Regional Total Electron Content Research Articles

Geomagnetic storm effect on equatorial ionosphere over Sri Lanka through total electron content observations from continuously operating reference stations network during Mar–Apr 2022

Abstract The technological advancements in the current era have highlighted the increasing significance of satellite-based positioning, navigation, and timing services in a wide range of dynamic and critical applications. This has led to significant efforts towards enhancing the performance of global navigation satellite systems (GNSS) operating under challenging ionospheric conditions. The Sri Lankan ionosphere region is a focal point of equatorial aeronomy scientists, being situated in the southernmost landmass of the Indian longitude sector within the vicinity of the magnetic equator where a combination of electric, wind, and temperature dynamics exerts a substantial influence on the ionosphere but was relatively unexplored in the past. In the present work, we employed a Kriging interpolation technique on the total electron content (TEC) variables from ten GNSS receivers operating under the Continuously Operating Reference Stations (CORS) network in Sri Lanka first ever of its kind to deliver two-dimensional regional ionospheric TEC maps at hourly intervals, both during quiet and disturbed ionospheric conditions in the equinoctial March and April months of 2022. The latitudinal variation patterns are discernable from the hourly TEC maps. Furthermore, a comparative analysis of the performance of GNSS-derived TEC with that of the routinely published Global Ionospheric Maps (GIMs) confirms overestimation characteristics of the latter irrespective of the local time of observation. The generated regional ionospheric maps are fairly responsive to the onset of the storm and the recovery phase thereafter. The extent of nighttime ionospheric irregularity is also probed through the rate of TEC index (ROTI) variations, demonstrating that the irregularities were insignificant during the selected storm event.

Deep Learning‐Based Regional Ionospheric Total Electron Content Prediction—Long Short‐Term Memory (LSTM) and Convolutional LSTM Approach

AbstractThis study evaluates the performance of deep learning approach in the prediction of the ionospheric total electron content (TEC) during magnetically quiet periods. Two deep learning techniques, long short‐term memory (LSTM) and convolutional LSTM (ConvLSTM), are employed to predict TEC values 24 hr ahead in the vicinity of the Korean Peninsula (26.5°–40°N, 121°–134.5°E). The LSTM method predicts TEC at a single point based on time series of data at that point, whereas the ConvLSTM method simultaneously predicts TEC values at multiple points using spatiotemporal distribution of TEC. Both the LSTM and ConvLSTM models are trained using the complete regional TEC maps reconstructed by applying the Deep Convolutional Generative Adversarial Network–Poisson Blending (DCGAN‐PB) method to observed TEC data. The training period spans from 2002 to 2018, and the model performance is evaluated using 2019 data. Our results show that the ConvLSTM method outperforms the LSTM method, generating more reliable TEC maps with smaller root mean square errors when compared to the ground truth (DCGAN‐PB TEC maps). This outcome indicates that deep learning models can improve the prediction accuracy of TEC at a specific point by taking into account spatial information of TEC. We conclude that ConvLSTM is a reliable and efficient approach for the prompt ionospheric prediction.

A Multi-Parameter Empirical Fusion Model for Ionospheric TEC in China’s Region

This article takes the measured Total Electron Content (TEC) from the GPS points of the China Regional Crust Observation Network as the starting point to establish a regional ionospheric empirical model. The model’s performance is enhanced by considering solar flux and geomagnetic activity data. The refinement function model of the ionospheric TEC diurnal variation component, seasonal variation component, and geomagnetic component is studied. Using the nonlinear least squares method to fit undetermined coefficients, MEFM-ITCR (Multi-parameter Empirical Fusion Model–Ionospheric TEC China Regional Model) is proposed to forecast the regional ionosphere TEC in China. The results show that the standard deviation of MEFM-ITCR residuals is 3.74TECU, and MEFM-ITCR fits the modeling dataset well. Analyses of geographic location variation, seasonal variation, and geomagnetic disturbance were carried out for MEFM-ITCR performance. The results indicate that in the Chinese region, MEFM-ITCR outperforms IRI2020 and NeQuick2 models in terms of forecast accuracy, linear correlation, and model precision for TEC measured using GPS points under different latitudes and longitudes, different seasons, and different geomagnetic disturbances. The empirical TEC model built for the Chinese region in this paper provides a new ionospheric delay correction method for GNSS single frequency users and is of great significance for establishing other new and improving existing ionospheric empirical models.

