Fourier Neural Operator (AFNO) surrogate using 24 years (2000–2023) of Thermosphere–Ionosphere Electrodynamics General Circulation Model (TIE-GCM) simulations. The model predicts neutral density, temperature, winds, and geopotential height over 24-h autoregressive forecasts. We compared direct state prediction with increment-based flow prediction and tested logarithmic density scaling and one-hour historical inputs. Both formulations preserved dominant large-scale density structures and the equatorial mass density anomaly, with anomaly correlation coefficients above 0.94 for all variables. The Direct formulation maintained lower errors and greater stability at longer lead times, whereas Flow performed better only at early steps. Logarithmic density scaling produced variable- and altitude-dependent trade-offs, and historical inputs yielded no overall benefit. During a representative geomagnetic storm, the baseline reproduced broad density morphology but increasingly underestimated enhancement magnitude with lead time. Because evaluation used the independent 2023 TIE-GCM test year with prescribed forecast-time forcing and no observational validation, the framework should be interpreted as a TIE-GCM-consistent surrogate rather than a validated predictor of the observed thermosphere. Full article

Subauroral geospace is a dynamic region. Its various features include Subauroral Polarization Streams (SAPS), hot and cold zones, and storm enhanced densities (SED). Previous studies have covered the nightside, leaving the dayside largely unexplored and poorly understood. This study investigates the prenoon and midday sectors, based on multi-instrument, multipoint observations. In the inner magnetosphere, the observed dayside SAPS’ development was set off by solar-wind flow pressure increases compressing the dayside magnetosphere in the equatorial plane and triggering earthward-directed hot plasma surges or particle injections in the coupled Alfvenic solar wind and dayside magnetosphere. The dayside SAPS developed in an inner-magnetosphere voltage generator and appeared sometimes within the cold zone where the isotropic ion temperature (Ti_‖ ≈ Ti_⊥) minimized and sometimes within the hot zone fueled by whistler-mode chorus waves locally enhancing the field-aligned temperature anisotropy (T_‖ > T_⊥) and providing localized plasma heating both via Landau damping and implicitly. In the ionosphere, the observed dayside SAPS’ development was unfolding in a prenoon eastward auroral electrojet (AEJ) scenario on the dawnside and in a midday westward AEJ scenario on the duskside. The observed dayside SAPS mapped down to the noontime SED plume base depicted by the total electron content maps. Full article

The westward electric field plays an important role in the hmF2-declining type (where hmF2 denotes the peak height of the F2 layer) of postmidnight electron density (Ne) enhancements at equatorial ionization anomaly (EIA) latitudes through the compression effects, whereas its effectiveness in causing ionospheric storms has not been carefully investigated. As the counter equatorial electrojet (CEJ) is an indicator of the westward electric field, in this study, we focused on the American sector during the long-lasting (~10 h) intense CEJ event on 26 August 2018, based on observations from magnetometers, ionosonde-derived Ne profiles, ground-based and satellite-borne total electron content (TEC) measurements, and ∑O/N₂. The peak density of the F2 layer (NmF2) and TEC at the ionosondes presented severe long-duration enhancements at southern EIA latitudes, accompanied by decreases in hmF2 and scale height (Hm) of the Ne profile, similar to the hmF2-declining type of postmidnight NmF2 enhancements. The dominant contribution to the TEC enhancements came from the topside ionosphere. Moreover, the TEC map displayed prominent enhancements spanning a wide range of longitudes in the American sector. This study suggests that the electric-field-driven compression and convergence played important roles in the F-region Ne enhancements by changing the shape of the F layer. Meanwhile, elevated O/N₂ and equatorward winds may also have contributed to the TEC enhancements. Full article

The rate of change in the total electron content index (ROTI) is a widely used proxy for phase fluctuations associated with ionospheric irregularities derived from GNSS total electron content measurements. This study investigates the longitudinal day-to-day variability of ionospheric irregularities over the African Equatorial Ionization Anomaly (EIA) region during 2014 using ROTI from six GNSS stations at low latitudes. Day-to-day variability is quantified through differences between consecutive daily ROTI values (ΔROTI), relative ROTI (RROTI), correlation coefficients, daily deviations from climatological trend, and variability magnitude. The results demonstrate notable longitudinal variations in day-to-day variability between the East and West African sectors, with predominantly higher variability observed in West Africa. Diurnal ROTI peaks reach about 2 TECU/min in East Africa and about 3 TECU/min in West Africa. Correlation coefficients within the same longitude sector range from 0.68 to 0.85, whereas cross-sector correlations range from 0.48 to 0.69. ΔROTI and RROTI indicate that day-to-day variability is driven mainly by short-period lower-atmospheric forcing rather than slow solar forcing. Relative variations range from about −70% to +150%, with predominantly negative values during solstices and positive values during equinoxes. Full article

