Total Electron Content Values Research Articles

Geometric deep learning for ionospheric TEC modeling using a temporal graph convolutional network

Abstract This document proposes a spatiotemporal deep learning model for ionospheric total electron content (TEC) modeling using global navigation satellite systems (GNSSs) observables. Data from dual-frequency GNSS receivers are used to compute the daily GNSS TEC timeseries. Usually, these timeseries are computed independently per GNSS permanent station, and the state-of-the art models proposed in literature exploit temporal characteristics of the timeseries and neglect any spatial dependencies and information from different stations. In our approach, we propose a practical solution for parallel processing of TEC timeseries and additional indicators from various adjacent stations to predict future VTEC values. We face the problem in both spatial and temporal dimensions adopting a graph neural network-based approach from the broader family of geometric deep learning. According to our proposed scheme, the different adjacent GNSS stations are structured in a graph and then, we apply the proposed temporal graph convolutional network called ION_TGNN. Our model predicts future vertical TEC (VTEC) values for all stations in a single run with mae error better than 1.0 TECU. Comparisons with state-of-the art models show the superiority of the proposed method in terms of performance but also in terms of computational cost during training and test phases.

Analysis of Ionospheric Disturbances Due to Cyclones in Geraldton City of Australia

Abstract A typhoon is a natural disaster that has the potential to cause damage and cause loss of life. On April 2, 2021, the tropical cyclone Seroja formed, reaching typhoon class category 3, which was characterized by a maximum wind speed of 140 km/s on April 11, 2021. Tropical cyclones reached typhoon class when the wind speed exceeded 119 km/h. Typhoon can generate Acoustic Gravity Waves which can cause Concentric Traveling Ionosphere Disturbances (CTIDs). One effort that can be made to mitigate typhoon disasters is to analyze the time when ionospheric disturbances are detected, which can be observed through changes in TEC values by utilizing GNSS technology. The propagation of the GNSS signal from the satellite to the receiver experiences a delay when passing through the ionosphere layer, which can be used to obtain the Total Electron Content (TEC) value. TEC is the number of electrons in a cylindrical vertical column with a cross-section of 1 m 2 along the line of sight. CTIDs due to typhoon Seroja were detected at around 09:00 UTC by GPS 9 at ~0.2 TECU. Interestingly, the CTIDs caused by typhoon Seroja were detected before the typhoon landed in Australia. It is hoped that additional information and variables regarding the comparison of the characteristics of ionospheric disturbances due to typhoons and earthquakes can be used to develop an early warning system for disasters in the future.

Artificial Intelligence for Earthquake Prediction: A Preliminary System Based on Periodically Trained Neural Networks Using Ionospheric Anomalies

There is increasing evidence that anomalies in the ionosphere could appear a few days before large earthquakes. Many significant successes with using anomalies for predictions have been reported, although they are usually limited, both in space, to a specific geographic area, and in time, to one or a few events. To date, no solution has been presented that consistently yields the location and magnitude of future earthquakes and thus can be used to develop a warning service. The purpose of this research is to improve on the possible use of Global Ionospheric Maps for earthquake prediction. The use of three-dimensional data matrices, having spatiotemporal information to feed a convolutional neural network, is proposed in this contribution. This network was trained on all large earthquakes occurring from the beginning of the year 2011 to the beginning of October 2024 but it is proposed that it be periodically retrained with new data. This network has reached an accuracy of around 60% in the validation data for a division into eight categories of different earthquake magnitudes. Nevertheless, this percentage increases considerably if the classification into neighboring categories is also accepted, something that could be clearly admissible for the purposes of a warning system. The author believes that success in this endeavor has to come from a collaborative effort. For this reason, the training and validation data with three-dimensional matrices (latitude/longitude/time) of total electron content values along with the subsequent earthquake magnitudes are provided in this paper along with the trained network. Researchers are strongly encouraged to improve on the current neural network with or without the inclusion of additional information.

