The bottomside thickness (B0) and shape (B1) parameters are crucial for representing ionospheric electron density profiles below the F2 layer in the IRI (International Reference Ionosphere) model. In the present study, the comprehensive analysis of diurnal, seasonal, longitudinal, and latitudinal variations of B0 and B1 is conducted using FORMOSAT-7/COSMIC-2 radio occultation electron density profiles over 2019–2024 and compared with corresponding IRI-2020 submodels, namely Bil-2000, Gul-1987, and ABT-2009, under different seasonal and solar activity conditions. The results show that B0 and B1 are strongly controlled by geomagnetic latitude and seasons, with maximum values near the equator and an apparent hemispheric asymmetry during the solstice. The consistent coupling among hmF2, NmF2, B0, and B1 is observed in geomagnetic latitude with local time variation, indicating that their variability is controlled by the equatorial dynamics. The magnitude of B0 and B1 primarily increases through solar activity without altering the spatial structure. The longitudinal analysis reveals pronounced modulation in B0, especially during the equinox and summer under high solar activity, whereas B1 exhibits weaker longitudinal dependence. On comparison with IRI-2020, it is observed that the model produces the spatial structure but with systematic differences in magnitude and variability from the COSMIC-2-derived B0 and B1 parameters. The results highlight the importance of these parameters for characterizing low and mid-latitude bottomside ionospheric structure and provide an opportunity for improvements of the empirical ionospheric model.
A report on the geomagnetic variations observed in Chile and Antarctica during the annular solar eclipse of February 26, 2017, is presented. This eclipse was visible from southern Chile in the morning and ended in the Democratic Republic of the Congo at sunset. Using data from three SAMBA network stations positioned at different magnetic latitudes along the 0° geomagnetic longitude and around the path of annularity, we analyzed changes in the geomagnetic field’s X, Y, and Z components during the eclipse. A baseline method, derived from the quietest days of the month, was applied to isolate eclipse-induced disturbances. Our analysis shows a decrease in the X component, an increase in the Y component, and a flattening of the Z component in synchrony with the eclipse. In addition, an analysis of ULF Pc3 pulsations reveals a localized attenuation of wave amplitudes during the eclipse, particularly near the umbral path. These results align with theoretical predictions and previous observations, suggesting a strong influence of the solar eclipse on the observed geomagnetic variations. The study reinforces the role of solar radiation reduction in modulating ionospheric currents and provides insights into the Earth’s magnetospheric response during these events. The study provides evidence of the role of solar radiation in regulating ionospheric currents and geomagnetic field variations in response to transient solar events, particularly in the Chile-Antarctica sector.
Users of the single frequency (SF) Global Navigation Satellite System (GNSS) are most affected by ionospheric delay, especially when solar and geomagnetic activity are at their strongest. Predicting the ionosphere total electron content (TEC) accordingly is therefore crucial for better replacement. Using Seasonal conditions and two intense geomagnetic storms that happened on 1 January and 12 November 2025, during solar cycle 25. This study examine the performance of three broadcast models over the low latitude Indian region. The models are Klobuchar (GPS), NeQuick-G (Galileo) and Neustrelitz TEC Model for Galileo (NTCM-G). we compare the TEC estimation from four GNSS stations (DRDN, BHPL, HYDE, and IISC), spanning low to high latitudes, are validated against the UPCG Global Ionospheric Map (GIM). Model performance is assessed using mean absolute error (MAE) and root mean square error (RMSE). Results show that the NTCM-G model consistently outperforms the Klobuchar and NeQuick-G models under both quiet and disturbed conditions. During the January storm, the NTCM-G model achieves a minimum RMSE of 11.68 TECU, while corresponding errors for NeQuick-G and Klobuchar reach 27.61 TECU and 22.63 TECU, respectively. Similar improvements are observed during the November storm event. Overall, the NTCM-G model demonstrates superior robustness in capturing seasonal variability and storm-time ionospheric disturbances, highlighting its suitability for enhanced ionospheric correction for SF GNSS applications over low-latitude regions.
