The article provides analysis of macroseismic descriptions from historical records of the strongest earthquakes in Kamchatka region in 1737. Results of the analysis were compared with data from parametric lines in «The New Catalogue of strong earthquakes in the USSR from ancient times to 1975» and «Seismic zoning in the USSR, 1968». The article contains updates on number of earthquakes in 1737 and provides estimations of their locations and magnitudes. Only two strongest events occurred in 1737: the first is dated 1737.10.17 and the second – 1737.11.04.

The data from the seismic networks of the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences are used for calculating the cross correlations of seismic noise for the stationary digital stations over 2013 and for radio telemetric stations (RTS) in the region of the Klyuchevskoy volcano over the period from January 1, 2009 to May 31, 2013. Four hundred and two correlations overall are calculated. The fundamental-mode group velocities of the Rayleigh waves are calculated in the periods ranging from 5 to 50 s. The calculations for the region of the Klyuchevskaya group of volcanoes are based on the RTS data and cover the periods from 2 to 8 s. The two-dimensional (2D) maps of group velocity distributions in different periods are constructed with the use of the algorithm of surface wave tomography (Barmin, 2001). The velocity sections for the selected Kamchatka regions are reconstructed by the dispersion curve inversion technique (Mordret, 2014). For each region, the structure of the Earth's crust and upper mantle down to a depth of 50 km was obtained.

This is the second part of an report of Chebrov et al. on notable events in Kamchatka in 2013 for the Summary of the Bulletin of the International Seismological Centre including the largest deep-focus Sea of Okhotsk earthquake from 24 May 2013 with a magnitude of Mw=8.3.

This is the first part of an report of Chebrov et al. on notable events in Kamchatka in 2013 for the Summary of the Bulletin of the International Seismological Centre including the February 28, 2013, Mw 6.8 South Kamchatka earthquake.

We present the results of analyzing the response of the Schumann-resonance frequencies to the Xray solar flares. A special technique, by which a sharp variation that is present in all the resonant modes, but is hidden by regular variations combined with stochastic fluctuations is singled out using the weighted average frequency, has been developed. On the basis of comparison of the response shape and the flare intensity, the parameters of the statistical relationship between the frequency variations and the X-ray radiation intensity were analyzed and determined for the nonlinear regression model. It has been shown that an increase in the resonant frequency is proportional on the average to the logarithm of the X-ray radiation intensity to the power of 1.7. The magnitude of changes in the cavity frequency is related with the corresponding changes in the characteristic “magnetic” height of the conductivity profile of the lower ionosphere and compared with the results of the independent analysis performed by measuring VLF radio signals.

We present a new 3D model of P and S wave velocities and Vp/Vs ratio to 20km depth beneath the active Klyuchevskoy and Bezymianny volcanoes (Kamchatka, Russia). In this study, we use travel time data from local seismicity recorded by temporary stations of the PIRE experiment from October 24 to December 15, 2009 and permanent stations operated by the Kamchatkan Branch of Geophysical Survey (KBGS). The calculations were performed using the LOTOS code (Koulakov, 2009). The resolution limitations were explored using a series of synthetic tests with checkerboard patterns in the horizontal and vertical sections. At shallow depths, the resulting Vp and Vs anomalies tend to alternate on opposite sides of the lineation connecting the most active volcanic centers of the Klyuchevskoy Volcanic Group (KVG). This prominent lineation suggests the presence of a large fault zone passing throughout the KVG, consistent with regional tectonics. We suggest that this fault zone weakens the crust creating a natural pathway for magmas to reach the upper crust. Beneath Bezymianny volcano we observe a shallow anomaly of high Vp/Vs ratio extending to 5–6km depth. Beneath Klyuchevskoy another high Vp/Vs anomaly is observed, at deeper depths of 7 and 15km. These findings are consistent with the regional-scale model of Koulakov et al. (2013a) and provide some explanation for how very different eruption styles can be maintained at two volcanoes in close proximity over numerous eruption cycles.