Constructing a Regional Ionospheric TEC Model in China with Empirical Orthogonal Function and Dense GNSS Observation

Using Global Navigation Satellite Systems (GNSS) observation data for developing a high-precision ionospheric Total Electron Content (TEC) model is one of the essential subjects in ionospheric physics research and the application of satellite navigation correction. In this study, we integrate the Empirical Orthogonal Function (EOF) method with the TEC data provided by the Center for Orbit Determination in Europe (CODE), and observed by the dense GNSS receivers operated by the Crustal Movement Observation Network of China (CMONOC) to construct a regional ionospheric TEC model over China. The EOF analysis of CODE TEC in China from 1998 to 2010 shows that the first-order EOF component accounts for 90.3813% of the total variation of the ionospheric TEC in China. Meanwhile, the average value of CODE TEC is consistent with the spatial and temporal distribution characteristics of the first-order EOF base function, which mainly reflects the latitude and diurnal variations of TEC in China. The first-order coefficient after EOF decomposition shows an obvious 11-year period and semi-annual variations. The maximum amplitude of semi-annual variation mainly appears in March and October, which is closely associated with the variation in geographical longitude, the semi-annual change of the low-latitude electric field, and the ionospheric fountain effect. The second-order coefficient has an evident annual variation, the minimum amplitude mainly occurs in March, August, and September, and the amplitude values in the high solar activity years are more significant than those in the low solar activity years. The third-order coefficient mainly shows the characteristics of annual variation, and the fourth-order coefficient shows the noticeable semi-annual and annual variations. The third and fourth-order coefficients are both modulated by the solar activity index F10.7. The ionospheric TEC model in China, driven by CMONOC real-time GNSS observation data, can better reflect the latitude, local time and seasonal variation characteristics of ionospheric TEC over China. In particular, it can clearly show the spring and autumn asymmetry of ionospheric TEC in the low latitudes. The root mean square error of the absolute error between the model and the actual observation is mainly distributed around 2.45 TECU (1 TECU = 1016 electrons/m2). The values of the TEC model constructed in this study are closer to the actual observed values than those of the CODE TEC in China.

IonosphericTotal Electron Content Changes during the 15 February 2018 and 30 April 2022 Solar Eclipses over South America and Antarctica

This is one of the first papers to study the ionospheric effects of two solar eclipses that occurred in South America and Antarctica under geomagnetic activity in different seasons (summer and autumn) and their impact on the equatorial ionization anomaly (EIA). The changes in total electron content (TEC) during the 15 February 2018 and 30 April 2022 partial solar eclipses will be analyzed. The study is based on more than 390 GPS stations, Swarm-A, and DMSP F18 satellite measurements, such as TEC, electron density, and electron temperature. The ionospheric behaviors over the two-fifth days on both sides of each eclipse were used as a reference for estimating TEC changes. Regional TEC maps were created for the analysis. Background TEC levels were significantly higher during the 2022 eclipse than during the 2018 eclipse because ionospheric levels depend on solar index parameters. On the days of the 2018 and 2022 eclipses, the ionospheric enhancement was noticeable due to levels of geomagnetic activity. Although geomagnetic forcing impacted the ionosphere, both eclipses had evident depletions under the penumbra, wherein differential vertical TEC (DVTEC) reached values <−40%. The duration of the ionospheric effects persisted after 24 UT. Also, while a noticeable TEC depletion (DVTEC ∼−50%) of the southern EIA crest was observed during the 2018 eclipse (hemisphere summer), an evident TEC enhancement (DVTEC > 30%) at the same crest was seen during the eclipse of 2022 (hemisphere autumn). Swarm-A and DMSP F18 satellite measurements and analysis of other solar eclipses in the sector under quiet conditions supported the ionospheric behavior.

