Total Electron Content Variations Research Articles

A machine learning approach for total electron content (TEC) prediction over the northern anomaly crest region in Egypt

In this paper, we developed an empirical model for predicting Total Electron Content (TEC) on a single station receiver located within the equatorial anomaly crest region at Helwan – Egypt (29.86°N, 31.32°E & MLAT 27.02°N). The neural network algorithm was developed from several inputs representing diurnal, seasonal, and solar cycle variations, solar and geomagnetic activity, and solar wind parameters using TEC data collected by the SCINDA GPS receiver. The TEC data collected for about nine years from 2009 to 2017 comprises almost the whole solar cycle 24 allowing the developed model to be validated and tested for different solar activity conditions. The 2009 – 2016 dataset was randomly divided into 70% for training, and 30% for validation during model development while the 2017 dataset was reserved for testing the model during independent validation. The validation was done by comparing TEC from the developed model and TEC derived from the GPS scintillation and TEC monitor (GPSTEC). Knowing that TEC modeling over the equatorial anomaly crest regions is challenging since it is characterized by high temporal and spatial variations, the developed model reconstructed diurnal GPSTEC from 2014 to 2016 with a root mean square error (RMSE) of 4.0 TECU and 3.2 TECU for high and low solar activity phases respectively. The neural network (NN) modeled TEC was highly correlated with GPSTEC, that is 0.93 and 0.94 for low and high solar activity respectively. In comparison, the International Reference Ionosphere (IRI)-2016 model predicted the general trend of GPSTEC in 2017 with RMSE of 5.43 TECU better than the developed TEC model with RMSE of 5.74 TECU. However, the NN model predicted diurnal GPSTEC for selected quiet and disturbed days, and seasonal TEC better than the IRI model in 2017. Therefore, the developed model was able to capture temporal ionospheric TEC for diurnal and seasonal variations during low solar activity. It was established that the performance of the empirical model depends on the size and distribution of the data used for model development. It’s worth noting that despite the improved performance of the NN algorithm in predicting diurnal and seasonal TEC variation, the NN-modeled TEC performed poorly in reconstructing the nighttime anomalies exhibited in the GPSTEC. The inclusion of the IRI-NmF2 as network input also adds to the improved performance of the network.

Variations of ionospheric TEC due to coronal mass ejections and geomagnetic storm over New Zealand

The variations of ionospheric Total electron content (TEC) due to coronal mass ejections (CMEs) and geomagnetic storms over New Zealand were studied. TEC data were collected from dual-frequency GPS sites operated by the University NAVSTAR Consortium in New Zealand, at Ous2 (−45.86°N, 170.51°E), Dund (−45.89°N, 170.59°E), Mtjo (−43.99°N, 170.46°E), and Quar (−43.53°N, 169.81°E) stations. The findings of this study show that the variability of ionospheric TEC was more noticeable during the main phase of the storm on September 08, 2017 than the initial phase on September 07, 2017, recovery phase on September 09, 2017, and during the CME day on September 06, 2017. Also, the enhancements of change in TEC (ΔTEC) were pronounced more over the Mtjo station during the CME day and over the Quar station during the geomagnetic storm day than over other stations. On September 06, 2017, two X-class solar flares, specifically X2.2 and X9.3, were observed with quiet geomagnetic storm conditions throughout the CME day, resulting in an increase in TEC. On September 07, 2017, the M7.3, X1.3, and on September 08, 2017, the X8.1 solar flare classes with disturbed geomagnetic conditions led to a significant enhancement of TEC over the stations at 02:00 UT (13:00 LT). Finally, during the main phase of the storm, the solar wind electric field (IEF Ey) and prompt penetration electric field (PPEF) showed good correlations in which the fluctuation of PPEF, an increase in Ey, Dst minimum, and horizontal Earth’s magnetic field are well associated with strong changes in TEC.

