Imaging New Zealand's Crustal Structure Using Ambient Seismic Noise Recordings from Permanent and Temporary Instruments

<p>We use ambient seismic noise to image the crust and uppermost mantle, and to determine the spatiotemporal characteristics of the noise field itself, and examine the way in which those characteristics may influence imaging results. Surface wave information extracted from ambient seismic noise using cross-correlation methods significantly enhances our knowledge of the crustal and uppermost mantle shear-velocity structure of New Zealand. We assemble a large dataset of three-component broadband continuous seismic data from temporary and permanent seismic stations, increasing the achievable resolution of surface wave velocity maps in comparison to a previous study. Three-component data enables us to examine both Rayleigh and Love waves using noise cross-correlation functions. Employing a Monte Carlo inversion method, we invert Rayleigh and Love wave phase and group velocity dispersion curves separately for spatially averaged isotropic shear velocity models beneath the Northland Peninsula. The results yield first-order radial anisotropy estimates of 2% in the upper crust and up to 15% in the lower crust, and estimates of Moho depth and uppermost mantle velocity compatible with previous studies. We also construct a high-resolution, pseudo-3D image of the shear-velocity distribution in the crust and uppermost mantle beneath the central North Island using Rayleigh and Love waves. We document, for the first time, the lateral extent of low shear-velocity zones in the upper and mid-crust beneath the highly active Taupo Volcanic Zone, which have been reported previously based on spatially confined 1D shear-velocity profiles. Attributing these low shear-velocities to the presence of partial melt, we use an empirical relation to estimate an average percentage of partial melt of < 4:2% in the upper and middle crust. Analysis of the ambient seismic noise field in the North Island using plane wave beamforming and slant stacking indicates that higher mode Rayleigh waves can be detected, in addition to the fundamental mode. The azimuthal distributions of seismic noise sources inferred from beamforming are compatible with high near-coastal ocean wave heights in the period band of the secondary microseism (~7 s). Averaged over 130 days, the distribution of seismic noise sources is azimuthally homogeneous, indicating that the seismic noise field is well-suited to noise cross-correlation studies. This is underpinned by the good agreement of our results with those from previous studies. The effective homogeneity of the seismic noise field and the large dataset of noise cross-correlation functions we here compiled, provide the cornerstone for future studies of ambient seismic noise and crustal shear velocity structure in New Zealand.</p>

Imaging New Zealand's Crustal Structure Using Ambient Seismic Noise Recordings from Permanent and Temporary Instruments

<p>We use ambient seismic noise to image the crust and uppermost mantle, and to determine the spatiotemporal characteristics of the noise field itself, and examine the way in which those characteristics may influence imaging results. Surface wave information extracted from ambient seismic noise using cross-correlation methods significantly enhances our knowledge of the crustal and uppermost mantle shear-velocity structure of New Zealand. We assemble a large dataset of three-component broadband continuous seismic data from temporary and permanent seismic stations, increasing the achievable resolution of surface wave velocity maps in comparison to a previous study. Three-component data enables us to examine both Rayleigh and Love waves using noise cross-correlation functions. Employing a Monte Carlo inversion method, we invert Rayleigh and Love wave phase and group velocity dispersion curves separately for spatially averaged isotropic shear velocity models beneath the Northland Peninsula. The results yield first-order radial anisotropy estimates of 2% in the upper crust and up to 15% in the lower crust, and estimates of Moho depth and uppermost mantle velocity compatible with previous studies. We also construct a high-resolution, pseudo-3D image of the shear-velocity distribution in the crust and uppermost mantle beneath the central North Island using Rayleigh and Love waves. We document, for the first time, the lateral extent of low shear-velocity zones in the upper and mid-crust beneath the highly active Taupo Volcanic Zone, which have been reported previously based on spatially confined 1D shear-velocity profiles. Attributing these low shear-velocities to the presence of partial melt, we use an empirical relation to estimate an average percentage of partial melt of < 4:2% in the upper and middle crust. Analysis of the ambient seismic noise field in the North Island using plane wave beamforming and slant stacking indicates that higher mode Rayleigh waves can be detected, in addition to the fundamental mode. The azimuthal distributions of seismic noise sources inferred from beamforming are compatible with high near-coastal ocean wave heights in the period band of the secondary microseism (~7 s). Averaged over 130 days, the distribution of seismic noise sources is azimuthally homogeneous, indicating that the seismic noise field is well-suited to noise cross-correlation studies. This is underpinned by the good agreement of our results with those from previous studies. The effective homogeneity of the seismic noise field and the large dataset of noise cross-correlation functions we here compiled, provide the cornerstone for future studies of ambient seismic noise and crustal shear velocity structure in New Zealand.</p>

CC-FJpy: A Python Package for Extracting Overtone Surface-Wave Dispersion from Seismic Ambient-Noise Cross Correlation

In the past two decades, seismic ambient-noise cross correlation (CC) has been one of the most important technologies in seismology. Usually, only the fundamental-mode surface-wave dispersion was extracted from the ambient noise. Recently, with the frequency–Bessel transform (F-J) method, overtone dispersion can also be extracted from the ambient noise and it adds significant value in inversion. This method has also been verified to be effective for array seismic records of earthquake events. In this article, we describe our algorithm and a Python package called CC-FJpy. For the F-J method, we use the Nvidia’s graphics processing unit to accelerate the computation, which can achieve a 100-fold computational efficiency. We have encapsulated our experiences and technologies into CC-FJpy and tested the CC-FJpy by ambient-noise and earthquake data to ensure its speed and ease of use. Our open-source package CC-FJpy can benefit the development of surface-wave studies using ambient noise and make it easier to start with high-mode surface waves.

