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The analysis was performed in time domain using moving time window technique.

We then calculate the mean amplitude every 0.1 s within a moving time window of 0.2 s.

A polarization analysis of waveform within a moving time window of 0.5 s during a lapse time was performed.

Subsequently, we calculate the root-mean-square (RMS) amplitude in a moving time window with a duration of 4/f for each frequency band.

We apply a moving time window over the observed spectral radius (TE or ATE±) time series to derive the unknown coefficients and constants for natural logarithm curves.

We calculated both the amplitude ratio and the phase lag, with a moving time window of 15 days and a running step of 3 days (Fig. 6).

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We find significant positive trends in the marginal distribution parameters as well as in the dependence measure from analyzing 50-year moving time windows.

In line with previous works (see for example [2]), we here pursue the latter approach and employ standard non-parametric tests to moving time windows.

The Z-mapping approach measures the difference in seismicity rate, within moving time windows, to the background rate by a standard deviation, Z (Wiemer and Wyss 1994; Wyss et al. 2004; Katsumata 2015).

Therefore, the proposed method allows us to perform analysis at least once each 30 days for approximately 80% of the observing period and once each 60 days for 95%. Figure 6 Frequency distribution of the number of analyzed teleseismic events within moving time windows.

But moving time windows provide only partial insights into the time course of processing.

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