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As part of the international collaboration of several research groups from Russia, France, and Germany, 77 temporary seismic stations were installed in the summer of 2015 for one-year period to conduct a detailed study of the deep structure of the Earth's crust and upper mantle in the region of the Klyuchevskoi Volcano Group (KGV) in the Kamchatka Peninsula. One of the results of the KISS experiment (Klyuchevskoi Investigation – Seismic Structure of an extraordinary volcanic system) was the final catalog of the joint data from the temporary stations and the permanent network of the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences (KB GS RAS). The catalog comprises 2136 events, including 560 for which the permanent network catalog lacked sufficient data for correct processing. The catalog in .xlsx format and the station bulletin in .isf format are presented in the supplementary material to the paper. A comparative analysis was conducted on the joint solutions of two catalogs: one obtained solely from the data of the KB GS RAS permanent network stations and another from a denser seismic network integrated with KISS stations.

Continuous noise-based monitoring of seismic velocity changes provides insights into volcanic unrest, earthquake mechanisms and fluid injection in the subsurface. The standard monitoring approach relies on measuring traveltime changes of late coda arrivals between daily and reference noise cross-correlations, usually chosen as stacks of daily cross-correlations. The main assumption of this method is that the shape of the noise correlations does not change over time or, in other terms, that the ambient-noise sources are stationary through time. These conditions are not fulfilled when a strong episodic source of noise, such as a volcanic tremor, for example, perturbs the reconstructed Green's function. In this paper, we propose a general formulation for retrieving continuous time-series of noise-based seismic velocity changes without the requirement of any arbitrary reference cross-correlation function (CCF). Instead, we measure the changes between all possible pairs of daily cross-correlations and invert them using different smoothing parameters to obtain the final velocity change curve. We perform synthetic tests in order to establish a general framework for future applications of this technique. In particular, we study the reliability of velocity change measurements versus the stability of noise CCFs. We apply this approach to a complex data set of noise cross-correlations at Klyuchevskoy volcanic group (Kamchatka), hampered by loss of data and the presence of highly non-stationary seismic tremors. ; All the data used in this study were provided by the Kamchatka Branch of Geophysical Survey of Russian Academy of Sciences (http://www.emsd.ru). This study was supported by REPSOL CO-DOS and REPSOL CO-DOS Phase 2 projects, by the European COST action TIDES (ES1401), by the Russian Ministry of Education and Science (grant number 14.W03.31.0033), by the French projects 'Labex UnivEarth' and Université Sorbonne Paris Cité project 'VolcanoDynamics', by the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Program (grant agreement number 742335, F-IMAGE) and by a research grant from Science Foundation Ireland (SFI) under grant number 13/RC/2092 and co-funded under the European Regional Development Fund and by iCRAG industry partners. Computations were performed using the IPGP High-Performance Computing infrastructure S-CAPADE (supported by the Îlle-de-France region via the SEASAME programme, by France-Grille, and by the CNRS MASTODONS programme). ; Peer reviewed