Genetic algorithm for TEC seismo-ionospheric anomalies detection around the time of the Solomon (Mw = 8.0) earthquake of 06 February 2013

On 6 February 2013, at 12:12:27 local time (01:12:27 UTC) a seismic event registering M_w 8.0 struck the Solomon Islands, located at the boundaries of the Australian and Pacific tectonic plates. Time series prediction is an important and widely interesting topic in the research of earthquake precursors. This paper describes a new computational intelligence approach to detect the unusual variations of the total electron content (TEC) seismo-ionospheric anomalies induced by the powerful Solomon earthquake using genetic algorithm (GA). The GA detected a considerable number of anomalous occurrences on earthquake day and also 7 and 8 days prior to the earthquake in a period of high geomagnetic activities. In this study, also the detected TEC anomalies using the proposed method are compared to the results dealing with the observed TEC anomalies by applying the mean, median, wavelet, Kalman filter, ARIMA, neural network and support vector machine methods. The accordance in the final results of all eight methods is a convincing indication for the efficiency of the GA method. It indicates that GA can be an appropriate non-parametric tool for anomaly detection in a non linear time series showing the seismo-ionospheric precursors variations.     

Thermal and TEC anomalies detection using an intelligent hybrid system around the time of the Saravan,Iran, (Mw = 7.7) earthquake of 16 April 2013

A powerful earthquake of M_w = 7.7 struck the Saravan region (28.107° N, 62.053° E) in Iran on 16 April 2013. Up to now nomination of an automated anomaly detection method in a non linear time series of earthquake precursor has been an attractive and challenging task. Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) have revealed strong potentials in accurate time series prediction. This paper presents the first study of an integration of ANN and PSO method in the research of earthquake precursors to detect the unusual variations of the thermal and total electron content (TEC) seismo-ionospheric anomalies induced by the strong earthquake of Saravan. In this study, to overcome the stagnation in local minimum during the ANN training, PSO as an optimization method is used instead of traditional algorithms for training the ANN method. The proposed hybrid method detected a considerable number of anomalies 4 and 8 days preceding the earthquake. Since, in this case study, ionospheric TEC anomalies induced by seismic activity is confused with background fluctuations due to solar activity, a multi-resolution time series processing technique based on wavelet transform has been applied on TEC signal variations. In view of the fact that the accordance in the final results deduced from some robust methods is a convincing indication for the efficiency of the method, therefore the detected thermal and TEC anomalies using the ANN + PSO method were compared to the results with regard to the observed anomalies by implementing the mean, median, Wavelet, Kalman filter, Auto-Regressive Integrated Moving Average (ARIMA), Support Vector Machine (SVM) and Genetic Algorithm (GA) methods. The results indicate that the ANN + PSO method is quite promising and deserves serious attention as a new tool for thermal and TEC seismo anomalies detection.     

Ionospheric anomalies of local earthquakes detected by GPS TEC measurements using data from Tashkent and Kitab stations

This paper reports the ionospheric anomalies observed during strong local earthquakes (M?5.0) which occurred mostly in and around Uzbekistan in seismically active zones, during years 2006 to 2009 within approximately 1000 km distance from the observing GPS stations located in Tashkent and Kitab, Uzbekistan. The solar and geomagnetic conditions were quiet during occurrence of the selected strong earthquakes. We produce Total Electron Content (TEC) time series over both sites and apply them to detect anomalous TEC signals preceding or accompanying the local earthquakes. The results show anomalous increase or decrease of TEC before or during the earthquakes. In general the anomalies occurred 1–7 days before the earthquakes as ionospheric electromagnetic precursors. To identify the anomalous values of TEC we calculated differential TEC (dTEC). dTEC is obtained by subtracting monthly averaged diurnal vTEC from the values of observed vTEC at each epoch. This procedure removes normal diurnal variations of vTEC. The present results are in good agreement with the previous observations on ionospheric earthquake precursors reported by various researchers.     

