Search Results (87)

Accurate modeling of ionospheric variability is critical for space weather forecasting and GNSS applications. While machine learning approaches have shown promise, progress is hindered by the absence of standardized benchmarking practices and narrow test periods. In this paper, we take the first step toward fostering rigorous and reproducible evaluation of AI models for ionospheric forecasting by introducing IonoBench: a benchmarking framework that employs a stratified data split, balancing solar intensity across subsets while preserving 16 high-impact geomagnetic storms (Dst ≤ $-100$ nT) for targeted stress testing. Using this framework, we benchmark a field-specific model (DCNN) against state-of-the-art spatiotemporal architectures (SwinLSTM and SimVPv2) using the climatological IRI 2020 model as a baseline reference. DCNN, though effective under quiet conditions, exhibits significant degradation during elevated solar and storm activity. SimVPv2 consistently provides the best performance, with superior evaluation metrics and stable error distributions. Compared to the C1PG baseline (the CODE 1-day forecast product), SimVPv2 achieves a notable RMSE reduction up to $32.1\%$ across various subsets under diverse solar conditions. The reported results highlight the value of cross-domain architectural transfer and comprehensive evaluation frameworks in ionospheric modeling. With IonoBench, we aim to provide an open-source foundation for reproducible comparisons, supporting more meticulous model evaluation and helping to bridge the gap between ionospheric research and modern spatiotemporal deep learning. Full article

This study focuses on the mid- and low-midlatitude ionospheric response to the 2024 Mother’s Day superstorm, utilizing ground-based and Swarm satellite observations. The ground-based ionosonde measured F1, F2-layer, B0 and B1 parameters, as well as isodensity data, were used. The ionospheric absorption was investigated with the so-called amplitude method, which is based on ionosonde data. Auroral sporadic E-layer was the first time ever recorded at Sopron. Moreover, the auroral F-layer appeared at exceptionally low latitude (35° mlat, over San Vito) during the storm main phase. These unprecedented detections were confirmed by optical all-sky cameras. The observations revealed that these events were linked to the extreme equatorward shift of the auroral oval along with the midlatitude trough. As a result, the midlatitude ionosphere became confined to the trough itself. Three stages of F2-layer uplift were identified during the night of 10/11 May, each caused by different mechanisms: most probably by the effect of prompt penetration electric fields (PPEFs) (1), the travelling ionospheric disturbances (TIDs) (2) and the combination of electrodynamic processes and decreased O/N₂ ratio (3). After a short interval of G-condition, an unprecedented extended disappearance of the layers was observed during daytime hours on 11 May, which was further confirmed by Swarm data. This phenomenon appeared to be associated with a reduced O/N₂ along with the influence of disturbance dynamo electric fields (DDEFs) and it cannot be explained only by the increased ionospheric absorption according to the results of the amplitude method. Full article

The present study analyzes the global ionospheric response to the intense geomagnetic storm of 10–11 October 2024 (SYM—H minimum of −346 nT), using observations from COSMIC—2 and Swarm satellites, GNSS TEC, and Digisondes. Significant uplift of the F-region was observed across both Hemispheres on the dayside, primarily driven by equatorward thermospheric winds and prompt penetration electric fields (PPEFs). However, this uplift did not correspond with increases in foF2 due to enhanced molecular nitrogen-promoting recombination in sunlit regions and the F2 peak rising beyond the COSMIC—2 detection range. In contrast, in the Southern Hemisphere nightside ionosphere exhibited pronounced Ne depletion and low hmF2 values, attributed to G-conditions and thermospheric composition changes caused by storm-time circulation. Strong vertical plasma drifts exceeding 100 m/s were observed during both the main and recovery phases, particularly over Ascension Island, driven initially by southward IMF—Bz-induced PPEFs and later by disturbance dynamo electric fields (DDEFs) as IMF—Bz turned northward. Swarm data revealed a poleward expansion of the Equatorial Ionization Anomaly (EIA), with more pronounced effects in the Southern Hemisphere due to seasonal and longitudinal variations in ionospheric conductivity. Additionally, the storm excited Large-Scale Travelling Ionospheric Disturbances (LSTIDs), triggered by thermospheric perturbations and electrodynamic drivers, including PPEFs and DDEFs. These disturbances, along with enhanced westward thermospheric wind and altered zonal electric fields, modulated ionospheric irregularity intensity and distribution. The emergence of anti-Sq current systems further disrupted quiet-time electrodynamics, promoting global LSTID activity. Furthermore, storm-induced equatorial plasma bubbles (EPBs) were observed over Southeast Asia, initiated by enhanced PPEFs during the main phase and suppressed during recovery, consistent with super EPB development mechanisms. Full article

