Total Electron Content Disturbances Research Articles

Response of total electron content to the October 25, 2022 partial solar eclipse from high to low latitudes in the Euro-Asian region

Solar eclipses (SEs) pertain to high-energy sources. They are capable of causing significant disturbances in all geoshells and geophysical fields. Despite the almost century-long history of studying the influence of eclipses on geoshells, the task of observing and analyzing disturbances in them remains relevant. This is explained by the fact that the response of the media significantly depends on the state of atmospheric and space weather, the location and time of observation, the SE magnitude, etc. The aim of this paper is to present the results of a statistical analysis of the features of the total electron content (TEC) variations during the October 25, 2022 SE from high to low latitudes in the Euro-Asian region. Data from Global Navigation Satellite System were used for the analysis. The error in estimating TEC in the vertical column did not exceed 0.1 TECU. For the first time, the response of the ionosphere to an SE has been studied on a global scale (from the Reykjavik station to the Novosibirsk station) using methods of statistical analysis, including the time moments after sunset. The decrease in TEC reached 1.0–19.0 TECU, and the relative decrease was approximately –0.32. Changes in all TEC disturbance parameters depended in a complex manner on the relative obscuration area of the solar disk. This can be explained by non-monotonic changes in electron density during the daytime, by the intensification of the ionosphere–plasmasphere coupling, the disturbance of the ionospheric current system, vertical plasma drift in crossed electric and magnetic fields, as well as the generation of wave disturbances during the SE period. The delay time of the maximum ionospheric response (maximum |δV| value) with respect to the maximum magnitude of the eclipse was 15–25 min. The duration of the ionospheric response to the SE slightly exceeded the duration of the perturbing source influence.

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.

Detection of Traveling Ionospheric Disturbances Triggered by 2022 Tonga Volcanic Eruptions Through CubeSats Coherent GNSS‐Reflectometry Measurement

AbstractWe present two case studies of traveling ionospheric disturbances (TIDs) triggered by the 2022 Tonga volcanic eruption observed by low‐cost CubeSat‐based global navigation satellite system reflectometry (GNSS‐R) measurements. The GNSS‐R data used in this work are from Spire Global CubeSats. Our analysis shows that coherent GNSS signals reflected over the ocean can be used to derive precise ionospheric total electron content (TEC) measurements. The first case shows clear TID structures with a TEC disturbance magnitude of ∼1 TEC unit (TECu) and horizontal wavelength of ∼330 km over Northwest Australia on the day of Tonga volcanic eruption. The second case shows the TIDs with ∼0.05 TECu disturbance magnitude and horizontal wavelength of ∼240 km over East Russia the day after the eruption. The second case is likely a TIDs propagated outward from Tonga for the second time after it traversed around the Earth. The GNSS‐R observed TID may be associated with the incident or reflection signal ray path. In this paper, the appropriate ray path was identified using simultaneous observations from ground receiver networks in the areas of both ray paths.

A model of TEC perturbations possibly related to seismic activity

For application of observed anomalies of the total electron content (TEC) in the ionosphere for short-term earthquake prediction, it is necessary to understand the physical nature of such anomalies during the preparation of a strong seismic event. The physical mechanism of occurrence of such anomalies is considered in order to distinguish the TEC disturbance of a seismic origin and to clear the processes in the lithosphere resulted in an appearance of the TEC anomaly in the ionosphere. It is supposed that the observed TEC anomalies arise as a result of occurrence of additional electric field in the ionosphere demonstrated by numerous satellite data before the impending earthquakes. At the same time, an injection of charged aerosols into the atmosphere in the epicentral earthquake area was detected. As a result, an electromotive force arises in the surface layer of the atmosphere, which initiates a perturbation of the electric current in the global circuit and the electric field appearance in the ionosphere. We have shown that the TEC disturbance arises as a result of the heating of the ionosphere by electric current and the plasma drift in the electric field of this current. The spatial distribution of TEC arises as a result of the combined action of these two factors, and its nature depends on the relationship between them. Based on the developed model the numerical study of the spatial distribution of TEC in the ionosphere is possible for a given horizontal distribution of the concentration of charged aerosols in the atmosphere near the Earth’s surface.

