Harmonization check of M w within the central, northern, and northwestern European earthquake catalogue (CENEC)

Large data sets covering large areas and time spans and composed of many different independent sources raise the question of the obtained degree of harmonization. The present study is an analysis of the harmonization with respect to the moment magnitude M _w within the earthquake catalogue for central, northern, and northwestern Europe (CENEC). The CENEC earthquake catalogue (Grünthal et al., J Seismol, 2009) contains parameters for over 8,000 events in the time period 1000–2004 with magnitude M _w ≥ 3.5. Only about 2% of the data used for CENEC have original M _w magnitudes derived directly from digital data. Some of the local catalogues and data files providing data give M _w, but calculated by the respective agency from other magnitude measures or intensity. About 60% of the local data give strength measures other than M _w, and these have to be transformed by us using available formulae or new regressions based on original M _w data. Although all events are thus unified to M _w magnitude, inhomogeneity in the M _w obtained from over 40 local catalogues and data files and 50 special studies is inevitable. Two different approaches have been followed to investigate the compatibility of the different M _w sets throughout CENEC. The first harmonization check is performed using M _w from moment tensor solutions from SMTS and Pondrelli et al. (Phys Earth Planet Inter 130:71–101, 2002; Phys Earth Planet Inter 164:90–112, 2007). The method to derive the SMTS is described, e.g., by Braunmiller et al. (Tectonophysics 356:5–22, 2002) and Bernardi et al. (Geophys J Int 157:703–716, 2004), and the data are available in greater extent since 1997. One check is made against the M _w given in national catalogues and another against the M _w derived by applying different empirical relations developed for CENEC. The second harmonization check concerns the vast majority of data in CENEC related to earthquakes prior to 1997 or where no moment tensor based M _w exists. In this case, an empirical relation for the M _w dependence on epicentral intensity (I ₀) and focal depth (h) was derived for 41 master events, i.e., earthquakes, located all over central Europe, with high-quality data. To include also the data lacking h, the corresponding depth-independent relation for these 41 events was also derived. These equations are compared with the different sets of data from which CENEC has been composed, and the goodness of fit is demonstrated for each set. The vast majority of the events are very well or reasonably consistent with the respective relation so that the data can be said to be harmonized with respect to M _w, but there are exceptions, which are discussed in detail.     

The lessons from the Simushir earthquakes of November 15, 2006 (M w 8.3) and January 13, 2007 (M w 8.1)

According to S.A. Fedotov’s long-term earthquake forecast, the Middle Kuril Is. has long (since 1965) been a likely location for the next M ≥ 7.7 earthquake, i.e., a seismic gap. The present study integrates seismological, geological, and geophysical data to assess the earthquake potential of the gap prior to November 15, 2006. Seismological data were used to carry out a comparative analysis of 3D seismic energy density for three zones of the Kuril region. The density for the Middle Kuril Is. turned out to be twice as small as that for the North Kuril Is. and nearly six times as small as that for the South Kurils. Various parameters of the seismic process for the Kuril region have been estimated in quantitative terms. It is shown that the rate of completely reported (M ≥ 6) earthquakes occurring down to 70 km depth in the Middle Kuril Is. is approximately three times as small as that for the entire Kuril arc. Increased heat flow was recorded there (up to 100 mW/m²). The top of the high conductivity layer is shallower (at a depth of 100 km). The trends of major faults and other seismotectonic features have been taken into account. Based on these data (prior to November 15, 2006), the previous conclusion about the low seismic activity of the Middle Kuril Is. was corroborated. Two great earthquakes occurred in the region on November 15, 2006 (M _w = 8.3) and January 13, 2007 (M _w = 8.1) with subsequent tsunami waves. The erroneous inference as to low seismic activity was related to the fact that the seismic cycle in the Middle Kuril Is. may be as long as 150–200 years. We come to the conclusion that an analysis of the level of seismic activity for the region should start with the construction of standardized recurrence curves and determining the magnitude of the maximum possible earthquake.     