Regional Ionospheric Frequency Domain Characterization and Short-term Forecasting Methods

Total electron content (TEC) is an important characteristic parameter of the ionosphere, which has a great impact on applications such as navigation error correction. The paper addresses the need for short- and medium-term forecasting of regional ionospheric TEC. Firstly, we analyze the frequency domain characteristics of ionospheric TEC, and analyze the data in the frequency domain based on the characteristics of trend, periodicity and abruptness of ionospheric TEC changes influenced by solar activity, combined with the Prophet algorithm. Then, according to its frequency domain characteristics, Prophet is used to achieve hour-by-hour prediction. The computer modeling results show that the RMSE of the 7-day forecast is better than 1.262 TECU during the geomagnetically quiet period, and the method is suitable for the short- and medium-term forecasting of ionospheric TEC with good forecast accuracy and time efficiency.

Dynamic Processes Associated With Prominent Ionospheric Variations in a Narrow Longitudinal Zone Near the EIA Crest Region as Revealed by ICON Satellite and Ground Beidou Receiver Observations Over South Asia

AbstractNeutral winds and plasma motions from the Ionospheric Connection Explorer mission were used to investigate dynamic processes associated with large regional total electron content (TEC) differences in a narrow longitudinal zone exceeding ∼45 TECU obtained from dense Beidou geostationary receivers at low latitudes over South Asia. The TEC east‒west asymmetry was defined to quantify this difference, which exceeded ∼5 TECU per 1° longitude distance and occurred around the equatorial ionization anomaly (EIA) crest on 31 March 2021 under geomagnetically quiescent conditions. Moreover, the magnetic meridional ion velocity exhibited a large longitude difference around the EIA crest during periods with strong ionospheric east‒west asymmetry. Furthermore, the longitude difference variation was consistent with the TEC east‒west asymmetry variation during 11–21 March 2020 and 27 March–4 April 2021. No significant correlations between TEC east‒west asymmetry and longitude differences under conditions with neutral winds and magnetic zonal ion drifts were observed in either case. The different vertical plasma drifts could contribute to ionospheric changes with a zonal range of a few hundred kilometers.

Short-term regional ionospheric TEC forecast using a hybrid deep learning neural network

The total electron content (TEC) of the ionosphere is one of the key parameters for both scientific study and engineering application. A hybrid deep learning network based on Grapy Convolution Network (GCN) and Long Short Term Memory (LSTM) is proposed to predict the regional ionospheric TEC 24 h in advance across China. The extensive 14-year dataset during 2005–2018 from the CODE TEC measurements, covering a wide variety of solar activity, are used to comprehensively evaluate the performance of the predictive model. The experimental results show that the model predicted TEC is in good agreement with the actual CODE TEC. Over 90% of differences between the actual TEC and the predicted TEC are within ±2 TECU, and the model errors obviously depend on seasons, latitudes and solar activity. Comparison with the previous work indicate that the proposed regional forecast model is competitive.

Spatiotemporal Analysis of Regional Ionospheric TEC Prediction Using Multi-Factor NeuralProphet Model under Disturbed Conditions

The ionospheric total electron content (TEC) is susceptible to factors, such as solar and geomagnetic activities, resulting in the enhancement of its non-stationarity and nonlinear characteristics, which aggravate the impact on radio communications. In this study, based on the NeuralProphet hybrid prediction framework, a regional ionospheric TEC prediction model (multi-factor NeuralProphet model, MF-NPM) considering multiple factors was constructed by taking solar activity index, geomagnetic activity index, geographic coordinates, and IGS GIM data as input parameters. Data from 2009 to 2013 were used to train the model to achieve forecasts of regional ionospheric TEC at different latitudes during the solar maximum phase (2014) and geomagnetic storms by sliding 1 day. In order to verify the prediction performance of the MF-NPM, the multi-factor long short-term memory neural network (LSTMNN) model was also constructed for comparative analysis. At the same time, the TEC prediction results of the two models were compared with the IGS GIM and CODE 1-day predicted GIM products (COPG_P1). The results show that the MF-NPM achieves good prediction performance effectively. The RMSE and relative accuracy (RA) of MF-NPM are 2.33 TECU and 93.75%, respectively, which are 0.77 and 1.87 TECU and 1.91% and 6.68% better than LSTMNN and COPG_P1 in the solar maximum phase (2014). During the geomagnetic storm, the RMSE and RA of TEC prediction results based on the MF-NPM are 3.12 TECU and 92.86%, respectively, which are improved by 1.25 and 2.30 TECU and 2.38% and 7.24% compared with LSTMNN and COPG_P1. Furthermore, the MF-NPM also achieves better performance in low–mid latitudes.

