TEC Anomalies Research Articles

Response to geomagnetic storm on 23–24 March 2023 long-lasting longitudinal variations of the global ionospheric TEC

This study examines the global behavior of the ionospheric TEC anomalies, i.e. their structures and temporal variability, during the initial, main and recovery phase of the geomagnetic storm occurring on 23–24 March 2023. For this purpose the global vertical TEC maps, generated by the NASA JPL IGS Ionosphere center, have been used and the geomagnetically forced anomalies have been presented in 2D (longitude-modip latitude) and polar maps. The main peculiar features of the TEC response could be summarized as: (i) the TOI-like event observed at the SH midnight hours during the main storm phase, and (ii) a clear longitude asymmetry between the TEC response at low and middle latitudes of the western and eastern hemispheres was seen; while the long-lasting positive response was evident for a full day in the western hemisphere the negative response or almost the lack of response was a characteristic of the eastern part. The study presented possible explanations of the above mentioned basic type of TEC anomalies by using the GUVY [O/N2] ratio maps and geomagnetic data from eight magnetometric stations situated at low latitudes for the separation of the effect generated by the DDEF. An attempt was made the observed TEC response during different storm phases to be reproduced. The presented reconstructions described in almost perfect way the real TEC responses and the RMSE assessments provided clear evidence for this evaluation.

Analysis of ionospheric anomalies before the Fukushima Mw 7.3 earthquake of March 16, 2022

Abstract In order to study the coupling relationship between earthquakes and ionospheric disturbances, TEC data during the Mw 7.3 earthquake that occurred near Fukushima, Japan on March 16, 2022, were processed using global ionospheric data provided by the Center for Orbit Determination in Europe (CODE). In this paper, the sliding quartile interval method is used to eliminate solar activity in a 27-day window, including sunspot number (SSN), F10.7 cm radio flux (F10.7), total solar irradiation (TSI), solar wind velocity (Vsw) and geomagnetic activity. The impact of disturbance storm time index (DST) and global geomagnetic activity index (KP) on TEC anomaly disturbance can obtain more accurate TEC anomaly information. The results indicate that when the solar and geomagnetic activity cycles are inconsistent with the TEC anomalies on fifth day before the earthquake, the TEC anomalies above the epicenter are significantly greater than those observed in other regions, and the corresponding magnetic conjugate region is accompanied by anomalies, which is the characteristic of TEC anomalies caused by earthquakes. This means that the detected TEC anomalies can be used as a potential ionospheric precursors, indicating that the Fukushima earthquake is imminent.

Comparative Analysis of Global and Regional Ionospheric Responses during Two Geomagnetic Storms on 3 and 4 February 2022

The present work examines the spatial and temporal distribution of positive and negative TEC anomalies on the global and regional scale. To study the local response of the ionosphere, foF2 data from ground ionosonde stations and TEC data from Madrigal and CODE databases have been used. The relative deviation, which also determines the type of TEC response during geomagnetic storms on 3 and 4 February 2022, is considered. In the present study, the regions of positive and negative TEC anomalies and their evolution during storms are examined in detail. As a result of the study, estimates of the following were obtained: (i) the location of the sectors of the polar regions, in where the particle precipitation from the solar wind is observed, (ii) the mid-latitude regions, in which the mechanism of influence of the O/N2 ratio dominates, and (iii) the region around the equator, in which the influence of the electric field dominates. An attempt was made to determine which mechanism of influence of geomagnetic storms on the ionospheric electron density is dominant in different regions. The following main mechanisms are considered: (a) the additional ionization from the particles’ precipitation, (b) the change of the ratio of atomic oxygen (O) to molecular nitrogen (N2) due to the heating of the neutral air, and (c) the influence on the equatorial ionospheric anomaly.