The April 9, 2001 Juan Fernández Ridge (M w 6.7) Tensional Outer-Rise Earthquake and its Aftershock Sequence

On April 9, 2001 a M _w 6.7 earthquake occurred offshore of the Chilean coast close to the intersection of the subducting Juan Fernández Ridge (JFR) and the trench near 33°S. The mainshock as well as an unprecedented number of aftershocks were recorded on regional broad-band and short-period seismic networks. We obtained a regional moment tensor solution of the mainshock that indcates a tensional focal mechanism consistent with the Harvard CMT solution. Based on waveform modeling and relocation, the depth of the mainshock was found to be 10–12 km. We relocated 142 aftershocks, which are strongly clustered and restricted to 10–30 km in depth. The seismicity distribution indicates a conjugate normal fault system extending into the lithospheric mantle that correlates with ridge-parallel fractures observed by previous seismic and bathymetric surveys. In conjunction with the historic regional distribution of outer-rise and large interplate seismicity, our results indicate that, with the exception of anomalously large thrust events, preexisting fractures associated with large bathymetric features like ridges have to exist to allow the generation of outer-rise seismicity along the Chilean margin. Hence, flexural bending and time-dependent interplate earthquakes can locally affect the nucleation of outer-rise events. The occurrence of the outer-rise seismicity in the oceanic mantle suggests the existence of lithospheric scale faults which might act as conduits to hydrate the subducting slab.Robert Fromm-Rhim passed away July 31st, 2004.     

A look at global seismicity during 1999 in the longer-term time frame

An analysis and discussion of the main features and effects of the 1999global seismicity based especially on the inferred patterns of strong(M_w 7) earthquakes using NEIC/USGS data is presented.Based on the above data and their statistical features (see also Table 1)one may state that from the point of view of occurrence rate (number/yr)the 1999 global seismicity was fairly regular, but from the moment (orenergy) release standpoint it is well under the long-term average. The spacepartition was again rather typical and time distribution was quasi-Poissonian,noteworthy, the 1999 worldwide seismicity had an anomalously high deathtoll, to be discussed later. Two main new insights are brought by ouranalysis: (i) a (mega)quiescence along the whole south American segmentof circum-Pacific earthquake belt, which was inferred and rated asanomalous while it was underway and which, in retrospect, ended with thegreat (M_w = 8.4 HRV) 2001 Arequipa (Peru) event; (ii) an intriguingmonotonous rate decrease within only magnitude class 5.0 to 5.9 duringthe analyzed period (i.e., 1990–1999).     

Earthquake activity in the Aswan region,Egypt

The November 14, 1981 Aswan earthquake (M _L= 5.7), which was related to the impoundment of Lake Aswan, was followed by an extended sequence of earthquakes, and is investigated in this study. Earthquake data from June 1982 to late 1991, collected from the Aswan network, are classified into two sets on the basis of focal depth (i.e., shallow, or deeper than 10 km). It is determined that (a) shallow seismicity is characterized by swarm activity, whereas deep seismicity is characterized by a foreshock-main shock-aftershock sequence; (b) the b value is equal to 0.77 and 0.99 for the shallow and deep sequences, respectively; and (c) observations clearly indicate that the temporal variations of shallow seismic activity were associated with a high rate of water-level fluctuation in Lake Aswan; a correlation with the deeper earthquake sequence, however, is not evident. These features, as well as the tomographic characteristics of the Aswan region (Awad andMizoue, this issue), imply that the Aswan seismic activity must be regarded as consisting of two distinct earthquake groups.We also relocated the largest 500 earthquakes to determine their seismotectonic characteristics. The results reveal that the epicenters are well distributed along four fault segments, which constitute a conjugate pattern in the region. Moreover, fault-plane solutions are determined for several earthquakes selected from each segment, which, along with the 14 November 1981 main shock, demonstrate a prominent E-W compressional stress.     