A variety of surface waves in ocean-bottom DAS records

&lt;p&gt;Distributed acoustic sensing (DAS) can transform existing telecommunication fiber-optic cables into arrays of thousands of sensors, enabling meter-scale recordings over tens of kilometers. Recently, DAS has demonstrated its utility for many seismological applications onshore. However, the use of offshore cables for seismic exploration and monitoring is still in its infancy.&lt;br&gt;In this work, we introduce some new results and observations obtained from a fiber-optic cable offshore the coast of Sanriku, Japan. In particular, we focus on surface wave retrieved from various signals and show that ocean-bottom DAS can be used to extract dispersion curves (DC) over a wide range of frequencies. We show that multi-mode DC can be easily extracted from ambient seismo-acoustic noise cross-correlation functions or F-K analysis. Moderate magnitude earthquakes also contain multiple surface-wave packets that are buried within their coda. Fully-coupled 3-D numerical simulations suggest that these low-amplitude signals originate from the continuous reverberations of the acoustic waves in the ocean layer.&amp;#160;&lt;/p&gt;

Passive estimation of scattering and intrinsic absorption parameters at 18 active volcanoes in Japan using envelopes of seismic ambient noise cross-correlation functions

&lt;p&gt;&amp;#160; &amp;#160; Estimating seismic scattering and intrinsic absorption parameters, which are measures of medium heterogeneity, is important for understanding the complex structure in shallow regions of volcanoes. In recent years, seismic ambient noise cross-correlation functions (CCFs) have been used instead of records of natural earthquakes or active seismic experiments to estimate those parameters (e.g., Hirose et al., 2019; Hirose et al., 2020; van Dinther et al., 2020). This passive approach possibly allows us to estimate scattering and intrinsic absorption parameters in previously unmeasured regions and frequency bands. In this study, we apply the passive estimation method proposed by Hirose et al. (2019) to 18 active volcanoes in Japan and measure those parameters of Rayleigh waves.&amp;#160;We used three-component seismic ambient noise data in the frequency bands of 0.5-1 Hz, 1-2 Hz, and 2-4 Hz at seismic stations of NIED, JMA, HSRI, and MFRI. Before computing CCFs, the temporal flattening technique (Weaver, 2011) was applied to ambient noise data for reducing the effect of temporal fluctuations in noise levels with retaining relative amplitudes among the stations. Daily CCFs of three components (ZZ, ZR, ZT) were computed by stacking 10-minutes-CCFs. We stacked daily CCFs over 1 year and computed mean squared envelopes by smoothing squared amplitude with 4 s (0.5-1 Hz), 2 s (1-2 Hz), or 1 s (2-4 Hz) long time windows. Scattering and intrinsic absorption parameters were estimated by modeling the space-time distributions of energy densities calculated from CCFs with 2D radiative transfer theory.&amp;#160;Best-fit values of scattering mean free path at the 18 active volcanoes range between 1.0-4.6 km at 0.5-1Hz band, 0.7-2.9 km at 1-2 Hz band, and 0.9-2.9 km at 2-4 Hz band, respectively. These values are 2 orders of magnitude shorter than those in non-volcanic regions (e.g., Sato et al., 2012). Those of intrinsic absorption parameter range between 0.05-0.26 s&lt;sup&gt;-1&lt;/sup&gt; at the 0.5-1 Hz band, 0.06-0.24 s&lt;sup&gt;-1&lt;/sup&gt; at the 1-2 Hz band, and 0.06-0.32 s&lt;sup&gt;-1 &lt;/sup&gt;at the 2-4 Hz band, respectively. They are at most one order of magnitude larger than those in the non-volcanic regions. Especially strong intrinsic attenuations are estimated at volcanic islands. Water-bearing layers at a depth of several hundred meters below these islands may cause such strong intrinsic attenuations. The frequency dependence of scattering attenuations is also strong at these volcanic islands, suggesting non-uniform structures that largely fluctuate along depths.&amp;#160;The results of this study suggest that the passive estimation method of scattering and intrinsic absorption parameters proposed by Hirose et al. (2019) is applicable to various volcanoes. Comparing estimated values of these parameters at various volcanoes will improve our understanding of complex structure at the shallow regions of volcanoes. Moreover, the parameters estimated in this study will boost locating spatial distributions of seismic velocity and/or scattering property changes associated with volcanic activities at the 18 volcanoes.&lt;/p&gt;&lt;p&gt;Acknowledgments: We used seismograms recorded by Japan Meteorological Agency (JMA), Hot Springs Research Institute (HSRI) of Kanagawa Prefecture, and Mount Fuji Research Institute (MFRI), Yamanashi Prefectural Government.&lt;/p&gt;