TEC Anomalies Detection for Qinghai and Yunnan Earthquakes on 21 May 2021

Earthquake prediction by using total electron content is a commonly used seismic research method. The long short-term memory model is a kind of method to predict time series and has been used for the prediction of total electron content, and the relative power spectrum method is one of the pre-seismic infrared anomaly detection algorithms in the frequency domain. In this paper, a new method combining these two algorithms is used to extract abnormal signals; thus scientists can more easily detect anomalies of total electron content similar to those before the Qinghai and Yunnan earthquakes happened on 21 May 2021. There are pre-seismic anomalies with the high-value relative power spectrum near two epicenters. To validate the correlation between anomalies and earthquakes statistically, the spatiotemporal characteristics of TEC anomalies are analyzed based on connected region recognition. Then, the proportion of earthquake-related anomalies (the correlation rate), the proportion of earthquakes outside the predicted range (the miss rate), and the ratio of the proportion of earthquakes within the predicted range to the spatiotemporal occupancy of anomalies, which is called the probability gain, were used to assess the method. The appropriate parameters of the algorithm for the miss rate below 50% were searched. The highest probability gain is 1.91, which means anomalies of total electron content may decrease the uncertainty of earthquake prediction.

Investigation of the Relationship among Fault Types, Focal Depths, and Ionospheric TEC Anomalies before Large Earthquakes between 2000 and 2020

Investigation of the Relationship among Fault Types, Focal Depths, and Ionospheric TEC Anomalies before Large Earthquakes between 2000 and 2020

Atmosphere-ionosphere coupling induced by volcanoes eruption and dust storms and role of GEC as the agent of geospheres interaction

In this publication we demonstrate how interdependent are our geophysical shells. The large-scale air pollution provided by the intensive volcano eruptions and dust storms from desert areas modify the electric properties of the troposphere creating the low conducting layers and increasing the column resistance for the vertical current flowing between the ionosphere and ground within the Global Electric Circuit (GEC). This modification leads to the local modulation of the ionospheric potential (IP) magnitude and hence to formation of the large-scale irregularities of electron concentration in the ionosphere. To reveal these phenomena, we use the differential GIM TEC mapping procedure showing specific features of the ionosphere reaction. In low latitude and equatorial regions we observe the formation of positive TEC anomalies not only over the area of air pollution but in the magnetically conjugated area as well. We can conclude that these phenomena pose the double error for Precise Point Positioning (PPP). To the danger of aircraft engines destroying is added the increase of navigational PPP errors due to sharp TEC gradients on the borders of the formed large-scale positive irregularities of electron concentration.

Developing a Deep Learning-Based Detector of Magnetic, Ne, Te and TEC Anomalies from Swarm Satellites: The Case of Mw 7.1 2021 Japan Earthquake

Since the appearance and evolution of earthquake ionospheric precursors are expected to show a nonlinear and complex behaviour, the use of nonlinear predictor models seems more appropriate. This paper proposes a new approach based on deep learning as a powerful tool for extracting the nonlinear patterns from a time series of ionospheric precursors. A Long Short-Term Memory (LSTM) network as a type of Recurrent Neural Network (RNN) was used to investigate 52 six-month time series, deduced from the three Swarm satellite (Alpha (A), Bravo (B) and Charlie (C)) measurements, including electron density (Ne), electron temperature (Te), magnetic scalar and vector (X, Y, Z) components, Slant and Vertical Total Electron Content (STEC and VTEC), for day and night periods around the time and location of a seismic event. This new approach was tested on a strong Mw = 7.1 earthquake in Japan on 13 February 2021, at 14:07:50 UTC by comparing the results with two implemented methods, i.e., Median and LSTM methods. Furthermore, clear anomalies are seen by a voting classification method 1, 6, 8, 13, 31 and 32 days before the earthquake. A comparison with atmospheric data investigation is further provided, supporting the lithosphere–atmosphere–ionosphere coupling (LAIC) mechanism as a suitable theory to explain the alteration of upper geolayers in the earthquake preparation phase. In other words, using multi-method and multi-precursor analysis applied to 52 time series and also to the orbit-by-orbit investigation, the observed anomalies on the previous day and up to 32 days before the event in normal solar and quiet geomagnetic conditions could be considered as a striking hint of the forthcoming Japan earthquake.