2022年门源MS6.9和2016年门源MS6.4地震序列比较分析

2022年1月8日青海省海北州门源县发生M_S6.9地震,震中距离2016年1月21日门源M_S6.4地震震中约33km,两次门源地震均发生在冷龙岭断裂附近,但在震源机制、主发震断层破裂过程及地震序列余震活动等方面显著不同。针对两次门源地震序列的比较分析,对研究冷龙岭断裂及其附近区域强震序列和余震衰减特征等具有重要研究意义。通过对比分析2022年门源M_S6.9地震和2016年门源M_S6.4地震余震的时空演化特征,发现二者在震源过程和断层破裂尺度上存在明显差异,前者发震断层破裂充分,震后能量释放充分,余震丰富且震级偏高;而后者发震断层未破裂至地表,余震震级水平偏低。综合分析两次门源地震序列表现出来的差异性,认为其可能与地震发震断层的破裂过程密切相关,且同时受到区域构造环境的影响。     

Activation of seismicity in Central and South Asia after the Makran earthquakes: Possible acceleration of preparation of large seismic events in the Tien Shan region

Two zones of seismicity (ten events with M _w = 7.0–7.7) stretching from Makran and the Eastern Himalaya to the Central and EasternTien Shan, respectively, formed over 11 years after the great Makran earthquake of 1945 (M _w = 8.1). Two large earthquakes (M _w = 7.7) hit theMakran area in 2013. In addition, two zones of seismicity (M ≥ 5.0) occurred 1–2 years after theMakran earthquake in September 24, 2013, stretching in the north-northeastern and north-northwestern directions. Two large Nepal earthquakes struck the southern extremity of the “eastern” zone (April 25, 2015, M _w = 7.8 and May 12, 2015, M _w = 7.3), and the Pamir earthquake (December 7, 2015, M _w = 7.2) occurred near Sarez Lake eastw of the “western” zone. The available data indicate an increase in subhorizontal stresses in the region under study, which should accelerate the possible preparation of a series of large earthquakes, primarily in the area of the Central Tien Shan, between 70° and 79° E, where no large earthquakes (M _w ≥ 7.0) have occurred since 1992.     

Correlating Precursory Declines in Groundwater Radon with Earthquake Magnitude

Both studies at the Antung hot spring in eastern Taiwan and at the Paihe spring in southern Taiwan confirm that groundwater radon can be a consistent tracer for strain changes in the crust preceding an earthquake when observed in a low‐porosity fractured aquifer surrounded by a ductile formation. Recurrent anomalous declines in groundwater radon were observed at the Antung D1 monitoring well in eastern Taiwan prior to the five earthquakes of magnitude (M_w): 6.8, 6.1, 5.9, 5.4, and 5.0 that occurred on December 10, 2003; April 1, 2006; April 15, 2006; February 17, 2008; and July 12, 2011, respectively. For earthquakes occurring on the longitudinal valley fault in eastern Taiwan, the observed radon minima decrease as the earthquake magnitude increases. The above correlation has been proven to be useful for early warning local large earthquakes. In southern Taiwan, radon anomalous declines prior to the 2010 M_w 6.3 Jiasian, 2012 M_w 5.9 Wutai, and 2012 M_L 5.4 Kaohsiung earthquakes were also recorded at the Paihe spring. For earthquakes occurring on different faults in southern Taiwan, the correlation between the observed radon minima and the earthquake magnitude is not yet possible.     

Asperity Distribution of the 1952 Great Kamchatka Earthquake and its Relation to Future Earthquake Potential in Kamchatka

—The 1952 Kamchatka earthquake is among the largest earthquakes of this century, with an estimated magnitude of M _w = 9.0. We inverted tide gauge records from Japan, North America, the Aleutians, and Hawaii for the asperity distribution. The results show two areas of high slip. The average slip is over 3 m, giving a seismic moment estimate of 155×10²⁰Nm, or M _w = 8.8. The 20th century seismicity of the 1952 rupture zone shows a strong correlation to the asperity distribution, which suggests that the large earthquakes (M > 7) are controlled by the locations of the asperities and that future large earthquakes will also recur in the asperity regions.     

