Search Results (101)

While space weather indices (e.g., F10.7, Dst index) are commonly employed to characterize ionospheric activity levels, the Global Mean Electron Content (GMEC) provides a more direct and comprehensive indicator of the global ionospheric state. This metric demonstrates greater potential than space weather indices for calibrating empirical ionospheric models such as IRI-2020. The COSMIC-2 constellation enables continuous, all-weather global ionospheric monitoring via radio occultation, unimpeded by land–sea distribution constraints, with over 8000 daily occultation events suitable for GMEC modeling. This study developed two lightweight GMEC models using COSMIC-2 data: (1) a POD GMEC model based on slant TEC (STEC) extracted from Level 1b podTc2 products and (2) a PROF GMEC model derived from vertical TEC (VTEC) calculated from electron density profiles (EDPs) in Level 2 ionPrf products. Both backpropagation neural network (BPNN)-based models generate hourly GMEC outputs as global spatial averages. Critically, GMEC serves as an essential intermediate step that addresses the challenges of utilizing spatially irregular occultation data by compressing COSMIC-2’s ionospheric information into an integrated metric. Building on this compressed representation, we implemented a convolutional neural network (CNN) that incorporates GMEC as an auxiliary feature to calibrate IRI-2020’s global ionospheric maps. This approach enables computationally efficient correction of systemic IRI TEC errors. Experimental results demonstrate (i) 48.5% higher accuracy in POD/PROF GMEC relative to IRI-2020 GMEC estimates, and (ii) the calibrated global IRI TEC model (designated GCIRI TEC) reduces errors by 50.15% during geomagnetically quiet periods and 28.5% during geomagnetic storms compared to the original IRI model. Full article

Geomagnetic storms induce ionospheric disturbances, significantly affecting Global Navigation Satellite System (GNSS) positioning accuracy. This study investigates how geomagnetic storm-induced ionospheric irregularities influence GNSS Precise Point Positioning (PPP), using data from approximately 260 GNSS stations across China during 15 storm events between 1 January and 30 June 2015. We applied two indices—the Gradient Ionosphere Index (GIX), representing spatial gradients of vertical total electron content (VTEC), and the Rate of TEC Index (ROTI), describing temporal TEC variations. The analysis identified the St. Patrick’s Day geomagnetic storm (17 March 2015) as causing the most pronounced ionospheric disruptions, with significant east–west TEC gradients (|GIXx,P95| > 50 mTECU/km) consistently associated with substantial PPP errors (>0.5 m). Spatial analyses further indicated that significant 3D PPP errors (PPP, P₉₅ > 0.4 m) closely overlapped with regions experiencing intense east–west TEC gradients, predominantly in the 20–35°N latitude band. Further analysis indicated notable pre-storm ionospheric enhancements driven by zonal electric fields, distinct ionospheric suppression associated with westward disturbance dynamo electric fields (DDEFs) on 18 March, and re-intensification due to eastward penetration electric fields (PEFs) on 19 March. Full article

In this paper, we study the geomagnetic storm that occurred on 23–24 April 2023. We present variations in the values of interplanetary magnetic field (IMF-Bz), solar wind parameters (Vsw, Nsw, Tsw, and Psw), geomagnetic index (SYM-H), and vertical total electron content (VTEC) obtained from 18 GPS-TEC stations situated in equatorial, mid-latitude, and high-latitude regions. We analyze the variations in total electron content (TEC) before, during, and after the storm using VTEC plots, dTEC% plots, and global ionospheric maps for each GNSS receiver station, all referenced to universal time (UT). Our results indicate that GNSS receiver stations located at high latitudes detected an increase in ionospheric density during the main phase and a decrease during the recovery phase. In contrast, stations in equatorial and mid-latitude regions detected a decrease in ionospheric density during the main phase and an increase during the recovery phase. Large dTEC% values ranging from −80 to 190 TECU were observed a few hours before and during the storm period (23–24 April 2023); these can be compared to values ranging from −10 to 20 TECU on the day before (22 April 2023) and the day after (25 April 2023). Notably, higher dTEC% values were observed at stations in high and middle latitudes compared to those in the equatorial region. As the storm progressed, the TEC intensification observed on global ionospheric maps appeared to shift from east to west. A detailed analysis of these maps showed that equatorial and low-latitude regions experienced larger spatial and temporal TEC variations during the storm period compared to higher-latitude regions. Full article

