Total Electron Content Anomalies Research Articles

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, (Mw=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 62days. 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 2days 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.

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 Mw 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 8days 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.

Taiwan’ Chi-Chi earthquake precursor detection using nonlinear principal component analysis to multi-channel total electron content records

This research uses eigenvalue characteristics of nonlinear principal component analysis (NLPCA) and principal component analysis (PCA) to investigate total electron content (TEC) anomalies associated with Taiwan’s Chi-Chi earthquake of 21 September 1999 (LT) (M w=7.6). The transforms are used for ionospheric TEC from 01 August to 20 September 1999 (local time) using data from 13 GPS receivers. The data were collected at 22°N–26°N Lat. and 120°E–122°E Long.. Applying the NLPCA to the multi-channel total electron content records of GPS receivers, the earthquake-associated TEC anomalies were represented by large principal eigenvalues of NLPCA (>0.5 in a normalized set) on 14 August and 17, 18, and 20 September, with allowance given for the Dst index, which was quiet for the study period. Comparisons were then made with other researchers who also found TEC anomalies on September 17, 18, and 19 associated with the Chi-Chi earthquake, which cannot be detected by PCA. Consideration is also given for reported ground level geomagnetic field activity that occurred between mid-August and late October, leading up to and including the Chi-Chi and Chia-Yi earthquakes, which are associated with the same series of faults. It is possible that Aug. 14 is representative of an earthquake-associated TEC anomaly. This is an interesting result given how much earlier than the earthquake it occurred.

Seismo-ionospheric anomalies in total electron content of the GIM and electron density of DEMETER before the 27 February 2010 M8.8 Chile earthquake

In this paper we examine the pre-earthquake ionospheric anomalies by the total electron content (TEC) extracted from GIM (global ionospheric map) and the electron density (Ne) observed by the DEMETER (Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions) satellite during the 2010 M8.8 Chile earthquake. Temporal variations show the nighttime TEC and Ne simultaneously increase 9–19 days before the earthquake. A cross-comparison of data recorded during the period of 1 February to 3 March in 2006–2010 confirms the above temporal anomalies specifically appear in 2010. The spatial analyses show that the anomalies tend to appear over the epicenter.

Support vector machines for TEC seismo-ionospheric anomalies detection

Abstract. Using time series prediction methods, it is possible to pursue the behaviors of earthquake precursors in the future and to announce early warnings when the differences between the predicted value and the observed value exceed the predefined threshold value. Support Vector Machines (SVMs) are widely used due to their many advantages for classification and regression tasks. This study is concerned with investigating the Total Electron Content (TEC) time series by using a SVM to detect seismo-ionospheric anomalous variations induced by the three powerful earthquakes of Tohoku (11 March 2011), Haiti (12 January 2010) and Samoa (29 September 2009). The duration of TEC time series dataset is 49, 46 and 71 days, for Tohoku, Haiti and Samoa earthquakes, respectively, with each at time resolution of 2 h. In the case of Tohoku earthquake, the results show that the difference between the predicted value obtained from the SVM method and the observed value reaches the maximum value (i.e., 129.31 TECU) at earthquake time in a period of high geomagnetic activities. The SVM method detected a considerable number of anomalous occurrences 1 and 2 days prior to the Haiti earthquake and also 1 and 5 days before the Samoa earthquake in a period of low geomagnetic activities. In order to show that the method is acting sensibly with regard to the results extracted during nonevent and event TEC data, i.e., to perform some null-hypothesis tests in which the methods would also be calibrated, the same period of data from the previous year of the Samoa earthquake date has been taken into the account. Further to this, in this study, the detected TEC anomalies using the SVM method were compared to the previous results (Akhoondzadeh and Saradjian, 2011; Akhoondzadeh, 2012) obtained from the mean, median, wavelet and Kalman filter methods. The SVM detected anomalies are similar to those detected using the previous methods. It can be concluded that SVM can be a suitable learning method to detect the novelty changes of a nonlinear time series such as variations of earthquake precursors.