This study investigates the low-latitude ionospheric response over the Eastern Hemisphere during two successive geomagnetic storms on 12–13 November 2025. BDS-GEO observations from 20 GNSS stations, CODE GIM data, Swarm satellite observations, and simulations from the TIEGCM and HWM14 models were integrated to investigate regional ionospheric disturbances, single-station responses, and Equatorial Ionization Anomaly (EIA) evolution. During the first storm, with SYM-H reaching −254 nT, EIA intensification and poleward expansion beyond ±20° magnetic latitude were observed, with VTEC approaching 100 TECU at stations over Australia and rTEC exceeding 80% over Australia and the adjacent Pacific Ocean. Swarm observations showed TEC decreases within the EIA crest region and TEC increases in the surrounding areas. In contrast, the second storm, with SYM-H reaching −154 nT, produced disturbances with lower amplitudes, mainly characterized by localized positive TEC anomalies near the magnetic equator within 100°E–180°E, together with negative TEC anomalies in the surrounding low-latitude regions. The first storm was associated with southward IMF Bz reaching −54 nT and electrodynamic uplift related to PPEF, which contributed to the superfountain effect, whereas the second storm was influenced by residual disturbed neutral winds, reduced O/N₂ ratios at low latitudes, and the preconditioned ionospheric state inherited from the first storm. These results demonstrate that successive geomagnetic storms can produce different ionospheric responses in terms of intensity, spatial morphology, and driving mechanisms, highlighting the event dependence and regional variability of low-latitude ionospheric storm responses. BDS-GEO observations offer distinct advantages for monitoring localized ionospheric disturbances over the Eastern Hemisphere. Full article

Accurate modeling of topside ionospheric electron density is essential for improving GNSS positioning and understanding upper-atmosphere dynamics. A new four-dimensional (spatial and temporal) topside electron density model is developed using global GNSS radio occultation data within an L2-regularized artificial neural network framework. The model combines both empirical and physical variables, including geomagnetic coordinates, temporal parameters, solar flux ($F_{10.7}$), geomagnetic activity index ($Kp$), and key ionospheric parameters (NmF2 and hmF2). To support the modeling framework, two sub-models are first constructed to estimate NmF2 and hmF2 when direct measurements are unavailable. The full model is trained using COSMIC-1 data and evaluated against independent datasets, including COSMIC-1, GRACE, and incoherent scatter radar (ISR). The results show that the proposed sub-models reduce relative errors by 4.5% for hmF2 and 11.0% for NmF2 compared with IRI-2016. For the full topside $N_e$ modeling, the proposed approach achieves improvements of 35%, 36%, and 53% relative to IRI-2016 when evaluated against COSMIC-1, GRACE, and ISR datasets, respectively. A systematic analysis of input variables further indicates that both physical drivers and ionospheric structural parameters play essential roles in determining model performance. The new model incorporated with NmF2 and hmF2 sub-models still achieves a 16% improvement over IRI-2016 based on ISR data. In addition to statistical improvements, the model reproduces key ionospheric features, including the equatorial ionization anomaly (EIA) and the midlatitude summer nighttime anomaly (MSNA), under different solar activity conditions. These results demonstrate that the proposed model captures not only the statistical variability but also the underlying physical behavior of the topside ionosphere. Full article

This paper presents the design, optimization, and performance evaluation of a Satellite-Based Augmentation System (SBAS) ground segment tailored to Colombia’s air navigation infrastructure, with emphasis on ionospheric anomalies in equatorial latitudes. The configuration comprises six Reference Stations (RIMS), strategically sited via geometric dilution of precision (GDOP) minimization and airspace demand models from ADS-B data. A simulation suite—integrating STK^®, Radio Mobile™, and Stanford-ESA certified monitors—quantifies service volume, link margins, and protection level compliance. Ionospheric threat characterization uses regional scintillation datasets (σln ≈ 0.36, ROTI₉₅ ≈ 85 mm/km), informing GIVE inflation and dual-frequency pseudorange integrity validation. Simulations confirm the system sustains ≥ 99.8% APV-I availability over the CAR/SAM FIR, with Horizontal and Vertical Protection Levels (HPL/VPL) bounded below 28 m and 46 m. Uplink integrity and GEO broadcast continuity are modelled under worst-case masking and multipath, confirming ICAO Annex 10 SARPs compliance. The architecture achieves a high performance-to-cost ratio, enabling nationwide SBAS coverage with a 65% cost reduction versus legacy navaids. The system is forward-compatible with dual-frequency multi-constellation SBAS (DFMC), supporting future APV-II scalability. These results position Colombia as a regional node for GNSS augmentation, fostering safety, efficiency, and procedural harmonization. Full article

