Similarity of fluctuations in correlated systems: The case of seismicity

We report a similarity of fluctuations in equilibrium critical phenomena and non-equilibrium systems, which is based on the concept of natural time. The world-wide seismicity as well as that of San Andreas fault system and Japan are analyzed. An order parameter is chosen and its fluctuations relative to the standard deviation of the distribution are studied. We find that the scaled distributions fall on the same curve, which interestingly exhibits, over four orders of magnitude, features similar to those in several equilibrium critical phenomena (e.g., 2D Ising model) as well as in non-equilibrium systems (e.g., 3D turbulent flow).Comment: 5 pages, 9 figure

Natural entropy fluctuations discriminate similar looking electric signals emitted from systems of different dynamics

Complexity measures are introduced, that quantify the change of the natural entropy fluctuations at different length scales in time-series emitted from systems operating far from equilibrium. They identify impending sudden cardiac death (SD) by analyzing fifteen minutes electrocardiograms, and comparing to those of truly healthy humans (H). These measures seem to be complementary to the ones suggested recently [Phys. Rev. E {\bf 70}, 011106 (2004)] and altogether enable the classification of individuals into three categories: H, heart disease patients and SD. All the SD individuals, who exhibit critical dynamics, result in a common behavior.Comment: Published in Physical Review

Effect of significant data loss on identifying electric signals that precede rupture by detrended fluctuation analysis in natural time

Electric field variations that appear before rupture have been recently studied by employing the detrended fluctuation analysis (DFA) as a scaling method to quantify long-range temporal correlations. These studies revealed that seismic electric signals (SES) activities exhibit a scale invariant feature with an exponent $\alpha_{DFA} \approx 1$ over all scales investigated (around five orders of magnitude). Here, we study what happens upon significant data loss, which is a question of primary practical importance, and show that the DFA applied to the natural time representation of the remaining data still reveals for SES activities an exponent close to 1.0, which markedly exceeds the exponent found in artificial (man-made) noises. This, in combination with natural time analysis, enables the identification of a SES activity with probability 75% even after a significant (70%) data loss. The probability increases to 90% or larger for 50% data loss.Comment: 12 Pages, 11 Figure

Geoelectric field and seismicity changes preceding the 2018 Mw6.8 earthquake and the subsequent activity in Greece

A strong earthquake of magnitude Mw6.8 struck Western Greece on 25 October 2018 with epicenter at 37.515N 20.564E. It was preceded by an anomalous geolectric signal that was recorded on 2 October 2018 at a measuring station 70km away from the epicenter. Upon analyzing this signal in natural time, we find that it conforms to the conditions suggested (e.g., Entropy 19 (2017) 177) for its identification as precursory Seismic Electric Signal (SES) activity. Notably, the observed lead time of 23 days lies within the range of values that has been very recently identified (Entropy 20 (2018) 561) as being statistically significant for the precursory variations of the electric field of the Earth. Moreover, the analysis in natural time of the seismicity subsequent to the SES activity in the area candidate to suffer this strong earthquake reveals that the criticality conditions were obeyed early in the morning of 18 October 2018, i.e., almost a week before the strong earthquake occurrence, in agreement with earlier findings. Furthermore, upon employing the recent method of nowcasting earthquakes, which is based on natural time, we find an earthquake potential score around 80% just before the occurrence of this Mw6.8 earthquake. In the present version of this manuscript, we also report the recording of additional SES activities after the occurrence of the latter earthquake and update the results until 16 April 2019.Comment: 10 pages including 12 figures. The major part of this paper appeared in Entropy 20 (2018) 882 by the first two author

Entropy of seismic electric signals: Analysis in natural time under time-reversal

Electric signals have been recently recorded at the Earth's surface with amplitudes appreciably larger than those hitherto reported. Their entropy in natural time is smaller than that, $S_u$, of a ``uniform'' distribution. The same holds for their entropy upon time-reversal. This behavior, as supported by numerical simulations in fBm time series and in an on-off intermittency model, stems from infinitely ranged long range temporal correlations and hence these signals are probably Seismic Electric Signals (critical dynamics). The entropy fluctuations are found to increase upon approaching bursting, which reminds the behavior identifying sudden cardiac death individuals when analysing their electrocardiograms.Comment: 7 pages, 4 figures, copy of the revised version submitted to Physical Review Letters on June 29,200

New spectral functions of the near-ground albedo derived from aircraft diffraction spectrometer observations

The airborne spectral observations of the upward and downward irradiances are revisited to investigate the dependence of the near-ground albedo as a function of wavelength in the entire solar spectrum for different surfaces (sand, water, snow) and under different conditions (clear or cloudy sky). The radiative upward and downward fluxes were determined by a diffraction spectrometer flown on a research aircraft that was performing multiple flight paths near the ground. The results obtained show that the near-ground albedo does not generally increase with increasing wavelengths for all kinds of surfaces as is widely believed today. Particularly, in the case of water surfaces it was found that the albedo in the ultraviolet region is more or less independent of the wavelength on a long-term basis. Interestingly, in the visible and near-infrared spectra the water albedo obeys an almost constant power-law relationship with wavelength. In the case of sand surfaces it was found that the sand albedo is a quadratic function of wavelength, which becomes more accurate if the ultraviolet wavelengths are neglected. Finally, it was found that the spectral dependence of snow albedo behaves similarly to that of water, i.e. both decrease from the ultraviolet to the near-infrared wavelengths by 20–50%, despite the fact that their values differ by one order of magnitude (water albedo being lower). In addition, the snow albedo vs. ultraviolet wavelength is almost constant, while in the visible near-infrared spectrum the best simulation is achieved by a second-order polynomial, as in the case of sand, but with opposite slopes