Pre-earthquake ionospheric anomalies before three major earthquakes by GPS-TEC and GIM-TEC data during 2015–2017

Tariq, M. Arslan; Shah, Munawar; Hernández‐Pajares, Manuel; Iqbal, Talat

doi:10.1016/j.asr.2018.12.028

Cited by 72 publications

(28 citation statements)

References 32 publications

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“…GNSS iyonosfer çalışmaları için önemli bir araç olarak kullanılmaktadır. Buna ek olarak GNSS sistemlerinin konum doğruluğunun artırılması için iyonosferik düzeltmelerin yapılması gerekmektedir [22][23][24][25][26]. GPS sinyaline ilişkin iyonosferik gecikme frekans (f) ve uydu-alıcı arasındaki Eğik Toplam Elektron Miktarı'na (STEC) bağlıdır.…”

Section: Materyal Ve Metotunclassified

Manyetik Fırtına Kaynaklı İyonosferik Değişimlerin GNSS Ölçüleri Kullanılarak İrdelenmesi

İnyurt

Şentürk

2020

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi

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Öz 08.09.2017 tarihinde gerçekleşen manyetik fırtınanın iyonosfer tabakasında sebep olduğu değişim, GNSS ölçüleri kullanılarak elde edilen TEC değerleri üzerinden analiz edilmiştir. Kuzey ve güney yarımkürede, iyonosferin farklı bölgelerinde bulunan GNSS istasyonlarına ait RINEX gözlemlerinden TEC değerleri elde edilmiştir. Manyetik fırtına kaynaklı TEC değişiminin ortaya çıkarılabilmesi için manyetik fırtına öncesi 10 gün, manyetik fırtına günü ve sonrası 1 gün olmak üzere her istasyona ilişkin toplam 12 günlük veri değerlendirilmiştir. Yapılan analiz sonucunda manyetik fırtınanın olduğu gün, öncesi ve sonrasında pozitif ve negatif anomaliler elde edilmiştir. Bu çalışma sonucunda Türkiye'de bulunan GNSS istasyonları kullanılarak manyetik fırtına kaynaklı iyonosfer değişimlerinin tespit edilebileceği gösterilmiştir.

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Section: Materyal Ve Metotunclassified

Manyetik Fırtına Kaynaklı İyonosferik Değişimlerin GNSS Ölçüleri Kullanılarak İrdelenmesi

İnyurt

Şentürk

2020

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi

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“…The pre-earthquake ionospheric perturbation is one of the most important phenomena of earthquakes precursor studies (Liu et al, 2001;Pulinets et al, 2003;Liu et al, 2006;He et al, 2011;Le et al, 2011;Sarkar et al, 2011;Parrot, 2012;Li and Parrot, 2013;Pisa et al, 2013;Guo et al, 2015;Rozhnoi et al, 2015). The total electron content (TEC) changes of the ionosphere associated with earthquakes have been reported by many researchers worldwide (e.g., Liu et al, 2001;Liu et al, 2004;Saroso et al, 2008;Heki, 2011;Heki and Enomoto, 2015;Iwata and Umeno, 2016;Liu et al, 2018;Tariq et al, 2019;Shah et al, 2020;Zhang et al, 2020). For instance, some studies displayed TEC anomalies prior to devastating earthquakes including the Wenchuan earthquake (Lin et al, 2009;Zhang et al, 2019), the Tohoku earthquake (Heki, 2011;Yao et al, 2012;Hirooka et al, 2016;Iwata and Umeno, 2016), and so on.…”