This study presents a 3D model of the P and S seismic velocities above the Kamchatkan slab obtained as a result of tomographic inversion of arrival times of body waves from deep seismicity in the subduction zone. Various tests performed have shown limitations of the spatial resolution of the model and provided arguments for the reliability of the major structures used in the interpretation. In the uppermost layer down to 20 km depth, the model reveals strong low-velocity anomalies coinciding with Holocene volcanoes of the Klyuchevskoy group and Kizimen. In the seismogenic zone at depths from 80 to 150 km, we observe a low-velocity anomaly, which probably reflects the presence of the relatively thick oceanic crust sinking together with the subducting slab. This anomaly may also represent a zone of phase transitions, melting, and release of fluids from the slab. In the cross sections, we observe vertical and inclined low-velocity anomalies connecting the slab with the volcanic groups that probably represent the paths of ascending fluids and melts, which feed the volcanoes. In the case of Kizimen, we observe a single conduit connecting the volcano with the slab transformation area at 100 km depth. Beneath the Klyuchevskoy group, we identify several linear inclined patterns having different dipping angles. This may show that the volcanoes of the group are fed from different segments of the slab and might be one of the reasons for the diversity of lava compositions in the volcanoes of the Klyuchevskoy group.

In this paper, we suggest a technique for forecasting seismic events based on the very low and low frequency (VLF and LF) signals in the 10 to 50 Hz band using the neural network approach, specifically, the error back-propagation method (EBPM). In this method, the solution of the problem has two main stages: training and recognition (forecasting). The training set is constructed from the combined data, including the amplitudes and phases of the VLF/LF signals measured in the monitoring of the Kuril-Kamchatka region and the corresponding parameters of regional seismicity. Training the neural network establishes the internal relationship between the characteristic changes in the VLF/LF signals a few days before a seismic event and the corresponding level of seismicity. The trained neural network is then applied in a prognostic mode for automated detection of the anomalous changes in the signal which are associated with seismic activity exceeding the assumed threshold level. By the example of several time intervals in 2004, 2005, 2006, and 2007, we demonstrate the efficiency of the neural network approach in the short-term forecasting of earthquakes with magnitudes starting from M ≥ 5.5 from the nighttime variations in the amplitudes and phases of the LF signals on one radio path. We also discuss the results of the simultaneous analysis of the VLF/LF data measured on two partially overlapping paths aimed at revealing the correlations between the nighttime variations in the amplitude of the signal and seismic activity.

off a coast, the resulting ground motion can soon be followed by the of tsunami waves. This interrelationship can be useful for issuing tsunami alerts. This study at detecting correlative relationships between the intensity (runup) of a tsunami at a site along the coast and ground motion parameters at the same site due to the earthquake that produced the tsunami. Our estimates were derived by combining historical and instrumental data for eight sites along the Pacific coast of Japan

The january 30th, 2016 earthquake with К s = 15.7, Mw = 7.2, I = 6 in the Zhupanovsky region (Kamchatka)

When a large earthquake occurs off a coast, the resulting ground motion can soon be followed by the arrival of tsunami waves. This interrelationship can be useful for issuing tsunami alerts. This study aims at detecting correlative relationships between the intensity (runup) of a tsunami at a site along the coast and ground motion parameters at the same site due to the earthquake that produced the tsunami. Our estimates were derived by combining historical and instrumental data for eight sites along the Pacific coast of Japan. Our regression analysis of collected and systematized data used the tobit model, which is able to incorporate all tsunami data, including those below the tsunami-detection threshold. We show that if such tsunamis are neglected by the standard regression model, the result is to overestimate the height of predicted tsunamis. Analysis of the regression results shows that when a tsunami-generating earthquake has occurred a tsunami with runup that is equal to or greater than 50 cm should be expected if peak ground motion velocities greater than 7 cm/s have been recorded at the same site, with the probability of the failure to predict being 16%.