Statistical Study of the Ionospheric Slab Thickness at Yakutsk High-Latitude Station

The ionospheric equivalent slab thickness (EST, also named τ) is defined as the ratio of the total electron content (TEC) to the F2-layer peak electron density (NmF2), and it is a significant parameter representative of the ionosphere. This paper presents a comprehensive statistical study of the ionospheric slab thickness at Yakutsk, located at the high latitude of East Asia, using the GPS-TEC and ionosonde NmF2 data for the years 2010–2017. The results show that the τ has different diurnal and seasonal variations in high- and low-solar-activity years, and the τ is greatest in the winter, followed by the equinox, and it is smallest in the summer in both high- and low-solar-activity years, except during the noontime of low-solar-activity years. Specifically, the τ in inter of high-solar-activity year shows an approximate single peak pattern with the peak around noon, while it displays a double-peak pattern with the pre-sunrise and sunset peaks in winter of the low-solar-activity years. Moreover, the τ in the summer and equinox have smaller diurnal variations, and there are peaks with different magnitudes during the sunrise and post-sunset periods. The mainly diurnal variation of τ in different seasons of high- and low-solar-activity years can be explained within the framework of relative variation of TEC and NmF2 during the corresponding period. By defining the disturbance index (DI), which can visually assess the relationship between instantaneous values and the median, we found that the geomagnetic storm would enhance the τ at Yakutsk. An example on 7 June 2013 is also presented to analyze the physical mechanism. It should be due to the intense particle precipitation and expanded plasma convection electric field during the storm at high-latitude Yakutsk station. The results would improve the current understanding of climatological and storm-time behavior of τ at high latitudes in East Asia.

Deep Learning of Detecting Ionospheric Precursors Associated With M ≥ 6.0 Earthquakes in Taiwan

AbstractA short‐term (30 days before an earthquake) prediction of an earthquake is a big challenge in seismology. As a first step, we apply deep learning to the ionospheric total electron content (TEC) data between 2003 and 2014 to detect the seismo‐ionospheric precursors of M ≥ 6.0 earthquakes in Taiwan. The bidirectional Long Short‐Term Memory (Bi‐LSTM) network is employed to use observed input data (features) to obtain the sequential TEC variations. The five input features are sequential vectors of TEC, the geomagnetic index Dst, the solar activity index F10.7, sunspot number (SSN), and solar emission index Lyman‐α. The daily values of F10.7, SSN, and Lyman‐α are converted into hourly values, depending on the solar elevation angle. The calculated hourly TEC variations can be more precisely predicted with this data conversion. We calculate the normalized difference of errors between two 15‐day adjacent stages as the “relative error”. Three trained models with the best discrimination between the relative errors of earthquake and no‐earthquake cases are chosen as classifiers. These three classifiers are then used to have a majority vote to declare whether the 30‐day period is related to the preparation of an earthquake or not. The results show that all 22 positive cases (earthquakes) are successfully predicted, giving a true positive rate of 100%. Among the 19 negative cases (normal cases), 10 of them are true negative.” Overall, a high accuracy of 78.05% is obtained.

Ionospheric Semidiurnal Lunitidal Perturbations During the 2021 Sudden Stratospheric Warming Event: Latitudinal and Inter‐Hemispheric Variations in the American, Asian‐Australian, and African‐European Sectors

