Search Results (101)

This study investigates ionospheric total electron content (TEC) estimation based on GPS and Galileo data collected aboard the training ship (HANS) from DOY 249 to 300 in 2024. The combined GPS/Galileo TEC is compared with the CODE global ionospheric map (GIM), resulting in a mean difference of −2.41 TEC units (TECU) and a root mean square (RMS) error of 6.53 TECU. Furthermore, although inland GNSS stations in South Korea are incorporated to stabilize receiver differential code bias (DCB) estimation, the results still exhibited significant temporal fluctuations. The relationship between the Dst indices and the GPS satellite DCB values is observed. In addition, the Pearson correlation (R) and a significance level (p) are considered to analyze the relationship between receiver DCB variations and some factors, such as geomagnetic indices (Dst, Kp, and F10.7a), vertical TEC (VTEC), and multipath error. Geomagnetic indices show no clear correlation. Furthermore, receiver DCB changes exhibit a weak correlation (R~0.33 and p~0.01) with VTEC. Multipath errors show negligible correlation with receiver DCB changes. Significant fluctuations in receiver DCB values prevent a clear correlation. Therefore, we suggest that there are inherent difficulties in precisely estimating ionospheric TEC and DCB values on a HANS trajectory. Full article

There is increasing interest in space domain awareness (SDA), motivating the use of non-traditional sensors for space surveillance. One such sensor is the Buckland Park Stratospheric–Tropospheric (BPST) very high frequency (VHF) radar, which has demonstrated an ability to detect over 2000 resident space objects (RSO) daily. A by-product of the RSO observations is the measurement of ionospheric group retardation, which can be used to estimate the total electron content (TEC) between the ground and the satellite altitude. This paper describes the use of BPST radar observations of Starlink satellites to measure vertical TEC (vTEC) from the ground to 490 km and from the ground to 560 km. The variation in BPST radar vTEC is demonstrated for both geomagnetically quiet and storm periods. The results are combined with global ionospheric TEC maps to calculate the ratio of the ionospheric to plasmaspheric (or LEO to GPS) vTEC. This allows investigation of the diurnal and annual variation in the LEO to GPS vTEC for the radar location at a temporal resolution unavailable to LEO satellite-based measurements. The results indicate that the RMS uncertainty of the BPST radar vTEC estimates is 0.41 TEC units (TECU), comparing favorably with the ≈2 TECU RMS uncertainty typically measured by GNSS receivers. The technique described in this paper may be applied to any ST or boundary layer (BL) radar without the need for hardware changes. Full article

Global Positioning System (GPS)-derived ionospheric electron concentration measurements provide a powerful observational framework for seismo-electromagnetic studies, enabling quantitative investigation of lithosphere–atmosphere–ionosphere coupling processes through statistically detectable perturbations in ionospheric electron concentration. We analyze GPS-derived Vertical Total Electron Content (VTEC) variations associated with the 14 August 2021 Haiti earthquake ($M_w$ 7.2) and the 11 January 2022 Cyprus earthquake ($M_w$ 6.6) using data from nearby International GNSS (Global Navigation Satellite System) Service (IGS) stations located within their respective earthquake preparation zones. VTEC time series spanning 45 days before and 7 days after each event are processed to remove the diurnal component, yielding residuals that isolate short-term ionospheric variability. Anomaly detection is performed using three statistical frameworks: a Gaussian mean, standard deviation model, a robust median/median absolute deviation (MAD) model, and a distribution-free quantile-based model. Daily “occurrence” and “energy” indices are constructed to quantify the frequency and cumulative strength of detected anomalies, respectively. While the indices exhibit similar temporal patterns across all methods, they indicate frequent anomaly detection, limiting statistical selectivity. To address this, both indices are normalized by their median values and filtered using a 95% quantile threshold, retaining only extreme deviations. This procedure substantially reduces background fluctuations and isolates a small number of statistically significant anomaly peaks. For both earthquakes, enhanced anomaly activity is identified in the weeks preceding the events, whereas post-event peaks coincide with periods of elevated meteorological and geomagnetic activity. The results demonstrate that normalization combined with robust statistical methods is essential for discriminating significant ionospheric TEC anomalies from background variability. 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