Co-Seismic Ionospheric Disturbances Following the 2016 West Sumatra and 2018 Palu Earthquakes from GPS and GLONASS Measurements

The study of ionospheric disturbances associated with the two large strike-slip earthquakes in Indonesia was investigated, which are West Sumatra on 2 March 2016 (Mw = 7.8), and Palu on 28 September 2018 (Mw = 7.5). The anomalies were observed by measuring co-seismic ionospheric disturbances (CIDs) using the Global Navigation Satellite System (GNSS). The results show positive and negative CIDs polarization changes for the 2016 West Sumatra earthquake, depending on the position of the satellite line-of-sight, while the 2018 Palu earthquake shows negative changes only due to differences in co-seismic vertical crustal displacement. The 2016 West Sumatra earthquake caused uplift and subsidence, while the 2018 Palu earthquake was dominated by subsidence. TEC anomalies occurred about 10 to 15 min after the two earthquakes with amplitude of 2.9 TECU and 0.4 TECU, respectively. The TEC anomaly amplitude was also affected by the magnitude of the earthquake moment. The disturbance signal propagated with a velocity of ~1–1.72 km s−1 for the 2016 West Sumatra earthquake and ~0.97–1.08 km s−1 for the 2018 Palu mainshock earthquake, which are consistent with acoustic waves. The wave also caused an oscillation signal of ∼4 mHz, and their azimuthal asymmetry of propagation confirmed the phenomena in the Southern Hemisphere. The CID signal could be identified at a distance of around 400–1500 km from the epicenter in the southwestern direction.

Ionospheric anomalies related to strong earthquakes in North America as observed by TEC

Research studies have recently illustrated a plausible relationship between seismic activity and ionospheric disturbances. To elucidate seismo-ionospheric disturbances, we analyzed the temporal and spatial characteristics of ionospheric disturbances associated with large earthquakes that occurred in North America. We selected two strong events with M ≥ 6.5 that took place in 2009 and 2010 during the solar minimum. We used the United States total electron content (US-TEC) measurements as a main dataset, and the changes in the TEC were compared with the variations in the topside plasma density measured by the Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions (DEMETER) satellite. Positive or negative TEC anomalies were observed before (as a precursor) and after the earthquakes. In addition, we found that positive anomalies occurred more frequently than negative ones. Although TEC anomalies occurred at all local times, strong anomalies usually appeared from late afternoon to dawn (16–6 local time). Seismic activity-related TEC anomalies were typically limited to the earthquake region, whereas geomagnetic activity-related TEC anomalies were observed over a vast region. Furthermore, local TEC anomalies occurred over a long period of 20 days preceding and succeeding the earthquakes, in contrast to those associated with geomagnetic activities which occurred concurrently with the geomagnetic disturbances. Additionally, most abnormal increments in the electron density obtained by the DEMETER satellite over the seismic zone coincided with the TEC anomalies. Thus, the variations observed in the TEC and topside electron density before and after these two earthquakes suggest that these ionospheric disturbances are related to seismic activities.

TEC anomalies observed before and after Sivrice-Elaziğ earthquake (24 January 2020, Mw: 6.8)

TEC anomalies observed before and after Sivrice-Elaziğ earthquake (24 January 2020, Mw: 6.8)

Piezoelectricity as a mechanism on generation of electromagnetic precursors before earthquakes