AbstractThe ionosphere exhibits enhanced semidiurnal lunitidal (M2) perturbations during sudden stratospheric warming (SSW) events, of which the manifestation and mechanism are not well documented and understood. This paper studies the latitudinal and inter‐hemispheric variations of the ionospheric M2 perturbations during the 2021 major Arctic SSW with total electron content (TEC) data in the American, Asian‐Australian, and African‐European sectors. Results show that the M2 perturbations in the three sectors all enhanced during the SSW, with the strongest M2 perturbations in the Northern and Southern Hemispheres at about 10°∼15°N and 25°∼30°S geomagnetic latitudes, respectively. Also, clear M2 perturbations in the three sectors all extended to middle latitudes during the SSW only in the Southern Hemisphere. Comparatively, the inter‐hemispheric asymmetry of the magnitude of the M2 perturbations during the SSW was more complex. The inter‐hemispheric asymmetry of the crest locations of the low‐latitude M2 perturbations in the three sectors during the SSW was probably due to the F‐region meridional wind effect on the diffusion process of the low‐latitude plasma fountain. Meanwhile, the longitudinal differences were also obvious. The TEC M2 amplitude in the American sector was obviously larger than those in the Asian‐Australian and African‐European sectors during the SSW. The M2 characteristics in the southern middle latitude in the American sector were significantly different from those in the other two sectors during the SSW, which may be related to the differences of the combined effects of the local wind and geomagnetic configuration. In addition, a moderate geomagnetic activity occurred during the 2021 SSW, which brings difficulties to the analysis of the SSW‐related TEC variation.

Precursors Identification for Forecasting UHF‐Band Ionospheric Scintillation Events Over Chinese Low‐Latitude Region by Deep Learning

AbstractThe occurrences of the UHF‐band ionospheric scintillation events caused by Equatorial Plasma Bubbles (EPBs) in the low‐latitude region depend on many factors. Nowadays, it is also a hard work for researchers to analyze and find out the useful precursory signatures of the generation of EPBs from several kinds of observations, which is a necessary work to build a forecasting model base on the priori knowledge. Many studies have revealed that there are distinctive features of daytime background ionosphere characteristics on scintillation and nonscintillation days. Deep learning technique (DLT) could automatically discover the distinctive variations from the daytime background ionospheric observations of scintillation and nonscintillation days. It is found that the forecasting problem of postsunset ionospheric scintillation events could be converted to a classification problem, and easily solved by DLT. The effectiveness of DLT for building a forecasting model of the UHF‐band ionospheric scintillation events over Chinese low‐latitude region is studied and evaluated. By analyzing the performance metrics of different combinations of related factors as the input parameters of DLT, a new important precursor for forecasting the UHF‐band ionospheric scintillation events over Chinese low‐latitude region is identified for the first time. It is suggested that the latitudinal and diurnal variations of the transequatorial Total Electron Content (TEC) profile in the east of the forecasting area is one of the key precursors.

Climatology of global, hemispheric and regional electron content variations during the solar cycles 23 and 24

We present the results of study on the variations of ionospheric total electron content (TEC) by using global, hemispheric, and regional electron contents computed from the global ionospheric maps (GIMs) for the period from 1999 to 2020. For a low and moderate solar activity, the global and regional electron contents vary linearly with solar 10.7 cm radio flux and EUV flux. While a saturation effect in the electron content verses EUV and F10.7 is found during the high solar activity periods at all regions, the maximum effect is observed at low-latitudes followed by high and mid-latitudes region. The extent of saturation effect is more pronounced for F10.7 as compared to EUV. A wavelet transform is applied to global and hemispheric electron contents to examine the relative strength of different variations. The semi-annual variations dominate in the northern hemisphere, whereas annual variations dominate in the southern counterpart. The amplitude of annual variations in southern hemisphere is found to be higher than northern counterpart at all latitudes. This asymmetry in the amplitude of annual variation is maximum at low-latitudes, followed by mid and high-latitudes, respectively. The semi-annual variations are in-phase in both hemisphere and follow the solar cycle. The northern hemisphere depicts relatively large amplitude of semi-annual variations and exhibit the maximum effect at high-latitudes.

