Growth and Inhibition of Equatorial Anomaly Prior to an Earthquake (EQ): Case Studies with Total Electron Content (TEC) Data for Major EQs of Japan 2011 and Indonesia 2012

Devi, M.; Medhi, Alaka; Sarma, A. J.D.; Barbara, A. K.

doi:10.4236/pos.2013.43024

Cited by 14 publications

(7 citation statements)

References 28 publications

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“…The simultaneous growth of strong EEA in the latitude zone of -5° N to 10° N and near the epicentre longitudes suggests coupling process between development of EEA and EEAC. The intense EEA at the night sector that was observed in presence of mid latitude earthquakes from TEC global data was suggested by Devi et al, [2013] to be due to the result of westward E-field enhanced by the EQ induced processes that propagates density to lower latitudes from mid latitude epicenter through downward drift. The increase in TEC at this longitude zone is further enhanced by EM focusing effect generated at the EEA location due to the presence of the distortion of earth magnetic field in this sector [Devi et al, 2013].…”

Section: Discussionmentioning

confidence: 99%

“…Equatorial anomaly factor takes a key role in such changes specially when the epicentre lies near to the equator and at low latitudes [Depueva and Ratanova, 2001;Devi et al, 2001;Devi et al, 2004;Devi et al, 2011(b)] . In case of an EQ with epicentre at mid latitude, the equatorial anomaly effect may not be very effective but there are still evidences of growth of Earthquake time Equatorial Anomaly (EEA), significantly at the longitude zone of a mid-latitude EQ epicentre Devi et al, 2013;Ryu et al, 2014;Ryu et al, 2016]. Such modifications of anomaly prior to mid latitude EQs are also shown through model computation by Karpov et al, [2013].…”

Section: Introductionmentioning

confidence: 90%

“…The intensity of both EEA and EEAC decreases from April 25 [Figure1(h)] and disappears after that . Based on the growth and development process of EEA and EECA from April 18 to 24, an EQ is predicated to occur on April 25 th , on basis of the approach ofDevi et al, [2013]. But to identify the epicene location, it is essential to estimate the magnitude of EEA and EEAC.…”

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confidence: 99%

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Expansion of Earthquake (EQ) time Equatorial Anomaly: an index of precursor as seen in major Nepal EQ of April 2015

Devi¹,

Barbara²,

Oyama³

et al. 2015

IJEAR

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The application of Electromagnetic methods in the research field of EQ precursor study with aims of identifying signature of an impending EQ and its epicenter, needs new approaches and techniques, because even with the available volume of work and reports on these aspects, the problem remains still a challenging one. The paper addresses such aspects in case of the Nepal EQ of April , 2015 (epicentre at 28.266N and 84.463 E ),of magnitude M= 7.9, by examining through analysis of global Total Electron content (TEC) data for detection of precursive anomaly signature in the Earthquake time Equatorial Anomaly (EEA), a feature observed to develop at the equator and in the longitude sector of the epicentre. Significant that, along with the EEA, a remarkable increase in TEC develops days before the impending earthquake persisting even to late night hours at the epicentre, a location just outside the normal equatorial anomaly belt . This feature is associated with the expansion of Earthquake time Equatorial Anomaly Crest (we call EEAC). The explanations of such phenomena are sought in pumping process of ionization density mainly by ExB drift, where E is the earthquake modified electric field. Possible additional sources working for growth & development of EEA and EEAC are also suggested.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 90%

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confidence: 99%

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Expansion of Earthquake (EQ) time Equatorial Anomaly: an index of precursor as seen in major Nepal EQ of April 2015

Devi¹,

Barbara²,

Oyama³

et al. 2015

IJEAR

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“…It is however important to examine association of orographic role on EQ time changes in atmospheric dynamics in enhancement of LOS path length in the environment taken under this study. This indeed is a difficult task as earthquake preparatory processes could cause diverse effects in the near Earth space and their manifestations are observed at the surface that may extend even up to the ionosphere [Depueva and Ruzhin 1995, Devi et al 2001, Liu et al 2001, Devi et al 2004, Parrot et al 2008, Devi et al 2013a, Devi et al 2013b. However, in the context of present observation, the atmospheric factors with reference to EQ-time drop in temperature will be specially discussed as this is one of the prime factors leading to changes in near Earth dynamics and also that in almost all the reported cases related to EQ induced temperature variations, be it surface temperature, the Sea Surface Temperature (SST) or Surface Latent Heat Flux (SLHF) [Qiang 1997, Tronin 2000, Tronin 2002, Dey and Singh 2003, Cervone et al 2004, Ouzonov et al 2007, Singh et al 2007, Alvan et al 2012, Goswami et al 2014], an increase in its value has been noted except a few cases [Singh et al 2010].…”

Section: Discussionmentioning

confidence: 99%

Orographic role in anomalous VHF propagation on the background of impending earthquakes (EQ)