Disturbances of Ionospheric Total Electron Content during Great and Severe Geomagnetic Storms above Iraq and Surrounding Areas

Several studies have been made to understand the behavior of Total Electron Content (TEC) in the topside of the ionosphere during two types of geomagnetic storms. The aim of this research is to examine the ionospheric disturbances using the TEC parameter during the great and severe geomagnetic storms that occurred during the period (28-30 October 2003). Theexamination was conducted for the region,includingIraq and surrounding areas that cover the arealatitude 27-39oN; longitude 27-54oE). TEC data were obtained fromthe Defense Meteorological Satellite Program (DMSP), to determine the type of geomagnetic storm, the Disturbance storm time (Dst) index was gathered for the selected days from the website Koyota, Japan WDC.Fromthe results,it wasfound that there was a good relationship between Dst-indexand TEC parameter values. There is a discrepancy in observations recorded about TEC values during the period of geomagnetic storms.There were significant enhancements in the values of TEC during storms; however, there was an anomaly when the storm continued for several hours during the day, there was a highly broad increase in TEC from sunrise to sunset. Moreover, when two types of storms occurred, two peaks or more appeared, and they remained for one event, or even for more than one day. Comparisons between the observed TEC and the predicted values were applied in order to check the validity of the IRI-20 ionospheric model during the storm time above the mid-latitude studiedareas;it found that there is a non-linear correlation between them withi24 hours and three days, so the model wouldneed some modification in the future to be suitable for the Iraq region during storm time.

Peculiar Nighttime Ionospheric Enhancements Over the Asian Sector During the May 2024 Superstorm

AbstractThis study reports a peculiar nighttime ionospheric enhancement in the total electron content (TEC) from the geostationary (GEO) satellites in response to the geomagnetic superstorm of May 2024. The enhancements occurred at low to mid‐latitudes during the storm's recovery phase on 11–12 May, with the TEC values almost twice as high as the quiet ones. Surprisingly, the nighttime ionospheric enhancements sub‐rotated westward with a speed of ∼130.5 m/s. The nighttime TEC enhancements lasted ∼5–7 hr for a given location and persisted over half a day over wide longitude ranges. Meanwhile, ionosonde data from two equatorial ionization anomaly (EIA) stations showed a higher peak height of the F2 layer, and a significant double‐crest EIA structure was observed by both GEO TECs and in situ electron densities from China Seismo‐Electromagnetic Satellite during this period of interest, indicating a possible contribution from disturbance electric fields producing nighttime eastward equatorial electric fields. Nevertheless, it remains a mystery whether the nighttime TEC enhancement and its movement were associated with the wind disturbance dynamo.

Construction of global IGS-3D electron density (Ne) model by deep learning

In this study, we construct a global IGS-3D Ne model that generates global 3-D electron density (Ne) from International Global Navigation Satellite Systems (GNSS) Service (IGS) total electron content (TEC) data through deep learning. As a first step towards this, we make a model to generate a vertical electron density profile from a TEC value using Multi-Layer Perceptron (MLP). In this process, we use the vertical electron density profiles and the corresponding TEC values of the IRI-2016 model from 2001 to 2008 for training, 2009 and 2014 for validation, and 2010 to 2013 for a test. The next step is to generate global IGS electron density profiles using the global IGS TECs as input data for the model, which is called the global IGS-3D Ne model. We evaluate the IGS-3D Ne model by comparing the electron density profiles from the incoherent scatter radars (ISRs) at three stations with the IGS-3D Ne model from 2010 to 2013. The evaluation shows that the electron density profiles from the IGS-3D Ne model are closer to the ISR data than those of the IRI model, especially at high latitudes. The IGS-3D Ne model shows that the averaged root mean square error (RMSE) values between IGS and ISR electron density profiles are 0.37 log(m−3), 0.22 log(m−3), and 0.34 log(m−3) for all test datasets at Jicamarca, Millstone Hill, and EISCAT stations, respectively. These results suggest that our method has sufficient potential to enhance the ability to predict global electron density profiles.