Two Hours Ahead Prediction of the TEC over China Using a Deep Learning Method

In this paper, we forecast the regional total electron content (TEC) over China (0–60° N, 70–140° E) two hours in advance using a deep learning method called pix2pixhd that is based on Generative Adversarial Networks (GAN). We use the International GNSS Service (IGS) TEC maps over China during the 2003–2018 period for training and divide the data into three parts: a training set (2003–2013), a test set (2014–2017), and a validation set (2018). We evaluate the prediction effect of our model using Root Mean Square Error and correlation coefficient and compare our model with IRI-2016. The result demonstrates that our model shows a good performance for TEC prediction in China. Under different geomagnetic and solar activity conditions, the performance of our model is always better than IRI-2016. Analyzing the average difference map between the output of our model and the target IGS TEC map (+2 h), our model behaves well in China including the low-latitude region. In addition, our model behaves better during quiet time and high solar activity years. The successful application of pix2pixhd in forecasting the regional TEC maps over China demonstrates that deep learning methods can solve many geoscience problems, especially for ionospheric parameter forecasting.

Reconstruction of the Regional Total Electron Content Maps Over the Korean Peninsula Using Deep Convolutional Generative Adversarial Network and Poisson Blending

AbstractThis study reconstructs total electron content (TEC) maps in the vicinity of the Korean Peninsula by employing a deep convolutional generative adversarial network and Poisson blending (DCGAN‐PB). Our interest is to rebuild small‐scale ionosphere structures on the TEC map in a local region where pronounced ionospheric structures, such as the equatorial ionization anomaly, are absent. The reconstructed regional TEC maps have a domain of 120°–135.5°E longitude and 25.5°–41°N latitude with 0.5° resolution. To achieve this, we first train a DCGAN model by using the International Reference Ionosphere‐based TEC maps from 2002 to 2019 (except for 2010 and 2014) as a training data set. Next, the trained DCGAN model generates synthetic complete TEC maps from observation‐based incomplete TEC maps. Final TEC maps are produced by blending of synthetic TEC maps with observed TEC data by PB. The performance of the DCGAN‐PB model is evaluated by testing the regeneration of the masked TEC observations in 2010 (solar minimum) and 2014 (solar maximum). Our results show that a good correlation between the masked and model‐generated TEC values is maintained even with a large percentage (∼80%) of masking. The performance of the DCGAN‐PB model is not sensitive to local time, solar activity, and magnetic activity. Thus, the DCGAN‐PB model can reconstruct fine ionospheric structures in regions where observations are sparse and distinguishing ionospheric structures are absent. This model can contribute to near real‐time monitoring of the ionosphere by immediately providing complete TEC maps.

SHAKING: Adjusted spherical harmonics adding KrigING method for near real-time ionospheric modeling with multi-GNSS observations

Precise positioning based on Global Navigation Satellite System (GNSS) technique requires high accuracy ionospheric total electron content (TEC) correction models to account for the ionospheric path delay errors. We present an adjusted Spherical Harmonics Adding KrigING method (SHAKING) approach for regional ionospheric vertical TEC (VTEC) modeling in real time. In the proposed SHAKING method, the VTEC information over the sparse observation data area is extrapolated by the Adjusted Spherical Harmonic (ASH) function, and the boundary distortion in regional VTEC modeling is corrected by the stochastic VTEC estimated using Kriging interpolation. Using real-time GPS, GLONASS and BDS-2/3 data streams of the Crust Movement Observation Network of China (CMONOC), the SHAKING-based regional ionospheric VTEC maps are re-constructed over China and its boundary regions. Compared to GNSS VTECs derived from the independent stations, the quality of SHAKING solution improves by 13–31% and 6–33% with respect to the ASH-only solution during high and low geomagnetic periods, respectively. Compared to the inverse distance weighting (IDW) generated result, significant quality improved of SHAKING-based VTEC maps is also observed, especially over the edge areas with an improvement of 60–80%. Overall, the proposed SHAKING method exhibits notable advantage over the existing regional VTEC modeling techniques, which can be used for regional TEC modeling and associated high-precision positioning applications.

