9:30 AM - 9:45 AM
[SVC32-12] Extraction of Multimodal Surface Wave Dispersion Curves in Volcanic Area: Case Study on Mt. Ontake, Central Japan
Keywords:volcano, Mt. Ontake, geophysical exploration of crustal structure, seismic interferometry, ambient noise tomography, surface wave dispersion curves
1. Background & Objective
Ambient noise tomography (ANT) is used to image subsurface structures based on seismic interferometry, and its usefulness has been confirmed recently. It consists of the following 3 steps; (I) preprocess seismic waves and extract ambient noise, (II) calculate its cross-correlation function (CCF), and (III) extract surface wave dispersion curves from CCFs and invert it to estimate the subsurface structure. Previous studies have given reasonable processes for I and II, whereas there remain some challenges to improve inversion results in III. In particular, most previous studies of ANT set flat fields on the order of 102 km for both synthetic and real data; therefore, steep fields of a narrower scale are not sufficiently considered. In this study, we extracted multimodal surface wave dispersion curves by analyzing seismic data from Mt. Ontake, central Japan, to apply ANT to volcanic areas. Our attempts not only expand the usefulness of ANT but also contribute to understanding the exploration of subsurface structures and the behavior of surface waves in volcanic areas.
2. Method
All 43 three-component seismic stations were located within a 50 km square centered on the mountaintop. The maximum, average, and median interstation distances were 42.0, 12.7, and 11.6 km, respectively. The analyzed data term was from January 1 to December 31, 2019. Ambient noise to calculate CCFs for each station pair was extracted by preprocessing the 1-h raw data in the same way as in previous studies. The 1-h CCFs were stacked to derive the term-average CCFs, and they were rotated in horizontal coordinates to obtain the multi-component CCF among the vertical (Z), radial (R), and transverse (T) components. We applied the modified multicomponent frequency-Bessel transform (MMFJ) method to them to calculate MMFJ spectra that show the dispersion curves of the Reyleigh and Love waves. Because the MMFJ spectra diverge to positive infinity at an actual surface wave velocities of each frequency, the dispersion curves can be estimated from their local maxima.
3. Result & Discussion
In the MMFJ spectra, R0-R2 (based on the CCFs of ZZ, ZR and RZ, and RR, respectively) and L0 (based on TT) represent the dispersion data of the Rayleigh and Love waves, respectively. The pink crosses indicate the local maxima at each frequency; thus, they indicate the dispersion curves. The fundamental mode is clear in all spectra, while higher modes are unclear in some spectra. The accuracy of R0 is the best as it shows up to the second-higher mode. R0 and R2 show a clear third-higher mode at different frequencies complementarily. In R1, we also should pick the local minima because they diverge to negative infinity at the dispersive points where the pro-grade Rayleigh wave propagates; however, simply taking these points will allow contamination by second and third artifacts in the dispersion data. In R2, the resolution of the fundamental mode is high, but the dispersive points of higher modes are discrete, suggesting that they are not precise. Compared to previous studies, the resolution and continuity of L0 are low, and ambiguity noticeably emerges owing to noise above the microseism band (0.05-0.5 Hz) where the seismic ambient noise excels. These features show that the MMFJ spectra derived from the data of Mt. Ontake were accurate only in the ZZ component. Previous studies that treated more flat and vast fields did not show these features; hence, the differences in the dispersion data quality among the components are probably caused by the topography and heterogeneity of Mt. Ontake.
4. Future Plan
The simulation analysis using the synthetic data is necessary to confirm whether the dispersion curves we derived results from true structure. Synthetic data should be made considering the topography and heterogeneity of Mt. Ontake to appropriately evaluate the applicability of ANT in volcanic areas.
5. Acknowledgement
This work was supported by JSPS KAKENHI Grant Number JP19K04016. Seismic stations we used are maintained by Nagoya University, JMA, Gifu and Nagano Prefectures, and NIED.
Ambient noise tomography (ANT) is used to image subsurface structures based on seismic interferometry, and its usefulness has been confirmed recently. It consists of the following 3 steps; (I) preprocess seismic waves and extract ambient noise, (II) calculate its cross-correlation function (CCF), and (III) extract surface wave dispersion curves from CCFs and invert it to estimate the subsurface structure. Previous studies have given reasonable processes for I and II, whereas there remain some challenges to improve inversion results in III. In particular, most previous studies of ANT set flat fields on the order of 102 km for both synthetic and real data; therefore, steep fields of a narrower scale are not sufficiently considered. In this study, we extracted multimodal surface wave dispersion curves by analyzing seismic data from Mt. Ontake, central Japan, to apply ANT to volcanic areas. Our attempts not only expand the usefulness of ANT but also contribute to understanding the exploration of subsurface structures and the behavior of surface waves in volcanic areas.
2. Method
All 43 three-component seismic stations were located within a 50 km square centered on the mountaintop. The maximum, average, and median interstation distances were 42.0, 12.7, and 11.6 km, respectively. The analyzed data term was from January 1 to December 31, 2019. Ambient noise to calculate CCFs for each station pair was extracted by preprocessing the 1-h raw data in the same way as in previous studies. The 1-h CCFs were stacked to derive the term-average CCFs, and they were rotated in horizontal coordinates to obtain the multi-component CCF among the vertical (Z), radial (R), and transverse (T) components. We applied the modified multicomponent frequency-Bessel transform (MMFJ) method to them to calculate MMFJ spectra that show the dispersion curves of the Reyleigh and Love waves. Because the MMFJ spectra diverge to positive infinity at an actual surface wave velocities of each frequency, the dispersion curves can be estimated from their local maxima.
3. Result & Discussion
In the MMFJ spectra, R0-R2 (based on the CCFs of ZZ, ZR and RZ, and RR, respectively) and L0 (based on TT) represent the dispersion data of the Rayleigh and Love waves, respectively. The pink crosses indicate the local maxima at each frequency; thus, they indicate the dispersion curves. The fundamental mode is clear in all spectra, while higher modes are unclear in some spectra. The accuracy of R0 is the best as it shows up to the second-higher mode. R0 and R2 show a clear third-higher mode at different frequencies complementarily. In R1, we also should pick the local minima because they diverge to negative infinity at the dispersive points where the pro-grade Rayleigh wave propagates; however, simply taking these points will allow contamination by second and third artifacts in the dispersion data. In R2, the resolution of the fundamental mode is high, but the dispersive points of higher modes are discrete, suggesting that they are not precise. Compared to previous studies, the resolution and continuity of L0 are low, and ambiguity noticeably emerges owing to noise above the microseism band (0.05-0.5 Hz) where the seismic ambient noise excels. These features show that the MMFJ spectra derived from the data of Mt. Ontake were accurate only in the ZZ component. Previous studies that treated more flat and vast fields did not show these features; hence, the differences in the dispersion data quality among the components are probably caused by the topography and heterogeneity of Mt. Ontake.
4. Future Plan
The simulation analysis using the synthetic data is necessary to confirm whether the dispersion curves we derived results from true structure. Synthetic data should be made considering the topography and heterogeneity of Mt. Ontake to appropriately evaluate the applicability of ANT in volcanic areas.
5. Acknowledgement
This work was supported by JSPS KAKENHI Grant Number JP19K04016. Seismic stations we used are maintained by Nagoya University, JMA, Gifu and Nagano Prefectures, and NIED.