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Surface wave tomography : 1. dispersion or phase based approaches (part A) Huajian Yao USTC April 19, 2013
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Surface wave propagates along the surface of the earth, mainly sensitive to the crust and upper mantle (Vs) structure From IRIS Surface waves
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Love and Rayleigh waves Generated by constructive interference between postcritically reflected body waves
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Surface waves: evanescent waves Decreasing wave amplitudes as depth increases Wave displacement patterns in a layer over half space Wavelength increases Generally, wavespeed increases as the depth increases. Therefore, longer period (wavelength) surface waves tend to propagate faster.
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Surface wave dispersion: frequency-dependent propagation speed (phase or group speed) Group V: Energy propagation speed
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Phase or group velocity dispersion curves (PREM model)
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Phase or group velocity depth sensitivity kernels is the 1-D depth sensitivity kernel Usually 80-90% importance
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Phase or group velocity depth sensitivity kernels fundamental mode Rayleigh waveLove wave dc/dV SV dc/dV SH dU/dV SV
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(A) 0.15 Hz, (B) 0.225 Hz, (C) 0.3 Hz. Rayleigh wave phase velocity depth sensitivity kernels at shorter periods: also quite sensitive to Vp and density at shallow depth
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Rayleigh wave phase velocity depth sensitivity kernels: An image view
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1. Construct period-dependent 2-D phase/group velocity maps from many dispersion measurements 2. Point-wise (iterative) inversion of dispersion data at each grid point for 1-D Vs model; combine all the 1-D Vs models to build up the final 3-D Vs model Surface wave tomography from dispersion data: a two-step approach Now the global search approaches are widely used for this step due to very non-linear situation of this problem.
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(1). Single-station group velocity approach (event station) (2). Two-station phase velocity approach (event station1 station 2) (3). Single-station phase velocity approach (1) U = D/t g (2) c = (D 2 – D 1 )/Δt Popular approaches for surface wave tomography (Step 1)
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(1). Single-station group velocity approach frequency-time analysis (matched filter technique) to measure group velocity dispersion curves Widely used in regional surface wave tomography Ritzwoller and Levshin, 1998 Possible errors: (1) off great-circle effect, (2) mislocations of earthquake epicenters, (3) source origin time errors and (4) the finite dimension and duration of source process. (2 – 4): source term errors
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Eurasia surface wave group velocity tomography Ritzwoller and Levshin, 1998
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(2). Two-station phase velocity approach (very useful for regional array surface wave tomography) Teleseismic surface waves C TS (20 – 120 s) Yao et al., 2006,GJI Narrow bandpass filtered waveform cross-correlation travel time differences between stations almost along the same great circle path (circle skipping problem!) Advantage: can almost remove “source term errors”
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SW China Rayleigh wave phase velocity tomography from the two-station method Yao et al., 2006,GJI
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(3). Single-station phase velocity approach Observed Seismogram: Theoretical reference Seismogram from a spherical Earth model Propagation phase
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Perturbation Theory Ekstrom et al, 1997 Spherical harmonics representation of the 3-D model circle skipping problem at shorter periods!
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Example: Global phase velocity tomography (Ekstrom et al., 1997)
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Iterative linearize inversion Inversion of Vs from point-wise dispersion curves (Step 2) 2. non-linear inversion or global searching methods Simulated annealing, Genetic algorithm Monte Carlo method, Neighborhood algorithm
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Iterative linearize inversion: example The results may depend on the initial velocity model. Better to give appropriate prior constraints, e.g., Moho depth.
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Nonlinear inversion: example using neighborhood algorithm (Yao et al. 2008) http://rses.anu.edu.au/~malcolm/na/na.html http://rses.anu.edu.au/~malcolm/na/na.html (Sambridge, 1999a, b) Neighborhood search
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Bayesian Analysis of the model ensemble Posterior mean: 1-D marginal PPDF 2-D marginal PPDF 1-D PPDF: resolution & standard error of model parameter; 2-D PPDF: correlation between two model parameters
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