This study presents a comprehensive analysis of the impact of Storm Laura, which was observed over Europe and the Baltic Sea on 12 March 2020, on the thermosphere–ionosphere system. The investigation of ionospheric disturbances caused by the meteorological storm was carried out using a combined modeling approach, incorporating the regional AtmoSym and the global GSM TIP models. This allowed for the consideration of acoustic and internal gravity waves (AWs and IGWs) generated by tropospheric convective sources and the investigation of wave-induced effects in both the neutral atmosphere and ionosphere. The simulation results show that, three hours after the activation of the additional heat source, an area of increased temperature exceeding 100 K above the background level formed over the meteorological storm region. This temperature change had a significant impact on the meridional component of the thermospheric wind and total electron content (TEC) variations. For example, meridional wind changes reached 80 m/s compared a the meteorologically quiet day, while TEC variations reached 1 TECu. Good agreement was obtained with experimental TEC maps from CODE (Center for Orbit Determination in Europe), MOSGIM (Moscow Global Ionospheric Map), and WD IZMIRAN (West Department of Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation Russian Academy of Sciences), which revealed a negative TEC value effect over the meteorological storm region. Full article

This study investigates the ionospheric response over China during the geomagnetic storm that occurred on 1–2 December 2023. The data used include GPS measurements from the Crustal Movement Observation Network of China, BDS-GEO satellite data from IGS MEGX stations, [O]/[N₂] ratio information obtained by the TIMED/GUVI, and electron density (Ne) observations from Swarm satellites. The Prophet time series forecasting model is employed to detect ionospheric anomalies. VTEC variations reveal significant daytime increases in GNSS stations such as GAMG, URUM, and CMUM after the onset of the geomagnetic storm on 1 December, indicating a dayside positive ionospheric response primarily driven by prompt penetration electric fields (PPEF). In contrast, the stations JFNG and CKSV show negative responses, reflecting regional differences. The [O]/[N₂] ratio increased significantly in the southern region between 25°N and 40°N, suggesting that atmospheric gravity waves (AGWs) induced thermospheric compositional changes, which played a crucial role in the ionospheric disturbances. Ne observations from Swarm A and C satellites further confirmed that the intense ionospheric perturbations were consistent with changes in VTEC and [O]/[N₂], indicating the medium-scale traveling ionospheric disturbance was driven by atmospheric gravity waves. Precise point positioning (PPP) analysis reveals that ionospheric variations during the geomagnetic storm significantly impact GNSS positioning precision, with various effects across different stations. Station GAMG experienced disturbances in the U direction (vertical positioning error) at the onset of the storm but quickly stabilized; station JFNG showed significant fluctuations in the U direction around 13:00 UT; and station CKSV experienced similar fluctuations during the same period; station CMUM suffered minor disturbances in the U direction; while station URUM maintained relatively stable positioning throughout the storm, corresponding to steady VTEC variations. These findings demonstrate the substantial impact of ionospheric disturbances on GNSS positioning accuracy in southern and central China during the geomagnetic storm. This study reveals the complex and dynamic processes of ionospheric disturbances over China during the 1–2 December 2023 storm, highlighting the importance of ionospheric monitoring and high-precision positioning corrections during geomagnetic storms. The results provide scientific implications for improving GNSS positioning stability in mid- and low-latitude regions. Full article