Ionospheric precursors of strong earthquakes observed using six GNSS stations data during continuous five years (2011–2015)

This study reports the morphological characteristics of anomalous variations in Global Navigation Satellite System Total Electron Content (GNSS-TEC) prior to the strong local earthquakes (EQ) that occurred during the period of 2011–2015. We have analyzed 20 earthquakes of magnitude M ≥ 5.6. A statistical technique is implemented on the data of six GNSS stations located in Tashkent, Kitab, and Maidanak in Uzbekistan, and Islamabad, Multan, Quetta in Pakistan. The results show continuous anomalous variations in TEC during 24 h before the occupancy of local earthquakes. It is shown that the precursors before the occurrence of strong earthquakes, in particular of magnitude 5.7, 7.7, 7.5, 7.8 and 7.3 are detected near Eastern Uzbekistan (26 May 2013), Southwestern Pakistan (24 September 2013), Hindukush region of Afghanistan (26 October 2015), and Central Nepal (25 April 2015) and (12 May 2015), respectively. The ionospheric anomalies appearing before the strong earthquakes at six GNSS stations are registered in 14 cases (70%) out of 20 selected EQs. It is depicted that anomalies referred to as ionospheric precursors appeared about 1–7 days prior to the occurrence of strong earthquakes.

Altitude Distribution of Large and Small‐Scale Equatorial Ionospheric Irregularities Sampled From an Elliptical Low‐Earth Orbit

AbstractWe provide insight into the vertical distribution of multi‐scale scintillation‐inducing irregularities in the low‐latitude ionosphere. In four sets of novel experiments, we sampled altitudes from 330 to 1,280 km in the 18–24 magnetic local time (MLT) sector using the Swarm Echo GPS Attitude, Positioning, and Profiling Experiment occultation receiver (GAP‐O) GPS receiver with its antenna oriented toward zenith. In order to identify multi‐scale irregularities both above and at the satellite's position, we utilize high‐sample‐rate GAP‐O amplitude and phase measurements along with a measurement of net current on the surface of the imaging and rapid‐scanning ion mass spectrometer sensor on board, which serves as a proxy for density variations. By calculating the rate of change of total electron content index using two sets of GPS parameter choices, we are able to sample irregularities as small as 160 m, which is comparable to or smaller than the Fresnel scale responsible for scintillation‐inducing irregularities. During one campaign, we find that amplitude scintillations on the GPS signal coincide with strong in‐situ small‐scale density irregularities in 32% of cases, indicative of a broad irregularity region extending from the satellite's position to hundreds of kilometers above. Also, we show that large‐scale ionospheric disturbances (larger than 80 km) occur predominantly below 500 km, and down to the 330 km perigee of Swarm Echo in the 18–21 MLT sector. In contrast, small‐scale variations of total electron content are detected at all MLTs between 18 MLT and magnetic midnight and at all altitudes sampled in this experiment. However, they are more frequent in the 22–24 MLT range.

An Investigation of Ionospheric TEC Prediction Maps Over China Using Bidirectional Long Short‐Term Memory Method

AbstractThe ionospheric total electron content (TEC) is an important ionospheric parameter, and it is widely utilized in research such as space weather prediction and precise positioning. However, it is still challenging to develop an ionospheric TEC prediction model with high accuracy. In this study, a new ionospheric TEC model over China was developed using the bidirectional long short‐term memory (bi‐LSTM) method and observations from 257 ground‐based global navigation satellite system (GNSS) stations in the Crustal Movement Observation Network of China from January 2018 to December 2021. The root mean square errors of the bi‐LSTM‐based model’s 1 and 2 hr ahead predictions on the test data set (from June 2021 to December 2021) are 1.12 and 1.68 TECU, respectively, which are 75/50/32% and 72/48/22% smaller than those of the IRI‐2016, artificial neural network and LSTM‐based models, correspondingly. The bi‐LSTM‐based model shows the best performance, which is most likely due to the fact that the sequence information in both forward and backward directions is taken into consideration in the new model. In addition, the diurnal variation, seasonal variation of the ionospheric TEC, and variations under geomagnetic storm conditions are successfully captured by the bi‐LSTM‐based model. Moreover, the TEC maps resulting from the bi‐LSTM model agree well with those obtained from the final ionospheric product from the Chinese Academy of Sciences. Hence, the new model can be a good choice for the investigation of the spatiotemporal variation trend in the ionosphere and GNSS navigation.

