scholarly journals 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

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Jyh-Woei Lin
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
The Philippines ◽  
Electron Content ◽  
Two Dimensional ◽  
Total Electron ◽  
Duration Time ◽  
Time Period ◽  
A Tec

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) (Mw= 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 (Mw= 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.

scholarly journals DETECTING IONOSPHERIC ANOMALIES ASSOCIATED WITH THREE JAPAN MIYAKO EARTHQUAKES TO SHOW THEIR CORRELATIONS AND ASSOCIATED EARTHQUAKE-INDUCED TSUNAMIS

2016 ◽  
Vol 42 (1) ◽  
pp. 7-15 ◽  
Author(s):  
Lin Jyh-Woei
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Electron Content ◽  
Mathematical Tool ◽  
Two Dimensional ◽  
Total Electron ◽  
Ionospheric Total Electron Content ◽  
Duration Time ◽  
Close Proximity ◽  
A Tec

This study employed two-dimensional principal component analysis (2DPCA) for the detection of anomalies in the two-dimensional ionospheric total electron content (TEC) associated with Japan three earthquakes and earthquake-induced tsunamis. From 04:40 to 04:50 (UTC) on February 15th, first TEC precursor was detected over the epicentre of the 16 February quake with the duration time of at least 10 minutes. A weak TEC anomaly associated with an earthquake-induced tsunami was also detected from 23:15 to 23:20 (UTC) on 16 February with the duration time of at least 5 minutes. An additional earthquake (Mw = 6.3) occurred in Miyako in the vicinity of the first earthquake. Second TEC precursor to the 20 February Miyako earthquake was recorded over the epicentre between 10:20 and 10:30 (UTC) on 19 February with the duration time of at least 10 minutes. A supplemental earthquake occurred (Mw = 6.1) as well in Miyako in the vicinity of the first earthquake. A TEC precursor to the 21 February Miyako earthquake was recorded over the epicentre between 04:15 and 04:25 (UTC) on 20 February with the duration time of at least 10 minutes. The three Miyako earthquakes presented similar anomalies and duration time in the TEC fluctuations, due largely to similarities in the magnitudes of the largest principal eigenvalues and the close proximity of the epicentres. Our results led to the reasonable confirmation that the very weak TEC anomaly following the Miyako earthquake on 16 February was associated with the earthquake-induced tsunami. 2DPCA is a useful mathematical tool for the monitoring of anomalous ionospheric fluctuations for use in the early warning of weak tsunamis.

scholarly journals Early warning of tsunami from seismo-ionospheric fluctuation after Japan’s March 11, 2011, M=9.0 Tohoku earthquake using two-dimensional principal component analysis

2015 ◽  
Vol 58 (4) ◽  
Author(s):  
Jyh-Woei Lin
Keyword(s):  
Principal Component Analysis ◽  
Shock Waves ◽  
Early Warning ◽  
Principal Component ◽  
Tohoku Earthquake ◽  
Component Analysis ◽  
Satellite System ◽  
Electron Content ◽  
Two Dimensional ◽  
Total Electron

<p>Two-dimensional principal component analysis (2DPCA) is implemented to analyze the total electron content (TEC) anomalies after Japan’s Tohoku earthquake that occurred at 05:46 on March 11, 2011 (UTC) (M<sub>w</sub>=9). 2DPCA and TEC data processing were conducted just after this devastating earthquake. Analysis results show an earthquake-associated TEC anomaly near the epicenter that began at 05:47. This may represent an extension of the precursor of the earthquake, to the precursor of China’s Wenchuan earthquake on May 12, 2008, detected by the study of Lin [2012], for which the data were obtained at a height of 150-200 km by the FORMOSAT-3 satellite system. It is impossible that such precursor caused by the acoustic shock waves. Another TEC anomaly near the epicenter occurred at 05:53, and this initiated the propagation of the tsunami effect related to the ionosphere through the acoustic shock waves from the epicenter. However, the TEC anomalies did not appear to be affected by a contemporaneous geomagnetic storm and other non-earthquake effects. The propagation of anomalous fluctuation could be an early warning of the tsunami for the regions far from the epicenter as it began to propagate with the higher speed of 3960-4950 km/h than the tsunami speed (720-800 km/h).</p><div> </div>

