Multi-Scale ARMA Residual Correction Model for Detecting Pre-earthquake Ionospheric Anomalies

TANG Jun; MAO Wenfei

doi:10.13203/j.whugis20170321

Volume 44 Issue 6

Jun. 2019

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Geomatics and Information Science of Wuhan University > 2019 > 44(6): 791-798. > DOI: 10.13203/j.whugis20170321

TANG Jun, MAO Wenfei. Multi-Scale ARMA Residual Correction Model for Detecting Pre-earthquake Ionospheric Anomalies[J]. Geomatics and Information Science of Wuhan University, 2019, 44(6): 791-798. DOI: 10.13203/j.whugis20170321

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Multi-Scale ARMA Residual Correction Model for Detecting Pre-earthquake Ionospheric Anomalies

TANG Jun^{1, 3,},
MAO Wenfei²

1.
School of Civil Engineering and Architecture, East China Jiaotong University, Nanchang 330013, China
2.
School of Geodesy and Geomatics, East China University of Technology, Nanchang 330013, China
3.
State Key Laboratory of Geodesy and Earth's Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China

Funds:

The National Natural Science Foundation of China 41504025

The National Natural Science Foundation of China 41761089

the Natural Science Foundation of Jiangxi Province 20181BAB203027

the China Postdoctoral Science Foundation (CPSF) 2015M582312

the Foundation of Jiangxi Educational Committee GJJ170362

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Author Bio:
TANG Jun, PhD, associate professor, specializes in GNSS data processing and ionosphere model estimation. E-mail:tj928@163.com
Received Date: June 23, 2018
Published Date: June 04, 2019

Graphical Abstract

Abstract

Abstract

To improve the prediction accuracy of the background values of the ionospheric total electronic content (TEC) disturbance, we have proposed multi-scale autoregressive moving average (ARMA) residual correction model (MARCM) by comparing the precision of this method, ARMA model, inter quartile range(IQR)and sliding window method in predicting the ionospheric total electronic content reference background values. The results show that the average relative accuracy of TEC background value predicted by MARCM is 89.78%, which is higher than the ARMA model, IQR and sliding window method with values of 5.18%, 1.41% and 1.42% respectively and show that the percentage of absolute residual values less than or equal to 3.0 TECU predicted by MARCM is 91.67%, significantly better than the other three methods, It is demorstrated that using MARCM to detect pre-earthquake ionospheric anomalies is feasible. We use this method to detect pre-earthquake ionospheric anomalies of the earthquake happened in Lushan on April 20, 2013, and prove the effectiveness of the proposed method. The results show that obviously ionospheric positive anomalies on 9 and 13 days before the earthquake and apparently ionospheric negative anomalies on 1 to 4 days before the earthquake, are most likely to be caused by the earthquake. And positive anomalies mainly emerge in the 08:00 UT to 10:00 UT, the negative anomalies are mainly concentrated in 00:00 UT to 14:00 UT
- multi-scale,
- ARMA,
- residual correction,
- earthquake,
- ionospheric TEC anomaly

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References (19)

References

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Multi-Scale ARMA Residual Correction Model for Detecting Pre-earthquake Ionospheric Anomalies

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