THE CORRELATION OF SHORT-PERIOD WAVE DISTURBANCES IN THE PEAK ELECTRON DENSITY OF THE F2 LAYER AND THE TOTAL ELECTRON CONTENT (TEC) IN THE IONOSPHERE

Using data of the vertical sounding ionosonde and the GNSS receiver operating in Irkutsk, we analyzed the correlation of short-period (periods less than 24 hours) wave disturbances of the peak electron density of the F2 layer (NmF2) and the total electron content (TEC) in the ionosphere. The measurement data for the period 2003–2020, which included almost two solar cycles, were processed. It has been established that the most probable case is a high positive correlation of short-period disturbances of NmF2 and TEC. With the growth of solar and geomagnetic activity, the number of cases of strong positive correlation increases (from 53% to 66%) and the number of cases of both positive and negative weak correlation decreases (from 46% to 33%). During powerful geomagnetic storms, the highest correlation (up to R = 0.89) is observed in the storm main phase and then decreases in the recovery phase up to negative R values. Possible physical mechanisms of the obtained results are considered.

Correlation of Short-Period Wave Disturbances of the Peak Electron Density of the F2 Layer and the Total Electron Content in the Ionosphere

Correlation analysis of short-period (periods less than 24 h) wave disturbances of the maximum electron density in the F2 layer (NmF2) and the total electron content (TEC) was analyzed based on the data of the vertical ionosonde sounding and receiver of the Global Navigation Satellite Systems operating in Irkutsk. The measurement data in the period 2003–2020, which included almost two solar cycles, have been processed. It was found that the most likely case is a high positive correlation of short-period NmF2 and TEC disturbances. The number of cases of strong positive correlation increases (from 53 to 66%), and the number of cases of positive and negative weak correlation decreases (from 46 to 33%) as the solar and geomagnetic activity increases. During strong geomagnetic storms, the highest correlation (up to R = 0.89) is observed in the main phase of the storm and then decreases in the recovery phase to negative R values. Possible physical mechanisms of the results are considered.

The 6 February 2023 Türkiye Earthquake Sequence as Detected in the Ionosphere

AbstractOn 6 February 2023, a series of large earthquakes struck Turkey and Northern Syria. The main earthquake of Mw 7.8 occurred at 01:17:34 UTC and was followed by the three notable (Mw > 5.5) aftershocks within the next 18 min. Then, ∼9 hr later, the biggest aftershock with magnitude Mw 7.5 and a Mw 6.0 earthquake occurred to the north‐east from the first main earthquake. In this work, we use data of ground‐based Global Navigation Satellite Systems (GNSS) receivers in Turkey, Israel and Cyprus to analyze the ionospheric response to this series of earthquakes. We separate these events in two groups: the first sequence of earthquakes (at 01–02 UTC) and the second sequence (at 10–11 UTC). For the first sequence, we observe a clear N‐shaped total electron content (TEC) response after the Mw 7.8 mainshock earthquake and Mw 6.7 aftershock, and a smaller TEC disturbance that is, most likely, caused by the Mw 5.6 earthquake. The latter is now the smallest earthquake detected by using ionospheric GNSS data. The co‐seismic ionospheric disturbances (CSID) propagated from the epicentral area in the south‐west direction with velocities of about 750–830 m/s. For the second sequence, we observed the response to the Mw 7.5 aftershock earthquake and the Mw 6.0 aftershock. The CSID propagated both to the south‐west and the north‐west to the epicentral area, with velocities of about 950–1,100 m/s.

Responses of Total Electron Content to Solar Flares over Low and Mid-Latitude Regions during Sun Halo Day