SUMMARYTo produce the electromagnetic (E&M) precursors of an earthquake, the existence of electric field due to stress-induced charges on the ground surface or in shallow depths of upper crust inside the fault zone is a basic condition. Here, we consider the piezoelectric effect or the elastic–electric coupling as a major mechanism on generating such an electric field. A 1-D model based on the elastic mechanics and electromagnetic Maxwell equations is built up to formulate the relationship between electric field and slip as well as stress on a fault before an earthquake. From the model, we may estimate the low-bound values of stress and slip to yield the critical electric field, Ec, for generation of electromagnetic signals. The normal and shear stresses on the fault planes for three faulting types are constructed. The normal stress is stronger than the shear stress to result in piezoelectricity. The depth ranges for yielding an average normal stress being able to generate Ec are similar for thrust and strike-slip faults and deep for normal faults. The possibility of generating Ec is almost the same for thrust and strike-slip faults and low for normal faults. The pre-earthquake slip could be related to nucleation phases or microfractures. The possible occurrence time of E&M signals may be several 10 min to few hours before impending earthquakes. The major factor in yielding a piezoelectric field to generate the TEC anomalies before an earthquake is the existence of fault gouges composed mainly of clays. A thick gouge layer with low electric resistivity and a piezoelectric coupling coefficient ≥0.67 × 10−12 coul nt–1 is an important condition for yielding piezoelectricity.

Thermal Infrared and Ionospheric Anomalies of the 2017 Mw6.5 Jiuzhaigou Earthquake

Taking the 2017 Mw6.5 Jiuzhaigou earthquake as a case study, ionospheric disturbances (i.e., total electron content and TEC) and thermal infrared (TIR) anomalies were simultaneously investigated. The characteristics of the temperature of brightness blackbody (TBB), medium-wave infrared brightness (MIB), and outgoing longwave radiation (OLR) were extracted and compared with the characteristics of ionospheric TEC. We observed different relationships among the three types of TIR radiation according to seismic or aseismic conditions. A wide range of positive TEC anomalies occurred southern to the epicenter. The area to the south of the Huarong mountain fracture, which contained the maximum TEC anomaly amplitudes, overlapped one of the regions with notable TIR anomalies. We observed three stages of increasing TIR radiation, with ionospheric TEC anomalies appearing after each stage, for the first time. There was also high spatial correspondence between both TIR and TEC anomalies and the regional geological structure. Together with the time series data, these results suggest that TEC anomaly genesis might be related to increasing TIR.

Investigation of ionospheric TEC anomalies caused by space weather conditions

This study examines the influence of space weather conditions on ionospheric TEC variations at different latitudes around the world. According to the space weather condition indices (geomagnetic storm-activity indices, solar activity indices, magnetic field change indices, plasma density and proton flux indices) different time periods were chosen. GPS observations were used to obtain TEC data derived from International GNSS Service (IGS) stations located at northern and southern hemisphere latitude regions (equatorial, mid-latitude and high latitude). GPS TEC data were evaluated associated with the space weather conditions using 15-day running median statistical analysis method. The results showed that besides the commonly used geomagnetic storm-activity and solar activity indices, plasma density, magnetic field change and particle flux indices are also important in determining whether there is any TEC anomaly in the ionosphere. This study illustrated that all indices should be examined in the applications associated with the ionosphere and particularly in the research of pre-earthquake ionospheric anomalies.

Analysis of ionospheric TEC anomalies for global earthquakes during 2000-2019 with respect to earthquake magnitude (Mw≥6.0)

In this work, a relationship between ionospheric TEC anomalies and different earthquake magnitude groups before the main shocks was investigated. For this purpose, 2942 global earthquakes with Mw≥6 from 2000 to 2019 and possible ionospheric TEC anomalies that occurred before earthquakes were examined by considering 13 different index values of space weather conditions (geomagnetic storm indices and solar activity indices). Anomalies of ionospheric TEC changes were defined for 15-days before and 4-days after the earthquakes by using 15-days moving median method with the length of 15 days. Earthquakes were first grouped according to their magnitudes, and then negative and positive TEC anomalies in quiet days before the earthquakes were detected. These anomalies were observed as ∼5–13, ∼5-10, ∼5-15, ∼3-13, ∼7-15, ∼1 and ∼5-8 days ago for the earthquakes of 6.0 ≤ Mw<6.5, 6.5 ≤ Mw<7.0, 7.0 ≤ Mw<7.5, 7.5 ≤ Mw<8.0, 8.0 ≤ Mw<8.5, 8.5 ≤ Mw<9.0, and 9.0 ≤ Mw<9.5, respectively. Mean of changes in TEC anomalies of these groups is 44.2 % TECU and we detected that the number of positive anomalies in each group is larger than the number of negative anomalies. Consequently, these analyses clearly show that the day-to-day changes in TEC anomalies may supply significant precursors prior to the global earthquakes (M ≥ 6) in the short-term earthquake prediction for main shocks.

