## 1 Introduction  
Continuous records of microseismic oscillations recorded by broadband seismometers at a network of stations may contain information about geodynamic processes in the Earth's interior, despite the main part of the energy of such oscillations being due to atmospheric and oceanic influences [1, 2, 3]. The conditions for the propagation of natural and man-made signals in the geological environment and its transmission properties can vary over time, including under the influence of earthquake preparation processes [4]. Statistical characteristics of microseisms can reflect changes in properties of the geological environment, so the study of their spatiotemporal structure is a promising direction in search for signs of strong earthquake preparation in seismically active regions. New opportunities for studying the properties of continuous microseismic oscillations (below \"seismic noise\") are provided by the method developed by [PERSON] [5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17]. This method implements ideas about the general patterns of complex dynamic systems' behavior when they approach a critical state associated with irreversible changes. In particular, an increase in the synchronization (coherence) of changes in the properties of such systems is considered as one of the signs of the approach to a catastrophic state [12; 18]. Synchronization effects can manifest themselves both in the behavior of natural objects and in experiments. For example, it was shown in [19] that weak mechanical periodic forcing applied to a model spring-slider system imitating the behavior of a seismogenic fault can lead to synchronization of slip events, documented as acoustic emission bursts with the frequency of a weak forcing. Strong earthquakes are associated with abrupt changes in seismicity over vast areas and can be considered as \"catastrophes\" preceded by manifestations of various precursors, including an increase in the correlation radius of random fluctuations of microseismic oscillations. A physical description of the growth mechanism of microseismic synchronization is impossible due to the complexity of geological environmental structures and a large number of external influences and processes, many of which cannot be traced during the observation period. Therefore, the use of synchronous behavior in the statistical measures of a certain set of seismic noise parameters at a network of stations makes it possible to formally solve the problem of diagnosing preparation for a strong earthquake. The possibility of the method for identifying areas of strong earthquakes in the Northwestern part of the Pacific seismic belt, North America, and the whole world with a lead time of months-a few years was demonstrated in [5; 13; 14; 16]. In particular, regular spatiotemporal changes in seismic noise parameters before the 2003 and 2011 earthquakes with \(M_{w}=8.3\) and \(9.0\) were found according to data of the Japanese F-net network. Such changes showed the evolution of the statistical structure of microseismic oscillations to white noise [8]. This paper presents the results of applying the method of [PERSON] to the data of continuous recording of seismic signals at the network of stations in the Kamchatka Peninsula to search for signs of preparation for strong earthquakes in the variations of seismic noise taking into account the specific conditions of the region such as modern volcanic activity and coastal sea disturbances. To do this, the maps of the spatial distribution of four noise statistics were created and increased values of spectral coherence in the time series of noise parameters for 2011-2021 were analyzed in comparison with major earthquakes that have occurred.