Analysis of ionospheric anomalies in earthquakes using mean index and short time Fourier transform

Earthquake every year in the world, especially in a seismic country like Iran, causes huge human and financial losses. Earthquake prediction has become one of the great challenges of scientists in recent decades. One of the new methods is the evaluation of anomalies in the ionospheric parameters before the earthquake. The parameter investigated in this method is the total electron content (TEC). The study areas in this paper are the Ahar-Varzaghan earthquake with a magnitude of 6.5 and 6.3, the Sarpol Zahab earthquake with a magnitude of 6.3. In the Ahar-Varzaghan earthquake, the observations of 6 GPS stations and in the Sarpol Zahab earthquake, the observations of 5 GPS stations of the IGS network were used to calculate the ionosphere TEC. Short time Fourier transform (STFT) along with statistical parameters of mean and standard deviation have been used to detect of ionosphere time series anomalies. Also, geomagnetic and weather indicators KP, Dst, F10.7, Vsw (plasma velocity), Ey (magnetic field) and IMFBz (interplanetary magnetic field) have been investigated and analyzed to know the conditions of the days before the earthquake.

In recent years, the spectral analysis of ionospheric anomalies using the STFT method and its application in earthquake forecasting has become popular. The research results show that spectral methods can be a useful and reliable tool in further analysis, and the STFT method can be evaluated as a successful method for detecting ionosphere anomalies, which is also compatible with classical methods. Also, STFT is a powerful tool for processing a time series without the need for average and median values, so it can be used for other studies such as navigation, geophysics, geology and climatology. STFT is used as a modified version of the classical Fourier transform to obtain the frequency information of a signal in the time domain. This method provides the analysis of a small part of the signal at a certain time through windowing the signal. In STFT, the signal with a constant time-frequency resolution and with the same window length in all frequencies is divided into smaller parts, Fourier transform is applied on it and finally the output will be presented in two time-frequency dimensions. As a result, it is possible to obtain information about when and with what frequency each signal occurred.

In the Sarpol Zahab earthquake and in both classic and STFT methods, anomalies were observed on 309, 314 and 323 DOY, before the earthquake. The amount of these anomalies in the ionosphere time series was in the 0.058 to 5.44 TECU. The parameters related to solar and geomagnetic activities were also investigated in the days before and after the earthquake. Considering that the solar and geomagnetic activities (as an important factor in creating anomalies in the ionosphere time series) were calm in the days before the earthquake, these detected anomalies can be attributed to the earthquake. However, in the Ahar-Varzaghan earthquake and using both methods, in 5 to 15 days before the earthquake, anomalies of about 0.13 to 1.4 TECU were observed. In the days before the Ahar-Varzaghan earthquake, there were almost undisturbed conditions on most days, and therefore it cannot be said with certainty that the observed anomalies are completely related to the earthquake. The results of this paper showed that the STFT method is a powerful tool for spectral analysis without the need for values such as average or median. This feature of STFT is its strength compared to classical methods; because independence from these values minimizes the sources of error related to them (abnormalities, sudden variations in the ionosphere such as annual, semi-annual and seasonal variations). It is important to mention that the STFT method is more accurate in calm solar and geomagnetic conditions and provides high accuracy results.

The results show that for the Ahar-Varzaghan earthquake, there are anomalies on the 11, 12, 13 and 5 days before the earthquake. But for the Sarpol Zahab earthquake, anomalies can be seen 6, 7, 13 and 21 days before the earthquake. The analyzes of this paper show that if all the geomagnetic and weather parameters before the earthquake are investigated, the existing anomalies can be directly observed by analyzing the time series of the ionosphere with the STFT method. It is important that on days when geomagnetic conditions and calm weather are not prevailing, the occurrence of earthquake cannot be considered as the cause of anomalies detected in the ionosphere time series.