Reconstruction of ionospheric VTEC using empirical orthogonal function and its performance during extreme geomagnetic storm

This paper demonstrates that the spatial distribution of the ionospheric TEC over the Indian region can be reconstructed with appreciable accuracy using minimal numbers of empirical orthogonal functions as a basis. These basis functions were derived using the Singular Value Decomposition of a matrix composed of pragmatic vertical Total Electron Content (VTEC) values collected across varied ionospheric conditions and measured over the region of interest. The reconstruction was achieved by linearly combining the appropriately chosen significant bases with corresponding weight factors. The reconstruction accuracy of the algorithm was found to be better than 4 TECU (TECU = 1016 electrons/m2) for more than 99.9 % of the time when tested over the complete year of 2016 with only eight basis vectors. The containment factor, defined here, indicates the goodness of the chosen bases in representing the arbitrary VTEC distributions and is found to remain typically high, aiding in improved algorithm performance. The performance, however, was found to be sensitive to the seasons and geomagnetic conditions. Deteriorated performance was observed when tested for the St. Patrick's Day storm data. The deterioration was attributed to the structural alteration of the ionospheric plasma density and the presence of atypical modes during the storm. The results ascertain the prospect of a faithful representation of the spatial distribution of the ionospheric VTEC using limited parametric variables, which may find utility in navigation, radar, and various other applications.

An investigation into the influence of solar flares and geomagnetic storms on the F2 layer of the ionosphere in Western Europe during March 2024

On March 23 and 24, 2024, the M-class and X-class solar storms significantly intensified. Subsequently, from March 24 to 26, the monitoring station’s Kp index notably increased, at times exceeding 8, indicating that a severe geomagnetic storm was occurring. During this period, the IGS Global Ionosphere Maps (GIMs) displayed a substantial decrease in Total Electron Content (TEC) in Western Europe due to the impact of the intense geomagnetic storms. To investigate this occurrence, data from the Lowell GIRO Data Center were utilized. The analysis revealed that a concentrated solar flare eruption on March 23, 2024, triggered geomagnetic storm events on Earth, causing significant ionospheric anomalies in Western European countries. Specifically, compared to typical levels, parameters such as foF2, m3000F2, and TEC values experienced significant reductions in Western European countries. Moreover, the hmF2 data exhibited higher values at night and lower values during the day, deviating from the expected diurnal pattern. Analysis of the Rate of TEC Index (ROTI) indicated varying effects of geomagnetic storms across different latitudes in Western Europe. Through detailed graphical analysis, this study elucidates the alterations in the ionosphere under geomagnetic storm conditions in Western Europe, shedding light on the dynamic behavior of the ionosphere during a specific timeframe.

Investigating Different Interpolation Methods for High-Accuracy VTEC Analysis in Ionospheric Research

The dynamic structure of the ionosphere and its changes play an important role in comprehending the natural cycle by linking earth sciences and space sciences. Ionosphere research includes a variety of fields like meteorology, radio wave reflection from the atmosphere, atmospheric anomaly detection, the impact on GNSS (Global Navigation Satellite Systems) signals, the exploration of earthquake precursors, and the formation of the northern lights. To gain further insight into this layer and to monitor variations in the total electron content (TEC), ionospheric maps are created using a variety of data sources, including satellite sensors, GNSS data, and ionosonde data. In these maps, data deficiencies are addressed by using interpolation methods. The objective of this study was to obtain high-accuracy VTEC (Vertical Total Electron Content) information to analyze TEC anomalies as precursors to earthquakes. We propose an innovative approach: employing alternative mathematical surfaces for VTEC calculations, leading to enhanced change analytical interpretation for anomaly detections. Within the scope of the application, the second-degree polynomial method, kriging (point and block model), the radial basis multiquadric, and the thin plate spline (TPS) methods were implemented as interpolation methods. During a 49-day period, the TEC values were computed at three different IGS stations, generating 1176 hourly grids for each interpolation model. As reference data, the ionospheric maps produced by the CODE (Center for Orbit Determination in Europe) Analysis Center were used. This study’s findings showed that, based on statistical values, the TPS model offered more accurate results than other methods. Additionally, it has been observed that the peak values in TEC calculations based on polynomial surfaces are eliminated in TPSs.