Devi

Medhi

Barbara

et al. 2015

Annals of Geophysics

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<p>The role of orographic factors in modifying atmospheric dynamics on the background of an impending earthquake (EQ) that might lead to propagation of a signal beyond the Line Of Sight (LOS) is examined in the paper. The analysis is based on the data of anomalous reception of VHF FM-signal at Gauhati University (GU, 26.15°N, 91.66°E), a station located in the sub Himalayan terrain. The signal reception records show that their anomalous appearance are associated closely with earthquake events of M >5.0, a phenomenon identified as EQ precursor. To identify sources of such reception, the paper presents some analytical approaches involving the terrain factors, impending EQ and atmospheric variabilities. Finally, the contribution of location/topography of the transmitter, receiver and epicenter in modifying the EQ induced atmospheric factors, is brought in to the ambit of analysis for explaining the observed over horizon VHF signal propagation. A special reference is made on the EQ time drop in temperature, increase in humidity and hence modification in Radio Refractive Index (RRI) gradient, in favoring such reception. A model in support of the observation on EQ time lithosphere-atmosphere coupling relevant to widening of radio horizon limit is also proposed.</p>

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“…There are also several other studies supporting these alternative mechanisms that ionospheric disturbances in ion temperatures, foF 2, and TEC had been observed prior to strong EQs around Japan (Karatay et al, 2010; Ouzounov et al, 2011; Oyama et al, 2016; Zolotov et al, 2013), Chile (Namgaladze et al, 2009; Yadav et al, 2015), Italy (Akhoondzadeh, 2016; Davidenko & Pulinets, 2019; Kouris et al, 2006; Pulinets, 1998), El‐Salvador (Plotkin, 1999), India (Trigunait et al, 2004), the United States (Kouris & Fotiadis, 2002; Pulinets et al, 2007), Mexico (Pulinets, 2004; Pulinets et al, 2004, 2005), Taiwan (Liu et al, 2000, 2004, 2010), Indonesia (Devi et al, 2013), Nepal (Li et al, 2016), China (Karatay et al, 2010; Zhang et al, 2004), and Turkey (Akyol, 2013; Akyol et al, 2013; Arikan et al, 2012). In these studies, statistical methods have been used for the identification of the influence of seismic activities on the ionospheric variations such as TEC difference and variation analysis (Arikan et al, 2012; Karatay et al, 2010; Namgaladze et al, 2009; Ouzounov et al, 2011; Plotkin, 1999; Yadav et al, 2015; Zolotov et al, 2013), equatorial TEC abnormality analysis (Devi et al, 2013), ionospheric correction Trigunait et al (2004), correlation analysis between TEC and foF2 or different pairs of GPS receivers (Pulinets, 2004; Pulinets et al, 2004, 2005, 2007), generation of ionospheric‐precursor masks based on variation of TEC and foF2 (Davidenko & Pulinets, 2019), interquartile range and percentage analysis (Liu et al, 2000, 2004, 2010, 2016; Oyama et al, 2016; Zhang et al, 2004), relative deviation of daily ionospheric parameters from their corresponding monthly medians (Kouris & Fotiadis, 2002; Kouris et ...…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning‐Based Detection of Earthquake Precursors Using Ionospheric Data

Akyol

Arıkan

2020

Radio Science

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Detection of precursors of strong earthquakes is a challenging research area. Recently, it has been shown that strong earthquakes affect electron distribution in the regional ionosphere with indirectly observable changes in the ionospheric delays of GPS signals. Especially, the total electron content (TEC) estimated from GPS data can be used in the seismic precursor detection for strong earthquakes. Although physical mechanisms are not well understood yet, GPS‐based seismic precursors can be observed days prior to the occurrence of the earthquake. In this study, a novel machine learning‐based technique, EQ‐PD, is proposed for detection of earthquake precursors in near real time based on GPS‐TEC data along with daily geomagnetic indices. The proposed EQ‐PD technique utilizes support vector machine (SVM) classifier to decide whether an observed spatiotemporal anomaly is related to an earthquake precursor or not. The data fed to the classifier are composed of spatiotemporal variability map of a region. Performance of the EQ‐PD technique is demonstrated in a case study over a region covering Italy in between the dates of 1 January 2014 and 30 September 2016. The data are partitioned into three nonoverlapping time periods, that are used for training, validation, and test of detecting precursors of earthquakes with magnitudes above 4 in Richter scale. The EQ‐PD technique is able to detect precursors in 17 out of 21 earthquakes while generating 7 false alarms during the validation period of 266 days and 22 out of 24 earthquakes while generating 13 false alarms during the test period of 282 days.

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Growth and Inhibition of Equatorial Anomaly Prior to an Earthquake (EQ): Case Studies with Total Electron Content (TEC) Data for Major EQs of Japan 2011 and Indonesia 2012

Cited by 14 publications

References 28 publications

Expansion of Earthquake (EQ) time Equatorial Anomaly: an index of precursor as seen in major Nepal EQ of April 2015

Expansion of Earthquake (EQ) time Equatorial Anomaly: an index of precursor as seen in major Nepal EQ of April 2015

Orographic role in anomalous VHF propagation on the background of impending earthquakes (EQ)

A Machine Learning‐Based Detection of Earthquake Precursors Using Ionospheric Data

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