The G5 geomagnetic storm of May 2024 provided a significant opportunity to investigate global ionospheric disturbances using vertical total electron content (VTEC) data derived from 422 GNSS-IGS stations and GIM. This study presents a comprehensive spatio-temporal analysis of VTEC modulation before, during, and after the storm, focusing on hemispheric asymmetries and longitudinal variations. The primary objective of this study is to analyze the spatial and temporal modulation of VTEC under extreme geomagnetic conditions, assess the hemispheric asymmetry and longitudinal disruptions, and evaluate the influence of geomagnetic indices on storm-time ionospheric variability. The indices examined reveal intense geomagnetic activity, with the dst index plunging to −412 nT, the Kp index reaching 9, and significant fluctuations in the auroral electrojet indices (AE, AL, AU), all indicative of severe space weather conditions. The results highlight storm-induced hemispheric asymmetries, with positive storm effects (VTEC enhancement) in the Northern Hemisphere and negative storm effects (VTEC depletion) in the Southern Hemisphere. These anomalies are primarily attributed to penetration electric fields, neutral wind effects, and composition changes in the ionosphere. The storm’s peak impact on DoY 132 exhibited maximum disturbances at ±90° and ±180° longitudes, emphasizing the role of geomagnetic forces in plasma redistribution. Longitudinal gradients were strongly amplified, disrupting the usual equatorial ionization anomaly structure. Post-storm recovery on DoY 136 demonstrated a gradual return to equilibrium, although lingering effects persisted at mid- and high latitudes. These findings are crucial for understanding space weather-induced ionospheric perturbations, directly impacting GNSS-based navigation, communication systems, and space weather forecasting. Full article

This paper investigates the effects of a Corotating Interaction Region (CIR)/High-Speed Stream (HSS)-driven geomagnetic storm from 13 to 23 October 2003, preceding the well-known Halloween storm. This moderate storm exhibited a prolonged recovery phase and persistent activity due to a High-Intensity Long-Duration Continuous AE Activity (HILDCAA) event. We focus on low-latitude ionospheric responses induced by Prompt Penetration Electric Fields (PPEFs) and Disturbance Dynamo Electric Fields (DDEFs). To assess these effects, we employed ground-based GNSS receivers, Digisonde data, and satellite observations from ACE, TIMED, and SOHO. An empirical model by Scherliess and Fejer (1999) was used to estimate equatorial plasma drifts and assess disturbed electric fields. Results show a ∼120 km uplift in hmF2 due to PPEF, expanding the Equatorial Ionization Anomaly (EIA) crest beyond 20° dip latitude. DDEF effects during HILDCAA induced sustained F-region oscillations (∼100 km). The storm also altered thermospheric composition, with [[O]/[N₂] enhancements coinciding with TEC increases. Plasma irregularities, inferred from the Rate of TEC Index (ROTI 0.5–1 TECU/min), extended from equatorial to South Atlantic Magnetic Anomaly (SAMA) latitudes. These results demonstrate prolonged ionospheric disturbances under CIR/HSS forcing and highlight the relevance of such events for understanding extended storm-time electrodynamics at low latitudes. Full article

Global navigation satellite systems provide important data sets that can be used to study the influence of various space weather factors. We analyzed the effects of the main phase of the May 2024 extreme geomagnetic storm on the ionosphere and GPS kinematic precise point positioning (PPP). ROTI and global ionospheric maps showed the ionospheric dynamics. The auroral oval expanded up to low latitudes: up to 30°N in the American sector and up to 45°N in the European–Asian sector during the main phase of the geomagnetic storm. The ROTI peaked at 2 TECU/min, which is four times as much against the background. The equatorial anomaly crest intensified considerably (up to 200 TECU) and shifted poleward in the American sector. The counter-propagation finally caused the equatorial anomaly to cross the auroral oval boundary. The ROTI correlated with errors in the kinematic PPP. Positioning errors increased 1.5–5 times at the boundary of the auroral oval. Increased positioning errors propagated according to the shift of the auroral oval boundary. The geomagnetic storm significantly affected the positioning and the ionosphere, threatening various applications based on navigation and communication. Full article

Ionospheric tomography, an effective method for reconstructing 3-D electron density, is traditionally pictured by 3-D IED (ionospheric electron density) slices to express ionospheric disturbances, which may overlook the critical information in 3-D spherical manifold space. Here, we develop a novel visualization framework that integrates tomography reconstruction with a spherical latitude–longitude grid system, enabling the comprehensive characterization of 3-D IED dynamic evolution in 3-D manifold spherical space. Through this method, we visualized two cases: the Hualien earthquake on 2 April 2024 and the geomagnetic storm on 24 April 2023. The results demonstrate the evolution of the electron density during earthquake and geomagnetic storms in the real 3-D space, showing that seismic events induce bottom-up IED negative anomalies localized near epicenters, while geomagnetic storms trigger top-down depletion processes, with IED propagating from higher altitudes in the real 3-D manifold space. Compared to the conventional slice, our visualization model can visualize the characteristics, with the coverage area being observed to increase with the altitude within the same geospatial coordinates. This framework can advance the identification of ionosphere anomalies by enabling the precise differentiation of anomaly sources. This work bridges gaps in geospatial modeling by harmonizing ionospheric tomography with Earth system grids, offering a feasible solution for analyzing multi-scale ionospheric phenomena. Full article