The responses of total electron content (TEC) to solar flares over low- and mid-latitude regions during the sun halo days were investigated. The research is based on GPS data obtained from Bangalore (13.02117°N, 77.57038°E) on May 24, 2021; Cape Town (-33.918861°N, 18.423300°E) on October 26, 2020; and North Dakota (46.55756°N, -96.472300°E) on December 27, 2021, during the solar halo days. The results of this study demonstrate that the values of TEC increased at Bangalore and Cape Town stations during solar halo days as compared to other days. However, over the North Dakota station, TEC during the sun halo day was greater than that on the days before and after the halo day from around 19:00 UT to 23:59 UT hours. During the sun halo over Bangalore and Cape Town stations, positive relative changes in TEC prevail, suggesting that the action of the interplanetary electric field, the prompt penetration electric field, and the disturbance dynamo electric field lead to higher TEC values. However, during the sun halo over North Dakota station, negative relative changes in TEC prevail, which might be related to the consequence that low solar activity with no earth’s field disturbances (a positive Dst) leads to lower ionospheric TEC values. Stations that have greater relative changes in TEC have shown greater power spectrum and global wave spectrum energy. Cape Town has a greater relative change in TEC, a greater power spectrum, and a larger global wave spectrum than Bangalore and North Dakota stations. The values of TEC over three stations are different due to the latitudinal and longitudinal differences in addition to the universal time effects. Finally, solar flares have a major influence on ionosphere electrodynamics, and the upward drift velocity of ionospheres at the low latitude station is more strongly influenced by solar flares due to the effects of the ExB drifts, which induce TEC disturbances during the halo days over the suggested stations.

IONOSPHERIC TOTAL ELECTRON CONTENT VARIATIONS CAUSED BY THE TONGA VOLCANO EXPLOSION ON JANUARY 15, 2022

The capability of volcanoes to generate powerful explosive eruptions influencing the state of the ionosphere became known back in the 1980th. The Hunga-Tonga-Hunga-Ha’apai (Tonga for short) volcano explosion on January 15, 2022, has shown a surge of renewed interest in investigating effects in the Earth — atmosphere — ionosphere — magnetosphere system since this volcano can be rightfully classified as unique. A number of papers have already dealt with the ionospheric effects generated by the Tonga volcano. The temporal variations in the total electron content (TEC) were used to determine the number of volcano explosions to be five. The second and third explosions were the strongest, with the second being the most intense. The response of the ionosphere to the Tonga volcano explosion has been studied on local and global scales by making use of the Global Positioning System satellite constellation and measurements onboard the Swarm satellite network. In the vicinity of the volcano explosion, disturbances in TEC attained 5—10 TECU. In addition to the local effect, traveling ionospheric disturbances were observed to propagate, which were due to the generation and propagation of atmospheric gravity waves with speeds of 180 m/s to 1,050 m/s. Of particular importance to global-scale perturbations is the Lamb wave, which propagated with a speed of 315 m/s. At nighttime, plasma depletions of the equatorial ionosphere were revealed over the tropical Pacific Ocean when the electron density at 400—500 km altitude showed a decrease by 2-3 orders of magnitude. The length of these formations in longitude exceeded ~10 Mm, and they were observed for more than 4—5 h. The scientific objective of this study is further analysis of aperiodic and quasi-periodic perturbations in the ionosphere, which were caused by the Tonga volcano explosion, in a wide range of distances from the source of disturbance (from ~0.1 Mm to 5 Mm). To reveal the ionospheric response to the Tonga volcano explosion, the records of signals from Global Positioning System satellites have been analyzed. The intercomparison of temporal variations in TEC observed on the reference days and on the day when the volcano explosion occurred has resulted in the determination of basic principles of the generation of ionospheric perturbations and the estimation of numerical magnitudes of the parameters of the perturbations. Four groups of disturbances have been detected, each of which arrived at different time delays with respect to the moment of the volcano explosion. It is important to note that the time delay increases with increasing distance from the volcano to the observational instruments. The first group of speeds included the disturbances traveling with a speed close to 1,000 m/s and having an N-shaped profile. This perturbation was generated by a blast wave whose speed depended on the excess pressure and a priori exceeded the speed of sound. In the second group, the speed varied in the 336 m/s to 500 m/s range, within which the speeds of atmospheric gravity waves are found. The speeds in the third group exhibited variability within the 260—318 m/s limits, within which the Lamb wave propagates. The speed in the fourth group was estimated to be 190—220 m/s, which is a characteristic speed of the tsunami that was caused directly by the volcano explosion. The period of quasi-periodic perturbations varied from ~10 min to 20 min, while their amplitudes were from 0.5 TECU to 1 TECU. The observed ionospheric «hole» was proved to be produced by the volcano explosion directly, with the modules of the absolute and relative magnitudes of disturbances showing a tendency for decreasing with increasing distance from the explosion epicenter, from ~10 TECU to 2 TECU and from 37 % to 7 %, respectively. Contrary to the amplitude, the «hole» time delay and its duration exhibited an increase with distance from the volcano to the observational sensors, from 35 min to 100 min and from ~ 30—40 min to 120— 150 min, respectively. A mechanism for generating the ionospheric «hole» has been advanced, which is based on both the electric and non-electric processes (cracking, the friction of particles, condensation of water vapor, coagulation of water droplets, attachment of electrons, gravity segregation, etc.). The ionospheric «hole» is formed as a result of perturbing the global electric circuit, arising external electric currents, an increase in the electric field strengths by orders of magnitude in the atmosphere and the ionosphere, diffusion of the ionospheric plasma down to lower altitudes where the recombination processes become fast. The basic numerical characteristics have been established of the disturbances, whose fluctuations account for local time, the dusk terminator, sensor geographic locations, the location of subionospheric points on the satellite to receiver ray paths with respect to the equatorial anomaly, etc.

