Long-Lasting Patterns in 3 kHz Electromagnetic Time Series after the ML = 6.6 Earthquake of 2018-10-25 near Zakynthos, Greece

Abstract

This paper reports one-month 3 kHz EM disturbances recorded at Kardamas, Ilia, Greece after a strong M L = 6.6 earthquake occurred on 2018/10/25 near Zakynthos and Ilia. During this period 17 earthquakes occurred with magnitudes M L = 4.5 and M L = 5.5 and depths between 3 km and 17 km, all near Zakynthos and Ilia. A two-stage, fully computational methodology was applied to the outcomes of five different time-evolving chaos analysis techniques (DFA, fractal dimension analysis through Higuchi, Katz and Sevcik methods and power-law analysis). Via literature-based thresholds, the out-of-threshold results of all chaos analysis methods were located and from these, the common time instances of 13 selected combinations per five, four, three and two methods. Numerous persistent segments were located with DFA exponents between 1.6 ≤ α ≤ 2.0 , fractal dimensions between 1.4 ≤ D ≤ 2.0 and power-law exponents between 2.2 ≤ β ≤ 3.0 . Out of the 17 earthquakes, six earthquakes were jointly matched by 13 selected combinations of five, four, three and two chaos analysis methods, four earthquakes by all combinations of four, three and two, while the remaining seven earthquakes were matched by at least one combination of three methods. All meta-analysis matches are within typical forecast periods.

Stochastic and Self-Organisation Patterns in a 17-Year PM10 Time Series in Athens, Greece

“…Despite the increased evidence found for the two dates of Areas 1 and 2, all the dates of Table 3 are important, as well as the results of other dates reported in the previous publications of the team [ 36 , 37 ]. The above facts are indicative of the advancement of the new methodology described in the previous publications [ 36 , 37 , 38 , 39 ]. It is significant that the technique has been checked in other environmental systems (electromagnetic radiation disturbances and radon in soil variations).…”

“…As already mentioned, the team has utilised, in four publications [ 36 , 37 , 38 , 39 ], combinations of 2–13 different chaotic techniques to analyse time series for hidden fractal and long-memory trends. Two of these publications referred to PM 10 time series.…”

“…Following this logic, if a daily PM 10 relative concentration ( ) exceeds , it is considered as an anomaly from a stochastic tendency ( is the standard deviation of the whole data). Accepting the limit for the stochastic trends of the data, if cut-off limits for entropy (BE and TE) are set, as described in the previous publications of the team [ 36 , 37 , 38 , 39 ], the combination of the three techniques (one statistical and two entropic) can be implemented.…”

“…The corresponding cut-off limits are selected as −2.0 for BE and 1.18 for TE. These limits are arbitrarily set as in the previous related publications [ 36 , 37 , 38 , 39 ] in accordance to the ASCII data of the temporal variations of BE and TE. This part of the analysis is described as Step 2 meta-analysis of the data.…”

“…In [ 37 ], a combination of two techniques is employed (DFA versus analysis); however, most significantly, a combination of 13 different chaos analysis techniques is reported. The combination of many different chaos analysis techniques have been employed and checked in critical electromagnetic time series [ 38 ] and critical radon in groundwater series [ 39 ]. The importance of the above approach is that it employs sliding windows forwarded one sample, covering, in that manner, a fine analysis of the time series.…”