Shiga toxin-producing Escherichia coli are important foodborne pathogens. There are several subtypes of the Shiga toxin Stx known, with Stx2 (a–o) being more diverse than Stx1 (a, c, d). Multiple occurrences of stx2 genes as well as combinations of stx1 and stx2 have been reported. However, there is a lack of knowledge on the occurrence of multiple stx1 genes in STEC strains. Here, we report two strains from food and animal feces which show genomic variations in the stx1 operon. The first strain harbors stx1a and stx1c genes, and the second strain shows an inactive stx1 operon due to an insertion in the stxA1a subunit gene. The screening of publicly available complete genome sequences of STEC revealed further strains harboring multiple stx1 genes, indicating that those strains also occur in human infections. This should be kept in mind when applying routine diagnostic methods like PCR, that do not detect multiple occurrences of stx1 genes of the same subtype. Moreover, the impact on the severity of human infections due to multiple stx1 genes has not been investigated well. 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

Real-time ionospheric products can accelerate the convergence of real-time precise point positioning (PPP) to improve the real-time positioning services of global navigation satellite systems (GNSSs), as well as to achieve continuous monitoring of the ionosphere. This study applied an extended Kalman filter (EKF) to total electron content (TEC) modeling, proposing a regional real-time EKF-based ionospheric model (REIM) with a spatial resolution of 1° × 1° and a temporal resolution of 1 h. We examined the performance of REIM through a 7-day period during geomagnetic storms. The post-processing model from the China Earthquake Administration (IOSR), CODG, IGSG, and the BDS geostationary orbit satellite (GEO) observations were utilized as reference. The consistency analysis showed that the mean deviation between REIM and IOSR was 0.97 TECU, with correlation coefficients of 0.936 and 0.938 relative to IOSR and IGSG, respectively. The VTEC mean deviation between REIM and BDS GEO observations was 4.15 TECU, which is lower than those of CODG (4.68 TECU), IGSG (5.67 TECU), and IOSR (6.27 TECU). In the real-time single-frequency PPP (RT-SF-PPP) experiments, REIM-augmented positioning converges within approximately 80 epochs, and IGSG requires 140 epochs. The REIM-augmented east-direction positioning error was 0.086 m, smaller than that of IGSG (0.095 m) and the Klobuchar model (0.098 m). REIM demonstrated high consistencies with post-processing models and showed a higher accuracy at IPPs of BDS GEO satellites. Moreover, the correction results of the REIM model are comparable to post-processing models in RT-SF-PPP while achieving faster convergence. Full article

Although the traditional Carrier-to-Code Leveling (CCL) method can provide ideal slant total electron content (STEC) observables for establishing ionospheric models, it must rely on dual-frequency (DF) receivers, which results in high hardware costs. In this study, an ionosphere-weight (IW) single-frequency (SF) precise point positioning (PPP) method for extracting STEC observables is proposed, and multi-global navigation satellite system (GNSS)-integrated processing is adopted to improve the spatial resolution of the ionospheric model. To investigate the advantages of this novel method, 41 European stations are used to establish the regional ionospheric model, and both low- and high-solar-activity conditions are considered. The results show that the IW SFPPP-derived regional ionospheric model has a significantly better quality of vertical total electron content (VTEC) than the CCL method when using the final global ionospheric map (GIM) as a reference, especially in areas with sparse monitoring stations. Compared with the CCL method, the RMS VTEC accuracy of the IW SFPPP method can be improved by 17.4% and 12.7% to 1.09 and 2.83 total electron content unit (TECU) in low- and high-solar-activity periods, respectively. Regarding GNSS carrier-phase-derived STEC variation (dSTEC) as the reference, the dSTEC accuracy of the IW SFPPP method is comparable to that of the CCL method, and its RMS values are about 1.5 and 2.8 TECU in low- and high-solar-activity conditions, respectively. This indicates that the proposed method using SF-only observations can achieve the same external accord accuracy as the CCL method in regional ionospheric modeling. Full article

On 10 May 2024 at 17 h:07 UTC, the simultaneous arrival of several solar coronal mass ejections (CMEs) generated the strongest geomagnetic storm of the last twenty years, with a minimum Dst = −412 nT, usually referred to as the Mother’s Day event. On 10 October 2024, the second strongest event of solar cycle 25 appeared with a Dst = −335 nT, preceded on 8 October by an event with a Dst = −153 nT. In the present work, with measurements of the vertical total electron content and with ionosonde observations from Europe, USA, and South Korea, we show that the ionization of the upper atmosphere shortly increased at the arrival of the CME for these different events, followed by a fast decrease at all latitudes. The ionization remained very low for more than a full day. While the recovery started at the beginning of the second day after the onset for both events in October, the sudden recovery in the middle of the second day on 12 May is much more unusual. The analysis of the observations at different latitudes and longitudes shows that the causes of the ionization variations during the superstorms were mainly due to strong perturbations in the ionospheric F layer, amplified by the plasmasphere’s influence on the vertical total electron content (VTEC). The erosion of the plasmasphere during these two strong events led to a plasmapause located at exceptionally low radial distances smaller than 2 Re (Earth’s radii) in the post-midnight sector and a rotating plume in the afternoon–dusk sector clearly visible in the BSPM plasmasphere model. It took several days after the storms to recover normal ionization rates. Full article

