Reverberations, coda waves and ambient noise: Correlations at the global scale and retrieval of the deep phases
Introduction
From the regional to the global scale, ambient seismic noise primarily refers to the wavefield that is continuously produced by the interactions of the fluid envelopes, as mainly through ocean waves, and the solid Earth. The source mechanisms of these interactions are frequency dependent. Short-period noise (4 s to 30 s) is dominated by the two microseism peaks (e.g., Longuet-Higgins, 1950, Ardhuin et al., 2011). At longer periods (above 30 s), other mechanisms take place, which are also known as Earth hum (Kedar and Webb, 2005), such as the proposed shear-wave generation by infragravity waves (Fukao et al., 2010). Here the term “noise” is defined through its difference from the earthquake records. The duration of an earthquake record is defined with respect to a particular signal-to-noise ratio (SNR) threshold, and it varies with frequency for a given event magnitude. Furthermore, depending on the frequency, the scattering strength governs the ratio between the randomly scattered waves and the ballistic waves that reverberate between the main boundaries (i.e., the Earth surface, the core–mantle boundary).
It has been demonstrated that the elastic response between two stations can be evaluated by correlation of the records of scattered waves (Campillo and Paul, 2003) or long ambient noise records (Shapiro and Campillo, 2004). As expected from the theoretical Green's function between two points at the free surface, the correlations of continuous records are dominated by surface waves. The application of this approach has led to numerous examples of surface-wave imaging (e.g. Shapiro et al., 2005, Sabra et al., 2005a, Ritzwoller et al., 2011). The extension of the approach to body waves is indeed appealing, although the level of the remaining random fluctuations in the correlations makes the identification and exploitation of weak signals difficult. Furthermore, the sources of ambient noise are likely located at the surface, which results in a dominance of surface waves in the noise records. However, teleseismic body-waves have been observed in noise records (e.g. Vinnik, 1973, Gerstoft et al., 2008, Landès et al., 2010). The search for body waves in the correlations has been successful in the last few years, which started with the crustal phases (Zhan et al., 2010, Ruigrok et al., 2011, Poli et al., 2012a). Then, deep vertical reflections were detected from the mantle transition zone (Poli et al., 2012b) and from the core (Lin et al., 2013), with data from regional arrays. The complete teleseismic section was reconstructed by cross-correlation using a worldwide combination of arrays at short to long periods (5 s to 100 s; Boué et al., 2013) and at long to very long periods (30 s to 300 s; Nishida, 2013). These last studies demonstrated the feasibility of ambient noise body-wave imaging. Lin and Tsai (2013) also discussed core-phase retrievals using antipodal station pairs.
Different processing has been used in all of these studies, and especially regarding the removal of transient signals. Nishida (2013) applied the most rigorous processing, using the Global Centroid Moment Tensor catalog (Ekström et al., 2012) to systematically remove long time windows corresponding to earthquakes and the following few days, the number of which depended on the event magnitude (Nishida and Kobayashi, 1999). Lin et al. (2013) and Boué et al. (2013) used less restrictive criteria. At the global scale, both Nishida (2013) and Boué et al. (2013) observed mantle body waves but obtained different results for the amplitudes of the core phases, which are weaker, and were more realistic in the correlation computed by Nishida (2013). Note that large-amplitude core phases were also reported by Lin et al. (2013).
Boué et al. (2013) questioned the relevance of these high-amplitude phases, and suggested that they show non-physical features. By non-physical, we mean here that these features do not appear in the natural Green's function. For example, the phase in the correlation corresponding to ScS is observed at short distances with strong amplitudes for the vertical component, which leads to an obvious problem of polarization. The presence of spurious arrivals in the correlation section challenges the applicability of noise imaging to body-wave problems in the deep Earth. We address this problem here, by analyzing the conditions under which reliable information can be extracted from noise correlations.
