Finite-frequency sensitivity of body waves to anisotropy based upon adjoint methods

Sieminski, Anne; Liu, Qinya; Trampert, Jeannot; Tromp, Jeroen

doi:10.1111/j.1365-246x.2007.03528.x

Cited by 59 publications

(50 citation statements)

References 47 publications

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“…The width of the banana and of the doughnut hole depend on the path length and the wave period. For anisotropy, the general sensitivity pattern is still a banana doughnut in 1D reference models, but it is strongly controlled by a directional dependence (Sieminski et al, 2007b). The amplitude of the sensitivity asymptotically varies with the incidence angle and azimuth of the propagation.…”

Section: Favorable Properties For Imagingmentioning

confidence: 99%

“…This azimuthal dependence has been widely studied for surface waves (Smith and Dahlen, 1973;Montagner and Nataf, 1986). Analyses of surface-wave (Sieminski et al, 2007a) and body-wave sensitivity (Sieminski et al, 2007b) to anisotropy show that finite-frequency propagation presents the same type of directional dependence. Seismic travel times are more efficiently described by wave speed rather than elastic parameters and density (Tromp et al, 2005;Liu and Tromp, 2006).…”

Section: Sensitivitymentioning

confidence: 99%

“…In Sieminski et al (2007b), we proposed to use temporal observables, inspired by the cross-correlation travel-time anomaly, to analyze S-wave sensitivity to anisotropy. The observable we present here comes from the general definition for S waves (equation 18 of Sieminski et al, 2007b).…”

Section: The Splitting Intensitymentioning

confidence: 99%

“…In the section entitled Sensitivity, we explore how the SKS-splitting intensity sees general anisotropy by investigating its sensitivity to perturbations of 21 elastic parameters with the adjoint spectral-element method (Tromp et al, 2005;Liu and Tromp, 2006;Sieminski et al, 2007aSieminski et al, , 2007b. This numerical method accounts for the full physics of seismic-wave propagation and provides the sensitivity to first-order perturbations.…”

Section: Introductionmentioning

confidence: 99%

“…The observable we present here comes from the general definition for S waves (equation 18 of Sieminski et al, 2007b). Before discussing this observable in the specific case of SKS waves, we first review the definition and advantages of measuring travel-time anomalies by cross correlation.…”

Section: The Splitting Intensitymentioning

confidence: 99%

See 4 more Smart Citations

Finite-Frequency SKS Splitting: Measurement and Sensitivity Kernels

Sieminski

Paulssen

Trampert

et al. 2008

Bulletin of the Seismological Society of America

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Splitting of SKS waves caused by anisotropy may be analyzed by measuring the splitting intensity, i.e., the amplitude of the transverse signal relative to the radial signal in the SKS time window. This quantity is simply related to structural parameters. Extending the widely used cross-correlation method for measuring travel-time anomalies to anisotropic problems, we propose to measure the SKSsplitting intensity by a robust cross-correlation method that can be automated to build large high-quality datasets. For weak anisotropy, the SKS-splitting intensity is retrieved by cross-correlating the radial signal with the sum of the radial and transverse signals. The cross-correlation method is validated based upon a set of Californian seismograms. We investigate the sensitivity of the SKS-splitting intensity to general anisotropy in the mantle based upon a numerical technique (the adjoint spectralelement method) considering the full physics of wave propagation. The computations reveal a sensitivity remarkably focused on a small number of elastic parameters and on a small region of the upper mantle. These fundamental properties and the practical advantages of the measurement make the cross-correlation SKS-splitting intensity particularly well adapted for finite-frequency imaging of upper-mantle anisotropy.

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Section: Favorable Properties For Imagingmentioning

confidence: 99%

Section: Sensitivitymentioning

confidence: 99%

Section: The Splitting Intensitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: The Splitting Intensitymentioning

confidence: 99%

See 3 more Smart Citations

Finite-Frequency SKS Splitting: Measurement and Sensitivity Kernels

Sieminski

Paulssen

Trampert

et al. 2008

Bulletin of the Seismological Society of America

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Full‐wave multiscale anisotropy tomography in Southern California

Lin

Zhao

Hung

2014

Geophysical Research Letters

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Understanding the spatial variation of anisotropy in the upper mantle is important for characterizing the lithospheric deformation and mantle flow dynamics. In this study, we apply a full-wave approach to image the upper-mantle anisotropy in Southern California using 5954 SKS splitting data. Three-dimensional sensitivity kernels combined with a wavelet-based model parameterization are adopted in a multiscale inversion. Spatial resolution lengths are estimated based on a statistical resolution matrix approach, showing a finest resolution length of~25 km in regions with densely distributed stations. The anisotropic model displays structural fabric in relation to surface geologic features such as the Salton Trough, the Transverse Ranges, and the San Andreas Fault. The depth variation of anisotropy does not suggest a lithosphere-asthenosphere decoupling. At long wavelengths, the fast directions of anisotropy are aligned with the absolute plate motion inside the Pacific and North American plates.

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Seismic velocity structure and anisotropy of the Alaska subduction zone based on surface wave tomography

Wang

Tape

2014

JGR Solid Earth

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Southcentral Alaska is a complex tectonic region that transitions from subduction of Pacific crust to flat slab subduction—and collision—of overthickened Yakutat crust. Because much of the Yakutat crust has been subducted, seismic imaging is needed in order to understand the crustal and upper mantle structural framework for this active tectonic setting. Here we use teleseismic Rayleigh waves to image large‐scale variations in shear wave structure. Our imaging technique employs a two‐plane wave representation with finite frequency sensitivity kernels. Our 3‐D isotropic model reveals several features: the subducting Pacific/Yakutat slab, slow wave speeds characterizing the onshore Yakutat collision zone, slow wave speeds of the Wrangell subduction zone, and a deep tomographic contrast at the eastern edge of the Pacific/Yakutat slab. We produce anisotropic phase velocity maps that exhibit variations in the fast direction of azimuthal anisotropy. These maps show the dominance of the Yakutat slab on the observed pattern of anisotropy. West of the Yakutat slab the fast directions are approximately aligned with the plate convergence direction. In the region of the Yakutat slab the pattern is more complicated. Along the margins of the slab the fast directions are roughly parallel to the margins. We identify notable differences and similarities with published SKS splitting measurements. Integrative modeling using 3‐D anisotropy models and different seismic measurements will be needed in order to establish a detailed 3‐D anisotropic velocity model for Alaska. This study provides a large‐scale starting point for such an effort.

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Finite-frequency sensitivity of body waves to anisotropy based upon adjoint methods

Cited by 59 publications

References 47 publications

Finite-Frequency SKS Splitting: Measurement and Sensitivity Kernels

Finite-Frequency SKS Splitting: Measurement and Sensitivity Kernels

Full‐wave multiscale anisotropy tomography in Southern California

Seismic velocity structure and anisotropy of the Alaska subduction zone based on surface wave tomography

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