Ionospheric Disturbance in the Near-Field Area of the Epicenter of the September 25, 2003 Hokkaido Earthquake

A method which we developed for spatio-temporal data processing is employed to yield the source coordinates of the September 25, 2003 Hokkaido earthquake (magnitude 8.3), the switch-on time, and the propagation velocity of the earthquake-induced ionospheric disturbance. Distribution of total electron content (TEC) variations obtained from the GPS sites located in the near-field area of the earthquake epicenter is used for the data analysis. Parameters calculated in this paper are in good agreement with the real location of the earthquake epicenter, the real shock time (seismic data), and the results obtained earlier for ionospheric disturbances due to strong earthquakes. __________ Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 48, No. 4, pp. 299–313, April 2005.     

On the recent seismic activity in North-Eastern Aegean Sea including the Mw5.8 earthquake on 8 January 2013

In the last week of November 2012, we announced that a strong electrotelluric disturbance, which we judged to be a Seismic Electric Signal (SES) activity, was recorded at station Assiros located in Northern Greece. This disturbance was actually followed by an M_w5.8 earthquake on 8 January 2013 in North-Eastern Aegean Sea. Here we show that, by analyzing this SES activity and employing the natural time analysis of subsequent seismicity, we estimated the epicentral location, magnitude and occurrence time which are reasonably compatible with those of the M_w5.8 event.     

Analysis of complex networks associated to seismic clusters near the Itoiz reservoir dam

On September 18, 2004, a 4.6 mbLg earthquake occurred in the western Pyrenees, with an epicenter located approximately 4 km from the Itoiz reservoir dam. We study the aftershock sequence of this earthquake and compare it with others that occurred in the same area in order to evaluate whether this might be a case of reservoir induced seismicity triggered by impounding of water. In order to do so, we first decluster the catalog by means of a link algorithm whose distance is based on the ETAS model. We then analyze the different clusters obtained in terms of their fractal dimension and the properties of the complex network formed by the individual earthquakes belonging to these clusters. We conclude that there are properties of the cluster representing the September 18, 2004 earthquake that are distinctively different from the properties of other clusters found in the same region. This could be an indicator of a different seismic source, potentially produced by the Itoiz dam impoundment.     

An examination of the correlation between earthquake, positions of solar system bodies and solid tide

After processing 204 data of historical earthquakes for M ⩾ 4.5 from 1900 to 1996 in the area centered at Beijing (39.9°N, 116.4° E; ±3°), two correlations have been suggested: One is between earthquake and the position distribution of major solar system bodies; the other is between the earthquake magnitude and the tidal force at the epicenter. A tentative is presented for future seism prediction. Because this work is at the test stage based on a statistic analysis, further test and verification are expected.     

对图像信息学(PI)算法的一个回溯性预测检验：四川芦山7.0级地震

文章针对中强地震预测的图像信息学(PI)算法,对2013年4月20日芦山MS7.0地震的预测效果进行了回溯性震例分析。结果表明,在芦山地震的震中附近存在“PI热点”。在与2008年汶川地震的PI算法预测进行比较后建议,在以后的“PI热点”计算中,也许还应把背景形变速率作为一个权重因素考虑在内。     

Continuous radon monitoring in soil gas towards earthquake precursory studies in basaltic region

The Koyna-Warna region, near the west coast of India, is well known for reservoir-triggered seismicity. The seismic activity in this region greatly increased following the construction of an artificial reservoir across the Koyna River during the 1960s. A destructive earthquake of M 6.3 occurred on December 10, 1967, and further 19 earthquakes of M>5 have been recorded during the preceding 40 years until 2007. The soil gas radon (²²²Rn) has been studied as an earthquake precursor by continuous monitoring (hourly) at two sites around the Warna reservoir. One site has a multi-sensor probe (installed at three different depths), together with a rainfall recording facility, and another probe is mounted on a hillock at Nivle. During the study period (2005–2007), a total of 11 earthquakes (including 2 aftershocks) of M 4–4.8 were recorded. Most of these events had recorded precursory radon signals. For a given earthquake, the ²²²Rn precursory signatures were recorded at one of the two sites only. Even multiple depth probes showed discordant behaviour in recording temporal Rn variation. Causes of non-concurrence in Rn recording between sites and probes, including the combined effect of site heterogeneity, focal depth, epicentral distance, earthquake magnitude, faults responsible for the earthquake, etc, are discussed.     