The ionospheric layer contains free electrons and charged particles, which influence the propagation of radio signals. Total electron content (TEC) is a significant ionospheric parameter that represents the total number of electrons along the path between a radio transmitter and a receiver. Variations in TEC can affect communication and navigation systems and are mainly changed by solar ultraviolet radiation, geomagnetic storms, and atmospheric waves initiating from the lower atmosphere. Besides these activities, earthquakes can also cause TEC disturbances in the ionosphere. This research studies the TEC variations of five significant earthquakes of magnitude greater than 5.9 Mw that happened in Indonesia between the years 2004 and 2024. To do this study, we have selected the earthquakes that include the Western New Guinea, Wharton Basin, Papua, Maluku, and Sarangani events. The required TEC data was recorded from the BAKO GNSS station in Indonesia. In the case of each selected earthquake, TEC values of 30 days prior to that particular earthquake were used in the estimation of median TEC. A comparative analysis is carried out among the observed True TEC, Median TEC, and NeQuick model TEC for five days before and one day after each quake. This comparison is evaluated based on the statistical parameters such as the Root Mean Square Error (RMSE), Mean Absolute Gross Error (MAGE), Nash–Sutcliffe Efficiency (NSE), and Spearman Correlation Coefficient (SCC). The result indicates that the Median TEC is closer to the observed true TEC compared to the NeQuick TEC during these earthquake periods. The variations of TEC were observed at the time of the earthquake; this indicates variations that occurred due to changes in the ionosphere. This study helps to understand the relationship between earthquakes and disturbances in the ionosphere, which will be very effective in doing further research related to seismic studies.
Typhoon formation and development in the ocean area, leading to a major challenge in the study of ionospheric response to typhoon is the sparse distribution of observation sites. To address this limitation, this study proposes a ground and space based (G/SBased) joint ionospheric detection technique that integrates data from ground-based Global Navigation Satellite System (GNSS) receivers and Low Earth Orbit (LEO) satellites. The approach combines LEO-derived Total Electron Content (TEC) with ground-based GNSS-TEC for unified ionospheric modeling. Prior to integration, the LEO-TEC is adjusted using the Chapman function to ensure consistency with the vertical sensing altitude of the ground-based GNSS-TEC. This innovative approach was applied to examine ionospheric anomalies during Super Typhoon Hagibis (1919). The results demonstrate that the G/SBased joint detection method effectively addresses the spatial sparsity of ground based GNSS sites over oceans, substantially increasing both the quantity and spatial homogeneity of ionospheric piercing points (IPPs). This approach resolves the issue of TEC overfitting associated with uneven IPP distribution in ground based GNSS monitoring. Comparative analysis reveals that the G/SBased technique significantly enhances TEC retrieval accuracy in the typhoon’s core region, reducing the mean error (ME) from –3.98 to –0.67 TECU and the root mean square error (RMSE) from 5.83 to 5.16 TECU compared to standalone ground based GNSS measurements. Furthermore, the study identifies distinct ionospheric TEC anomalies in the typhoon center as it approached landfall. The G/SBased joint detection technique exhibits superior capabilities for monitoring typhoon-related ionospheric disturbances. By incorporating LEO satellite constellations, it overcomes the challenge of insufficient direct observation data over ocean areas, which otherwise hinders the use of GNSS observation data to detect typhoon induced ionospheric disturbances in remote seas.