A combined estimator using TEC and b-value for large earthquake prediction

Ionospheric anomalies have been shown to occur a few days before several large earthquakes. The published works normally address examples limited in time (a single event or few of them) or space (a particular geographic area), so that a clear method based on these anomalies which consistently yields the place and magnitude of the forthcoming earthquake, anytime and anywhere on earth, has not been presented so far. The current research is aimed at prediction of large earthquakes, that is with magnitude Mw 7 or higher. It uses as data bank all significant earthquakes occurred worldwide in the period from January 1, 2011 to December 31, 2018. The first purpose of the research is to improve the use of ionospheric anomalies in the form of TEC grids for earthquake prediction. A space–time TEC variation estimator especially designed for earthquake prediction will show the advantages with respect to the use of simple TEC values. Further, taking advantage of the well-known predictive abilities of the Gutenberg–Richter law’s b-value, a combined estimator based on both TEC anomalies and b-values will be designed and shown to improve prediction performance even more.

Precursory Response of Low Frequency Signals for Detection of Seismic Rapture in Indian Region

Recognition of seismic precursors is exigent task. Its study depends upon the environmental parameters, ground motion emissions (Low frequency signals), geological and tectonic structure. The theory of signal conductivity of two crust model between the epicenter region and above the ground surface calculated the amplitude enhancement of electromagnetic emissions. Extremely low frequency signals generate due to seismic emissions and penetrate the crystal layer to change the earth’s surrounding and upper atmosphere conditions. These outputs are used to correlate the seismogenic VLF signals (f=3 KHz), which are recorded by borehole antenna system. It is observed that the low frequency signals goes to vertically and accumulated as low conductivity medium in the outer most layer through which transmitted to the atmosphere. The seismogenic ULF emissions, DEMETER satellite data, TEC anomalies, ionospheric disturbances and bio-electric amplitude was recorded at places nearby active fault line in Indian region and it is used to recognized the pre- seismic behaviour. We have also observed the stimulus data (solar flux, audio frequency signals, or electric charge emissions) as abnormal signals. These relations are verified and correlated by statistical analysis with null hypothesis testing and power spectrum magnitude which is helping us to understand the precursory signature of earthquakes.

Application of BDS-GEO for studying TEC variability in equatorial ionosphere on different time scales

The Earth's ionosphere and especially its equatorial part is a highly dynamical medium. Geostationary satellites are known to be a powerful tool for ionospheric studies. Recent developments in BDS-GEO satellites allow such studies on the new level due to the best noise pattern in TEC estimations, which corresponds to those of GPS/GLONASS systems. Here we used BDS-GEO satellites to demonstrate their capability for studying equatorial ionosphere variability on different time scales. Analyzing data from the equatorial SIN1 IGS station we present seasonal variations in geostationary slant TEC for the periods of high (October 2013 - October 2014) and low (January 2017 - January 2018) solar activity, which show semi-annual periodicity with amplitudes about 10 TECU during solar maximum and about 5 TECU during the solar minimum. The 27-day variations are also prominent in geostationary slant TEC variations, which correlates quite well with the variations in solar extreme UV radiation. We found semi-annual pattern in small scale ionospheric disturbances evaluated based on geostationary ROTI index: maximal values correspond to spring and fall equinoxes and minimum values correspond to summer and winter solstices. The seasonal asymmetry in ROTI values was observed: spring equinox values were almost twice as higher than fall equinox ones. We also present results on the 2017 May 28–29 G3 geomagnetic storm, when ∼30 TECU positive anomaly was recorded, minor and final major sudden stratospheric warmings in February and March 2016, with positive daytime TEC anomalies up to 15–20 TECU, as well as the 2017 September 6 X9.3 solar flare with 2 TECU/min TEC rate. Our results show the large potential of geostationary TEC estimations with BDS-GEO signals for continuous monitoring of space weather effects in low-latitude and equatorial ionosphere.