Influence of time and space correlations on earthquake magnitude

A crucial point in the debate on the feasibility of earthquake predictions is the dependence of an earthquake magnitude from past seismicity. Indeed, while clustering in time and space is widely accepted, much more questionable is the existence of magnitude correlations. The standard approach generally assumes that magnitudes are independent and therefore in principle unpredictable. Here we show the existence of clustering in magnitude: earthquakes occur with higher probability close in time, space, and magnitude to previous events. More precisely, the next earthquake tends to have a magnitude similar but smaller than the previous one. A dynamical scaling relation between magnitude, time, and space distances reproduces the complex pattern of magnitude, spatial, and temporal correlations observed in experimental seismic catalogs.     

Estimating the Epicenter of a Future Strong Earthquake in Southern California,Mexico, and Central America by Means of Natural Time Analysis and Earthquake Nowcasting

It has recently been shown in the Eastern Mediterranean that by combining natural time analysis of seismicity with earthquake networks based on similar activity patterns and earthquake nowcasting, an estimate of the epicenter location of a future strong earthquake can be obtained. This is based on the construction of average earthquake potential score maps. Here, we propose a method of obtaining such estimates for a highly seismically active area that includes Southern California, Mexico and part of Central America, i.e., the area N1035W80120. The study includes 28 strong earthquakes of magnitude M ≥7.0 that occurred during the time period from 1989 to 2020. The results indicate that there is a strong correlation between the epicenter of a future strong earthquake and the average earthquake potential score maps. Moreover, the method is also applied to the very recent 7 September 2021 Guerrero, Mexico, M7 earthquake as well as to the 22 September 2021 Jiquilillo, Nicaragua, M6.5 earthquake with successful results. We also show that in 28 out of the 29 strong M ≥7.0 EQs studied, their epicenters lie close to an estimated zone covering only 8.5% of the total area.     

Measurements of soil radon in South Russia for seismological application: Some results

Results of soil radon concentration measurements at the surface in Northern Caucasus (Krasnodar territory) in different geological features are shown. Measurements were made in mud volcanoes, faults, mineral deposits and landslips. The data were compared to seismicity. Before earthquakes, the changes in the concentration of radon appear as “humps” or “splashes” of various durations. Monthly, daily and hourly changes of the concentration of soil radon during the earthquakes are shown for each zone of researches. The simultaneous measurement of radon in the big area has shown the movement of the increased concentration of radon to the epicenter several days prior to the earthquake.     

Scale-invariant structure of energy fluctuations in real earthquakes

Earthquakes are obviously complex phenomena associated with complicated spatiotemporal correlations, and they are generally characterized by two power laws: the Gutenberg-Richter (GR) and the Omori-Utsu laws. However, an important challenge has been to explain two apparently contrasting features: the GR and Omori-Utsu laws are scale-invariant and unaffected by energy or time scales, whereas earthquakes occasionally exhibit a characteristic energy or time scale, such as with asperity events. In this paper, three high-quality datasets on earthquakes were used to calculate the earthquake energy fluctuations at various spatiotemporal scales, and the results reveal the correlations between seismic events regardless of their critical or characteristic features. The probability density functions (PDFs) of the fluctuations exhibit evidence of another scaling that behaves as a q-Gaussian rather than random process. The scaling behaviors are observed for scales spanning three orders of magnitude. Considering the spatial heterogeneities in a real earthquake fault, we propose an inhomogeneous Olami-Feder-Christensen (OFC) model to describe the statistical properties of real earthquakes. The numerical simulations show that the inhomogeneous OFC model shares the same statistical properties with real earthquakes.     

Analysis of the spatial distribution between successive earthquakes

Spatial distances between subsequent earthquakes in southern California exhibit scale-free statistics, with a critical exponent delta approximately 0.6, as well as finite size scaling. The statistics are independent of the threshold magnitude as long as the catalog is complete, but depend strongly on the temporal ordering of events, rather than the geometry of the spatial epicenter distribution. Nevertheless, the spatial distance and waiting time between subsequent earthquakes are uncorrelated with each other. These observations contradict the theory of aftershock zone scaling with main shock magnitude.     