Pattern of variation of TEC, hmF2 and foF2, and their correlation during the geomagnetic storm time conditions

This paper mainly examines the diurnal variation of the Total Electron Content (TEC) and critical frequency of the F2-layer (foF2) and their correlation with the height of the peak electron density (hmF2). This is carried out employing the observations (co-located Global Positioning System (GPS) and digisonde) and empirical models (International Reference Ionosphere, IRI, 2016 and IRI-extended to the Plasmasphere, IRI-Plas, 2017) in the low-to-high latitudes during relatively similar intense level geomagnetic storms that occurred during the high solar activity (February 19, 2014) and low solar activity (September 08, 2017). The GPS-derived TEC and digisonde-derived TEC, hmF2 and foF2 variabilities show large fluctuations on most of the stations when compared to the IRI 2016 and IRI-Plas 2017 variations. Moreover, the highest GPS-derived TEC values are observed when the hmF2 values reach in the ranges of about 270–309 km (low latitude), 203–266 km (mid latitude) and 259–311 km (high latitude) regions. The highest digisonde-derived TEC values are also depicted at the height ranges of about 256–451 km (low latitude), 250–326 km (mid latitude) and 309–388 km (high latitude) regions. In addition, the highest digisonde-derived foF2 values are observed when the hmF2 values reach about 253–384, 217–311 and 259–281 km in the low, mid and high latitudes, respectively. The model-derived TEC and foF2 variations also reveal that the highest values are generally observed at relatively similar height ranges with the observations. Moreover, the highest TEC and foF2 values are observed relatively at lower altitudes in the mid latitudes when compared to the low and high latitudes. The highest values also tend to move to the lower altitudes in shifting from the high to the low solar activity during similar intense level geomagnetic storms.

Empirical orthogonal function based modelling of ionosphere using Turkish GNSS network

The study investigates ionospheric total electron content (TEC) variation over Turkey from the five selected global navigation satellite system (GNSS) stations situated in diverse parts of Turkey. The geomagnetic indices are used and observed TEC are modeled with the technique known as Empirical orthogonal function (EOF). It is valuable to note that the correlation coefficient between observed GNSS TEC values and EOF TEC values varies from 0.8020 to 0.9394. The root means square error (RMSE) values between observed GNSS TEC values and EOF TEC lie between 3.1665 TECU to 4.4220 TECU. These results show that the EOF model performs quite well in the Turkish region and can present the model TEC variations perfectly. Finally, these GNSS observed and EOF-predicted TEC values along with geomagnetic indices are studied with the tropospheric wind speed. The results showed that both observed and modeled TEC have very low correlations with tropospheric wind speed and do not provide any significant value. Hence, we concluded that the ionospheric region is not affected by tropospheric wind speed. It happens because the tropospheric wind speed is a matter of the lower troposphere and its atmospheric pressure while the ionosphere is far from the earth and depends upon the number of free electrons.

Effect of ultraviolet radiation on total electron content in global positioning system observations

Climate is one of the basic elements for understanding natural phenomena and the development of civilizations throughout history. Climate change determines most of the modifications of human nature and culture, as human must adapt to changing conditions which are sometimes an important element that can enhance or threaten its existence. This study aims to determine the characteristics of changes in the total electron content (TEC) and determine the radiation has influence to TEC through observing the global positioning system (GPS) in the ionosphere. In addition, the TEC is a measure of ionospheric parameters that affect the radiation that occurs. This study uses secondary data obtained from the Cibinong Spatial Global Station in 2008 – 2012. This research was conducted as a comparison of the TEC and extreme ultraviolet (EUV). The method used is a simple statistical method which seeks the maximum and minimum the TEC and EUV data, as well as the correlation method to relate the coefficient of determination TEC and EUV. As the results the maximum TEC value is 55.895 TECU which occurred in 2012 at 7 unit time (UT) and the minimum TEC value is 1.955 TECU which occurred in 2010 at 22 UT. The correlation ratio between the TEC and EUV is directly proportional, where the higher the value of the TEC, the higher the EUV value. In closing, TEC and EUV are influence by solar activity.