Identifying the occurrence time of an impending major earthquake: a review

The procedure through which the occurrence time of an impending major earthquake can be determined is reviewed in the light of the recent advances. This can be achieved by analyzing in natural time the seismicity in the candidate area. To apply this general procedure, we need two important elements: first, to know when we should start the analysis, i.e., set the natural time equal to zero. This is the time at which the system enters the critical stage. Second a reliable estimation of the candidate epicentral area. If geoelectrical measurements are taken and the VAN method (after the initials of the three researchers Varotsos, Alexopoulos and Nomicos) is applied, both these elements become available upon the recording of a precursory Seismic Electric Signals (SES) activity, because its initiation marks the time when the system enters the critical stage, and in addition the SES data enable the determination of the epicentral area of the impending mainshock. On the other hand, if geoelectrical data are lacking, we make use of the following two recent findings by means of natural time analysis: First, the fluctuations of the order parameter of seismicity in a large area exhibit a minimum a few months before a major earthquake almost simultaneously with the initiation of an SES activity. Second, a spatiotemporal study of this minimum unveils an estimate of the epicentral area of the impending major earthquake. Two examples are given that refer to the strongest earthquakes that occurred in Greece and Japan during the last 3 decades, i.e., the M _W6.9 earthquake in southwestern Greece on 14 February 2008 and the M _W9.0 Tohoku earthquake in Japan on 11 March 2011.     

The Study on Seismicity and Relocation of the July 3,2015 Pishan MS6.5 Earthquake

The July 3, 2015 Pishan M_S6.5 earthquake occurred in the intersection area of the Tarim block and West Kunlun block where the moderate-strong earthquakes have become active in recent years. This paper has studied the seismicity parameters of the earthquake sequences such as the b-value in the Pishan region and its vicinity. In addition, we also relocated the aftershocks of the Pishan M_S6.5 earthquake using the seismic phase report by the double-difference method. The temporal and spatial variation characteristics of the Pishan earthquake sequence in the rupture zone are analyzed. The study is of great significance in the seismic hazard assessment in this region.     

Coseismic Slip from the 6 October 2008, M w6.3 Damxung Earthquake, Tibetan Plateau, Constrained by InSAR Observations

Coseismic deformation fields of the 6 October 2008 M _w6.3 Damxung earthquake were obtained from interferometric synthetic aperture radar by using three descending and two ascending Envisat images. Significant coseismic surface deformation occurred within 20?km?×?20?km of the epicenter with a maximum displacement of ~0.3?m along the satellite line of sight. We model a linear elastic dislocation in a homogeneous half space and use a nonlinear constraint optimized algorithm to estimate the fault location, geometry and slip distribution. The results indicate a moment magnitude M _w6.3, and the earthquake is dominated by oblique normal and right-lateral slip with a maximum slip of 2.86?m at depth of 8?km. The rupture plane is about 15?km?×?14?km with strike S190°W and dip 55° to NW, located at a secondary fault of the Southeastern Piedmont of the Nyainqentanglha Mountains. Slip on normal faults in the Tibetan Plateau contributes to the rift evolution.     

Multi-Methods Combined Analysis of Future Earthquake Potential

Prior to an earthquake, natural seismicity is correlated across multiple spatial and temporal scales. Many studies have indicated that an earthquake is hard to accurately predict by a single time-dependent precursory method. In this study, we attempt to combine four earthquake prediction methods, i.e. the Pattern Informatics (PI), Load/Unload Response Ratio (LURR), State Vector (SV), and Accelerating Moment Release (AMR) to estimate future earthquake potential. The PI technique is founded on the premise that the change in the seismicity rate is a proxy for the change in the underlying stress. We first use the PI method to quantify localized changes surrounding the epicenters of large earthquakes to objectively quantify the anomalous areas (hot spots) of the upcoming events. Next, we delineate the seismic hazard regions by integrating with regional active fault zones and small earthquake activities. Then, we further evaluate the earthquake potential in the seismic hazard regions using the LURR, SV and AMR methods. Retrospective tests of this new approach on the large earthquakes (M > 6.5) which have occurred in western China over the last 3 years show that the LURR and SV time series usually climb to an anomalously high peak months to years prior to occurrence of a large earthquake. And, the asymptote time, t _c, “predicted” by the AMR method correspond to the time of the actual events. The results may suggest that the multi-methods combined approach can be a useful tool to provide stronger constraints on forecasts of the time and location of future large events.     