The Effect of Catalogue Lead Time on Medium-Term Earthquake Forecasting with Application to New Zealand Data

‘Every Earthquake a Precursor According to Scale’ (EEPAS) is a catalogue-based model to forecast earthquakes within the coming months, years and decades, depending on magnitude. EEPAS has been shown to perform well in seismically active regions like New Zealand (NZ). It is based on the observation that seismicity increases prior to major earthquakes. This increase follows predictive scaling relations. For larger target earthquakes, the precursor time is longer and precursory seismicity may have occurred prior to the start of the catalogue. Here, we derive a formula for the completeness of precursory earthquake contributions to a target earthquake as a function of its magnitude and lead time, where the lead time is the length of time from the start of the catalogue to its time of occurrence. We develop two new versions of EEPAS and apply them to NZ data. The Fixed Lead time EEPAS (FLEEPAS) model is used to examine the effect of the lead time on forecasting, and the Fixed Lead time Compensated EEPAS (FLCEEPAS) model compensates for incompleteness of precursory earthquake contributions. FLEEPAS reveals a space-time trade-off of precursory seismicity that requires further investigation. Both models improve forecasting performance at short lead times, although the improvement is achieved in different ways.     

Investigation of seismicity after the initiation of a Seismic Electric Signal activity until the main shock

The behavior of seismicity in the area candidate to suffer a main shock is investigated after the observation of the Seismic Electric Signal activity until the impending main shock. This is based on the view that the occurrence of earthquakes is a critical phenomenon to which statistical dynamics may be applied. In the present work, analysing the time series of small earthquakes, the concept of natural time chi was used and the results revealed that the approach to criticality itself can be manifested by the probability density function (PDF) of kappa(1) calculated over an appropriate statistical ensemble. Here, kappa(1) is the variance kappa(1)(=-(2)) resulting from the power spectrum of a function defined as Phi(omega)= summation operator(k=1)(N) p(k) exp(iomegachi(k)), where p(k) is the normalized energy of the k-th small earthquake and omega the natural frequency. This PDF exhibits a maximum at kappa(1) asymptotically equal to 0.070 a few days before the main shock. Examples are presented, referring to the magnitude 6 approximately 7 class earthquakes that occurred in Greece.     

Self-organized critical earthquake model with moving boundary

A globally driven self-organized critical model of earthquakes with conservative dynamics has been studied. An open but moving boundary condition has been used so that the origin (epicenter) of every avalanche (earthquake) is at the center of the boundary. As a result, all avalanches grow in equivalent conditions and the avalanche size distribution obeys excellent finite size scaling. Though the recurrence time distribution of the time series of avalanche sizes obeys well both the scaling forms recently observed in analysis of the real data of earthquakes, it is found that the scaling function decays only exponentially in contrast to a generalized gamma distribution observed in the real data analysis. The non-conservative version of the model shows periodicity even with open boundary.     

Statistical and Criticality Analysis of the Lower Ionosphere Prior to the 30 October 2020 Samos (Greece) Earthquake (M6.9), Based on VLF Electromagnetic Propagation Data as Recorded by a New VLF/LF Receiver Installed in Athens (Greece)

In this work we present the statistical and criticality analysis of the very low frequency (VLF) sub-ionospheric propagation data recorded by a VLF/LF radio receiver which has recently been established at the University of West Attica in Athens (Greece). We investigate a very recent, strong (M6.9), and shallow earthquake (EQ) that occurred on 30 October 2020, very close to the northern coast of the island of Samos (Greece). We focus on the reception data from two VLF transmitters, located in Turkey and Israel, on the basis that the EQ’s epicenter was located within or very close to the 5th Fresnel zone, respectively, of the corresponding sub-ionospheric propagation path. Firstly, we employed in our study the conventional analyses known as the nighttime fluctuation method (NFM) and the terminator time method (TTM), aiming to reveal any statistical anomalies prior to the EQ’s occurrence. These analyses revealed statistical anomalies in the studied sub-ionospheric propagation paths within ~2 weeks and a few days before the EQ’s occurrence. Secondly, we performed criticality analysis using two well-established complex systems’ time series analysis methods—the natural time (NT) analysis method, and the method of critical fluctuations (MCF). The NT analysis method was applied to the VLF propagation quantities of the NFM, revealing criticality indications over a period of ~2 weeks prior to the Samos EQ, whereas MCF was applied to the raw receiver amplitude data, uncovering the time excerpts of the analyzed time series that present criticality which were closest before the Samos EQ. Interestingly, power-law indications were also found shortly after the EQ’s occurrence. However, it is shown that these do not correspond to criticality related to EQ preparation processes. Finally, it is noted that no other complex space-sourced or geophysical phenomenon that could disturb the lower ionosphere did occur during the studied time period or close after, corroborating the view that our results prior to the Samos EQ are likely related to this mainshock.     