We investigate the multi-layer atmospheric impacts of Typhoon Hagibis (2019), which formed on 6 October, tracked across 12–35° N and 135–155° E, and made landfall on 12 October over the Izu Peninsula, central Honshu, Japan. We present a multi-layer study that involves the troposphere, stratosphere and upper ionosphere to examine the thermodynamic and electromagnetic coupling between these layers due to such extreme weather conditions. Using ERA5 reanalysis, we identify pronounced stratospheric temperature perturbations, elevated atmospheric gravity wave (AGW) potential energy, substantial spatiotemporal variability in the zonal (U) and meridional (V) wind components, relative humidity, and specific rainwater content throughout the cyclone’s evolution. Quantitatively, AGW potential energy increased from background levels of <5 J kg⁻¹ to >40 J kg⁻¹ near the cyclone core, while tropospheric wind anomalies reached $\pm 30$–40 m s⁻¹, accompanied by relative humidity values exceeding 90% and specific rainwater content up to $1.5\times {10}^{-3}$ kg kg⁻¹, indicative of vigorous moist convection and strong vertical energy transport. The ionospheric response, derived from GPS-based Total Electron Content (TEC) at 10 Japanese IGS stations, reveals vertical TEC (VTEC) perturbations whose amplitudes and temporal evolution vary systematically with GPS-station-to-typhoon-eye distance, including clear enhancements and reductions around the closest-approach day. These signatures indicate a measurable ionospheric response to cyclone-driven atmospheric forcing under geomagnetically quiet conditions, confirming that Hagibis produced vertically coupled disturbances linking stratospheric AGW activity with ionospheric electron density variability. Full article

NavIC and GPS are satellite-based navigation systems developed by India and the United States, respectively, and are widely used for ionospheric and space weather studies. This paper presents a comparative analysis of NavIC- and GPS-derived total electron content (TEC) during a High-Intensity Long-Duration Continuous AE Activity (HILDCAA) event that occurred from 17 to 21 August 2017. The analysis covers the five days of the event, along with three days before and after, using observations from a single low-latitude station over the Indian region. NavIC performance is evaluated by comparing vertical TEC (vTEC) derived from dual-frequency pseudorange measurements with co-located GPS-derived vTEC. The results show a strong linear correspondence between the two datasets, with Pearson correlation coefficients exceeding ∼0.97 throughout the event interval. Such high correlation is physically expected, as the dominant contribution to TEC arises from the common vertical ionospheric column sampled by both systems. Nevertheless, the close agreement observed under sustained geomagnetic disturbance conditions demonstrates that NavIC is capable of consistently capturing ionospheric TEC variability during this specific HILDCAA event. Full article

Accurate estimation of the regional ionospheric model (RIM) is essential for Total electron content and high-precision applications of the Global Navigation Satellite System (GNSS). Utilizing dual-frequency observations from over 250 Crustal Movement Observation Network of China (CMONOC) monitoring stations, which are equipped with both GPS and GLONASS receivers, this study investigates the Vertical Total Electron Content (VTEC) estimation models over the China region and evaluates the estimation accuracy under both GPS-only and GPS+GLONASS configurations. Results indicate that, over the Chinese region, the spherical harmonic reginal ionospheric model (G_SH RIM) and polynomial function reginal ionospheric model (G_Poly RIM) based on single GPS observations demonstrate comparable accuracy with highly consistent spatiotemporal distribution characteristics, showing grid mean deviations of 1.60 TECu and 1.62 TECu, respectively. The combined GPS+GLONASS observation-based RIMs (GR_SH RIM and GR_Poly RIM) significantly improve the TEC modeling accuracy in the Chinese peripheral regions, though the overall average accuracy decreases compared to single-GPS models. Specifically, GR_SH RIM and GR_Poly RIM exhibit mean deviations of 2.15 TECu and 2.32 TECu, respectively. A preliminary analysis reveals that the reduced accuracy is primarily due to the systematic errors introduced by imprecise differential code biases (DCBs) of GLONASS satellites. These findings can provide valuable references for multi-GNSS regional ionospheric estimation. 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

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

This article discusses outcomes of the Polish–Chinese project dedicated to establishing multi-GNSS near-real-time ionospheric services. ARTEMIS (Advanced methodology development for Real-Time Multi-constellation (BDS, Galileo and GPS) Ionosphere Services) was a response to increasing GNSS data availability, including Galileo and BeiDou observations on the one hand and growing interest in high-quality ionospheric products on the other. The project resulted in elaborating methodologies to monitor the ionospheric Total Electron Content (TEC) and its fluctuations (ROTI index) based on a full multi-GNSS approach and establishing pilot real-time web services in a global and regional approach. The project’s outcomes are to be included in the International GNSS Service (IGS) and International Reference Ionosphere (IRI) in the near future. This article presents real-time ionospheric products developed under the ARTEMIS project and evaluates their performance using independent techniques such as DORIS observations and altimetry with regard to other existing products. The Discussion section also includes an evaluation of ARTEMIS products in positioning applications. Full article