The 2008 Kultuk earthquake with M w = 6.3 in the south of Baikal: Spatial-temporal analysis of seismic activation

The results of investigating the data of stationary and field observations in the epicentral zone of the Kultuk earthquake of August 27, 2008 with M _w = 6.3 localized south of Baikal are presented. The seismic activation amounting to 1790 aftershocks with K _p ?? 4 (M _w ?? 0.9) affected a part of the general fault bounding the southwestern coast of the lake and shallower intrabasin structures. It was established through the cluster analysis that the main shock was located at the periphery of the cloud of the concentrated seismicity component, and three main clusters reflecting a complex character of rupture in the earthquake source were identified in the zone of aftershocks. Owing to a high accuracy of aftershock hypocenters determinations (ERZ ?? 1.2 km), the local character of the seismisity-generating zones was revealed. Based on the method of mapping seismic regime parameters, it was established that zones of reduced fractionality are recognizable in the central part of the source area; in this case, the entire periphery, except for the southeastern direction (where the main shock epicenter is located), is characterized by a high fractionality, which also points to the complex character of the rupture in the source. On the whole, the aftershock sequence under consideration showed the activation of the southwestern flank of the Southern Baikal region, which remained passive for more than one century, and demonstrated destructive features of the Earth??s crust.     

The 2010 M w 7.2 El Mayor-Cucapah Earthquake Sequence, Baja California, Mexico and Southernmost California, USA: Active Seismotectonics along the Mexican Pacific Margin

The El Mayor-Cucapah earthquake sequence started with a few foreshocks in March 2010, and a second sequence of 15 foreshocks of M?>?2 (up to M4.4) that occurred during the 24?h preceding the mainshock. The foreshocks occurred along a north?Csouth trend near the mainshock epicenter. The M _w 7.2 mainshock on April 4 exhibited complex faulting, possibly starting with a ~M6 normal faulting event, followed ~15?s later by the main event, which included simultaneous normal and right-lateral strike-slip faulting. The aftershock zone extends for 120?km from the south end of the Elsinore fault zone north of the US?CMexico border almost to the northern tip of the Gulf of California. The waveform-relocated aftershocks form two abutting clusters, each about 50?km long, as well as a 10?km north?Csouth aftershock zone just north of the epicenter of the mainshock. Even though the Baja California data are included, the magnitude of completeness and the hypocentral errors increase gradually with distance south of the international border. The spatial distribution of large aftershocks is asymmetric with five M5+ aftershocks located to the south of the mainshock, and only one M5.7 aftershock, but numerous smaller aftershocks to the north. Further, the northwest aftershock cluster exhibits complex faulting on both northwest and northeast planes. Thus, the aftershocks also express a complex pattern of stress release along strike. The overall rate of decay of the aftershocks is similar to the rate of decay of a generic California aftershock sequence. In addition, some triggered seismicity was recorded along the Elsinore and San Jacinto faults to the north, but significant northward migration of aftershocks has not occurred. The synthesis of the El Mayor-Cucapah sequence reveals transtensional regional tectonics, including the westward growth of the Mexicali Valley and the transfer of Pacific?CNorth America plate motion from the Gulf of California in the south into the southernmost San Andreas fault system to the north. We propose that the location of the 2010 El Mayor-Cucapah, as well as the 1992 Landers and 1999 Hector Mine earthquakes, may have been controlled by the bends in the plate boundary.     