Memory in the occurrence of earthquakes

We study the statistics of the recurrence times tau between earthquakes above a certain magnitude M in six (one global and five regional) earthquake catalogs. We find that the distribution of the recurrence times strongly depends on the previous recurrence time tau0, such that small and large recurrence times tend to cluster in time. This dependence on the past is reflected in both the conditional mean recurrence time and the conditional mean residual time until the next earthquake, which increase monotonically with tau0. As a consequence, the risk of encountering the next event within a certain time span after the last event depends significantly on the past, an effect that has to be taken into account in any effective earthquake prognosis.     

Scale-free statistics of time interval between successive earthquakes

The statistical property of the calm times, i.e., time intervals between successive earthquakes with arbitrary values of magnitude, is studied by analyzing the seismic time series data in California and Japan. It is found that the calm times obey the Zipf–Mandelbrot power law, exhibiting a new scale-free nature of the earthquake phenomenon. Dependence of the exponent of the power-law distribution on threshold for magnitude is examined. As threshold increases, the tail of the distribution tends to become longer, showing difficulty in statistically estimating time intervals of earthquakes.     

Variation of radon flux along active fault zones in association with earthquake occurrence

Radon flux measurements were carried out at three radon stations along an active fault zone in the Langadas basin, Northern Greece by various techniques for earthquake prediction studies. Specially made devices with alpha track-etch detectors (ATDs) were installed by using LR-115, type II, non-strippable cellulose nitrate films (integrating method of measurements). Continuous monitoring of radon gas exhaling from the ground was also performed by using silicon diode detectors, Barasol and Clipperton type, in association with various probes and sensors including simultaneously registration of the meteorological parameters, such as precipitation height (rainfall events), temperature and barometric pressure. The obtained radon data were studied in parallel with the data of seismic events, such as the magnitude, M_L of earthquakes, the epicentral distance, the hypocentral distance and the energy released during the earthquake event occurred at the fault zone during the period of measurements to find out any association between the rad on flux and the meteorological and seismological parameters. Seismic events with magnitude M_L ≥ 4.0 appeared to be preceded by large precursory signals produced a well-defined “anomaly” (peak) of radon flux prior to the event. In the results, the radon peaks in the obtained spectra appeared to be sharp and narrow. The rise time of a radon peak, that is the time period from the onset of a radon peak until the time of radon flux maximum is about a week, while the after time, that is the time interval between the time of radon flux maximum and the time of a seismic event ranges from about 3 weeks or more.     

Concurrent concentration declines in groundwater-dissolved radon,methane and ethane precursory to 2011 MW 5.0 Chimei earthquake

Radon volatilization mechanism into the gas phase was hypothesized to explain the anomalous declines in groundwater radon precursory to three major earthquakes – (1) 2003 M_W = 6.8 Chengkung, (2) 2006 M_W = 6.1 Taitung, and (3) 2008 M_W = 5.4 Antung in Taiwan. The epicenters were located 24 km, 52 km, and 13 km from the Antung radon-monitoring well D1, respectively. To verify the mechanism of in situ volatilization, we monitored groundwater-dissolved ethane in addition to radon and methane at well D1 in the Antung hot spring since November 30, 2010. The mechanism of in situ radon volatilization has been corroborated by the simultaneous concentration declines in groundwater-dissolved radon, methane, and ethane precursory to the 2011 M_W 5.0 Chimei earthquake. The epicenter was located 32 km from the Antung radon-monitoring well D1. Observations at the Antung hot spring also suggest that radon is the best-choice tracer among the groundwater-dissolved gases for strain changes in the crust preceding an earthquake. On the southern segment of the Chihshang fault, the observed radon minima decrease as the earthquake magnitude increases.     

1993年7月12日日本北海道地震次声波

1993年7月12日北京时间21点21分19秒在北京中关村次声接收阵上及时地发现并完整地记录了日本北海道地震所产生的当地次声波(包括地震纵波、横波、表面波所辐射的声波)和震中次声波。其中当地次声波分别有:周期为12s,振幅为0.8 Pa,持续3.4min;及周期为12s,振幅为0.4 Pa,持续1min和周期为30s,振幅为1.3 Pa,持续12min;震中次声波周期为137s,振幅为6.9 Pa,持续28min。它们叠加在周期为12min、幅度为10 Pa的大气异常现象的波列上。