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.The duration of TEC time series dataset is 120days at time resolution of 2h. The results show that the MLP presents anomalies better than referenced and conventional methods such as Auto-Regressive Integrated Moving Average (ARIMA) technique. In this study, also the detected TEC anomalies using the proposed method, are compared to the previous results (Akhoondzadeh, 2012) dealing with the observed TEC anomalies by applying the mean, median, wavelet and Kalman filter methods. The MLP detected anomalies are similar to those detected using the previous methods applied on the same case study. The results indicate that a MLP feed-forward neural network can be a suitable non-parametric method to detect changes of a non linear time series such as variations of earthquake precursors.

Ionospheric Anomaly due to the volcanic eruption in Colima, Mexico, 06 January 2013: Two-Dimensional Principal Component Analysis

The ionospheric total electron content (TEC) data from 05 to 10 January 2013 (UT) were examined by two-dimensional principal component analysis (2DPCA) and revealed a TEC anomaly related to the volcanic eruption in Colima, Mexico on 06 January, 2013. A TEC anomaly was detected above the volcano from 21:00 to 21:05 on 06 January 2013 (UT). The anomaly occurred for at least 5 minutes, during this time period we could identify the equatorial ionization anomaly (EIA). The shock acoustic wave produced by eruption-induced seismic activity may be the cause of the observed TEC anomaly. We show that it is possible to monitor or predict volcanic eruptions and their associated seismic activity through the use of two-dimensional principal component analysis of the resulting TEC anomalies.

Ionospheric Anomalies Related to the (M = 7.3), August 27, 2012, Puerto Earthquake, (M = 6.8), August 30, 2012 Jan Mayen Island Earthquake, and (M = 7.6), August 31, 2012, Philippines Earthquake: Two-Dimensional Principal Component Analysis

Two-dimensional principal component analysis (2DPCA) and principal component analysis (PCA) are used to examine the ionospheric total electron content (TEC) data during the time period from 00:00 on August 21 to 12: 45 on August 31 (UT), which are 10 days before the M = 7.6 Philippines earthquake at 12:47:34 on August 31, 2012 (UT) with the depth at 34.9 km. From the results by using 2DPCA, a TEC precursor of Philippines earthquake is found during the time period from 4:25 to 4:40 on August 28, 2012 (UT) with the duration time of at least 15 minutes. Another earthquake-related TEC anomaly is detectable for the time period from 04:35 to 04:40 on August 27, 2012 (UT) with the duration time of at least 5 minutes during the Puerto earthquake at 04: 37:20 on August 27, 2012 (UT) (M w = 7.3) with the depth at 20.3 km. The precursor of the Puerto earthquake is not detectable. TEC anomaly is not to be found related to the Jan Mayen Island earthquake (M w = 6.8) at 13:43:24 on August 30, 2012 (UT). These earthquake-related TEC anomalies are detectable by using 2DPCA rather than PCA. They are localized nearby the epicenters of the Philippines and Puerto earthquakes.

The ionospheric anomalies prior to the M9.0 Tohoku-Oki earthquake

The GPS total electron content (TEC) data were used to investigate the ionospheric abnormal behaviors prior to the 2011 Tohoku-Oki earthquake. The observations show a significant enhancement in TEC on March 8, 2011, and during the same period the solar activity also has a large increase. Both an empirical model and a theoretical model were used to check whether the TEC anomalies were entirely contributed by the increase in solar radiation. The comparison between the observations and the simulation results shows that only the solar radiation enhancement was not enough to produce the observed significant TEC enhancement. It means that some additional mechanisms, such as the per-earthquake ionospheric disturbance or the geomagnetic activities, may play a significant role in the significant TEC enhancement on March 8. The temporal–spatial distribution of the extreme TEC enhancement within 30days before the earthquake was particularly pursued. It is found that the extreme enhancement was persistently located in the region adjacent to the epicenter and the magnetic conjugate point for a long time of 16h. In addition, a geomagnetic disturbance with Kp=4 occurred on March 7. Therefore, the significant TEC enhancement on March 8 might be related to the M9.0 Tohoku-Oki earthquake and the geomagnetic disturbance.