Section: Introductionmentioning

confidence: 99%

Singular Spectrum Analysis of the Total Electron Content Changes Prior to M ≥ 6.0 Earthquakes in the Chinese Mainland During 1998–2013

et al. 2021

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Early studies have shown evidence of the seismo-ionospheric perturbations prior to large earthquakes. Due to dynamic complexity in the ionosphere, the identification of precursory ionospheric changes is quite challenging. In this study, we analyze the total electron content (TEC) in the global ionosphere map and investigate the TEC changes prior to M ≥ 6.0 earthquakes in the Chinese Mainland during 1998–2013 to identify possible seismo-ionospheric precursors. Singular spectrum analysis is applied to extract the trend and periodic variations including diurnal and semi-diurnal components, which are dominated by solar activities. The residual ΔTEC which is mainly composed of errors and possible perturbations induced by earthquakes and geomagnetic activities is further investigated, and the root-mean-square error is employed to detect anomalous changes. The F10.7 and Dst index is also used as criterion to rule out the anomalies when intense solar or geomagnetic activities occur. Our results are consistent with those of previous studies. It is confirmed that the negative anomalies are dominant 1–5 days before the earthquakes at the fixed point (35°N, 90°E) during 0600–1000 LT. The anomalies are more obvious near the epicenter area. The singular spectrum analysis method help to establish a more reliable variation background of TEC and thus may improve the identification of precursory ionospheric changes.

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“…Significant progress has been recently made in evaluating the relationships between the earthquake-ionosphere (Namgaladze et al, 2018;Sorokin et al, 2020). During, before, and after the earthquake, physical variables such as friction, pressure, and physical changes in the ground layers occur (Pulinets et al 2006;Gousheva et al 2009;Sarlis et al 2015;Tariq et al 2019). The emergence of gases such as 222 Rn, He, and CO2 in the ground layers causes some chemical changes (He and CO2), which prevails up to the ionosphere.…”

Section: Introductionmentioning

confidence: 99%

Radon prediction using metrological parameters, and its significance in Seismo-Ionospheric coupling

Muhammad

Külahçı

2021

Preprint

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In order to derive boundary conditions, atmospheric and seismo-ionospheric models are coupled with generic assumptions. These boundary conditions are used to simulate possible interaction between earth’s atmospheric, geological processes and the Ionosphere. Rn is one of the major contributors to surface ionization, which is also believed to contribute to the geophysical and geochemical processes causing disturbance in the Ionosphere. Its relationship with metrological parameters in a given region gives an insight on the natural processes in the underground, as well as the relationship with atmospheric processes. It can enable models to establish realistic results rather than ideal theoretical consequences. Rn can be influenced by a number of physical variables, and therefore, this influence is sometimes very complicated to study, because of the Forcing researchers to make ideal assumptions. The relationship between Rn and some geological variables are studied, namely; soil temperature at 5 cm, 10 cm, 20 cm, and 50 cm, atmospheric pressure, and atmospheric temperature. A hybrid model is established based on the artificial neural network (ANN), which is referred to as multiANN model. This model is a combination of multi-regression and ANN models. Itenables Rn prediction to metrological parameters. To test the robustness of our model 50% training periods is employed with 50% testing periods. The model is able to forecast the remaining 50% effectively. With the aid of the Monte-Carlo method, it is possible to predict multiple future Rn variations with high precision. The regions with low performance of the multiANN are identified for possibly relationship to seismic events. The model could be a good candidate for predicting of Rn concentration from metrological parameters, especially in establishing the lower boundary conditions in seismo-ionospheric coupling models.

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Pre-earthquake ionospheric anomalies before three major earthquakes by GPS-TEC and GIM-TEC data during 2015–2017

Cited by 72 publications

References 32 publications

Manyetik Fırtına Kaynaklı İyonosferik Değişimlerin GNSS Ölçüleri Kullanılarak İrdelenmesi

Manyetik Fırtına Kaynaklı İyonosferik Değişimlerin GNSS Ölçüleri Kullanılarak İrdelenmesi

Singular Spectrum Analysis of the Total Electron Content Changes Prior to M ≥ 6.0 Earthquakes in the Chinese Mainland During 1998–2013

Radon prediction using metrological parameters, and its significance in Seismo-Ionospheric coupling

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