Unexpected Regional Zonal Structures in Low Latitude Ionosphere Call for a High Longitudinal Resolution of the Global Ionospheric Maps

This study reports unexpected strong longitudinal structures from Global Navigation Satellite System (GNSS) derived total electron content (TEC) observations in the low-latitude ionosphere over Asia. The observations during 2019–2020 show diverse patterns in the zonal difference of regional TEC, even under geomagnetically quiet conditions. The TEC in the northern hemisphere occasionally exhibits drastic zonal gradients. The intense regional gradients in TEC span a longitudinal extent of about 20°. The higher values may appear on the east or the west side. Strong zonal gradients may appear in all seasons, regardless of geomagnetically quiet or active conditions. The 15 December 2019 and 16 March 2020 cases depict an intense zonal differences cluster in the narrow latitudinal band of 16°N to 28°N, spanning a regional scale smaller than the normal longitudinal structures. In contrast, the Global Ionospheric Maps (GIMs) with a longitudinal resolution of 5° show a much flatter zonal picture. Such intense and regional-scale zonal structures in the low-latitude ionosphere call for a high zonal resolution of GIMs in terms of better geographically distributed observations. Notably, no counterpart regional structures are found at the conjugated points in the southern hemisphere during the two cases. Although the physical drivers are not certain, the appearance only in the northern hemisphere possibly excludes the dominant contribution to forming the regional structures from the equatorial electric field.

Studying the winter anomaly with altimeter-derived TEC data

• This work presents of a new approach for using altimeter TEC data to study the ionospheric WA. • The outcomes agree with historical results on the locations of WA active regions. • A phenomenon leading to WA events during high solar activity was possibly identified. The ionospheric Winter Anomaly (WA) is a phenomenon discovered almost 100 years ago. It can be defined as the situations in which over a given location the winter ionization level is larger than the summer ionization level, for approximately the same solar activity conditions. Along the decades, a lot of studies have been carried out and relevant theories have been formulated to explain this phenomenon, but some aspects of the nature and physical principles of the WA are still a matter of discussion. The first objective of this work was to introduce a new technique for studying the WA, at any given location over the Oceans, based on the 27-year series of altimeter (TOPEX, Jason1, Jason 2 and Jason3 satellites)-derived Total Electron Content (TEC) data. The second objective of this work was to validate the new technique by presenting a comparative analysis between the results obtained with the new technique and those already published. This goal has been accomplished by studying the WA events over the 50°N and 50°S geographic parallels using the 27-year long altimeter data series. The results have indicated clear and systematic WA occurrences over the Northern Hemisphere and a more complex situation over the Southern Hemisphere, with two regions having different behaviors. These results are in full agreement with the findings published in relevant previous works. The last objective of this work was to present some original findings related to WA events. Taking advantage of the new technique, it has been shown that the WA might be interpreted as a high solar activity period consequence of a yearly periodic phenomenon. This phenomenon is always present, also during low solar activity years, even when WA effects are not visible. During winters over the Southern Hemisphere, it systematically produces (at any solar activity level) low maximum TEC values in the (180°E–360°E) longitudinal region and high maximum TEC values in the (0°E–180°E) longitudinal sector. Precisely, this last sector matches with the well-known region over which WA events are observed for high solar activity.