Seismicity anomalies before the great earth—quake of Ms=8.1 in the Kunlun Pass and its significance to earthquake prediction

A great earthquake of M _S=8.1 took place in the west of Kunlun Pass on November 14, 2001. The epicenter is located at 36.2°N and 90.9°E. The analysis shows that some main precursory seismic patterns appear before the great earthquake, e.g., seismic gap, seismic band, increased activity, seismicity quiet and swarm activity. The evolution of the seismic patterns before the earthquake of M _S=8.1 exhibits a course very similar to that found for earthquake cases with M _S≥7. The difference is that anomalous seismicity before the earthquake of M _S=8.1 involves in the larger area coverage and higher seismic magnitude. This provides an evidence for recognizing precursor and forecasting of very large earthquake. Finally, we review the rough prediction of the great earthquake and discuss some problems related to the prediction of great earthquakes.     

Temporal and spatial distributions of precursory seismicity rate changes in the Thailand-Laos-Myanmar border region: implication for upcoming hazardous earthquakes

To study the prospective areas of upcoming strong-to-major earthquakes, i.e., M _w  ≥ 6.0, a catalog of seismicity in the vicinity of the Thailand-Laos-Myanmar border region was generated and then investigated statistically. Based on the successful investigations of previous works, the seismicity rate change (Z value) technique was applied in this study. According to the completeness earthquake dataset, eight available case studies of strong-to-major earthquakes were investigated retrospectively. After iterative tests of the characteristic parameters concerning the number of earthquakes (N) and time window (T _w ), the values of 50 and 1.2 years, respectively, were found to reveal an anomalous high Z-value peak (seismic quiescence) prior to the occurrence of six out of the eight major earthquake events studied. In addition, the location of the Z-value anomalies conformed fairly well to the epicenters of those earthquakes. Based on the investigation of correlation coefficient and the stochastic test of the Z values, the parameters used here (N = 50 events and T _w  = 1.2 years) were suitable to determine the precursory Z value and not random phenomena. The Z values of this study and the frequency-magnitude distribution b values of a previous work both highlighted the same prospective areas that might generate an upcoming major earthquake: (i) some areas in the northern part of Laos and (ii) the eastern part of Myanmar.     

The moment magnitude <Emphasis Type="Italic">M</Emphasis><Subscript>w</Subscript> and the energy magnitude <Emphasis Type="Italic">M</Emphasis><Subscript>e</Subscript>: common roots and differences

Starting from the classical empirical magnitude-energy relationships, in this article, the derivation of the modern scales for moment magnitude M _w and energy magnitude M _e is outlined and critically discussed. The formulas for M _w and M _e calculation are presented in a way that reveals, besides the contributions of the physically defined measurement parameters seismic moment M ₀ and radiated seismic energy E _S, the role of the constants in the classical Gutenberg–Richter magnitude–energy relationship. Further, it is shown that M _w and M _e are linked via the parameter Θ = log(E _S/M ₀), and the formula for M _e can be written as M _e = M _w + (Θ + 4.7)/1.5. This relationship directly links M _e with M _w via their common scaling to classical magnitudes and, at the same time, highlights the reason why M _w and M _e can significantly differ. In fact, Θ is assumed to be constant when calculating M _w. However, variations over three to four orders of magnitude in stress drop Δσ (as well as related variations in rupture velocity V _R and seismic wave radiation efficiency η _R) are responsible for the large variability of actual Θ values of earthquakes. As a result, for the same earthquake, M _e may sometimes differ by more than one magnitude unit from M _w. Such a difference is highly relevant when assessing the actual damage potential associated with a given earthquake, because it expresses rather different static and dynamic source properties. While M _w is most appropriate for estimating the earthquake size (i.e., the product of rupture area times average displacement) and thus the potential tsunami hazard posed by strong and great earthquakes in marine environs, M _e is more suitable than M _w for assessing the potential hazard of damage due to strong ground shaking, i.e., the earthquake strength. Therefore, whenever possible, these two magnitudes should be both independently determined and jointly considered. Usually, only M _w is taken as a unified magnitude in many seismological applications (ShakeMap, seismic hazard studies, etc.) since procedures to calculate it are well developed and accepted to be stable with small uncertainty. For many reasons, procedures for E _S and M _e calculation are affected by a larger uncertainty and are currently not yet available for all global earthquakes. Thus, despite the physical importance of E _S in characterizing the seismic source, the use of M _e has been limited so far to the detriment of quicker and more complete rough estimates of both earthquake size and strength and their causal relationships. Further studies are needed to improve E _S estimations in order to allow M _e to be extensively used as an important complement to M _w in common seismological practice and its applications.     