The ionospheric response to the intense geomagnetic storm of 10–13 November 2025 is investigated using multi-latitude GNSS-derived total electron content (TEC), ground magnetic field observations, and geomagnetic indices. The storm was characterized by a minimum Dst of –230 nT and elevated Kp values exceeding 8, while the solar flux F10.7 remained relatively stable. Differential TEC (dTEC) analysis reveals a strong latitude dependence of storm-time ionospheric perturbations. Low-latitude stations exhibit relatively smooth variations within ±15 TECU, mid-latitude stations show enhanced and structured responses reaching ±30–35 TECU, and high-latitude stations experience the largest disturbances, with dTEC values exceeding –40 to –45 TECU during the main phase. Ground magnetic field data indicate increasing disturbance amplitudes with latitude, and wavelet analysis of TEC residuals shows enhanced power during the storm main and early recovery phases, with dominant shorter-period fluctuations at higher latitudes. These results demonstrate the significant latitude-dependent impact of intense geomagnetic storms on ionospheric TEC and highlight the importance of multi-latitude GNSS observations for characterizing storm-time ionospheric variability. Pre-storm analysis shows that TEC variability during the 2–3 days prior to the sudden storm commencement (SSC) remained comparable to quiet-time levels, with no coherent ionospheric precursor. These results demonstrate a pronounced latitude-dependent ionospheric response to intense geomagnetic storms and highlight the importance of coordinated multi-latitude GNSS observations for understanding storm-time magnetosphere–ionosphere–thermosphere coupling.
This study investigates the ionospheric response over the East Africa region during solar flares and a geomagnetic storm from 8–15 May 2024. During this period, 12 X-class solar flares and one extreme geomagnetic storm occurred, causing pronounced variability in total electron content (TEC). X-ray flux measurements from the Extreme Ultraviolet and X-ray Irradiance Sensors (EXIS) on board the Geostationary Operational Environmental Satellites (GOES) are analyzed to detect solar flares. TEC derived from four GNSS receiver stations and the IRI-2020 model, O/N2 ratio maps, and an ionospheric electric fields model are used to identify ionospheric variation owing to the space weather events. The X-class flares prior to May 11 produced immediate TEC enhancements of up to +15 TECU relative to quiet day levels, consistent with sudden ionospheric disturbances. In contrast, the geomagnetic storm on May 10–11 induced both positive and negative storm phases, with TEC deviations ranging from –31.46 to +33.13 TECU. During the main phase of the geomagnetic storm, at the ADIS station, TEC increased by +10.8 TECU and then decreased by –8 TECU. In the recovery phase, it increased to +31 TECU. At the DJIG station during the main phase, TEC decreased by –16.1 TECU, followed by a significant positive enhancement reaching +30.5 TECU on May 12th. Similarly, the MAL2 station recorded a minimum negative TEC deviation of –16.6 TECU during the main phase, with a notable maximum positive deviation of +33.03 TECU also occurring on May 12th. For the MBAR station, the main storm phase on May 10th showed a minimum negative TEC deviation of –15.94 TECU, and a maximum positive deviation of +33.13 TECU was observed on May 12th. We have used correlation coefficients ( r ), Percentage Root-Mean Square Error (PRMSE) and root mean square errors (RMSE) to examine the variation of the IRI-2020 TEC from the GPS TEC during the storm. The results show that the model performed best at the ADIS station, with the highest r (0.93) and the lowest RMSE (13.33) and PRMSE (28.31
In this paper, we employ equatorial-latitude Global Navigation Satellite System (GNSS) data from TERONET to investigate the storm that occurred on August 27, 2021. To characterize the equatorial and mid-latitude ionosphere during the storm, the 10 quietest days of August 2021 were selected as background TECs, and we calculated the relative TEC (rTEC) from the deviation of the disturbed days using a median value of the TEC at each timestep, considering all 10 days and selecting the threshold |–30 ≤ rTEC ≥ 30| for the TEC anomaly. Additionally, we employ the African geodetic reference frame (AFREF) GNSS network to analyze the data from 19 stations in the African region during storms. We employ ROTIave as a proxy for scintillation to study irregularities and GNSS fluctuations during storm main and recovery phases and examine thermospheric variations from the [O]/[N2] ratio. Again, we employ the depression of the horizontal component (H) of the Earth’s magnetic field obtained from equatorial and mid-latitude magnetometers to feature the seeding of the TEC enhancements and depression. Our major findings reveal that ionospheric irregularities at low latitudes, as observed from GNSS measurements, show distinct latitudinal differences and seem not well experienced at the dip equator. The equatorial and mid-latitude ionosphere of the Africa sector shows a complex irregularity occurrence that may not have a stronger effect of the solar activity cycle but seems to follow storm-enhanced density, where morning-hour positive storms govern irregularities during the commencement of storms preceded by the equatorial ionization anomaly (EIA) due to localized expansion of the neutral atmosphere.