Atmospheric responses to earthquakes or volcanic eruptions have become an interesting topic and can potentially contribute to future forecasting of these events. Extensive anomalies of the total electron content (TEC) are most often linked with geomagnetic storms or Earth-dependent phenomena, like earthquakes, volcanic eruptions, or nuclear explosions. This study extends rarely discussed, but very frequent, interactions between tectonic plate boundaries and the ionosphere. Our investigations focus on the very frequent occurrence of TEC enhancements not exclusively linked with individual seismic phenomena but located over tectonic plate boundaries. The objective of this study is to provide a review of the global spatiotemporal distribution of TEC anomalies, facilitating the discussion of their potential relations with tectonic activity. We apply a Kriging-based UPC-IonSAT quarter-of-an-hour time resolution rapid global ionospheric map (UQRG) from the Polytechnic University of Catalonia (UPC) IonSAT group for the detection of relative vertical TEC (VTEC) changes. Our study describes global relative and normalized VTEC variations, which have spatial and temporal behaviours strongly indicating their relationship both with geomagnetic changes and the tectonic plate system. The variations in geomagnetic fields, including the storms, disturb the ionosphere and amplify TEC variations persisting for several hours over tectonic plate boundaries, mostly over the diverging ones. The seismic origin of the selected parts of these TEC enhancements and depletions and their link with tectonic plate edges are suspected from their duration, shape, and location. The changes in TEC originating from both sources can be observed separately or together, and therefore, there is an open question about the directions of the energy transfers. However, the importance of geomagnetic field lines seems to be probable, due to the frequent common occurrence of both types of TEC anomalies. This research also proves that permanent observation of global lithosphere–atmosphere–ionosphere coupling (LAIC) is also important in time periods without strong earthquake or volcanic events. The occurrence of TEC variations over diverging tectonic plate boundaries, sometimes combined with travelling anomalies of geomagnetic origin, can add to the studies on earthquake precursors and forecasting. Full article

Solar eclipses present a valuable opportunity for controlled in situ ionosphere studies. This work explores the response of the upper atmosphere’s F-layer during the total eclipse of 8 April 2024, which was primarily visible across North and South America. Employing a multi-instrument approach, we analyze the impact on the ionosphere’s Total Electron Content (TEC) and Very Low Frequency (VLF) signals over a three-day period encompassing the eclipse (7–9 April 2024). Ground-based observations leverage data from ten International GNSS Service (IGS)/Global Positioning System (GPS) stations and four VLF stations situated along the eclipse path. We compute vertical TEC (VTEC) alongside temporal variations in the VLF signal amplitude and phase to elucidate the ionosphere’s response. Notably, the IGS station data reveal a decrease in VTEC during the partial and total solar eclipse phases, signifying a reduction in ionization. While VLF data also exhibit a general decrease, they display more prominent fluctuations. Space-based observations incorporate data from Swarm and COSMIC-2 satellites as they traverse the eclipse path. Additionally, a spatiotemporal analysis utilizes data from the Global Ionospheric Map (GIM) database and the DLR’s (The German Aerospace Center’s) database. All space-based observations consistently demonstrate a significant depletion in VTEC during the eclipse. We further investigate the correlation between the percentage change in VTEC and the degree of solar obscuration, revealing a positive relationship. The consistent findings obtained from this comprehensive observational campaign bolster our understanding of the physical mechanisms governing ionospheric variability during solar eclipses. The observed depletion in VTEC aligns with the established principle that reduced solar radiation leads to decreased ionization within the ionosphere. Finally, geomagnetic data analysis confirms that external disturbances do not significantly influence our observations. Full article