Study of ionospheric anomalies due to impact of typhoon using Principal Component Analysis and image processing

Principal Component Analysis (PCA) and image processing are used to determine Total Electron Content (TEC) anomalies in the F-layer of the ionosphere relating to Typhoon Nakri for 29 May, 2008 (UTC). PCA and image processing are applied to the global ionospheric map (GIM) with transforms conducted for the time period 12:00–14:00 UT on 29 May, 2008 when the wind was most intense. Results show that at a height of approximately 150–200 km the TEC anomaly is highly localized; however, it becomes more intense and widespread with height. Potential causes of these results are discussed with emphasis given to acoustic gravity waves caused by wind force.

Ionospheric total electron content seismo-perturbation after Japan’s March 11, 2011, M=9.0 Tohoku earthquake under a geomagnetic storm; a nonlinear principal component analysis

Nonlinear principal component analysis (NLPCA) is implemented to analyze the spatial pattern of total electron content (TEC) anomalies 3 hours after Japan’s Tohoku earthquake that occurred at 05:46:23 on 11 March, 2011 (UTC) (M w =9). A geomagnetic storm was in progress at the time of the earthquake. NLPCA and TEC data processing were conducted on the global ionospheric map (GIM) for the time between 08:30 to 09:30 UTC, about 3 hours after this devastating earthquake and ensuing tsunami. Analysis results show stark earthquake-associated TEC anomalies that are widespread, and appear to have been induced by two acoustic gravity waves due to strong shaking (vertical acoustic wave) and the generation of the tsunami (horizontal Rayleigh mode gravity wave). The TEC anomalies roughly fit the initial mainshock and movement of the tsunami. Observation of the earthquake-associated TEC anomalies does not appear to be affected by a contemporaneous geomagnetic storm.

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.

Potential reasons for ionospheric anomalies detected by nonlinear principal component analysis just before the China Wenchuan earthquake, and their relationship to source conditions

Nonlinear principal component analysis (NLPCA) was performed to examine the total electron content (TEC) anomalies for the China Wenchuan earthquake of May 12, 2008 (= 7.9). This was applied to global ionospheric maps (GIMs) at heights from 150 km to 450 km, with the transforms conducted for the time period 00:00 to 06:00 UT on May 12, 2008. The earthquake occurred at 06:28 UT. The GIMs were analyzed by PCA and NLPCA, whereby they were separated into 100 smaller maps of 36° in longitude and 18° in latitude. These smaller maps are constructed at 71 × 71 pixels, which forms the transform matrix for NLPCA. The transform allows a principal eigenvalue to be assigned for each of the smaller maps. The results of the transforms provide 100 principal eigenvalues that cover the region, which includes the epicenter of the Wenchuan earthquake. The possibility of TEC anomalies caused by X-ray fluxes and geomagnetic activity is eliminated by reviewing X-ray flux data and the Kp index. The eigenvalues of NLPCA are compared with those of PCA. TEC anomalies were clearly detected using NLPCA, with large principal eigenvalues that represent earthquake-related TEC anomalies near the epicenter for the time period 00:00-0600 UT. The results of this study are discussed in terms of the potential causes of these TEC anomalies, especially for the time period 02:00-04:00 UT, when rocks around the epicenter were potentially subjected to a rapid increase in stress, which might have induced very pronounced p-type semiconductor effects. These effects will probably have been present for the other time periods, but might not have been so pronounced.