Deriving Ionospheric Sporadic E Intensity From FORMOSAT‐3/COSMIC and FY‐3C Radio Occultation Measurements

AbstractThe total electron content (TEC) profiles from the FORMOsa SATellite mission‐3/Constellation Observing System for the Meteorology, Ionosphere, and Climate (COSMIC) and the Fengyun‐3C (FY‐3C) radio occultation (RO) missions during 2006 and 2019 are used to establish the models for deriving the ionospheric sporadic E (Es) critical frequency (foEs). Smax is derived as the maximum vertical gradient of TEC disturbance, which is extracted from a RO TEC profile using the singular spectrum analysis method. Three candidate conversion models are obtained by fitting Smax with foEs observed by collocated ionosondes, and the one with the best performance, the COSMIC&FY‐3C (CF) model, is applied for deriving foEs (foEsCF) from the TEC data of the two missions jointly. For comparison, the C model, which is of similar form as the CF model while being established without using the FY‐3C data, is applied for deriving foEs (foEsC) from the COSMIC TEC data only. The validations over four independent ionosonde stations demonstrate that mean improvements of 0.11 MHz (32%) in the absolute bias and 0.24 MHz (17%) in the root mean square error are obtained by foEsCF compared with foEsC. The spatiotemporal distributions of Es intensity during 2015 and 2019, presented respectively by foEsCF and foEsC, are further compared. The CF model provides more abundant and more detailed information about Es intensity distribution, which is most distinct at high latitudes where the contribution of FY‐3C RO TEC data is significant. Our results reveal that with the aging of the COSMIC satellites, FY‐3C TEC data is a valuable supplementary RO data source for Es‐related studies.

Statistical Study of F‐Region Short Period Ionospheric Disturbances Related to Convection in the Lower Atmosphere Over Wuhan, China

AbstractWe investigated the relationship between convective activity and F‐region short‐period ionospheric disturbances at middle latitudes from 2018 to 2020. The ionospheric variations were extracted from the total electron content (TEC) data obtained by the BeiDou geostationary orbit receiver in Wuhan, China, while the convective activities were represented by precipitation data from the fifth generation European Center for Medium‐Range Weather Forecasts Reanalysis (ERA5). Additionally, an ionosonde located in Wuhan, China, was used to study the variation in the sporadic E (Es)‐layer. Seasonal variations in the convective activity and TEC disturbances were studied. It was found that short‐period ionospheric disturbances occurred mainly around summer midnight and around the June solstice. In addition, the correlations between convective activity and the ionosphere have also been studied. A positive correlation between precipitation and short‐period ionospheric disturbances was found. Similarly, precipitation and also had a positive correlation. By analyzing the precipitation azimuth and upward propagation of convective gravity waves, we proposed a possible coupling mechanism between the ionosphere and the troposphere, through which convective gravity waves could indirectly affect F‐region short‐period ionospheric disturbances by modulating the Es‐layer.