Probabilistic Assessment of Earthquake Recurrence in Northeast India and Adjoining Regions

Northeast India and adjoining regions (20°–32° N and 87°–100° E) are highly vulnerable to earthquake hazard in the Indian sub-continent, which fall under seismic zones V, IV and III in the seismic zoning map of India with magnitudes M exceeding 8, 7 and 6, respectively. It has experienced two devastating earthquakes, namely, the Shillong Plateau earthquake of June 12, 1897 (M _w 8.1) and the Assam earthquake of August 15, 1950 (M _w 8.5) that caused huge loss of lives and property in the Indian sub-continent. In the present study, the probabilities of the occurrences of earthquakes with magnitude M ≥ 7.0 during a specified interval of time has been estimated on the basis of three probabilistic models, namely, Weibull, Gamma and Lognormal, with the help of the earthquake catalogue spanning the period 1846 to 1995. The method of maximum likelihood has been used to estimate the earthquake hazard parameters. The logarithmic probability of likelihood function (ln L) is estimated and used to compare the suitability of models and it was found that the Gamma model fits best with the actual data. The sample mean interval of occurrence of such earthquakes is estimated as 7.82 years in the northeast India region and the expected mean values for Weibull, Gamma and Lognormal distributions are estimated as 7.837, 7.820 and 8.269 years, respectively. The estimated cumulative probability for an earthquake M ≥ 7.0 reaches 0.8 after about 15–16 (2010–2011) years and 0.9 after about 18–20 (2013–2015) years from the occurrence of the last earthquake (1995) in the region. The estimated conditional probability also reaches 0.8 to 0.9 after about 13–17 (2008–2012) years in the considered region for an earthquake M ≥ 7.0 when the elapsed time is zero years. However, the conditional probability reaches 0.8 to 0.9 after about 9–13 (2018–2022) years for earthquake M ≥ 7.0 when the elapsed time is 14 years (i.e. 2009).     

The European-Mediterranean Earthquake Catalogue (EMEC) for the last millennium

The catalogue by Grünthal et al. (J Seismol 13:517?C541, 2009a) of earthquakes in central, northern, and north-western Europe with M _w????3.5 (CENEC) has been expanded to cover also southern Europe and the Mediterranean area. It has also been extended in time (1000?C2006). Due to the strongly increased seismicity in the new area, the threshold for events south of the latitude 44°N has here been set at M _w????4.0, keeping the lower threshold in the northern catalogue part. This part has been updated with data from new and revised national and regional catalogues. The new Euro-Mediterranean Earthquake Catalogue (EMEC) is based on data from some 80 domestic catalogues and data files and over 100 special studies. Available original M _w and M ₀ data have been introduced. The analysis largely followed the lines of the Grünthal et al. (J Seismol 13:517?C541, 2009a) study, i.e., fake and duplicate events were identified and removed, polygons were specified within each of which one or more of the catalogues or data files have validity, and existing magnitudes and intensities were converted to M _w. Algorithms to compute M _w are based on relations provided locally, or more commonly on those derived by Grünthal et al. (J Seismol 13:517?C541, 2009a) or in the present study. The homogeneity of EMEC with respect to M _w for the different constituents was investigated and improved where feasible. EMEC contains entries of some 45,000 earthquakes. For each event, the date, time, location (including focal depth if available), intensity I ₀ (if given in the original catalogue), magnitude M _w (with uncertainty when given), and source (catalogue or special study) are presented. Besides the main EMEC catalogue, large events before year 1000 in the SE part of the investigated area and fake events, respectively, are given in separate lists.