A Preliminary Study on Ionospheric Scintillation Anomalies Detected Using GNSS-R Data from NASA CYGNSS Mission as Possible Earthquake Precursors

Ionospheric perturbations affect the propagation of electromagnetic waves. These perturbations, besides being a problem for space communications, satellite navigation, and Earth observation techniques, could also be used as another Earth observation tool. Several recent studies showed correlations with earthquakes with ionospheric anomalies, but almost all of them use ground stations to measure the Total Electron Content (TEC) variations, and, in particular, the ones occurring after an earthquake. Here, a preliminary study is presented on how the ionospheric scintillation measured with GNSS-R instruments over oceanic regions shows a small, but detectable correlation with the occurrence of earthquakes, which in some cases occurs before the earthquakes. This study uses GNSS-R data from NASA CYGNSS Mission to measure the ionospheric amplitude scintillation (S4) for 6 months from March 2019 to August 2019, applying a statistical analysis based on confusion matrixes, and the Receiver Operating Characteristic (ROC) curves to correlate S4 anomalous variations to earthquakes. A small positive correlation is found between the ionospheric scintillation and the earthquakes during the six previous days. However, the study has some weakness because (a) a small number (∼45) of large (M > 6) earthquakes over oceanic regions are studied, (b) the region studied is close to the geomagnetic equator, where ionospheric scintillations are usual, and (c) the overall correlation is small.

Solar activity influence on the temporal and spatial variations of the Arctic and Antarctic ionosphere

Based on Total Electron Content (TEC) data in polar areas derived from Global Ionospheric Maps (GIMs) and observations of single GPS stations from 2000 to 2020, combined with solar activity parameters F10.7, the influence of solar activity on the polar ionosphere is studied. Firstly, the spatiotemporal variation characteristics of the Arctic and Antarctic ionosphere TEC are analyzed in different solar activity intensities. Secondly, the correlations between polar TEC and F10.7 are studied in different solar activity stages. Thirdly, the variations of TEC during the polar day and polar night in year of very low solar activity (2008) are analyzed. The results show the monthly average value of the polar ionospheric TEC reaches its maximum in May and June under the influence of solar activity. However, during the peak year of solar activity, the monthly average peak value of TEC may arrive early, reaching its maximum value in March or April. The dependence of polar TEC on the solar activity varies at different periods of solar activity (rising or declining period). The correlation between polar TEC and F10.7 is higher in the declining period of solar activity than in the rising period of solar activity. During the rising period of solar activity, the TEC at different times under the same solar activity intensity is also different, and the low value of TEC has a lower correlation with solar activity. The ionosphere at the Arctic and Antarctic is quiet during polar night in 2008, and ionization patch appears in the Arctic. During the polar days, the ionospheric peaks of the Arctic and Antarctic occur in the areas with a high solar irradiation altitude angle. However, the ionospheric peak region in the Antarctic area from 10:00 UT to 20:00 UT does not follow this rule.

Study of the equatorial ionosphere using the Giant Metrewave Radio Telescope (GMRT) at sub-GHz frequencies

ABSTRACTRadio interferometers, which are designed to observe astrophysical objects in the universe, can also be used to study the Earth’s ionosphere. Radio interferometers like the Giant Metrewave Radio Telescope (GMRT) detect variations in ionospheric total electron content (TEC) on a much wider spatial scale at a relatively higher sensitivity than traditional ionospheric probes like the Global Navigation Satellite System (GNSS). The hybrid configuration of the GMRT (compact core and extended arms) and its geographical location make this interferometer an excellent candidate to explore the sensitive regions between the northern crest of the Equatorial Ionization Anomaly (EIA) and the magnetic equator. For this work, a bright radio source, 3C 68.2, is observed from post-midnight to post-sunrise (∼ 9 h) to study the ionospheric activities at solar-minima. This study presents data reduction and processing techniques to measure differential TEC ($\delta \rm {TEC}$) between the set of antennas with an accuracy of 1 × 10−3 TECU. Furthermore, using these $\delta \rm {TEC}$ measurements, we have demonstrated techniques to compute the TEC gradient over the full array and micro-scale variation in 2D TEC gradient surface. These variations are well equipped to probe ionospheric plasma, especially during the night-time. Our study, for the first time, reports the capability of the GMRT to detect ionospheric activities. Our result validates, compared to previous studies with VLA, LOFAR, and MWA, the ionosphere over the GMRT is more active, which is expected due to its location near the magnetic equator.