Global Navigation Satellite Systems (GNSS) are highly affected in equatorial regions, especially due to the formation of Equatorial Plasma Bubbles (EPBs), which cause disturbances in the ionosphere resulting in different forms of signal degradation. Despite Colombia’s privileged geographic position, its limited monitoring infrastructure hinders the detection and mitigation of these effects. This study proposes the development of a Low-Cost Scintillation Laboratory (LCSL) using a cognitive radio–based approach for real-time scintillation monitoring, aimed at improving GNSS reliability. The system was designed following a Systems Engineering methodology, defining functional architectures and constraints. A communication system model was developed to account for EPBs’ effects on GNSS signals, while cognitive radio algorithms within a Software-Defined Radio (SDR) framework enabled real-time detection, monitoring, and alert generation. To implement this approach, monitoring stations were deployed in Bogotá, Cartagena, and Santa Marta utilized low-cost GNSS receivers integrated with Machine Learning (ML) algorithms for the automatic classification of scintillation events. Additionally, the system’s accuracy was validated by comparing experimental data with historical records from the Geophysical Institute of Peru (IGP). The results demonstrated that the integration of cognitive radio and ML-based detection enhanced precision and adaptability compared to traditional methods. The network of monitoring stations effectively validated the system’s performance, providing valuable insights into equatorial ionospheric dynamics. This study contributes to the advancement of monitoring methodologies and highlights the importance of accessible infrastructure for mitigating EPB effects on GNSS, ultimately fostering more resilient navigation and communication systems. Full article

The 12 November 2025 G4 geomagnetic storm—the third most intense of solar cycle 25—was triggered by a complex shock-ICME (interplanetary coronal mass ejection) structure as a result of three ICMEs and driven shocks that arrived on 11–12 November. The main enhancement in the interplanetary magnetic field occurred in the sheath region behind the shock driven by the second ICME. The Dst index reached −217 nT (the SYM-H index reached −254 nT) and the maximum Kp index was 9-. To comprehensively analyze the causes of the storm and its complex effects on near-Earth space, we used a multi-instrumental data set, involving data from satellite missions (ACE, SDO, PROBA2), GNSS networks, ionosondes, optical instruments, high-frequency radars (SuperDARN-like), and cosmic ray monitors. The auroral oval expanded equatorward (down to ~35° N in America). We recorded a super equatorial plasma bubble that almost reached the auroral oval boundary. The equatorial anomaly crests intensified, exceeding 175 TECU, and shifted poleward (8–10°). At mid-latitudes, the F2 layer critical frequency exhibited a strong negative disturbance (−50%) during the main phase, followed by an unusually prolonged and intense positive phase (+100%). GPS Precise Point Positioning errors increased to 2–3 m at high latitudes and in regions affected by the equatorial bubble. The event also featured a Forbush decrease and ground-level enhancement (GLE 77 according to the database hosted by the University of Oulu) associated with the X5.1 solar flare. The results underscore the complex chain of processes from solar storm to geomagnetic and ionospheric responses, highlighting the risks to satellite-based navigation and communication systems. Full article

This study presents U-Net deep learning of total electron content (TEC) obtained from Global Ionosphere Maps (GIMs) to forecast ionospheric TEC over the African 0–40° N latitude sector during geomagnetic storms which have occurred between 2011 and 2024. Before being utilized in the deep learning procedure, the GIM-TEC data were improved by assimilating ground-based vertical TEC (VTEC) observations from available Global Navigation Satellite System (GNSS) receiver stations. The U-Net one-hour-ahead prediction of TEC was examined during the intense geomagnetic storm of May 2024. Additionally, the model’s accuracy and reliability were evaluated through quantitative comparison with established climatological models, including IRI-2020 and AfriTEC storm time models. The results indicate that the integration of data assimilation with the deep learning framework yields TEC estimates that closely agree with observations, achieving a RMSE of approximately 5 TECU. On the other hand, the IRI-2020 model exhibits substantially larger errors, with RMSE ~10–17 TECU, while the AfriTEC model shows the poorest performance, with RMSE reaching approximately 15–22 TECU. Further, the U-Net was validated using two equatorial and mid-latitude GNSS stations whose data were excluded from the assimilation process, achieving RMSE values of 4.44 and 6.75 TECU and correlation coefficients of 0.93 and 0.97, confirming the model forecasting capability for reproducing ionospheric TEC variability. These results establish the model as a precise, robust tool for TEC prediction in regions with sparse GPS coverage that is crucial for ionospheric monitoring and space weather applications. Full article