Ionospheric responses to the tropical cyclones from different oceanic basins over the globe

The perturbations in the ionosphere due to eight tropical cyclones (TCs), namely Iota, Haima, Harold, Willa, Amphan, Gaja, Vadrah and Bulbul, originated and grown in different oceanic basins, are investigated. Total Electron Content (TEC) data, from Global Positioning System (GPS) TEC receiver in operation at Agartala (AGT) or different International GNSS Service (IGS) stations near the cyclone landfall regions, are used in this study. Despite some differences, the ionosphere responds to all tropical cyclones in an almost similar manner. Though the geomagnetic conditions are quiet and there are no perturbations due to any other geophysical phenomena in the active cyclonic storm stage, in all the cases there is a fall in average vertical total electron content (VTEC) deviations below the monthly mean value either on the landfall day or on the following day or even on just previous day. Decrements in Vertical Total Electron Content are found higher for tropical cyclones over North Indian and South Pacific oceanic basins. Recoveries in vertical total electron content values are slower for cyclones over the North Atlantic and North West Pacific basins. Recoveries in vertical total electron content (VTEC) values are slow for tropical cyclones (TCs) over the North Atlantic and North West Pacific basins. But those over other basins are quick. The longer the track of a tropical cyclone (TC), the higher is the reduction in the vertical total electron content (VTEC) value. A negative correlation exists between the maximum sustained surface wind velocities and the total periods of different TCs and also the difference of lowest average differential VTECs with that on the previous day. The observed anomaly in ionospheric responses might be due to the combined effect of TC-inspired gravity waves, ejection of neutral particles from the terminator of a tropical cyclone (TC) and lightning electric fields. To explain the observed results convective activities during TC, with the help of outgoing long wave radiation (OLR) map, are also taken into account. This study provides the primary results regarding regional characteristics and hence a comparative idea for the responses of the ionosphere to different tropical cyclones (TCs) from different geographical positions on the globe, which needs further comprehensive investigation in future.

The dynamic effects of solar eclipses of October 25, 2022, and October 14, 2023, on GPS-derived total electron content

This study analyzes total electron content (TEC) variations during two solar eclipse events that occurred on October 25, 2022, and October 14, 2023. The solar eclipse of October 25, 2022, was a partial solar eclipse, while the eclipse of October 14, 2023, was an annular solar eclipse. For this study, the data of eight International GNSS Service (IGS) stations from different eclipse coverage zones are used to analyze TEC variations. It is found that the stations located in the maximum eclipse cover zone exhibited notable decreases in TEC values. The minimum variation of about 11.76% in TEC values is observed at the station situating in about 20 percent eclipse cover zone, while it varies from 22% to 38% at the stations falling in about 60 percent eclipse cover zone. The highest variation in TEC values of about 44% is found at the stations in about 80 percent eclipse cover zone. The time of occurrence of maximum depletion in TEC values at each station is in line with their longitudinal sequence. Atmospheric gravity waves (AGWs) are also observed by performing wavelet analysis on TEC data. The global TEC maps visualize and confirm observed TEC variations, providing spatial and temporal insights into the ionospheric response. This analysis highlights the influence of station location and eclipse coverage on the magnitude and spatial distribution of TEC variations.

Effects of local time on the variations of the total electron contents at an American and Asian longitudes and their comparison with IRI-2016, IRI-Plas2017 and NeQuick-2 models during solar cycle 24

Ionospheric modelling is one of the major tools to study the behavior of the ionosphere. Ionospheric models have been useful in predicting the true state of the ionosphere particularly in regions where Global Positioning System (GPS) are not readily available. This research paper aims to study the longitudinal variations and the effects of local time on the total electron content (TEC) recorded in two different sectors (Asia and America) during the ascending, maximum and descending phases of solar cycle 24 (2011–2017) and also to compare its values to IRI-2016, IRI-Plas2017 and NeQuick-2 models in order to evaluate their performances. An hourly interval profile computed on seasonal basis were used to study the behaviors of TEC diurnally and seasonally. A monthly interval error profile plotted on annual basis was also used to investigate the deviations of the models from the GPS values. Our results showed that the peak values of TEC in the Asian and American sectors were recorded around the dawn,06:00UT (13:00LT) and dusk, 18:00UT (15:00LT) respectively. We also affirmed from our results that seasonal/winter anomalies were recorded in all the phases of the solar cycle in both sectors. Equinoctial Asymmetry was also observed to be predominant during different phases of the solar cycle in both sectors except during ascending and descending phases in the Asian and American sectors respectively. Out of the 168 months of data collated for this study, only 162 months of data were available. The IRI-2016, IRI-Plas2017 and NeQuick-2 models have 11.7%, 23.5% and 64.8% better performance in all the months under consideration. Therefore, the NeQuick-2 model had the best performance in both the Asian and American sectors. Finally, from the results of our statistical analysis, Mean Absolute Error (MAE) has ∼3 TECU lower than the Root Mean Square Error (RMSE) values in both sectors and in all the solar cycle phase. Hence, MAE can evaluate the performance of ionospheric models better than RMSE.