Recent advancements have led to a growing prevalence of studies examining ionospheric and atmospheric anomalies as potential precursors to earthquakes. In this context, the study involved analyzing variations in ionospheric total electron content (TEC), investigating anomalies, assessing space weather conditions, and examining changes in atmospheric parameters to evaluate potential precursors and post-seismic effects related to the Mw 7.7 and Mw 7.6 earthquakes that struck Kahramanmaraş consecutively in 2023. To compute the total electron content (TEC) values, data from 29 GNSS receivers covering a period of approximately 49 days were processed. In addition, since identical code signals were not available among all receiver stations, the study conducted an analysis of TEC estimations applying different GPS codes. To analyze space weather conditions, which are considered the main source of changes in the ionosphere, variations in sunspot number, solar activity index, magnetic activity indices (Kp and Dst), and geomagnetic field components were examined across the relevant period. To assess the potential presence of a distinct relationship between seismic activity at the Earth’s surface and ionospheric conditions, atmospheric parameters including temperature, relative humidity, and pressure were meticulously monitored and evaluated. As a result of the study, it was determined that TEC anomalies that could be evaluated as earthquake precursors independent of space weather conditions were observed starting from the 3rd day before the earthquake, and high positive TEC anomalies occurred immediately after the earthquakes. In atmospheric parameters, the change in behavior, particularly in temperature value, 10 days before the earthquake, is noteworthy. Full article

The use of a rapid heating method to achieve heterogeneity of Mn in medium-manganese steel and improve its comprehensive performance has been widely studied and these techniques have been widely applied. However, the heating rate (from α to γ) has not received sufficient attention with respect to its microstructure-evolution mechanism. In this study, the effect of heating rate on the microstructure evolution and hardness of heterogeneous medium-manganese steel was investigated by using X-ray diffraction (XRD), scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), transmission electron microscopy (TEM) and DICTRA simulation. The results showed that the Mn distribution was heterogeneous in the initial microstructure of pearlite due to strong partitioning of Mn between ferrite and cementite. At low heating rates (<10 °C/s), the heterogeneity of Mn distribution was diminished to some extent due to the long-distance diffusion of Mn in high-temperature austenite. Contrastingly, at high heating rates, the initial heterogeneity of the Mn element could be largely preserved due to insufficient diffusion of Mn, which resulted in more ghost pearlite (GP: pearlite-like microstructure with film martensite/RA). Moreover, the high heating rate not only refines the prior austenite grain but also increases the total RA content, which is mainly composed of additional film RA. As the heating rate increases, the hardness gradually increases from 628.1 HV to 663.3 HV, due to grain refinement and increased dislocation density. Dynamic simulations have also demonstrated a strong correlation between this interesting microstructure and the non-equilibrium diffusion of Mn. Full article

In this study, we present the first results of detecting ionospheric irregularities using non-typical GPS observations recorded onboard the Geostationary Operational Environmental Satellites (GOES) mission operating at ~35,800 km altitude. Sitting above the GPS constellation, GOES can track GPS signals only from GPS transmitters on the opposite side of the Earth in a rather unique geometry. Although GPS receivers onboard GOES are primarily designed for navigation and were not configured for ionospheric soundings, these GPS measurements along links that traverse the Earth’s ionosphere can be used to retrieve information about ionospheric electron density. Using the radio occultation (RO) technique applied to GPS measurements from the GOES–16, we analyzed variations in the ionospheric total electron content (TEC) on the links between the GPS transmitter and geostationary GOES GPS receiver. For case-studies of major geomagnetic storms that occurred in September 2017 and August 2018, we detected and analyzed the signatures of storm-induced ionospheric irregularities in novel and promising geostationary GOES GPS observations. We demonstrated that the presence of ionospheric irregularities near the GOES GPS RO sounding field of view during geomagnetic disturbances was confirmed by ground-based GNSS observations. The use of RO observations from geostationary orbit provides new opportunities for monitoring ionospheric irregularities and ionospheric density. Full article

This paper presents a multi-parameter ionospheric disturbance analysis of the total electron content (TEC), density (Ne), temperature (Te), and critical frequency foF2 variations preceding two significant earthquake events (2015 Mw 7.5 and 2023 Mw 6.3) that occurred in Afghanistan. The analysis from various ground stations and low-Earth-orbit satellite measurements involved employing the sliding interquartile method to process TEC data of Global Ionospheric Maps (GIMs), comparing revisit trajectories to identify anomalies in Ne and Te from Swarm satellites, applying machine learning-based envelope estimation for GPS-derived TEC measurements, utilizing the least square method for foF2 data and ionograms obtained from available base stations in the Global Ionosphere Radio Observatory (GIRO). After excluding potential influences caused by solar and geomagnetic activities, the following phenomena were revealed: (1) The GIM-TEC variations displayed positive anomalies one day before the 2015 Mw 7.5 earthquake, while significant positive anomalies occurred on the shock days (7, 11, and 15) of the 2023 Mw 6.3 earthquake; (2) the Swarm satellite observations (Ne and Te) for the two earthquakes followed almost the same appearance rates as GIM-TEC, and a negative correlation between the Ne and Te values was found, with clearer appearance at night; (3) there were prominent positive TEC anomalies 8 days and almost 3 h before the earthquakes at selected GPS stations, which were nearest to the earthquake preparation area. The anomalous variations in TEC height and plasma density were verified by analyzing the foF2, which confirmed the ionospheric perturbations. Unusual ionospheric disturbances indicate imminent pre-seismic events, which provides the potential opportunity to provide aid for earthquake prediction and natural hazard risk management in Afghanistan and nearby regions. Full article