Possible reason of ionospheric anomaly post the April 20, 2013, Mw = 6.6 China' Lushan earthquake: Applying two-dimensional principal component analysis (2DPCA) to two-dimensional total electron content (TEC)

2014 ◽  
Vol 80 (3) ◽  
pp. 437-446
Author(s):  
Jyh-Woei Lin
Keyword(s):  
Principal Component Analysis ◽  
Total Electron Content ◽  
Principal Component ◽  
Component Analysis ◽  
Lushan Earthquake ◽  
Electron Content ◽  
Two Dimensional ◽  
Total Electron ◽  
Acoustic Shock Wave ◽  
Density Variance

In this study, two-dimensional principal component analysis (2DPCA) was used to determine the reason for the ionospheric two-dimensional total electron content (TEC) anomaly after China's Lushan earthquake at 00:02:47 UT on April 20, 2013 (Mw = 6.6). TEC data from 00:00 to 00:15 (UT) on April 20, 2013 were examined. The TEC anomaly was very intense 00:05 to 00:10 (UT) after the earthquake. One potential cause of the TEC anomaly, which might have been a density variance, is a rising acoustic shock wave, with speed of at least 1127.82, ms−1, resulting from the mainshock. The duration of the TEC anomaly was at least 5 min.

scholarly journals Investigasi Anomali TEC Ionosfer Berkaitan Dengan Gempa Bumi Jailolo 15 Nopember 2019 Menggunakan Metode 2DPCA

2020 ◽  
Vol 20 (2) ◽  
pp. 128
Author(s):  
Gloria R Kaindeh ◽  
Seni H Tongkukut ◽  
Gerald H Tamuntuan ◽  
R Telleng ◽  
Ferdy Ferdy ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Total Electron Content ◽  
Seismic Activity ◽  
Principal Component ◽  
Component Analysis ◽  
Electron Content ◽  
Two Dimensional ◽  
Total Electron ◽  
Ionospheric Total Electron Content ◽  
Eigen Value

Penelitian ini berfokus pada upaya menginvestigasi anomali Total Electron Content (TEC) ionosfer berkaitan dengan gempa bumi Jailolo yang terjadi pada tanggal 15 November 2019 pukul 01:17 Waktu Indonesia Timur (WIT) dengan menggunakan metode Two Dimensional Principal Component Analysis (2DPCA). Anomali TEC yang teridentifikasi oleh metode 2DPCA digunakan untuk menentukan prekusor  dari gempa bumi Jailolo. Citra Global Ionosphere Maps (GIM) TEC selang tanggal 9-15 Nopember 2019 dianalisis dan dikonversi menjadi citra nilai Eigen menggunakan program Matlab_2DPCA. Berdasarkan citra nilai Eigen ditemukan bahwa pada tanggal 13 Nopember 2019 pukul 22:15 – 22:35 WIT telah terjadi anomali TEC ionosfer di atas episenter gempa bumi Jailolo dengan durasi 20 menit. Selama aktivitas pra seismik, ionosfer memberikan respon berupa penurunan nilai TEC. Anomali kandungan elektron total ionosfer merupakan suatu prekursor yang berasosiasi dengan pelepasan gas radon selama aktivitas pra seismik sebelum gempa bumi. Kata Kunci: Anomali TEC; gempa bumi Jailolo; metode 2DPCA; nilai eigen, prekursor Investigation of Ionosphere TEC Anomalies Associated with the 15 November 2019 of Jailolo Earthquake Using the 2DPCA Method ABSTRACTThis research focuses on investigating of the ionospheric total electron content (TEC) anomaly associated with the Jailolo Earthquake earthquake that occurred on November 15, 2019 at 01:17 Eastern Indonesian Time (WIT) using the 2DPCA method. The TEC anomaly identified by the 2DPCA method was used to determine the precursor of the Jailolo earthquake. Global ionosphere maps (GIM) TEC images between November 9-15, 2019 were analyzed and converted into several images of the Eigen value using the Matlab_2DPCA program. Based on Eigen value images, it was found that on November 13, 2019 at 22:15 – 22:35 WIT, an ionosphere TEC anomaly occurred above the epicenter of the Jailolo Earthquake with a duration of 20 minutes. During pre-seismic activity, ionosphere given a responds by decreasing of TEC value. The total electron content anomaly of the ionosphere is a precursor associated with the release of radon gas during pre-seismic activity before an earthquake.Keywords: TEC anomaly; Jailolo earthquake; 2DPCA method; eigen value,  precursor

