Abstract
Earthquake ionosphere coupling phenomenon is one of the hot research topics using the Global Positioning System (GPS). Taking Lushan earthquake in April 2013 as an example, this paper firstly establishes ionosphere TEC models and determines the optimal model based on Autoregression model by analyzing the TEC values of the epicenter area detected by GPS. Then it makes predictions about the ionosphere data, obtains the background value, and conducts anomaly analysis by using the optimal model. Finally the correlation between ionosphere anomalies and earthquake is analyzed quantitatively by presenting data diagrams explicitly; then a new method to do short-term and imminent earthquake prediction is proposed in the end.
Highlights
An earthquake, as a result of a sudden release of energy in the Earth’s crust that creates seismic waves, is one of the major natural disasters which may cause huge property damage and casualties
Leonard and Barnes firstly discovered the coupling relationship between earthquakes and ionospheric when they observed the ionospheric anomaly in the foreshock of Alaska earthquake [3]
Inside the formula T ECt is the predicted value, the abnormal disturbances (TEC) is actual value, and S is the sum of error square
Summary
As a result of a sudden release of energy in the Earth’s crust that creates seismic waves, is one of the major natural disasters which may cause huge property damage and casualties. In order to advance earthquake prediction research, many scientists continue to explore new methods of seismic monitoring, and the relationship between the earthquake gestation period ionospheric disturbances and seismic coupling has become a hot topic [2]. Leonard and Barnes firstly discovered the coupling relationship between earthquakes and ionospheric when they observed the ionospheric anomaly in the foreshock of Alaska earthquake [3]. The main methods of ionospheric anomalies coupling studies include quartile method and sliding window method. Xinzhou recently proposed a preseismic ionospheric anomaly detection using time series method. Adopting time series method (ARMA model) can better take into account the uncertainty components and be able to calculate changes in the ionosphere TEC uncertainty [5]
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