Ionospheric variability due to solar flares has been studied at different latitudes during the solar cycle 24. In the course of this cycle 24 on September 6, 2017, two powerful and intense solar flares of class X2.2 and X9.3 were emitted by the Sun at 0857 UT and 1153 UT respectively. To examine the ionospheric response simultaneously at low, mid, and high latitudes, total electron content (TEC) values derived from Global Navigation Satellite System (GNSS) receivers were investigated during the solar flare of September 6, 2017, which are the most remarkable flare events during the solar cycle-24. Our observations show a noticeable enlargement in TEC at low, mid, and high-latitude stations. Further, the mean method has been used to investigate TEC variations due to solar flares at low, mid, and high latitudes and considered all PRN which has a one-to-one correlation with the time of solar flares. We describe our findings in the context of earlier research which examined the correlation between change in VTEC (DVTEC) and solar fluxes in X-class solar flares. The aim of this study is to minimize the latitudinal variability of total electron content (TEC) during such events, although the extent of TEC increase seems to be influenced by the class of the solar flare. The results exhibited that X-class flare effects were more pronounced at low latitudes in comparison to mid and high latitudes.
Geomagnetic storms, driven by solar wind–magnetosphere interactions, can significantly disturb the ionosphere, altering electron density and degrading satellite-based communication and navigation systems. The extended geomagnetic storm that occurred from November 5–6, 2023, presents a noteworthy but little-studied chance to investigate its multi-parameter impacts on the ionosphere of South Africa. Although previous research has examined ionospheric disturbances in the area, this event’s prolonged duration and dynamic solar wind solar wind parameters. The findings show significant TEC depletion at five GPS stations. The most noticeable decrease was seen at Springbok (SBOK) on November 6, when the minimum Δ TEC was –35.88 TECU in comparison to International Quiet Days for the case of severe geomagnetic storms and latitudinal positions. Magnetic field data from the Hartebeesthoek observatory showed significant storm-time disturbances in the northward (X), eastward (Y), and horizontal (H) components. These variations are attributed to intensified ionospheric Hall and Pedersen currents, where X reflects the dominant Pedersen current aligned with the geomagnetic field, Y indicates enhanced Hall currents due to zonal electric fields, and H captures the net horizontal current response. Furthermore, Global Ultraviolet Imager (GUVI) satellite measurements recorded a sharp decline in the thermospheric O/N2 ratio over South Africa during the main phase of the storm, indicative of increased recombination rates that suppress electron density. These findings underscore the importance of continued space weather monitoring and ionospheric modeling in the African region to support GNSS reliability and regional forecasting capabilities.
This study presents a comparative statistical analysis of solar activity during the first six years of Solar Cycles 24 (2008–2013) and 25 (2019–2024). The analysis focuses on key solar and geophysical parameters, including sunspot numbers, halo coronal mass ejections (CMEs), solar radio flux at 10.7 cm (F10.7), and geomagnetic storms, to assess differences in solar behavior between the two cycles. Sunspot numbers varied between 0 and 139.1 in Solar Cycle 24, whereas they ranged from 0.2 to 216 during the corresponding period of Solar Cycle 25. Similarly, the F10.7 cm radio flux fluctuated between 65.7 and 153.5 in solar flux unit (s.f.u.) during 2008–2013, and between 67.05 and 245.6 s.f.u. from 2019 to 2024, reflecting an overall increase in solar output. The study also includes an analysis of halo CMEs, with 192 events observed during Solar Cycle 24 and 227 during Solar Cycle 25, both characterized by an angular width of 360°. Geomagnetic activity was assessed using 104 events from Cycle 24 and 179 from Cycle 25, with disturbance storm time (Dst) index values ranging from –50 to –350 nT. The results indicate a significant increase in solar activity during the early phase of Solar Cycle 25 compared to Solar Cycle 24. This suggests a more intense and dynamic space weather environment in the current solar cycle, which may have important implications for space weather forecasting and satellite operations.