Manifestations of the earthquake preparations in the ionosphere total electron content variations

Recent ionospheric observations report anomalous total electron content (TEC) deviations prior strong earthquakes. We discuss common fetures of the pre-earthquake TEC disturbances on the basis of statistics covering 50 strong seismic events during 2005-2006. The F2-layer ionospheric plasma drift under action of the electric fields of seismic origin is proposed as the main reason of producing TEC anomalies. The origin of such electric fields is discussed in terms of the lithosphere-atmosphere-ionosphere coupling system. This theory is supported by numerical simulations using global Upper Atmosphere Model (UAM). UAM calculations show that the vertical electric current with the density of about 20 - 40 nA/m2 flowing between the Earth and ionosphere over an area of about 200 by 2000 km is required to produce the TEC disturbances with the amplitude of about 30% - 50% relatively to the non-disturbed conditions. Ionosphere responses on the variations of the latitudinal position, direction and configuration of the vertical electric currents have been investigated. We show that not only the vertical component of the ionospheric plasma drift but also horizontal components play an important role in producing pre-earthquake TEC disturbances.

Ionospheric total electron content anomalies due to Typhoon Nakri on 29 May 2008: A nonlinear principal component analysis

This paper uses Nonlinear Principal Component Analysis (NLPCA) and Principal Component Analysis (PCA) to determine Total Electron Content (TEC) anomalies in the ionosphere for the Nakri Typhoon on 29 May, 2008 (UTC). NLPCA, PCA and image processing are applied to the global ionospheric map (GIM) with transforms conducted for the time period 12:00–14:00UT on 29 May 2008 when the wind was most intense. Results show that at a height of approximately 150–200km the TEC anomaly using NLPCA is more localized; however its intensity increases with height and becomes more widespread. The TEC anomalies are not found by PCA. Potential causes of the results are discussed with emphasis given to vertical acoustic gravity waves. The approximate position of the typhoon's eye can be detected if the GIM is divided into fine enough maps with adequate spatial-resolution at GPS-TEC receivers. This implies that the trace of the typhoon in the regional GIM is caught using NLPCA.

Variations of equatorial electrojet as possible seismo-ionospheric precursor at the occurrence of TEC anomalies before strong earthquake

The measurements of GPS signal delays show that the local areas of increased/decreased Total Electron Content ( TEC) of the ionosphere can be observed before strong earthquakes. The main possible cause of these TEC disturbances is the vertical plasma drift under the action of zonal electric field. The spatial pattern of electric potentials for such electric field was proposed. The model calculations were done to investigate the efficiency of the proposed mechanism. The calculation results revealed the agreement with TEC variations observed before strong earthquakes and showed that the equatorial electrojet variations can be considered as precursors of earthquakes.

Is it possible to detect earlier ionospheric precursors before large earthquakes using principal component analysis (PCA)?

The goal of this study was to determine whether principal component analysis (PCA) can be used to process GPS ionospheric total electron content (TEC) data on a monthly basis to identify early earthquake-associated TEC anomalies. PCA is applied to GPS (mean value of a month) ionospheric TEC records collected from the Japan GEONET system to detect TEC anomalies associated with 10 earthquakes in Japan (M ≥ 6.0) from 2006 to 2007. According to the results, PCA was able to discriminate clear TEC anomalies in the months when all 10 earthquakes occurred. After reviewing the months when no M ≥ 6.0 earthquake occurred but the geomagnetic storm activity was present, it is possible that the maximal principal eigenvalues PCA returned for these 10 earthquakes indicate earthquake-associated TEC anomalies. Previously, PCA has been used to discriminate earthquake-associated TEC anomalies recognized by other researchers who found that a statistical association between large earthquakes and TEC anomalies could be established in the 5 days before earthquake nucleation and in 24 h before earthquake; however, since PCA uses the characteristics of principal eigenvalues to determine earthquake-related TEC anomalies, it is possible to show that such anomalies existed earlier than this 5-day statistical window. In this paper, this is shown through the application of PCA to one-dimensional TEC data relating to the earthquake of 17 February 2007 (M = 6.0). The analysis is applied to daily TEC and reveals a large principal eigenvalue (representative of an earthquake-associated anomaly) for 02 February, 15 days before the 17 February earthquake.