Multi precursors analysis associated with the powerful Ecuador (MW = 7.8) earthquake of 16 April 2016 using Swarm satellites data in conjunction with other multi-platform satellite and ground data

After DEMETER satellite mission (2004–2010), the launch of the Swarm satellites (Alpha (A), Bravo (B) and Charlie (C)) has created a new opportunity in the study of earthquake ionospheric precursors. Nowadays, there is no doubt that multi precursors analysis is a necessary phase to better understand the LAIC (Lithosphere Atmosphere Ionosphere Coupling) mechanism before large earthquakes. In this study, using absolute scalar magnetometer, vector field magnetometer and electric field instrument on board Swarm satellites, GPS (Global Positioning System) measurements, MODIS-Aqua satellite and ECMWF (European Centre for Medium-Range Weather Forecasts) data, the variations of the electron density and temperature, magnetic field, TEC (Total Electron Content), LST (Land Surface Temperature), AOD (Aerosol Optical Depth) and SKT (SKin Temperature) have been surveyed to find the potential seismic anomalies around the strong Ecuador (M_w = 7.8) earthquake of 16 April 2016. The four solar and geomagnetic indices: F10.7, D_st, K_p and a_p were investigated to distinguish whether the preliminary detected anomalies might be associated with the solar-geomagnetic activities instead of the seismo-ionospheric anomalies. The Swarm satellites (A, B and C) data analysis indicate the anomalies in time series of electron density variations on 7, 11 and 12 days before the event; the unusual variations in time series of electron temperature on 8 days preceding the earthquake; the analysis of the magnetic field scalar and vectors data show the considerable anomalies 52, 48, 23, 16, 11, 9 and 7 days before the main shock. A striking anomaly is detected in TEC variations on 1 day before earthquake at 9:00 UTC. The analysis of MODIS-Aqua night-time images shows that LST increase unusually on 11 days prior to main shock. In addition, the AOD variations obtained from MODIS measurements reach the maximum value on 10 days before the earthquake. The SKT around epicentral region presents anomalous higher value about 40 days before the earthquake. It should be noted that the different lead times of the observed anomalies could be acknowledged based on a reasonable LAIC earthquake mechanism. Our results emphasize that the Swarm satellites measurements play an undeniable role in progress the studies of the ionospheric precursors.     

A nonlinear background removal method for seismo-ionospheric anomaly analysis under a complex solar activity scenario: A case study of the M9.0 Tohoku earthquake

A precise determination of ionospheric total electron content (TEC) anomaly variations that are likely associated with large earthquakes as observed by global positioning system (GPS) requires the elimination of the ionospheric effect from irregular solar electromagnetic radiation. In particular, revealing the seismo-ionospheric anomalies when earthquakes occurred during periods of high solar activity is of utmost importance. To overcome this constraint, a multiresolution time series processing technique based on wavelet transform applicable to global ionosphere map (GIM) TEC data was used to remove the nonlinear effect from solar radiation for the earthquake that struck Tohoku, Japan, on 11 March, 2011. As a result, it was found that the extracted TEC have a good correlation with the measured solar extreme ultraviolet flux in 26–34 nm (EUV_26–34) and the 10.7 cm solar radio flux (F_10.7). After removing the influence of solar radiation origin in GIM TEC, the analysis results show that the TEC around the forthcoming epicenter and its conjugate were significantly enhanced in the afternoon period of 8 March 2011, 3 days before the earthquake. The spatial distributions of the TEC anomalous and extreme enhancements indicate that the earthquake preparation process had brought with a TEC anomaly area of size approximately 1650 and 5700 km in the latitudinal and longitudinal directions, respectively.     