Connection of total electron content disturbances with AE index of geomagnetic activity during geomagnetic storm in March 2015

Ionospheric response to the March 17, 2015 geomagnetic storm has been investigated using simulations of the Global Self-consistent Model of the Thermosphere, Ionosphere, Protonosphere (GSM TIP) [Dmitriev et al., 2017; Klimenko et al., 2018]. GSM TIP demonstrates results that do not contradict experimental data. This paper deals with GSM TIP simulated disturbances in the Total Electron Content (TEC) at different longitudes and zonal averages on March 17–23, 2015. At all longitudes, we can observe the existence of a band of TEC positive disturbances, located over the geomagnetic equator, and the formation of an after-storm ionospheric effect that appeared as positive TEC disturbances at midlatitude 3–5 days after the geomagnetic storm main phase. We have analyzed the dependence of disturbances of the thermosphere-ionosphere system (total electron content, n(N2), n(O), zonal electric field, meridional component of the thermospheric wind at a height of 300 km, and electron temperature at a height of 1000 km), calculated by GSM TIP from variations in the geomagnetic activity index AE. The analysis is based on Pearson’s correlation coefficients, presented as maps of the dependence of the correlation coefficient on UT and latitude for selected longitudes and for zonal averaged values. The results suggest that at high latitudes of the Northern and Southern hemispheres the correlation coefficient of TEC disturbances and AE variations is close to 1 at all longitudes in the period from 12 UT to 23 UT. From 9 UT to 12 UT, the minimum value of the correlation coefficient is observed at all latitudes and longitudes. The time intervals of the correlation values are associated with the features of a particular geomagnetic storm, for which, for example, the interval from 12 UT to 23 UT on March 17, 2015 corresponds to the geomagnetic storm main phase. We discuss possible mechanisms for the formation of such a relationship between simulated TEC disturbances and the AE index.

Связь возмущений полного электронного содержания с AE-индексом геомагнитной активности во время геомагнитной бури в марте 2015 г.

Ionospheric response to the March 17, 2015 geomagnetic storm has been investigated using simulations of the Global Self-consistent Model of the Thermosphere, Ionosphere, Protonosphere (GSM TIP) [Dmitriev et al., 2017; Klimenko et al., 2018]. GSM TIP demonstrates results that do not contradict experimental data. This paper deals with GSM TIP simulated disturbances in the Total Electron Content (TEC) at different longitudes and zonal averages on March 17–23, 2015. At all longitudes, we can observe the existence of a band of TEC positive disturbances, located over the geomagnetic equator, and the formation of an after-storm ionospheric effect that appeared as positive TEC disturbances at midlatitude 3–5 days after the geomagnetic storm main phase. We have analyzed the dependence of disturbances of the thermosphere-ionosphere system (total electron content, n(N2), n(O), zonal electric field, meridional component of the thermospheric wind at a height of 300 km, and electron temperature at a height of 1000 km), calculated by GSM TIP from variations in the geomagnetic activity index AE. The analysis is based on Pearson’s correlation coefficients, presented as maps of the dependence of the correlation coefficient on UT and latitude for selected longitudes and for zonal averaged values. The results suggest that at high latitudes of the Northern and Southern hemispheres the correlation coefficient of TEC disturbances and AE variations is close to 1 at all longitudes in the period from 12 UT to 23 UT. From 9 UT to 12 UT, the minimum value of the correlation coefficient is observed at all latitudes and longitudes. The time intervals of the correlation values are associated with the features of a particular geomagnetic storm, for which, for example, the interval from 12 UT to 23 UT on March 17, 2015 corresponds to the geomagnetic storm main phase. We discuss possible mechanisms for the formation of such a relationship between simulated TEC disturbances and the AE index.

Robust uncertainty quantification of the volume of tsunami ionospheric holes for the 2011 Tohoku-Oki earthquake: towards low-cost satellite-based tsunami warning systems

Abstract. We develop a new method to analyze the total electron content (TEC) depression in the ionosphere after a tsunami occurrence. We employ Gaussian process regression to accurately estimate the TEC disturbance every 30 s using satellite observations from the global navigation satellite system (GNSS) network, even over regions without measurements. We face multiple challenges. First, the impact of the acoustic wave generated by a tsunami onto TEC levels is nonlinear and anisotropic. Second, observation points are moving. Third, the measured data are not uniformly distributed in the targeting range. Nevertheless, our method always computes the electron density depression volumes, along with estimated uncertainties, when applied to the 2011 Tohoku-Oki earthquake, even with random selections of only 5 % of the 1000 GPS Earth Observation Network System receivers considered here over Japan. Also, the statistically estimated TEC depression area mostly overlaps the range of the initial tsunami, which indicates that our method can potentially be used to estimate the initial tsunami. The method can warn of a tsunami event within 15 min of the earthquake, at high levels of confidence, even with a sparse receiver network. Hence, it is potentially applicable worldwide using the existing GNSS network.