scholarly journals Latitude-Time Total Electron Content Anomalies as Precursors to Japan's Large Earthquakes Associated with Principal Component Analysis

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Jyh-Woei Lin
Keyword(s):  
Principal Component Analysis ◽  
Total Electron Content ◽  
Principal Component ◽  
Component Analysis ◽  
Electron Content ◽  
Monthly Basis ◽  
Storm Activity ◽  
Total Electron ◽  
Principal Eigenvalues ◽  
Large Earthquakes

The goal of this study is to determine whether principal component analysis (PCA) can be used to process latitude-time ionospheric TEC data on a monthly basis to identify earthquake associated TEC anomalies. PCA is applied to latitude-time (mean-of-a-month) ionospheric total electron content (TEC) records collected from the Japan GEONET network to detect TEC anomalies associated with 18 earthquakes in Japan () from 2000 to 2005. According to the results, PCA was able to discriminate clear TEC anomalies in the months when all 18 earthquakes occurred. After reviewing months when no earthquakes occurred but geomagnetic storm activity was present, it is possible that the maximal principal eigenvalues PCA returned for these 18 earthquakes indicate earthquake associated TEC anomalies. Previously PCA has been used to discriminate earthquake-associated TEC anomalies recognized by other researchers, who found that statistical association between large earthquakes and TEC anomalies could be established in the 5 days before earthquake nucleation; 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.

scholarly journals Spatial and temporal variation of total electron content as revealed by principal component analysis

2016 ◽  
Vol 34 (12) ◽  
pp. 1109-1117 ◽  
Author(s):  
Elsayed R. Talaat ◽  
Xun Zhu
Keyword(s):  
Principal Component Analysis ◽  
Total Electron Content ◽  
General Circulation ◽  
Circulation Model ◽  
Principal Component ◽  
Component Analysis ◽  
Total Variance ◽  
Spatial And Temporal Variation ◽  
Electron Content ◽  
Total Electron

Abstract. Eleven years of global total electron content (TEC) data derived from the assimilated thermosphere–ionosphere electrodynamics general circulation model are analyzed using empirical orthogonal function (EOF) decomposition and the corresponding principal component analysis (PCA) technique. For the daily averaged TEC field, the first EOF explains more than 89 % and the first four EOFs explain more than 98 % of the total variance of the TEC field, indicating an effective data compression and clear separation of different physical processes. The effectiveness of the PCA technique for TEC is nearly insensitive to the horizontal resolution and the length of the data records. When the PCA is applied to global TEC including local-time variations, the rich spatial and temporal variations of field can be represented by the first three EOFs that explain 88 % of the total variance. The spectral analysis of the time series of the EOF coefficients reveals how different mechanisms such as solar flux variation, change in the orbital declination, nonlinear mode coupling and geomagnetic activity are separated and expressed in different EOFs. This work demonstrates the usefulness of using the PCA technique to assimilate and monitor the global TEC field.

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