IONORING: Real-Time Monitoring of the Total Electron Content over Italy

IONORING (IONOspheric RING) is a tool capable to provide the real-time monitoring and modeling of the ionospheric Total Electron Content (TEC) over Italy, in the latitudinal and longitudinal ranges of 35°N–48°N and 5°E–20°E, respectively. IONORING exploits the Global Navigation Satellite System (GNSS) data acquired by the RING (Rete Integrata Nazionale GNSS) network, managed by the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The system provides TEC real-time maps with a very fine spatial resolution (0.1° latitude x 0.1° longitude), with a refresh time of 10 min and a typical latency below the minute. The TEC estimated at the ionospheric piercing points from about 40 RING stations, equally distributed over the Italian territory, are interpolated using locally (weighted) regression scatter plot smoothing (LOWESS). The validation is performed by comparing the IONORING TEC maps (in real-time) with independent products: (i) the Global Ionospheric Maps (GIM) - final product- provided by the International GNSS Service (IGS), and (ii) the European TEC maps from the Royal Observatory of Belgium. The validation results are satisfactory in terms of Root Mean Square Error (RMSE) between 2 and 3 TECu for both comparisons. The potential of IONORING in depicting the TEC daily and seasonal variations is analyzed over 3 years, from May 2017 to April 2020, as well as its capability to account for the effect of the disturbed geospace on the ionosphere at mid-latitudes. The IONORING response to the X9.3 flare event of September 2017 highlights a sudden TEC increase over Italy of about 20%, with a small, expected dependence on the latitude, i.e., on the distance from the subsolar point. Subsequent large regional TEC various were observed in response to related follow-on geomagnetic storms. This storm is also used as a case event to demonstrate the potential of IONORING in improving the accuracy of the GNSS Single Point Positioning. By processing data in kinematic mode and by using the Klobuchar as the model to provide the ionospheric correction, the resulting Horizontal Positioning Error is 4.3 m, lowering to, 3.84 m when GIM maps are used. If IONORING maps are used as the reference ionosphere, the error is as low as 2.5 m. Real-times application and services in which IONORING is currently integrated are also described in the conclusive remarks.

Improving regional ionospheric TEC mapping based on RBF interpolation

Radial basis function (RBF) interpolation with multi-quadric is developed to perform ionospheric total electron content (TEC) mapping for the Chinese region between 15°N ~ 40°N and 100°E ~ 125°E. TEC measurements from the Centre for Orbit Determination in Europe (CODE) covering the solar maximum year 2011 are used to investigate the performance of the proposed RBF interpolation method. The differences between the RBF interpolated TEC and the CODE TEC are within 0.5 TECU and the root mean square error (RMSE) is very small when 49 data points are used. The maximum difference is ~5 TECU and the error is less than 1 TECU with 25 samples. Our study suggests that a random distribution of measurement points gives smaller RMSEs than a homogenous distribution when the number of sample points is low. The study indicates that RBF interpolation offers a powerful and reliable tool for ionospheric TEC mapping.

Kriging‐based ionospheric TEC, ROTI and amplitude scintillation index (S4) maps for India

In this study, an attempt is made to develop regional ionospheric total electron content (TEC), rate of TEC index (ROTI) and amplitude scintillation index (S 4) maps using data from 26 dual-frequency global positioning system (GPS) receivers under GPS aided geo-stationary earth orbit augmented navigation programme over Indian region. One-minute spatial TEC maps are generated for the entire Indian region covering 65–100°E geographic longitudes, 5–40°N geographic latitudes with 2° × 2° grid separation using Kriging method. Also, the ROTI and amplitude scintillation index (S 4) maps for every 5 min are generated. The performance of the generated regional TEC maps is evaluated during a severe geomagnetic storm condition. Patterns of equatorial ionisation anomaly (EIA) TEC structures are investigated for St. Patrick's storm between the days 15 and 20 March 2015 with the generated TEC maps. The proposed TEC maps depict the northern crest of EIA features in latitudinal extent and TEC strength. The kriging method detects the suppressed and downshift of EIA features on 18 March 2015. The movement of plasma bubbles are analysed over Indian latitudes during the transition period of a geomagnetic storm on 17 March 2015.