Ionospheric total electron content anomaly possibly associated with the April 4, 2010 Mw7.2 Baja California earthquake

• New decomposition and nonlinear fitting method to extract TEC disturbances. • TEC increasing near epicenter on March 25, 2010, 10 days before Mw7.2 Baja California earthquake. • Both data and model show the uniqueness of the TEC enhancement on March 25. Identifying ionospheric disturbances potentially related to an earthquake is a challenging work. Based on the ionospheric total electron content (TEC) data from the madrigal database at the Haystack Observatory, Massachusetts Institute of Technology, a new decomposition and nonlinear fitting method has been developed and applied in this work to extract the TEC disturbances that are potentially related to the Mw7.2 Baja California earthquake occurred on April 4, 2010. By analyzing the TEC data for a long period of time (72 days) before and after the earthquake, we found that a unique TEC enhancement occurred in the region around the epicenter on March 25. No other significant ionospheric TEC anomalies were identified in the 72-day period around the earthquake, except some TEC disturbances that appeared to be related to the geomagnetic activity between April 1 and 6, 2010. We further analyzed the TEC data from other magnetically quiet days, and no TEC anomaly like that occurred on March 25 was detected. The TEC data calculated from a first principles model SD-WACCM-X were also analyzed using the same method as that for the observational data. No TEC anomaly was found on March 25 from the model outputs either. Thus the source of the TEC anomaly on March 25 is unlikely from the lower atmosphere waves. In this study, we show the occurrence of TEC anomaly on March 25, 10 days before the Mw7.2 Baja California earthquake and this TEC anomaly may not be explained by lower atmosphere or geomagnetic activity forcing.

Vertical characterization on global ionospheric variations during the magnetic storm in September 2017 with hierarchical subtraction method

This study investigates the global ionospheric responses at different altitudes during the geomagnetic storm in September 2017 by using the observations from IGS GIMs and GRACE, TerraSAR-X, COSMIC, Metop LEO satellite missions. According to different satellite heights, a hierarchical subtraction method is proposed to characterize the disturbance of total electron content (TEC) at the vertical regions of below 340 km , 340 ∼ 520 km , 520 ∼ 800 km and above 800 km , respectively. The integrated TEC from IRI-Plas2017 are applied to verify the feasibility and rationality of the proposed method and the electron density (Ne) profiles from the ionosonde and radio occultation (RO) measurements are used to explore the variations of Ne in different height regions. The resulting TEC disturbances ( Δ TEC) on a global scale show that: 1) There was significant increase on Ne peak in F2 region during the magnetic storm, due to the strong recombination in the lower ionosphere while more intense electron ionization in the upper ionosphere; 2) During the main phase, TEC enhancement had a tendency to drift westward, which may correlate with the twice Dst minimums. 3) The east–west and north–south hemispheric asymmetry of Δ TEC exist simultaneously in this magnetic storm. However, the former is mainly attributed to ionospheric plasma bubbles, while the latter might be the seasonal thermospheric effects or the energetic particle emissions.

Ionospheric Total Electron Content and Disturbance Observations From Space-Borne Coherent GNSS-R Measurements

In this article, we investigate coherent global navigation satellite system reflectometry (GNSS-R) measurements obtained at the low earth orbits (LEOs) as a potential new data source for ionospheric total electron content (TEC) and ionospheric disturbance observations. Current global ionospheric TEC maps (GIMs) have limited spatial and temporal resolutions and accuracy due to lack of GNSS observations over oceans, polar caps, and inaccessible terrains. Our analysis of Spire Global’s CubeSat data indicates that coherent GNSS signals reflected off sea ice, inland water bodies, and calm ocean surface can be processed to achieve cm-level precision carrier phase estimations. Signal coherency is especially prevalent over sea ice where 41.7% reflections are coherent, compared to 4.3% in the overall dataset. This article presents the methodology to estimate slant TEC along the reflection signal ray path using coherent dual-frequency GNSS-R pseudoranage and carrier phase estimations obtained from low-cost CubeSats. The methodology is applied to Spire Global’s CubeSat data. The results show that the slant TEC retrieved from GNSS-R measurements and from GIM follow a similar trend. Moreover, the GNSS-R-based TEC time series offer a nearly “frozen in time” observation of the ionospheric structures due to the rapid scan velocity of GNSS-R rays across the ionosphere. The study demonstrates the potential of GNSS-R observations to fill the data gaps over the polar regions where space weather activities and TEC disturbances are most frequent and intense. Potential error sources and mitigation techniques are also discussed.