Exploring ionospheric plasma density trends in the Indian equatorial crest region under varying solar activity conditions

Long-term trends in the evolution of ionospheric plasma at Hyderabad (17.38∘N, 78.48∘E; 8.52∘N Magnetic Latitude), a near-equatorial anomaly (EIA) crest region of the Indian ionospheric sector, have been studied using 9 years of vertical Total Electron Content (TEC) data from 2004 to 2009 and 2011 to 2013 using global positioning satellites (GPS) measurements. The study examined the mean diurnal, monthly, seasonal, and yearly variations of TEC during geomagnetic quiet days in different seasons from 2004 to 2013. The findings reveal that the daytime TEC at the anomaly crest region exhibits semi-annual variations throughout the study period, while midnight TEC shows semi-annual variation only during the high solar activity years of 2011–2013. The winter anomaly was observed in 2004 and 2006. The study also assessed the performance of the International Reference Ionosphere (IRI) 2016 model in reproducing GPS TEC variability at the equatorial crest region. The diurnal and seasonal variation patterns in IRI-TEC show a good correlation with GPS TEC. However, the IRI 2016 model tends to overestimate TEC values during low solar activity conditions (2006–2009) but represents TEC variations reasonably well during high solar activity periods (2011–2013). Nevertheless, the IRI model fails to capture the wide plateau-like structure in the peak TEC, typically occurring between 1200–1600 IST at Hyderabad. Additionally, IRI-TEC consistently indicates very low TEC values during the early morning hours, whereas GPS-TEC measurements suggest a significant presence of plasma density. The study suggests a strong influence of the solar cycle on TEC variations at Hyderabad, evident from the positive correlation (R2= 0.71) with the F10.7 cm index. This characteristic is also well represented by the IRI 2016 model.

Analyzing the spatial variation characteristics of grid TEC using long-term GIM data

Global ionosphere maps (GIM), a grid model generated based on observations from global GNSS stations, is often used for ionospheric delay correction and total electron content (TEC) analysis, and is an important data for ionospheric modeling and code bias estimation, as well as related applications. Understanding the spatial variation characteristics of the grid TEC in GIM data can help the better use of GIM data. In this paper, the GIM data of CODE (Center for Orbit Determination in Europe) analysis center for a total of 15 years from 2008 to 2022 are used to analyze the variation of TEC of adjacent grid points and the difference of TEC of four grid points in each grid. The results show that the mean values of the grid TEC variations range from about 0.26–1.86 TECu in the longitude direction and 0.36–2.76 TECu in the latitude direction, and most of the differences in the TECs of neighboring grid points are within ± 2 TECu. In the low solar activity years, the STD of the TEC of the four grid points in most of the grids in the GIM data is less than 1.2 TECu, indicating that the TEC values of the four grid points in most of the grids in their GIMs are relatively close to each other and the differences are small, whereas the differences are larger in the high solar activity years. In other words, the TEC values of the areas covered by the GIM grids in the low solar activity years are close. The results of the study can provide some references and lessons for the interpolation and application of the TEC of the GIM grid, and the TEC modeling of the single-station area.