On the other hand, Lin et al. (2013) observed a strong correlation between the phases that reach the deepest parts of the Earth (ScS, ) and the seismicity. They suggested that earthquakes mainly excite these body waves. Finally the observations of Lin et al. (2013) and Boué et al. (2013) included spurious phases that are not in the Earth response, or at least, have different relative amplitudes. The problem of spurious arrivals due to multiples was discussed on a smaller scale by Snieder et al. (2006). Concerning wave propagation at the global scale, Ruigrok et al. (2008) discussed the imperfect reconstruction of the Green's function from surface source records, which reveals the presence of spurious arrivals (ghost events). They derived an elastodynamic relation from the representation theorem showing that knowledge of the responses of the medium with and without the effects of the free surface is required to retrieve the exact Green's function. They verified this theoretical statement numerically with acoustic simulations.
By investigating the temporal evolution of the reconstructed Green's function after large seismic events, it is shown in the present study that the processing used can explain these observations at long periods. The structure of this report is the following. First, the dataset used and the processing applied are shown. Then we compare the quality of the reconstruction of some of the phases with the seismicity and the microseism excitation over a whole year. We present a synthetic example of the reconstruction of the partial Green's functions using a simulated long time reverberated coda wavefield to explain the characteristics of spurious arrivals. Finally, the study focuses on the particular propagation geometry between Finland and Japan.
Section snippets
Data and processing
In this study, one year was selected (2008) for the vertical-component records from a set of 420 stations distributed worldwide (Fig. 1). The BH channels are used after removal of the instrumental response, and decimation to a 5-Hz sampling frequency. Note that some of these stations are not available during the whole of the year period. All of the networks involved are detailed in Appendix A. The continuous records were processed similarly to Boué et al. (2013), which includes spectral
Contributions to correlations
We construct daily global sections that are used to evaluate the temporal evolution of the contributions of the daily correlations to the reconstructed Green's function. The daily contributions are quantified by computing the coherence between the daily and yearly reconstructions in specific time–distance domains. We selected six different time–space domains that correspond to different phases (Fig. 2b, colored boxes), and processed the image correlation for the 366 days of the year. This
Long-period processing
Using the long-period band, the coherence is presented in Fig. 3d, where we define high-coherence days (HCDs) by selecting the days with high seismic activity that are also associated with high coherence for each phase. In practice, we selected days with a coherence >0.2 and with a corresponding local maximum in the cumulative seismic moment function. For the mantle P-waves and S-waves, this results in selecting a group of days that correspond to the high-amplitude peaks in February and March.
A specific geometry: the FNET–LAPNET dataset
The FNET (Japan) and LAPNET (Finland) arrays were selected (Fig. 5, blue triangles), as they are both dense (ca. 40 stations) and with relatively small apertures compare to their relative distance (ca. 63°). We first repeat the processing of the selection of HCDs and LCDs for this selected dataset. The comparisons between correlations stacked for the whole year for the HCDs and the LCDs are shown in Fig. 6. Specifically, we focus on S, SS and waves at long period (Fig. 6a–c), and on the
Conclusions
Nishida (2013) and Boué et al. (2013) showed that the global scale propagation of body waves can be retrieved by cross-correlation of continuous records. The conditions of the reconstruction of the deep body phases are different for the period band considered here. Two elements are to be considered: the nature of the excitation, and the part of the scattering associated to wave propagation.
The relation between seismicity and deep phase reconstructions at long period (25–100 s) is illustrated
Acknowledgments
This study was supported by the European Research Council through the advanced grant Whisper 227507. All of the data used in this study were obtained through the IRIS, NIED and RESIF data centers. We used data from numerous seismic networks, and we thank all of the dedicated seismologists and technical staff who run these networks for making their seismic data available. Finally the authors thank Kees Wapenaar and an anonymous reviewer for their careful review and constructive comments that
References (34)
- et al.
Preliminary reference earth model
Phys. Earth Planet. Inter.
(1981) - et al.
The global CMT project 2004–2010: Centroid-moment tensors for 13,017 earthquakes
Phys. Earth Planet. Inter.
(2012) - et al.