Enhancing reliability of seismo-ionospheric anomaly detection with the linear correlation between total electron content and the solar activity index F10.7: Nepal earthquake 2015

There is still no consensus on seismo-ionospheric anomalies and coupling mechanism. One of important reasons is that multi- excitation factors of ionospheric disturbances interfere with the judgment of their source. In this paper, a Linear Model between TEC and F10.7 (LMTF) was built to detect seismo-ionospheric TEC anomalies before and after Nepal earthquake 2015. Firstly, LMTF and Kalman filter (KFM) were utilized to predict TEC and compare with the TEC from Global Ionosphere Map (GIM) for evaluating their prediction accuracies. The statistical results show that the mean square error (MSE), average absolute relative error (Δ¯) and the correlation coefficient (Corr) between the TEC from GIM and the prediction TEC are ±0.88 TECU, 1.55 and 0.94 and all approximately equal to those of KMF, when their time moving windows are all set to 30 days. Further considering the period of the solar, the time moving window could be set to 27 days. Then, Sliding Quartile Method (SQM), KFM and LMTF were utilized to detect TEC anomalies above epicenter, International GNSS stations in affected area and the globe during the period of 15 days before and 10 days after Nepal earthquake by comparison. The comparative results demonstrate that LMTF is more effective to detect the TEC anomaly caused by Nepal earthquake in temporal and spatial scale. Moreover, the characteristics of the TEC anomalies caused by Nepal earthquake using LMTF are in agreement with the results of previous studies on Wenchuan and Nepal earthquake cases. At last, the coupling mechanism was discussed based on the characteristics of seismo-ionospheric TEC anomalies. It is supposed that the mechanism of seismo-ionospheric TEC anomalies can be explained by the combination action of internal gravity waves (IGWs) generated by the solar terminator and the electric field in seismogenic zone formed by the electric field effect of geochemical process and the piezo-electric potential effect of rock.

Ionospheric perturbations due to earthquakes as determined from VLF and GPS-TEC data analysis at Agra, India

Employing SoftPAL receiver, amplitude variations of VLF transmitter signals NWC (19.8 kHz) and NPM (21.4 kHz) are analyzed at Agra station in India (Geograph. lat. 27.2°N, long. 78°E) ±15 days from five major earthquakes of magnitude M = 6.9–8.5 occurred in Indian subcontinent during the years 2011–2013. We apply nighttime fluctuation (NF) method and show that in almost all cases the trend decreases and dispersion and NF increase on the same days corresponding to each earthquake about 11–15 days prior to the main shock. Assuming that the ionospheric perturbations are caused by atmospheric gravity waves (AGW), we also calculate AGW modulation index for each case and find its values increased on the days amplitude fluctuations take place. Its value is decreased in one case only where the perturbations may be attributed to penetration of seismogenic electric field.In order to support the above results we also present GPS-TEC data analyzed by us corresponding to three of the above earthquakes. We study the TEC anomalies (unusual enhancements) and find that in one case the precursory period is almost the same as that found in NF method.

Observed TEC Anomalies by GNSS Sites Preceding the Aegean Sea Earthquake of 2014

Observed TEC Anomalies by GNSS Sites Preceding the Aegean Sea Earthquake of 2014