Seismo ionospheric anomalies in Turkey associated with Mw ≥ 6.0 earthquakes detected by GPS stations and GIM TEC

Earthquake (EQ) anomalies in the form of enhancement and depletion in ionospheric Total Electron Content (TEC) from Global Positioning System (GPS) may considerably alarm about short and long term precursors of the impending main shock. In this paper, TEC anomalies are investigated from permanent GPS ground-stations in Turkey associated to M_w ≥ 6.0 EQs occurred in 2011–2012. Temporal and spatial analyses of TEC at 2 h sampling have shown significant evidences about EQ induced ionospheric anomalies during 10–14 h of UT (Universal Time) within 5 days before M_w 6.0 Greece, and M_w 7.1, Turkish EQ. Spatial analyses have manifested arrival of TEC anomalies at UT = 10 h to epicenter of both EQs, which linger above epicenter during UT = 12–14 h and left seismogenic zone after UT = 14 h before every EQ during K_p < 3 and Dst = 0 nT. Meanwhile, a geomagnetic storm (Dst < -100 nT) induce perturbation two days after the M_w 7.1 Turkish EQ, showing no relation with epicenter during spatial analysis. It also shows that TEC can be useful to distinguish geomagnetic storm variations to successfully detect EQ precursors. These anomalies during quiet storm (K_p < 3; Dst = 0 nT) conditions may be effective to link the lithosphere and ionosphere in severe seismic zones to detect EQ precursors before future EQs. Interpretation of TEC anomalies and it enhancements over EQ epicenters during UT = 12–14 h for both EQs have shown that EQs anomalies only occurred in particular time. Whereas, geomagnetic storm effect occurred during whole abnormal day over the Earth.     

Variations of ionospheric total electron content before three strong earthquakes in the Qinghai-Tibet region

We investigate the ionospheric total electron content (TEC) anomalies occurred in the Qinghai-Tibet region before three large earthquakes (M > 7.0). The temporal and spatial TEC variations were used to detect the ionospheric possible precursors of these earthquakes. We identified two TEC enhancements in the afternoon local time 9 days and 2–3 days before each earthquake, between which a TEC decrement occurred 3–6 days before earthquakes. These anomalies happened in the area of about 30° in latitude and the maximum is localized equatorward from the epicenters. These TEC anomalies can be found in all three earthquakes regardless the geomagnetic conditions. The features of these anomalies have something in common and may have differences from those caused by geomagnetic storms. Our results suggest that these ionospheric TEC perturbations may be precursors of the large earthquakes.     

Two-dimensional ionospheric total electron content map (TEC) seismo-ionospheric anomalies through image processing using principal component analysis

This paper examines China’s Wenchuan Earthquake of 12 May 2008 (UTC) (M_w = 7.9) using principal component analysis and image processing of the global ionospheric map (GIM) for the region. Transforms are conducted for 4, 8, and 9 May 2008. The GIMs are subdivided into 100 (36° in Long. and 18° in Lat.) smaller maps. The smaller maps (71 × 71 pixels) form the transform matrices of corresponding dimensions (2 × 1) through image processing. The transform allows for principle eigenvalues to be assigned to TEC anomalies for May 8 and 9. These may represent the seismo-ionospheric signature described by Zhao et al. (2008). The May 4 result shows no evidence of TEC anomalies. These results are in keeping with the findings of Liu et al. (2009). It is evident in this research that PCA could have the capacity to detect both the seismo-ionospheric signature and determine the approximate location of an earthquake’s epicenter prior to nucleation.     

An Adaptive Network-based Fuzzy Inference System for the detection of thermal and TEC anomalies around the time of the Varzeghan,Iran, (Mw = 6.4) earthquake of 11 August 2012

