RESUMO
The occurrence and the style of volcanic eruptions are largely controlled by the ways in which magma is stored and transported from the mantle to the surface through the crust. Nevertheless, our understanding of the deep roots of volcano-magmatic systems remains very limited. Here, we use the sources of seismovolcanic tremor to delineate the active part of the magmatic system beneath the Klyuchevskoy Volcanic Group in Kamchatka, Russia. The tremor sources are distributed in a wide spatial region over the whole range of crustal depths connecting different volcanoes of the group. The tremor activity is characterized by rapid vertical and lateral migrations explained by fast pressure transients and dynamic permeability. Our results support the conceptual model of extended and highly dynamic trans-crustal magmatic systems.
RESUMO
The neural network approach is proposed for studying very-low- and low-frequency (VLF and LF) subionospheric radio wave variations in the time vicinities of magnetic storms and earthquakes, with the purpose of recognizing anomalies of different types. We also examined the days with quiet geomagnetic conditions in the absence of seismic activity, in order to distinguish between the disturbed signals and the quiet ones. To this end, we trained the neural network (NN) on the examples of the representative database. The database included both the VLF/LF data that was measured during four-year monitoring at the station in Petropavlovsk-Kamchatsky, and the parameters of seismicity in the Kuril-Kamchatka and Japan regions. It was shown that the neural network can distinguish between the disturbed and undisturbed signals. Furthermore, the prognostic behavior of the VLF/LF variations indicative of magnetic and seismic activity has a different appearance in the time vicinity of the earthquakes and magnetic storms.