Amplitude enhancement of short period GPS-TEC oscillations over rainfall area

Correlation between rainfall and short period GPS-TEC (total electron content) variations are investigated by using the precipitation data obtained on the ground and estimated from satellite observations (JAXA/GSMaP) as a proxy of lower atmospheric wave activity. The GPS-TEC data obtained at a tropical station, PHIM, in Phimai, Thailand, for 2014–2020, and the data obtained at a mid-latitude station, NAKG, in Tokara Nakanoshima Island, Japan, for 2017–2019, are examined. A statistical analysis of MEM (maximum entropy method) power spectral density (PSD) in the period range from 50 to 1200 s over PHIM clearly shows an enhancement in the cases of rainfall from that in no-rainfall cases, in particular, on the dusk side. The enhancement is observed both acoustic wave periods less than 5–6 min and internal gravity wave periods more than 10 min. The enhancement after sunset could be an effect of strong rainfall more frequent on the dusk side than that in other local time, or it could suggest the importance of ionospheric electron density profile change for the TEC variation. On the other hand, the PSD does not show such clear enhancement over NAKG on the dusk side, although it shows a small enhancement on both dayside and night-side. A clear PSD bulge near the main vertical acoustic resonance periods, i.e., around 275 s, appears in the average PSD profile of the TEC at PHIM, which suggests that the resonance effect contribute to some extent the PSD enhancement under rainy condition. An event analysis also suggests the contribution of acoustic resonance to the enhancement of the short period TEC variation. A complicated spatial distribution of TEC oscillation over a rainfall area around PHIM, where the TEC oscillations with various periods co-exist, is presented.Graphical

GPS observations of ionospheric TEC variations over Nepal during 22 July 2009 solar eclipse

As the study of ionospheric behavior during various solar activities is an important task, various studies of ionospheric changes during eclipse events have been widely performed in the different regions of the globe. This paper investigates the ionospheric responses to the solar eclipse on 22 July 2009 over Nepal using the total electron content (TEC) measured by dual-frequency Global Positioning System (GPS) receivers. The time-averaged Vertical TEC (vTEC) of ten GPS stations from Nepal is analyzed and it is found that the value of ionospheric TEC decreases due to the reduction of ionizing radiation. In addition, the deviation in the TEC value on eclipse day from the mean vTEC value of the top five quietest days is found to lie in the range ~1–5 TECu at those regions which were associated with the partial eclipse shadow. On the other hand, the region with the total eclipse (BRN2 and RMTE) faced ~6–7 TECu on average reduction in the TEC value. Considering that the eclipse of 22 July 2009 occurred just at sunrise in the Nepalese zone, a maximum reduction of about 5 TECu is very significant. Higher deviation in TEC is therefore linked with the path of totality and the obscuration rate. This study reveals that the ionospheric TEC over Nepal was altered by wave-like energy and momentum transport, as well as obscuration of the solar disc due to the partial and total solar eclipse. Furthermore, the cross-correlation results presented similar type signatures of the eclipse-induced ionospheric modification over Nepal. This research work serves a crucial future reference for the comparative study of change of ionospheric TEC variability over the Nepal region during Eclipse events

A comparative study of ionospheric TEC diurnal variations at two stations near cusp latitudes in the Southern Hemisphere