Ambient noise tomography with a large seismic array
C. R. Géosci.
(2011) - et al.
Extraction of p-wave reflections from microseisms
C. R. Géosci.
(2011) - et al.
Ocean wave sources of seismic noise
J. Geophys. Res., Oceans
(2011) - et al.
Teleseismic correlations of ambient seismic noise for deep global imaging of the earth
Geophys. J. Int.
(2013) - et al.
Long-range correlations in the diffuse seismic coda
Science
(2003) - et al.
Estimation of the effect of nonisotropically distributed energy on the apparent arrival time in correlations
Geophysics
(2010) - et al.
Seafloor topography, ocean infragravity waves, and background love and Rayleigh waves
J. Geophys. Res. Solid Earth
(2010) - et al.
Passive sensor imaging using cross correlations of noisy signals in a scattering medium
SIAM J. Imaging Sci.
(2009)
Correlation-based virtual source imaging in strongly scattering random media
Inverse Probl.
Global p, pp, and pkp wave microseisms observed from distant storms
Geophys. Res. Lett.
Global oceanic microseism sources as seen by seismic arrays and predicted by wave action models
Geochem. Geophys. Geosyst.
The ocean's seismic hum
Science
Origin of deep ocean microseisms by using teleseismic body waves
J. Geophys. Res. Solid Earth
Fluctuations of correlations and Green's function reconstruction: Role of scattering
J. Appl. Phys.
Seismic interferometry with antipodal station pairs
Geophys. Res. Lett.
Cited by (71)
CCMOC: A new view of the Earth's outer core through the global coda correlation wavefield
2023, Physics of the Earth and Planetary InteriorsCitation Excerpt :An obvious significant advantage over previous approaches was that a new class of studies could be performed without earthquakes, relying merely on a constant ground motion due to the interaction among solid Earth, oceans, and atmosphere. Like in the ambient noise methods, a 2-D cross-correlation stack organized in inter-receiver distance bins can be obtained using the earthquake late coda (e.g., Boué et al., 2014; Phạm et al., 2018). This 2D representation of cross-correlation as a function of inter-receiver distance is a global correlogram (for a recent review, see Tkalčić et al., 2020).
Insights into the dynamics of the 2010 Eyjafjallajökull eruption using seismic interferometry and network covariance matrix analyses
2022, Earth and Planetary Science LettersCitation Excerpt :First, the CCFs computed for different station pairs show coherent arrivals at short lag-times, i.e. with apparent velocities greater than 4 km/s (Fig. 4) consistent with body waves. Other authors have shown the interferences of teleseismic arrivals close to zero lag-time (e.g. Boué et al., 2014). Second, direct wave arrivals also appear in the acausal part of the CCFs for stations located at different distances along the same radial line from the volcano (e.g., at the beginning of April in Fig. 4).
Teleseismic body waves extracted from ambient noise cross correlation between F-net and ChinArray phase II
2022, Earthquake Research AdvancesThe Earth's coda correlation wavefield: Rise of the new paradigm and recent advances
2020, Earth-Science ReviewsCitation Excerpt :It has become a usual practice to form stacks of cross-correlation functions with inter-receiver distance (correlograms) of both the ambient noise and the seismic-event coda wavefields (Fig. 2a). Apart from the retrieval of surface waves, many features that resemble body-wave phases in the direct wavefield were observed in those stacks for both regional (e.g., Poli et al., 2012a, 2012b; Zhan et al., 2010) and global scales (Boué et al., 2014, e.g., Boué et al., 2013; Lin et al., 2013; Lin and Tsai, 2013; Nishida, 2013; Xia et al., 2016). However, the accurate “body-wave reconstruction” requires seismic sources, which can be either primary or secondary, to be concentrated near the stationary points.
The structure of the central Makran accretionary prism and its implications for hydrocarbon exploration and seismic hazard
2024, Iranian Journal of GeophysicsAn estimate of absolute shear-wave speed in the Earth’s inner core
2023, Nature Communications