First Report of an Eclipse From Chilean Ionosonde Observations: Comparison With Total Electron Content Estimations and the Modeled Maximum Electron Concentration and Its Height

AbstractThe ionospheric responses to the total solar eclipse on 2 July 2019 over low latitudes in southern South America are presented. Ionosonde observations were used within the totality path at La Serena (LS: 29.9°S, 71.3°W) and at Tucumán (TU: 26.9°S, 65.4°W) and Jicamarca (JI: 12.0°S, 76.8°W), with 85% and 52% obscuration, respectively. Total electron content (TEC) estimations over the South American continent were analyzed. The ionospheric impact of the eclipse was simulated using the Sheffield University Plasmasphere‐Ionosphere Model (SUPIM) at the Instituto Nacional de Pesquisas Espaciais (INPE). The significant variability of the diurnal variations of the various ionospheric characteristics over equatorial and low latitudes on geomagnetically quiet days makes it difficult to unambiguously determine the ionospheric responses to the eclipse. Nonetheless, some specific issues can be derived, mainly using simulation results. The E and F1 layer critical frequencies and densities below 200 km are found to consistently depend on decreasing solar radiation. However, the F1 layer stratification observed at both TU and LS cannot be related to the eclipse or other processes. The F2 layer does not follow the changes in direct solar radiation during the eclipse. The SUPIM‐INPE‐modeled F region critical frequency and TEC are overestimated before the eclipse at LS and particularly at TU. However, these overestimations are within the observed large day‐to‐day variability. When an artificial prereversal enhancement is added, the simulations during the eclipse better reproduce the observations at JI, are qualitatively better for LS, and are out of phase for TU. The simulations are consistent with conjugate location effects.

Ionospheric and Magnetic Signatures of a Space Weather Event on 25–29 August 2018: CME and HSSWs

AbstractWe present a study concerning a space weather event on 25–29 August 2018, accounting for its ionospheric and magnetic signatures at low latitudes and midlatitudes. The effects of a storm in several longitudinal sectors (Asia, Africa, America, and the Pacific) have been analyzed using various parameters such as total electron content (TEC), geomagnetic field, and column [O/N2] ratio. Positive ionospheric storms are found in all the longitudinal sectors having its maximum effects in the Asian sector, whereas the negative ionospheric storms have been observed in the summer hemisphere (Northern Hemisphere). A large decrease in [O/N2] ratio in the Northern Hemisphere is a possible cause of the observed negative storm effects. Ionospheric F2 region maximum electron density (NmF2) and TEC have shown a positive correlation during this storm. The study suggests that storm time‐generated wind does not have a uniform planetary extension and mainly affects dayside (America and Pacific) and duskside (Africa) sectors. During the space weather event, we observe an asymmetric variation of the magnetic field as a function of the longitude. On the other hand, the magnetic variations at midlatitudes are found to be symmetric in both hemispheres. A signature of the disturbance dynamo (anti‐Sq circulation) has been observed, mainly at low latitudes. We emphasize that the partial ring current (PRC), estimated by the ASYM‐H magnetic index, must also be taken into account along with the SYM‐H index for a better approximation of ionospheric currents. The study further suggests existence of several electric current cells in the ionosphere, which is consistent with the Blanc‐Richmond model.

IONISE: An Ionospheric Observational Network for Irregularity and Scintillation in East and Southeast Asia

AbstractAn Ionospheric Observational Network for Irregularity and Scintillation in East and Southeast Asia (IONISE) is developed to identify and study the short‐term and fine‐scale ionospheric variations over China. The IONISE network mainly includes three crossed chains of Beidou geostationary satellite total electron content (TEC)/scintillation receivers along 110°E, 23°N, and 40°N respectively, multistatic portable digital ionosondes and bistatic very high‐frequency radars. Based on the IONISE observations, we report some preliminary results of ionospheric disturbances and irregularities, including (1) initially generated and zonally drifting equatorial plasma bubbles and related scintillations, (2) traveling ionospheric disturbances from middle to low latitudes, (3) drift of strong sporadic E structures over a wide area of more than 1,000 km, (4) fine‐scale ionospheric perturbation and regional TEC gradient, and (5) general features of ionospheric response to geomagnetic storms. Possible mechanisms responsible for these ionospheric phenomena are discussed. The IONISE provides new data set for investigation on ionospheric disturbances of various scales in a broad region with dense observations along specific latitude/longitude.