Based on ionospheric total electron content (TEC) data for Zhongshan station (ZHS) and Scott Base station (SBA) in Antarctica, acquired during 2010–2020, high-latitude ionospheric TEC diurnal variations of two near cusp latitude stations were studied. The magnetic latitude and longitude differences between the two stations were approximately 5° and 135°, respectively. It was found that during the 11-year solar activity cycle, the maximum diurnal variation of the ionospheric TEC at ZHS occurred mainly between local noon and magnetic noon. Statistically, the TEC peaks occurred closer to local (magnetic) noon under low (high) solar activity conditions. The maximum diurnal variation of ionospheric TEC at SBA occurred mainly around local noon under low solar activity conditions but before magnetic midnight under high solar activity conditions. The effects of solar radiation, particle precipitation, and polar ionospheric convection pattern on the diurnal variation of TEC were investigated. At both stations, photoionization caused by solar radiation was the main reason for the maximum diurnal variation of ionospheric TEC around local noon. During high solar activity with high concentration plasma in the dayside polar ionosphere, the convection pattern was the dominant influence on the maximum diurnal variation of TEC before magnetic midnight (noon) at SBA (ZHS).

How Credible Are Earthquake Predictions Based on TEC Variations?

AbstractThe possible relation between pre‐earthquake processes and ionospheric fluctuations is widely investigated and debated. Here, we conduct a numerical experiment to examine two studies that reported preseismic anomalies in the ionospheric total electron content (TEC) and argue for the significance of their respective analyses based on statistical evaluations. The first study is that by Liu et al. (2018, https://doi.org/10.3319/tao.2018.03.11.01), who statistically investigated the relationship between 62 M ≥ 6 earthquakes occurred in China over an 18‐year period and the TEC, which was deduced from the Global Ionospheric Map. According to this study, the TEC showed anomalies with specific polarities at certain days and times that preceded the earthquakes. Earthquake alarms they defined based on these anomalies showed a good performance. We conduct this same analysis using random synthetic earthquakes and obtain results that closely match those by Liu et al. (2018, https://doi.org/10.3319/tao.2018.03.11.01), thus indicating that the good performance of the Liu et al. (2018, https://doi.org/10.3319/tao.2018.03.11.01) alarm is an artifact. The second study is that by Le et al. (2011, https://doi.org/10.1029/2010ja015781), who classified the TEC time series into anomalous and non‐anomalous days based on the TEC perturbation. They found that the anomalous day rate increased as the nucleation time of the earthquakes was approached, especially for larger and shallower earthquakes. We conduct the same analysis using random synthetic earthquakes. The anomalous day rate that is comparable to their result occurs in ∼40% of the 1,000 random trials, thereby suggesting that their result may also be an artifact.

A Study of Possible Correlations between Seismo-Ionospheric Anomalies of GNSS Total Electron Content and Earthquake Energy

In this study, we conduct a correlation analysis between the daily occurrence times of the increase and decrease anomalies in the global total electron content (TEC) in the ionosphere, and the daily earthquake energy release within 110–130°E longitude over the following three latitude regions: A: 13°S–0.5°S (22.3°S–10°S geomagnetic), B: 0.5°S–19.5°N (10°S–10°N geomagnetic), and C: 19.5°N–32.1°N (10°N–22.5°N geomagnetic). The TEC data from global ionosphere maps (GIMs) during earthquake events of M ≥ 2.5 that occurred in 2015–2018 are used in this study. The time series of daily seismic wave energy releases within the three regions and the daily occurrence times of the TEC anomalies in each GIM grid are computed. By time-shifting the time series, the correlations are calculated and compared globally, and the temporal characteristics are also examined. The disturbance storm time (Dst) index, planetary geomagnetic index Kp, and daily observed 10.7 cm solar flux (F10.7) are used to remove data associated with space weather variations. Although the seismo-ionospheric precursor is not confirmed by the statistical investigations, the greater occurrence times of TEC decrease anomalies are observed in the southeast in Region A, and the conjugate point 13 days prior to a M6.9 earthquake in Region A, which occurred on 5 August 2018, in accordance with the statistical results. Therefore, it is required to apply more parameters to understand the causes of the ionospheric TEC variations and investigate whether ionospheric variations are caused by earthquakes.