TEC disturbances caused by CME-triggered geomagnetic storm of September 6–9, 2017

This study investigates the ionospheric response to a geomagnetic storm triggered by a Coronal Mass Ejection (CME) during 6–9 September 2017, across GPS stations located in diverse geographical regions. We analyze the changes in the magnetic field component (ΔH), the Prompt Penetration Electric Fields (PPEF), and the Total Electron Content (TEC). We find that ΔH exhibits latitude-dependent responses during the storm, with high-latitude stations experiencing more significant reductions compared to low-latitude stations. The PPEF behavior is found to be directly correlated with solar wind disturbances. Particularly during the main phase of the storm, fluctuations in PPEF were clearly associated with negative values in the Dst index. The KIRU station, located at a high latitude, shows the most pronounced PPEF effects, indicating the increased susceptibility of high-latitude regions to solar wind interactions. The time series plot of TEC, covering a full month at different stations, shows a distinct diurnal pattern driven by solar ionization. Equatorial stations such as HYDE, BOU, HON (HNLC), and DODM exhibit the highest daily TEC values. During the geomagnetic storm, TEC disturbances are evident across all stations, with significant disturbances and varying trends in TEC depletion rate observed at different locations. The TEC values differ by 5–25 TECU during the storm period, suggesting intricate ionospheric responses to geomagnetic storms at different stations. This highlights the importance of considering different geographical regions to fully understand the ionospheric dynamics related to solar activities.

Variation in Total Electron Content Over Ethiopia During the Solar Eclipse Events

AbstractThis work studies variations of ionospheric total electron content (TEC) during four distinct solar eclipse events over the Ethiopia region. Dual‐frequency global positioning system (GPS) data obtained from UNAVCO over Addis Ababa (9.036°N, 38.76°E) and Bahir Dar (11.6°N, 37.34°E) stations are used to examine the ionospheric variability during two annular solar eclipses on 15 January 2010 and 1 September 2016, a partial solar eclipse on 4 January 2011, and a hybrid solar eclipse (the eclipse path starts out as annular but later changes to total) on 3 November 2013. The results show a significant decrease in TEC values during the occurrence of the solar eclipses. Specifically, the TEC values are reduced to −20% and −10% during the annular eclipse on 15 January 2010, −33% and −38% during the partial solar eclipse on 4 January 2011, −26% and −24% during the annular solar eclipse on 1 September 2016, over the Addis Ababa and Bahir Dar stations, respectively. There is only minimal change in TEC of −8% and −9% at Addis Ababa and Bahir stations, respectively, during the 3 November 2013 solar eclipse even if the obstruction rate is high over the study area. Furthermore, the study shows that the spatial gradient of TEC reduction varies at different locations, which is attributed to the distinct amount of reduction in solar radiation reaching the Earth's surface, resulting in reduced photo‐ionization. Overall, this study provides insightful information about the behavior of the ionospheric TEC during solar eclipses over Ethiopia and emphasizes the use of dual‐frequency GPS data in tracking the variations of the TEC.

Forecasting Ionospheric TEC Changes Associated with the December 2019 and June 2020 Solar Eclipses: A Comparative Analysis of OKSM, FFNN, and DeepAR Models

This paper presents forecast and investigation of the variation in ionospheric Total Electron Content (TEC) during the solar eclipses (SEs) of December 2019 and June 2020 using three different methods: Deep Autoregressive model (DeepAR), Feed-Forward Neural Network (FFNN), and Ordinary Kriging-based Surrogate Model (OKSM), and the TEC data predicted by DeepAR, FFNN, and OKSM were compared with the actual TEC during the observation days. The study was conducted based on GPS data taken from the IISC receiver located in Bangalore, India, during the SEs which happened on 26.12.2019 and 21.06.2020. The TEC data were examined to assess the effect of solar eclipses on TEC values. Eighty-day prior TEC data for the IISC station are gathered from IONOLAB servers along with the other parameter data like Dst, Ap, F10.7, and Kp taken from OMNIWEB servers which were used to predict TEC. The reliability of the forecasted results is evaluated using numerical factors like Normalized Root Mean Square Error (NRMSE), Correlation Coefficient (CC), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and R-squared. The study demonstrates the usefulness of combining multiple methods for analyzing TEC variations during SEs and highlights the potential of OKSM, FFNN, and DeepAR models for studying TEC variation in the same context. The findings may be useful for satellite broadcasting and navigational services and for further research into the influence of solar eclipses on the TEC changes.