The present study investigates the subauroral ionospheric response to geomagnetically disturbed conditions across different seasons of 2012, using Total electron content (TEC) and S4 index data derived from a Global Positioning System (GPS) receiver installed at the Indian Antarctic station Maitri (geographic coordinates: 70.76° S, 11.74° E). TEC and S4-index measurements for January, March, and June 2012 were analysed alongside the corresponding Auroral Electrojet (AE) index and the interplanetary magnetic field (IMF) Bz component to assess seasonal variability in ionospheric behaviour. The results reveal that the subauroral ionosphere exhibits a negative response (i.e., TEC depletion) during periods of southward IMF Bz orientation, whereas a positive response is generally observed during northward IMF Bz, particularly during the summer and equinoctial periods. In contrast, this trend appears to reverse during the winter season. The observed negative ionospheric responses are attributed to a combination of equatorward plasma transport and thermospheric compositional changes. Additionally, poleward compression of the auroral oval and enhanced molecular precipitation are believed to contribute to these depletions. Furthermore, the study examines the occurrence characteristics of amplitude scintillations under disturbed geomagnetic conditions. It is observed that the intensity of amplitude scintillation during the winter (polar night) is significantly higher compared to that during summer and equinox periods, suggesting enhanced small-scale ionospheric irregularities under such conditions.
We analyzed the occurrence and characteristics of various types of magnetic storms during solar cycle 24. The annual mean total sunspot number (SSN) was used to quantify solar cycle activity. The intensity and classification of magnetic storms, by type and rank, were assessed using two geomagnetic indices: Dst (Disturbance Storm Time Index) and aa (global geomagnetic activity index), respectively. Based on the minimum Dst values, we identified a total of 130 magnetic storm events, comprising 104 moderate and 26 intense storms. Using the maximum aa values, we further classified these events by type and rank. Among them, 54 storms displayed sudden commencement (S-storms), while 76 storms exhibited gradual commencement (G-storms). Additionally, the types of storms were categorized by five ranks. According to established literature, the main common sources of storms are issued from interplanetary coronal mass ejections (ICMEs) and corotating interaction regions (CIRs). Our findings revealed that 76
This study aims to investigate the energy transfer mechanisms and the behavior of thermal conductivity of this region by examining the thermal conductivity coefficients calculated for critical altitudes in the F region of the ionosphere. Electron-ion collisions and the geometry of the magnetic field affect these coefficients. The thermal conductivity in the ionosphere can exhibit anisotropic properties (different values in different directions) due to the directional dependence of the Earth’s magnetic field. Theoretical approaches have been used and numerical calculations have been performed to analyze the thermal conductivity of the ionosphere. The findings indicate that the magnitudes of the thermal conductivity coefficients were at the level of electrical conductivity and the tensor elements (Kzx, Kxz, Kyz, Kzy) were negative, while the Kyx, Kxy elements were positive up to the equator and then became negative. This phenomenon, called effective thermal conductivity, is not actually a negative value for thermal conductivity, but rather an unusual situation resulting from the direction-dependent effect of the magnetic field. It has been determined that the magnitudes of the tensor elements on March 21 are slightly greater than those on September 23.