Potential reasons for ionospheric anomalies immediately prior to China's Wenchuan earthquake on 12 May 2008 detected by nonlinear principal component analysis

Nonlinear principal component analysis (NLPCA) is used to detect total electron content (TEC) anomalies for China's Wenchuan earthquake on 12 May 2008 (UT) (Mw=7.9). NLPCA is applied to global ionospheric maps (GIMs) at height ranging from 150 to 200km with transforms conducted for the time period 00:00–06:00UT on 12 May 2008. The GIMs are analyzed using NLPCA whereby the GIMs are separated into 100 smaller maps of 36° in longitude and 18° in latitude. These smaller maps are constructed at 71×71 pixels forming the transform matrix of the NLPCA. The transform allows for a principal eigenvalue to be assigned for each of the smaller maps. The results of the transforms provide 100 principal eigenvalues covering the region and the epicenter of the Wenchuan earthquake. The possibility of TEC anomalies being caused by X-ray flux and geomagnetic activity is eliminated by reviewing X-ray flux data and the Kp index. The eigenvalues of NLPCA are compared with the eigenvalues of principal component analysis (PCA), and TEC anomalies are clearly detected using NLPCA. Large principal eigenvalues representative of earthquake-related TEC anomalies were found nearby the epicenter for the time period 00:00–0600UT using NLPCA. The earthquake occurred at 06:28UT. A potential cause of the clear TEC anomaly almost directly over the epicenter in the time period 0200–0400 would be very stark p-type semiconductor effects caused by rocks under extreme stress. The stress may have abated during other time periods reducing p-type semiconductor effects and associated TEC anomalies.

Ionospheric total electron content: Global and hemispheric climatology

[1] A new general linear model of the climatology of the ionosphere's total electron content (TEC) is described, accounting simultaneously for the influences of solar and geomagnetic activity, oscillations at four frequencies and a secular trend. The model captures more than 98% of the variance in the daily averaged, global TEC derived from GPS observations during the 16 years from 1995 to 2010, and enables the reconstruction of TEC variations since 1950. Solar EUV irradiance variations, the dominant ionospheric influence, directly increase TEC by as much as 40 TECU from solar activity minimum to maximum and produce additional 27-day fluctuations of as much as 15 TECU (in October 2003). Semiannual and annual oscillations in TEC are comparable in magnitude to the 27-day fluctuations, with (peak to valley) amplitudes that increase from a few TECU at low solar activity to ∼17 TECU during solar activity maximum. The phase and amplitude of the semiannual oscillation are identical in the northern and southern geographic hemispheres (and hence globally). In contrast, the annual oscillation is twice as large in the southern hemisphere (where it peaks in December–January) than in the northern hemisphere (where it peaks in April–May). Seasonal, semiannual and annual anomalies in TEC are direct effects of semiannual and annual oscillations produced by orbitally driven photoionization and thermospheric composition changes, not of corresponding oscillations in solar or geomagnetic activity. Geomagnetic influences on daily averaged global TEC are relatively modest, with the maximum effect a reduction of 11 TECU (in October 2003) and only 11 episodes in excess of 5 TECU depletions during the past 16 years.

Ionospheric electron enhancement preceding the 2011 Tohoku-Oki earthquake

[1] The 2011 March 11 Tohoku-Oki earthquake (Mw9.0) caused vast damages to the country. Large events beneath dense observation networks could bring breakthroughs to seismology and geodynamics, and here I report one such finding. The Japanese dense network of Global Positioning System (GPS) detected clear precursory positive anomaly of ionospheric total electron content (TEC) around the focal region. It started ∼40 minutes before the earthquake and reached nearly ten percent of the background TEC. It lasted until atmospheric waves arrived at the ionosphere. Similar preseismic TEC anomalies, with amplitudes dependent on magnitudes, were seen in the 2010 Chile earthquake (Mw8.8), and possibly in the 2004 Sumatra-Andaman (Mw9.2) and the 1994 Hokkaido-Toho-Oki (Mw8.3) earthquakes, but not in smaller earthquakes.