Results of the ambient noise-based seismic velocity changes analysis of the seismic data recorded around Mutnovsky volcano in 2023-2024

This file contains the results of the ambient noise-based analysis of seismic velocity changes at Mutnovsky Volcano (Kamchatka) in 2024 presented in:Berezhnev Y., Belovezhets N., Abramenkov S., Abkadyrov I., Drobchik A., Chebrov D. and Koulakov I. (2026). Capturing pressurization preceding the hydrothermal explosions near Mutnovsky volcano (Kamchatka) via noise-based velocity changes observations. Submitted to Seismica. The dataset includes the following directories & files: CCF: Mutnovsky_CCF_2023_2024_1_3s.h5: Raw daily cross-correlation functions stored in ASDF-format. CSV_files_input: Meteorological_data.xlsx: Temperature data from the satelite observation. Rayleigh_sens_kernel.csv: Computed Rayleigh wave sensitivity kernels. Smoothed_temp.csv: Smoothed temperature data. CSV_files_output: Seismic velocity changes curves before and after detrending and its errors; velocity changes curves associated with Mutnovsky and its errors; mean curves and its errors; and results of the thermomechanical modeling (tempreture at the characteristic depths, trends of the modeled and observed velocity changes). raw_curves_dvv.csv raw_curves_err.csv detrend_curves_dvv.csv detrend_curves_err.csv volcanic_curves_dvv.csv volcanic_curves_err.csv detrend_mean_curve.csv volcanic_mean_curve.csv temp_at_characteristic_depth.csv trend_curves_dvv.csv Scripts: 1_denoise_svd.py: SVD-WF filtering of raw CCFs. 2_mwcs_dvv_single_component.py: MWCS measurements of traveltime delays and velocity changes of single CCF components. 3_mwcs_joint_component.py: MWCS measurements of velocity changes of all CCF components. 4_inverse_dvv_join_comp.py: MCMC inversion of joint component velocity changes estimations. 4_inverse_dvv_single_component.py: MCMC inversion of single component velocity changes estimations (optional for comparison). 5_dvv_curve_to_csv.py: Restore MCMC results (mean and std) to CSV-files. 6_compute_tempreature_profiles_for_trend.py: Thermomechanical modeling. 7_estimate_season_trend.py: Trend estimation from the thermomechanical modeling results. 8_detrend_dvv_curves.py: Detrending the velocity changes curves. 9_compute_dvv_spatial_sens_kernels.py: Computation of coda-wave sensitivity kernels. 10_dvv_spatial_inversion.py: Spatial location of the observed velocity changes. 11_model_dvv_source_depth_vs_time.py: Mechanical modeling as uplifting vertically pressure source. 12_build_2d_dvv_model.py: Mechanical modeling with arbitrary positions and checkerboard tests. utils.py Mutnovsky_topo.tif: Contains the digital elevation model of the study area.