Anomaly detection is extremely important for forecasting the date, location and magnitude of an impending earthquake. In this paper, an Adaptive Network-based Fuzzy Inference System (ANFIS) has been proposed to detect the thermal and Total Electron Content (TEC) anomalies around the time of the Varzeghan, Iran, (M_w = 6.4) earthquake jolted in 11 August 2012 NW Iran. ANFIS is the famous hybrid neuro-fuzzy network for modeling the non-linear complex systems. In this study, also the detected thermal and TEC anomalies using the proposed method are compared to the results dealing with the observed anomalies by applying the classical and intelligent methods including Interquartile, Auto-Regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and Support Vector Machine (SVM) methods. The duration of the dataset which is comprised from Aqua-MODIS Land Surface Temperature (LST) night-time snapshot images and also Global Ionospheric Maps (GIM), is 62 days. It can be shown that, if the difference between the predicted value using the ANFIS method and the observed value, exceeds the pre-defined threshold value, then the observed precursor value in the absence of non seismic effective parameters could be regarded as precursory anomaly. For two precursors of LST and TEC, the ANFIS method shows very good agreement with the other implemented classical and intelligent methods and this indicates that ANFIS is capable of detecting earthquake anomalies. The applied methods detected anomalous occurrences 1 and 2 days before the earthquake. This paper indicates that the detection of the thermal and TEC anomalies derive their credibility from the overall efficiencies and potentialities of the five integrated methods.     

Investigation of GPS-TEC measurements using ANN method indicating seismo-ionospheric anomalies around the time of the Chile (Mw = 8.2) earthquake of 01 April 2014

In 94 km NW of Iquique in Chile (19.610°S, 70.776°W) a powerful earthquake of M_w = 8.2 took place at 23:46:47 UTC (20:46:47 LT) on April 01, 2014. Using GPS-TEC (Total Electron Content) measurements, potential unusual variations around the time and location of the Chile earthquake have been detected based on the median and Artificial Neural Network (ANN) methods. The indices D_st, K_p, A_p and F10.7 were used to distinguish pre-earthquake anomalies from the other anomalies related to the solar-geomagnetic activities. Using the median method, striking anomalies in time series of TEC data are observed 4 days before the earthquake at 14:00 and 16:00 UTC. The ANN method detected a number of anomalies, 4 (02:00 and 16:00 UTC) and 13 (24:00 UTC) days preceding the earthquake. The results indicate that the ANN method due to its capability of non linear learning is quite promising and deserves serious attention as a robust predictor tool for seismo-ionospheric anomalies detection.     

Formation mechanism of great positive TEC disturbances prior to Wenchuan earthquake on May 12, 2008

The problems of physical explanation and possible mechanisms of the seismo-ionospheric effects formation are under discussion now. There are proposed different mechanisms of such effects, for example, large- and small-scale internal gravity waves (IGWs), atmospheric electric field, electromagnetic fields and emissions. However, the appearance of local large-scale seismo-ionospheric anomalies in Total Electron Content (TEC) is possible to explain only by two mechanisms: an atmospheric electric field and/or small-scale IGWs. In this paper, the simulation results for reproduction of the observed seismo-ionospheric great positive effects in TEC prior to strong Wenchuan earthquake are presented. The obtained results confirm the proposed mechanism of seismo-ionospheric effects formation by the penetration of the seismogenic electric field from the atmosphere into the ionosphere. It is suggested that so great TEC enhancement observed 3 days prior to Wenchuan earthquake could be explained by combined action of seismogenic vertical electric field and IGWs generated by the solar terminator.     

The global response of terrestrial ionosphere to the December 2015 space weather event

This paper investigates the ionospheric storm of December 19–21, 2015, which was initiated by two successive CME eruptions that caused a G3 space weather event. We used the in situ electron density (N_e) and electron temperature (T_e) and the Total Electron Content (TEC) measurements from SWARM-A satellite, as well as the O/N₂ observations from TIMED/GUVI to study the ionospheric impact. The observations reveal the longitudinal and hemispherical differences in the ionospheric response to the storm event. A positive ionospheric storm was observed over the American, African and Asian regions on 20 December, and the next day showed a negative storm. Both these exhibited hemispheric differences. A positive storm was observed over the East Pacific region on 21 December. It is seen that the net effect of both the disturbance dynamo electric field and composition differences become important in explaining the observed variability in topside ionospheric densities. In addition, we also discuss the T_e variations that occurred as a consequence of the space weather event.     