The temporal variations and spatial variations in the ionosphere during geomagnetic storms are exceptionally complex and drastic, significantly complicating ionospheric model construction. In this study, we present a multi-site, high-precision ionospheric vertical total electron content ($VTEC$) estimation method by constraining the $VTEC$ when the locations of ionospheric pierce points (IPPs), determined by multiple sites, are nearby. The root mean square error (RMSE) relative to the global ionospheric map (GIM) $VTEC$ is 3.22 TEC units (TECU), with a correlation coefficient of 0.98. This method enables the high-precision estimation of $VTEC$ at IPPs. Utilizing the Gauss–Markov Kalman filter data assimilation algorithm, we consider the relationship between various Dst indices and the ionospheric temporal scales, achieving a regional ionospheric total electron content $\left(TEC\right)$ Map during geomagnetic storms. This approach effectively monitors the impact of geomagnetic storms on the ionospheric total electron content $\left(TEC\right)$ and provides a more accurate representation of ionospheric changes during geomagnetic storms compared to the GIM $TEC$ Map and the International Reference Ionosphere (IRI)-2020 model. Full article

Total electron content (TEC) serves as a key parameter characterizing ionospheric conditions. Accurate prediction of TEC plays a crucial role in improving the precision of Global Navigation Satellite Systems (GNSS). However, existing research have predominantly emphasized spatial variations in the ionosphere, neglecting the periodic changes of the ionosphere with the diurnal cycle. In this paper, we propose a TEC prediction model, which simultaneously considers both spatial and temporal characteristics to extract spatiotemporal features of ionospheric distribution. Additionally, we integrate several space weather element datasets into the prediction model framework, allowing the generation of multiple space weather feature values that represent the influence of space weather on the ionosphere at different latitudes and longitudes. Moreover, we apply Gaussian process regression (GPR) interpolation to geomagnetic data to characterize impact on the ionosphere, thereby enhancing the prediction accuracy. We compared our model with traditional image-based models such as convolutional neural networks (CNNs), convolutional long short-term memory networks (ConvLSTMs), a self-attention mechanism-integrated ConvLSTM (SAM-ConvLSTM) model, and one-day predicted ionospheric products (C1PG) provided by the Center for Orbit Determination in Europe (CODE). We also examined the effect of using different numbers of space weather feature values in these models. Our model outperforms the comparison models in terms of prediction error metrics, including mean absolute error (MAE), root mean square error (RMSE), correlation coefficient (CC), and the structural similarity index (SSIM). Furthermore, we analyzed the influence of different batch sizes on model training accuracy to find the best performance of each model. In addition, we investigated the model performance during geomagnetic quiet periods, where our model provided the most accurate predictions and demonstrates higher prediction accuracy in the equatorial anomaly region. We also analyzed the prediction performance of all models during space weather events. The results indicate that the proposed model is the least affected during geomagnetic storms and demonstrates superior prediction performance compared to other models. This study presents a more stable and high-performance spatiotemporal prediction model for TEC. Full article

The present study examines the negative ionospheric response over Europe during two geomagnetic storms on 10–13 May 2024, known as the Mother’s Day geomagnetic superstorm. The first storm, with a peak SYM-H value of −436 nT, occurred in the interval 10–11 May, while the second, less intense storm (SYM-H~−103 nT), followed in the interval 12–13 May. Using data from four European locations, temporal and spatial variations in ionospheric parameters (TEC, foF2, and hmF2) were analyzed to investigate the morphology of the strong negative response. Sharp electron density (Ne) depletion is associated with the equatorward displacement of the Midlatitude Ionospheric Trough (MIT), confirmed by Swarm satellite data. A key finding was the absence of foF2 and hmF2 values over all ionosonde stations during the recovery phase of the storms, likely due to the coupling between the Equatorial Ionization Anomaly (EIA) crests and the auroral ionosphere influenced by the intense uplift of the F layer. Relevant distinct features such as Large-scale Travelling Ionospheric Disturbance (LSTID) signatures and Spread F were also noted, particularly during the initial and main phase of the first storm over high midlatitude regions. Regional effects varied, with high European midlatitudes exhibiting different features compared to lower European latitude areas. Full article