Estimating with low uncertainty the parameters of time and magnitude of upcoming earthquakes is necessary to create an earthquake warning system. Nowadays, by using different satellite data, it is possible to monitor a large number of earthquake precursors. Multi-precursor analysis, along with multi-method analysis, has made it possible to detect a large number of LAI (lithospheric atmospheric ionospheric) seismic anomalies in the study of strong earthquake-affected areas. In this study, the deviation values of 898 LAI anomalies detected using 20 implemented predictor algorithms around the time and location of 21 powerful earthquakes that occurred in recent years have been considered. Using different scenarios, various functions were fitted on the collected data, including the day of anomaly observation, anomaly intensity, geographic latitude of epicenter and real magnitude of the earthquake, and functions were developed to estimate magnitude parameters with RMSE of about 0.53 (MW) and the day of the earthquake with about RMSE of 8.27 day. In addition, by using an MLP neural network, and training it using the detected LAI anomalies, accuracies of 0.21 and 9.29 were obtained, respectively, for estimating the magnitude and time of an impending earthquake. Therefore, by comparing the two functional and machine learning-based methods proposed in this study, it can be concluded that the proposed functions are efficient for estimating magnitude and time of forthcoming strong earthquakes. Although the accuracy of predicting the magnitude of the earthquake is acceptable, the accuracy of about 8 days for predicting the day of the earthquake can be efficient for relatively short-time earthquake prediction.
Geomagnetic storms (GSs), driven by solar activity, produce significant disturbances in the Earth’s magnetic field—particularly in its horizontal component (H). This study investigates the response of the H-component to GSs during solar cycle 24 (2009–2019), using ground-based magnetometer data recorded at the TAM observatory in Tamanrasset, Algeria (22.79° N, 5.53° E), part of the INTERMAGNET network. A total of 130 storms were identified based on Dst-index thresholds and classified into 104 moderate (–100 nT < Dst ≤ –50 nT) and 26 intense (Dst ≤ –100 nT) events. The H-component was derived from the orthogonal north and east components (X, Y) of the geomagnetic field. The results reveal a gradual upward trend in the H-component over the solar cycle, consistent with secular geomagnetic field variations. However, during storm periods, the H-component exhibited significant decreases. These disturbances were quantified using the maximum deviation parameter ΔHmax, which displayed a statistically significant positive correlation with storm intensity (r = 0.71). Notably, the correlation was stronger for intense storms (r = 0.75) than moderate ones (r = 0.38). These results highlight the greater sensitivity of low-latitude geomagnetic observatories to high-intensity storms and demonstrate the diagnostic value of ΔHmax for space weather monitoring.
Taking into account the real magnetic field geometry of Earth in the northern hemisphere, this work produced the equations of real diffusion coefficients for the ionospheric F region (390, 410, 450, 500, 550, 600 km) at low latitudes. In a steady state, diffusion coefficients show real values, while in an unstable state, they show complex values with real and imaginary components. We performed numerical calculations at F region altitudes within the ionospheric plasma to determine the diffusion coefficients for both cases. The results show that in the steady state, the diffusion coefficients have values that are very close to the speed of light. In unstable conditions, on the other hand, the real parts are generally close to the conductivity values, while the imaginary parts are similar to the sound speed magnitudes. The fundamental focus of this technique is to demonstrate and calculate the complex structure of diffusion coefficients in the ionosphere, representing the first such instance in the literature.
Ground-based electron density measurements from ionosondes are used to evaluate the accuracy of ionospheric empirical models, such as the International Reference Ionosphere (IRI) and the NeQuick models. In the present study, the results obtained from ionosonde and empirical models (NeQuick2, IRI2016, and IRI2020) of the electron density at the Addis Ababa, Ethiopia ionosonde station, with a geographic latitude of 9.03° N and longitude 38.76° E on selected days in 2014 are presented. In the comparison of the NeQuick2, IRI2016, and IRI2020 models with the ionosonde data, the percentage deviation and the correlation coefficient (R) are used as measures of the performance of the models. The overall results show that the latest version of the IRI2020 model outperforms NeQuick2 and IRI2016 in ionospheric electron density value, with NeQuick2 showing slightly better performance than IRI2016. Mostly, the NeQuick2, IRI2016, and IRI2020 models show overestimation of the electron density values from the ionosonde data. The NeQuick2 model overestimates with a maximum percentage deviation of 38
An Erratum to this paper has been published: https://doi.org/10.1134/S0016793225550018