An accurate estimation of Differential Code Bias (DCB) is essential for high-precision applications of the Global Navigation Satellite System (GNSS) and for the precise determination of GNSS-derived total electron content (TEC). This study leverages BeiDou Navigation Satellite System (BDS) and Global Positioning System (GPS) dual-frequency observations of the China Seismo-electromagnetic Satellite (CSES) from day of the year (DOY) 201 to DOY 232 in 2018, we evaluate the quality of CSES onboard GNSS observations, improve the data preprocessing method, and use the least-squares to estimate DCBs for both GNSS satellites and CSES receivers. A comprehensive analysis of the estimation accuracy is presented, revealing that DCBs for BDS satellites, derived from joint BDS and GPS observations, exhibit superior consistency compared to those from single BDS observations. Notably, the stability of DCBs for the CSES BDS receiver as well as for BDS GEO, IGSO, and MEO satellites has been significantly enhanced by 70%, 14%, 22%, and 23%, respectively. Conversely, the consistency of GPS satellite DCBs estimated from joint observations shows a decline when compared to the DCB products from the Center for Orbit Determination in Europe (CODE) and the Chinese Academy of Sciences (CAS). When fewer than nine satellites are tracked daily and nighttime observations are under 25%, estimation errors increase. The optimal DCB estimation is achieved with a cutoff elevation angle set at 10°, with monthly mean DCB values for CSES GPS and BDS receivers determined to be −2.193 ns and −1.099 ns, respectively, accompanied by root mean square errors (RMSEs) of 0.10 ns and 0.31 ns. The highest accuracy of DCBs estimated by the single-GPS scheme is corroborated by examining the occurrence of negative vertical total electron content (VTEC) percentages. 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

In the last decades, the scientific community has been focused on searching earthquake signatures in the Earth’s atmosphere, ionosphere, and magnetosphere. This work investigates an offshore Mw 5.5 earthquake that struck off the Marche region’s coast (Italy) on 9 November 2022, with a focus on the potential coupling between the Earth’s lithosphere, atmosphere, and magnetosphere triggered by the seismic event. Analysis of atmospheric temperature data from ERA5 reveals a significant increase in potential energy (Ep) at the earthquake’s epicenter, consistent with the generation of Atmospheric Gravity Waves (AGWs). This finding is further corroborated by the MILC analytical model, which accurately simulates the observed Ep trends (within 5%), supporting the theory of Lithosphere–Atmosphere–Ionosphere–Magnetosphere coupling. The study also examines the vertical Total Electron Content (vTEC) and finds notable fluctuations at the epicenter, exhibiting periodicities (7–12 min) characteristic of AGWs and traveling ionospheric disturbances. The correlation between ERA5 observations and MILC model predictions, particularly in temperature deviations and Ep distributions, strengthens the hypothesis that earthquake-generated AGWs impact atmospheric conditions at high altitudes, leading to observable ionospheric perturbations. This research contributes to a deeper understanding of Lithosphere–Atmosphere–Ionosphere–Magnetosphere coupling mechanisms and the potential for developing reliable earthquake prediction tools. Full article

This study aims to investigate the impact of ionospheric models on Global Navigation Satellite System (GNSS) positioning and proposes an ionospheric prediction method based on a Transformer deep learning model. We construct a Transformer-based deep learning model that utilizes global ionospheric maps as input to achieve spatiotemporal prediction of Total Electron Content (TEC). To gain a deeper understanding of the model’s prediction mechanism, we employ integrated gradients for explainability analysis. The results reveal the key ionospheric features that the model focuses on during prediction, providing guidance for further model optimization. This study demonstrates the efficacy of a Transformer-based model in predicting Vertical Total Electron Content (VTEC), achieving comparable accuracy to traditional methods while offering enhanced adaptability to spatial and temporal variations in ionospheric behavior. Furthermore, the application of advanced explainability techniques, particularly the Integrated Decision Gradient (IDG) method, provides unprecedented insights into the model’s decision-making process, revealing complex feature interactions and spatial dependencies in VTEC prediction, thus bridging the gap between deep learning capabilities and explainable scientific modeling in geophysical applications. The model achieved positioning accuracies of −1.775 m, −2.5720 m, and 2.6240 m in the East, North, and Up directions respectively, with standard deviations of 0.3399 m, 0.2971 m, and 1.3876 m. For VTEC prediction, the model successfully captured the diurnal variations of the Equatorial Ionization Anomaly (EIA), with differences between predicted and CORG VTEC values typically ranging from −6 to 6 TECU across the study region. The gradient score analysis revealed that solar activity indicators (F10.7 and sunspot number) showed the strongest correlations (0.7–0.8) with VTEC variations, while geomagnetic indices exhibited more localized impacts. The IDG method effectively identified feature importance variations across different spatial locations, demonstrating the model’s ability to adapt to regional ionospheric characteristics. Full article