Research has found kernel anomaly regions in the power spectrum images of ionospheric electric fields in space, which are widely distributed. To effectively detect these kernel abnormal regions, this paper proposes a new kernel abnormal region detection method, KANs-Unet, based on KANs and U-net networks. The model embeds the KAN-Conv convolutional module based on KANs in the encoder section, introduces the feature pyramid attention module (FPA) at the junction of the encoder and decoder, and introduces the CBAM attention mechanism module in the decoder section. The experimental results show that the improved KANs-Unet model has a mIoU improvement of about 10% compared to the PSPNet algorithm and an improvement of about 7.8% compared to the PAN algorithm. It has better detection performance than the currently popular semantic segmentation algorithms. A higher evaluation index represents that the detected abnormal area is closer to the label value (i.e., the detected abnormal area is more complete), indicating better detection performance. To further investigate the characteristics of kernel anomaly areas and the differences in features during magnetic storms, the author studied the characteristics of kernel anomaly areas during two different intensities of magnetic storms: from November 2021 to October 2022 and from 1 May 2024 to 13 May 2024 (large magnetic storm), and from 11 October 2023 to 23 October 2023 (moderate magnetic storm). During a major geomagnetic storm, the overall distribution of kernel anomaly areas shows a parallel trend with a band-like distribution. The spatial distribution of magnetic latitudes is relatively scattered, especially in the southern hemisphere, where the magnetic latitudes are wider. Additionally, the number of orbits with kernel anomaly areas during ascending increases, especially during peak periods of major geomagnetic storms. The overall spatial distribution of moderate geomagnetic storms does not change significantly, but the global magnetic latitude distribution is relatively concentrated. Full article

The study of the Earth’s ionosphere is a topic that has increased in relevance over the past few decades. The ability to predict the ionosphere’s behavior, as well as to mitigate the effects of its rapid changes, is a matter of primary importance in satellite communications, positioning, and navigation applications at present. Ionosphere perturbations can be produced by geomagnetic storms correlated with the solar activity or by earthquakes, volcanic activities, and so on. The monitoring of space weather is achieved through analyzing the Vertical Total Electron Content (VTEC) and its anomalies by means of time series, maps, and other derived parameters. In this study, we outline a strategy to estimate the VTEC in real-time, its rate of change, and the corresponding Signal-to-Noise Ratio (SNR) based on dual-frequency GNSS Doppler observations. We describe how to compute these parameters from GNSS data for a regional network using Adjusted Spherical Harmonic Analysis (ASHA) applied to a local model. The proposed method was tested to study ionospheric anomalies for two seismic events: the 2015 Nepal and 2023 Turkey earthquakes. In both cases, anomalies were detected in the maps of the differential VTEC (DTEC), differential VTEC rate, and SNR of the VTEC produced close to the earthquake zone. The robustness of the results is strongly related to the availability of a dense Ionosphere Pierce Point (IPP) cloud on the ionospheric layer and surrounding the studied area. At present, the distribution of Continuously Operating Reference Stations (CORSs) around the world is insufficiently dense and homogeneous in certain regions (e.g., the oceans). Robustness can be improved by increasing the number of CORSs and developing new models involving measurements over ocean surfaces. Full article

Mesoscale convective systems are effective sources of atmospheric disturbances that can reach ionospheric heights and significantly alter atmospheric and ionospheric conditions. Convective systems can affect the Earth’s atmosphere on a continental scale and up to F-layer heights. Extratropical cyclone “Zyprian” occurred at the beginning of July, 2021 and dominated weather over the whole of Europe. An extensive cold front associated with “Zyprian” moved from the western part to the eastern part of Europe, followed by ground-level convergence and the formation of organized convective thunderstorm systems. Torrential rains in the Czech Republic have caused a great deal of damage and casualties. Storm-related signatures were developed in ground microbarograph measurements of infrasound and gravity waves. Within the stratosphere, a shift of the polar jet stream and increase in specific humidity related to the storm system were observed. At the ionospheric heights, irregular stratification and radio wave reflection plane undulation were observed. An increase in wave-like activity was detected based on ionograms and narrowband very-low-frequency (VLF) data. On directograms and SKYmaps (both products of digisonde measurements), strong and rapid changes in the horizontal plasma motion were recorded. However, no prevailing plasma motion direction was identified within the F-layer. Increased variability within the ionosphere is attributed mainly to the “Zyprian” cyclone as it developed during low geomagnetic activity and stable solar forcing. Full article