2009年7月22日日全食期间电离层参量的变化

利用多个电离层垂测站的数据和IGS-TEC数据资料, 结合日地空间环境指数, 分析了2009年7月22日日全食期间中国地区电离层参量(反射回波最低频率fmin及f0F2和TEC)的变化特征. 结果表明, 日食发生后fmin迅速降低, 日食结束后fmin迅速恢复到正常水平; 在食甚时刻附近, f0F2和TEC出现明显的降低, 显示了明显的光食效应. 日食结束后5~6 h, f0F2和TEC出现不同程度的正扰动, 在驼峰区更明显; 日食结束后9~10 h, f0F2和TEC出现较显著的负扰动. 由于此次日食发生时伴随着中等强度的磁暴和低纬电场穿透等空间天气事件, 给此次日食电离层效应的深入分析带来很大困难.      

Ionospheric precursors observed at low latitudes around the time of koyna earthquake

On December 11, 1967 at 05:21 LT, an immense earthquake of magnitude 6.7 struck Koyna, the Indian province of Maharashtra. Its epicenter was located at geographic latitude 17.37°N and longitude 73.75°E with depth of about 3 km. Ground based measurements show variation in the critical frequency of ionospheric F2 layer (foF2) before and after the shock. In the present study the behavior of F2-region of ionosphere has been examined over the equatorial and low latitudinal region ionosphere during the month of December 1967 around the time of Koyna earthquake. For this purpose, the ionospheric data collected with the help of ground-based ionosondes installed at Hyderabad (located close to the earthquake epicenter) Ahmedabad, Trichirapulli, Kodaikanal and Trivendrum have been utilized. The upper and lower bound of Interquartile range (IRQ) are constructed to monitor the variations in foF2 other than day-to-day and diurnal pattern for finding the seismo-ionospheric precursors. Some anomalous electron density variations are observed between post midnight hours to local pre-noon hours at each station. These anomalies are strongly time dependent and appeared a couple of days before the main shock. The period considered in this study comes under the quiet geomagnetic conditions. Hence, the observed anomalies (which are more than the usual day-to-day variability) over all stations are likely to be associated with this imminent earthquake. The possible mechanism to explain these anomalies is the effect of seismogenic electric field generated just above the surface of earth within the earthquake preparation zone well before the earthquake due to emission of radioactive particles and then propagated upward, which perturbs the F-region ionosphere.     

Surface latent heat flux anomalies quasi-synchronous with ionospheric disturbances before the 2007 Pu’er earthquake in China

One of various mechanisms of pre-earthquake lithosphere–atmosphere–ionosphere coupling as possible explanation of the seismo-ionospheric effects is connected with the release of latent heat. Abnormal variations of ionospheric electromagnetic parameters possibly related to the 2007 Ms 6.4 Pu’er earthquake in China were reported. This paper attempts to examine whether there were abnormal changes of surface latent heat flux (SLHF) linked with this pre-earthquake ionospheric disturbances. The spatio-temporal statistical analyzes of multi-years SLHF data from USA NCEP/NCAR Reanalysis Project reveal that local SLHF enhancements appeared 11, 10 and 7 days before the Pu’er earthquake, respectively. As contrasted to the formerly reported local ionospheric Ne enhancement 9 days before the shock observed by DEMETER satellite, it is discovered that the SLHF and Ne anomalies are quasi-synchronous and have good spatial correspondence with the epicentre and the local active faults. This is valuable for understanding the seismogenic coupling processes and for recognizing earthquake anomaly with multiple parameters from integrated Earth observation system.     

玉树地震前的电离层异常现象分析

分析了玉树地震前地基电离层探测临界频率、GPS TEC和卫星探测原位等离子体参量等多个参数的扰动变化信息, 研究了不同高度异常变化的时空关联性. 分析发现, 在地震前一天的4月13日, 多个电离层参量出现同步扰动异常, 电离层临界频率f₀F₂异常相对滑动中值增大40%, 异常空间上存在从震中东南向西南漂移的特性; GPS TEC异常增强15TECU (1TECU=1016m-2)左右, 分布于震中南部经度15°范围内, 且有明显的磁共轭效应; DEMETER观测的原位氧离子密度N_i(O+) 4月13日为1-4月中最强的一天, 异常分布偏向赤道区, 但仅局限在30°-50°左右的经度范围内. 综合三个参量的异常特征发现, 无论是空间的局地性还是时间上的密切关联均反映这次电离层扰动可能与玉树地震孕育有关. 结合其他观测信息, 进一步探讨了这次地震孕育过程的地震电离层耦合机理.      