Generation of Proxy GIM‐TEC for Extreme Storms Before the Era of GNSS Observations

AbstractFor the first time, we reconstructed global distribution of both the total electron content disturbance W index and TEC values for eight extreme storms (Dst < −250 nT) occurred before the epoch of GNSS observations in solar cycle 22. We created a model based on superposed epoch analysis of the training set of GIM‐W maps of nine SC23 extreme storms. Global GIM‐W index maps are calculated from 15‐min UPC GIM‐TEC (UQRG) as the logarithmic deviation of instantaneous TEC from the monthly median GIM‐MTEC empirical model. We introduced the storm phase metrics for main and recovery phases of the positive ionosphere disturbance (the WU‐index), the negative disturbance (the WL‐index) and the ring current (the Dst‐index). The probabilistic forecasting model (Pmodel) for SC22 GIM‐Wx maps is developed based on GIM‐W maps of the SC23 training set. The storm phase distribution Φx for the eight SC22 extreme storms is calculated from the proxy time shift (lag) of peak WUmax and WLmin relative to Dstmin. Proxy GIM‐TECx maps are calculated by adjusting the GIM‐MTEC median to the GIM‐Wx prediction. Validation of the technique based on data of UPC and JPL for four intense ionospheric storms showed a root‐mean‐square error less than 3 TECU. The proposed technique can be applied for both the past and future forecasting of GIM‐W index and GIM‐TEC maps.

GNSS TEC-Based Earthquake Ionospheric Perturbation Detection Using a Novel Deep Learning Framework

In this article, a new method for seismic ionospheric Global Navigation Satellite System (GNSS) total electron content (TEC) based anomaly detection using a deep learning framework is proposed. The performance of the proposed encoder&#x2013;decoder long short-term memory extended model is compared with those of five other benchmarking predictors. The proposed model achieves the best performance (<i>R</i>² &#x003D; 0.9105 and root-mean-square error (RMSE) &#x003D; 2.6759) in predicting TEC time series data, demonstrating a 20&#x0025; improvement in <i>R</i>² and 39.1&#x0025; improvement in the RMSE over the autoregressive integrated moving average model. To detect the pre-earthquake ionospheric disturbances more accurately, a reasonable strategy for determining anomaly limits is also proposed. Finally, the method is applied to analyze the pre-earthquake ionospheric TEC disturbance of the 2016 Xinjiang <i>M</i>_<i>s</i> 6.2 earthquake. By excluding the effects of solar activity and geomagnetic activity, obvious ionospheric anomalies could be observed, occurring during 4&#x2013;8 days prior to, and on 1 day before, the earthquake. Negative anomalies tended to occur in the earlier period, whereas positive anomalies occurred closer to the earthquake time, with increasing anomaly intensity with temporal proximity. Furthermore, confusion analysis is used in this article to verify the reliability of the proposed model. The proposed model achieves significant improvements in predicting GNSS TEC time series and is shown to advance the performance of earthquake anomaly detection technology.

Comparison of volcanic explosions in Japan using impulsive ionospheric disturbances

Using the ionospheric total electron content (TEC) data from ground-based Global Navigation Satellite System (GNSS) receivers in Japan, we compared ionospheric responses to five explosive volcanic eruptions 2004–2015 of the Asama, Shin-Moe, Sakurajima, and Kuchinoerabu-jima volcanoes. The TEC records show N-shaped disturbances with a period ~ 80 s propagating outward with the acoustic wave speed in the F region of the ionosphere. The amplitudes of these TEC disturbances are a few percent of the background absolute vertical TEC. We propose to use such relative amplitudes as a new index for the intensity of volcanic explosions.Graphical