This study investigates the temporal and latitudinal variability of the ionosphere over the Indian longitude region during the intense geomagnetic storm from 1 to 3 June 2025, using GNSS receiver observations and magnetometer recordings, along with space-based measurements from in situ Swarm satellite, COSMIC-2 radio occultation, GUVI/TIMED-derived O/N₂ ratios, and model-derived electric fields. This particular event is relatively new and is characterized by the bifurcated variation with two distinct main phases separated by a short-lived recovery phase. The results revealed distinct features associated with the geomagnetic storm, including positive and negative ionospheric phases, thermospheric compositional changes, and the latitudinal propagation of disturbances. On 1 June, the observed strong positive ionospheric storm was driven by Prompt Penetration Electric Fields (PPEFs) and equatorward neutral winds, which triggered the upliftment of F-region plasma to higher altitudes through the enhanced equatorial fountain effect, leading to an unusually long-lasting Total Electron Content (TEC) enhancement from day to night. The analysis also revealed the distinct latitudinal behaviour, exhibiting the clear poleward extension of the Equatorial Ionization Anomaly (EIA) crest and significant TEC enhancements (~150–200% of the quiet day values) from low to mid latitudes as compared to the equatorial location through an efficient plasma redistribution. Conversely, pronounced negative ionospheric storm effect at almost all latitudinal locations on 2 June confirms complex and unusual storm-time dynamics, with inhibited upward plasma drifts due to the presence of Disturbance Dynamo Electric Fields (DDEFs), while the thermospheric O/N₂ ratio caused an extensive decrease in electron density over the Indian region. Minor negative storm noticed on 3 June coincides with the storm recovery period, reflecting prolonged disturbance dynamo effects and gradual recovery in thermospheric conditions. Overall, the current study highlights the strong sensitivity of the regional ionosphere to prevailing coupled electrodynamic-thermospheric forcing during the June 2025 geomagnetic storm that has not yet been reported for this event over the Indian longitude sector. Moreover, the findings from this study underscore peculiar storm-time behaviour of summer solstice ionosphere over the Indian longitude sector, driven by complex coupled processes which could be incorporated into ionospheric models and forecasting frameworks. Full article

Precise characterization of the thermospheric neutral wind is essential for comprehending the dynamic interactions within the ionosphere-thermosphere system, as evidenced by the development of models like HWM and the need for localized data. However, numerical models often suffer from biases due to uncertainties in external forcing and the scarcity of direct wind observations. This study examines the influence of incorporating actual neutral wind profiles from the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) on the Ionospheric Connection Explorer (ICON) satellite into the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE-GCM) via an ensemble-based data assimilation framework. To address the challenges of assimilating real observational data, a robust background check Quality Control (QC) scheme with dynamic thresholds based on ensemble spread was implemented. The assimilation performance was evaluated by comparing the analysis results against independent, unassimilated observations and a free-running model Control Run. The findings demonstrate a substantial improvement in the precision of the thermospheric wind field. This enhancement is reflected in a 45–50% reduction in Root Mean Square Error (RMSE) for both zonal and meridional components. For zonal winds, the system demonstrated effective bias removal and sustained forecast skill, indicating a strong model memory of the large-scale mean flow. In contrast, while the assimilation exceptionally corrected the meridional circulation by refining the spatial structures and reshaping cross-equatorial flows, the forecast skill for this component dissipated rapidly. This characteristic of “short memory” underscores the highly dynamic nature of thermospheric winds and emphasizes the need for high-frequency assimilation cycles. The system required a spin-up period of approximately 8 h to achieve statistical stability. These findings demonstrate that the assimilation of data from ICON/MIGHTI satellites not only diminishes numerical inaccuracies but also improves the representation of instantaneous thermospheric wind distributions. Providing a high-fidelity dataset is crucial for advancing the modeling and understanding of the complex interactions within the Earth’s ionosphere-thermosphere system. Full article