Large-scale traveling ionospheric disturbances of auroral origin according to the data of the GPS network and ionosondes

The intensity of large-scale traveling ionospheric disturbances (LS TIDs), registered using measurements of total electron content (TEC) during the magnetic storms on October 29–31, 2003, and on November 7–11, 2004, had been compared with that of local electron density disturbances. The data of TEC measurements at ground-based GPS receivers located near the ionospheric stations and the corresponding values of the critical frequency of the ionospheric F region f_oF2 were used for this purpose. The variations of TEC and f_oF2 were similar for all events mentioned above. The previous assumption that the ionospheric region with vertical extension from 150 to 200 km located near the F-layer maximum mainly contributes to the TEC variations was confirmed for the cases when the electron density disturbance at the F region maximum was not more than 50%. However, this region probably becomes vertically more extended when the electron density disturbance in the ionospheric F region is about 85%.     

Change in refractivity of the atmosphere and large variation in TEC associated with some earthquakes,observed from GPS receiver

The present study reports the analysis of GPS based TEC for our station Surat (21.16°N, 72.78°E) located at the northern crest of equatorial anomaly region in India at times close to some earthquake events (M ? 5) during the year 2009 in India and its neighbouring regions. The TEC data used in the study are obtained from GPS Ionospheric Scintillation and TEC Monitoring (GISTM) system. The TEC data has been analysed corresponding to 11 earthquakes in low solar activity period and quiet geomagnetic condition. We found that, out of 11 cases of earthquakes (M > 5) there were seven cases in which enhancement in TEC occurred on earthquake day and in other four cases there was depletion in TEC on earthquake day. The variation in refractivity prior to earthquake was significant for the cases in which the epicentre lied within a distance of 600 km from the receiving station. By looking into the features on temporal enhancement and depletion of TEC a prediction was made 3–2 days prior to an earthquake (on 28 October 2009 in Bhuj – India). The paper includes a brief discussion on the method of potentially identifying an impending earthquake from ionospheric data.     

A MLP neural network as an investigator of TEC time series to detect seismo-ionospheric anomalies

Anomaly detection is extremely important for earthquake parameters estimation. In this paper, an application of Artificial Neural Networks (ANNs) in the earthquake precursor’s domain has been developed. This study is concerned with investigating the Total Electron Content (TEC) time series by using a Multi-Layer Perceptron (MLP) neural network to detect seismo-ionospheric anomalous variations induced by the powerful Tohoku earthquake of March 11, 2011.     

Ionospheric anomalies observed over South Korea preceding the Great Tohoku earthquake of 2011

We investigated the ionospheric anomalies observed before the Tohoku earthquake, which occurred near the northeast coast of Honshu, Japan on 11 March, 2011. Based on data from a ground-based Global Positioning System (GPS) network on the Korean Peninsula, ionospheric anomalies were detected in the total electron content (TEC) during the daytime a few days before earthquake. Ionospheric TEC anomalies appeared on 5, 8 and 11 March. In particular, the ionospheric disturbances on 8 March evidenced a remarkable increase in TEC. The GPS TEC variation associated with the Tohoku earthquake was an increase of approximately 20 total electron content units (TECU), observed simultaneously in local and global TEC measurements. To investigate these pre-earthquake ionospheric anomalies, space weather conditions such as the solar activity index (F10.7) and geomagnetic activity indices (the Kp and Dst indices) were examined. We also created two-dimensional TEC maps to visual the spatial variations in the ionospheric anomalies preceding the earthquake.