Manifestation of earthquake preparation zone in the ionosphere before 2021 Sonitpur, Assam earthquake revealed by GPS-TEC data

Global Positioning System (GPS) Continuously Operating Reference Station (CORS) data analysis shows that the ionosphere's electron density variability is linked to the deformation and stress accumulation in the Earth's crust. Anomalies in ionosphere total electron content (TEC) variability before 2021 M6.4 Sonitpur, Assam earthquake were detected using L1 and L2 GPS frequencies that showed three distinct abnormalities on April 3, 9, 10, 2021. Pearson's correlation coefficient (r) of TEC decreases in the CORS that lies away from the earthquake epicenter, indicating the possibilities of a positive relationship between TEC variability and earthquake epicenter. TEC concentration also decreases towards the epicenter within the earthquake preparation zone (EPZ). It is also observed that the Pearson's correlation coefficient (r) of TEC decreases linearly near the EPZ. The study demonstrates the possibilities of determining the TEC anomalous zone in the ionosphere that coincides with the EPZ in the crustal rocks. The research indicated the possibilities of magnitude estimation of an impending earthquake based on the TEC anomalous zone in the ionosphere using closely spaced dense CORS network data.

Regional application of C1 finite element interpolation method in modeling of ionosphere total electron content over Europe

• A novel approach for regional ionosphere grid model with high spatial-temporal resolution is suggested. • The results of the new model is analyzed at different disturb geomagnetic and solar conditions. • A comparative analysis between the results of new model, GIM, NeQuick and GPS-TEC is made. In this paper, a novel approach based on C 1 finite element (FE) interpolation is used to construct a regional ionospheric grid model (RIGM) with high spatio-temporal resolution over Europe. The spatial resolution of the new model is 0.5 0 for a longitude and latitude and a temporal resolution is 15 min. Observations of 38 GPS stations at different days and seasons with different geomagnetic and solar activity conditions are used to evaluate the new method. All stations are used to discretize the whole domain of the problem into separate triangular patches using a Delaunay triangulation algorithm. In this case, GPS stations would be the vertices of the triangular patches. Also, the position of stations in sun-fixed coordinate system with coordinates of latitude and longitude are chosen in order to consider the temporal variations of vertical total electron content (VTEC). To model the behavior of VTEC in each triangular patch, a particular shape function is defined which is fitted to VTEC values at three vertices of each triangle while it satisfies C 1 continuity of VTEC at the common edges of the adjacent triangles. The results of the new model are compared with the VTEC of GPS at 4 control stations as well as global ionosphere map (GIM) and NeQuick models. Statistical parameters, including correlation coefficient, root mean square error (RMSE), standard deviation and dVTEC = |VTEC GPS - VTEC model | have been used to evaluate the error of the models. In low geomagnetic activity (KP < 4), the average RMSE at 4 control stations for FE, GIM and NeQuick models are 0.89, 1.05 and 6.42 TECU, respectively, while in the high geomagnetic activity (KP > 4), they are 1.24, 1.68 and 7.62 TECU, respectively. For further analysis, the accuracy of three models in precise point positioning (PPP) has been also evaluated. In PPP method, there is an improvement of about 1–16 mm compared to GIM and NeQuick models at coordinate components of control stations in high geomagnetic activity. The results of the analysis performed in this paper show that the FE model has a very high capability and accuracy in regional VTEC modeling in high and low geomagnetic conditions. The regional accuracy of this model is higher than GIM and NeQuick models and therefore can be considered as a new model for the ionosphere.