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 "slug": "rayleigh-wave-tomography",
 "title": "Rayleigh wave tomography",
 "updated": "2026-09-30",
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 "excerpt": "Rayleigh wave tomography is a seismological imaging method that measures Rayleigh wave dispersion along earthquake–station paths and inverts it for 3-D shear-wave velocity models of the crust and upper mantle.",
 "snippet": "Rayleigh wave tomography is a seismological imaging method that measures Rayleigh wave dispersion along earthquake–station paths and inverts it for 3-D shear-wave velocity models of the crust and upper mantle.",
 "node": "physical.earth.planet.seismic-tomography",
 "markdown": "# Rayleigh wave tomography\n\nRayleigh wave tomography is a seismological imaging method that measures the dispersion of Rayleigh surface waves along many earthquake–station paths and inverts those measurements for a three-dimensional shear-wave velocity (\n\\( V_{S} \\)) model of the crust and upper mantle. Because [Rayleigh wave](https://www.edgepedia.org/rayleigh-wave) phase and group velocities at each period average structure over a depth band set by the wavelength, a 40 s Rayleigh wave has peak sensitivity around 60 km depth and a 100 s Rayleigh wave is sensitive to shear-wave structure in the upper 200 km of the mantle.<sup>[1](https://royalsocietypublishing.org/rspa/article-pdf/doi/10.1098/rspa.2024.0955/2813840/rspa.2024.0955.pdf)</sup>\n\n| Key fact | Value |\n|---|---|\n| Product | 3-D \\( V_{S} \\) model of the crust and upper mantle, built from period-by-period phase or group velocity maps<sup>[2](https://seismo.berkeley.edu/wiki_cider/images/3/32/Seismic_Tomography_Tutorial.pdf)</sup> |\n| Period–depth sampling | 10 s → ~5–15 km; 20 s → ~10–30 km; 40 s → peak sensitivity near 60 km; 100 s → upper ~200 km of the mantle<sup>[3](https://www.osti.gov/servlets/purl/877870)</sup><sup> • </sup><sup>[1](https://royalsocietypublishing.org/rspa/article-pdf/doi/10.1098/rspa.2024.0955/2813840/rspa.2024.0955.pdf)</sup> |\n| Dominant sensitivity | Shear-wave velocity; a common layer-by-layer approximation is used<sup>[4](https://www.nature.com/articles/s41598-025-30603-3)</sup> |\n| Typical data volume | Tens of thousands of paths regionally (over 40,000 in a 1° Eurasia study)<sup>[3](https://www.osti.gov/servlets/purl/877870)</sup>; ~26 million dispersion observations in the global model S40RTS<sup>[1](https://royalsocietypublishing.org/rspa/article-pdf/doi/10.1098/rspa.2024.0955/2813840/rspa.2024.0955.pdf)</sup> |\n| Lateral resolution | Few hundred kilometers globally; better than 100 km across much of the US from ambient noise; 50–75 km with array-based eikonal/Helmholtz methods<sup>[5](https://www.dias.ie/wp-content/uploads/2010/11/lebedevgji2008.pdf)</sup><sup> • </sup><sup>[6](http://jspc-www.colorado.edu/pubs/2007/jgr_na_vers6.pdf)</sup><sup> • </sup><sup>[7](http://ciei.colorado.edu/pubs/2012/Joint_Inversion_Submitted_GJI.pdf)</sup> |\n| Main limitation | Surface waves sense the crust at all periods, so a priori crustal corrections are required and errors in them propagate into the mantle model<sup>[1](https://royalsocietypublishing.org/rspa/article-pdf/doi/10.1098/rspa.2024.0955/2813840/rspa.2024.0955.pdf)</sup> |\n\n## How it works\n\nRayleigh waves are dispersive in vertically heterogeneous media: high-frequency (short-wavelength) energy propagates in shallow layers, while low-frequency energy samples deeper material.<sup>[8](https://gfzpublic.gfz-potsdam.de/rest/items/item_243803_1/component/file_243802/content?download=true)</sup> Sensitivity analyses show that \\( V_{S} \\) exerts the strongest control on the dispersion curve, followed by layer thickness, with \\( V_{P} \\) and density playing minor roles; this is why the measured curves constrain shear-wave velocity specifically.<sup>[4](https://www.nature.com/articles/s41598-025-30603-3)</sup>\n\nEach measurement is not a point sample. The lateral sensitivity of a surface wave is spread over a [Fresnel zone](https://www.edgepedia.org/fresnel-zone) whose width scales with the square root of wavelength times path length, \\( w \\approx \\sqrt{v \\cdot l / (2 f)} \\); a 0.1 Hz wave that travels 10,000 km has a Fresnel zone several hundred kilometers wide.<sup>[1](https://royalsocietypublishing.org/rspa/article-pdf/doi/10.1098/rspa.2024.0955/2813840/rspa.2024.0955.pdf)</sup> Ray theory, which assumes infinitesimally thin rays, becomes invalid when heterogeneity length scales are smaller than this width.<sup>[9](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2005JB003677)</sup>\n\n## How it is done\n\nThe workflow has three steps: data acquisition, signal processing to obtain dispersion curves, and inversion for a shear-wave velocity profile or model.<sup>[8](https://gfzpublic.gfz-potsdam.de/rest/items/item_243803_1/component/file_243802/content?download=true)</sup> In the earthquake-based form, phase and/or group velocity is measured over hundreds of small-arc and long-arc paths connecting earthquakes and stations, and these path averages are converted to three-dimensional images.<sup>[10](https://ntrs.nasa.gov/api/citations/19840009660/downloads/19840009660.pdf)</sup> Group velocities are commonly measured with the Multiple Filter Technique or with frequency-time analysis (FTAN), which applies a sequence of Gaussian filters and reads arrival times from the filtered signal envelopes.<sup>[8](https://gfzpublic.gfz-potsdam.de/rest/items/item_243803_1/component/file_243802/content?download=true)</sup><sup> • </sup><sup>[6](http://jspc-www.colorado.edu/pubs/2007/jgr_na_vers6.pdf)</sup>\n\nThe inversion is usually two-step. First, dispersion measurements at each period are inverted for a 2-D phase or group velocity map. Classical schemes relate the velocity deviation on a path to the average of variations along the great circle (the path average approximation, PAVA).<sup>[2](https://seismo.berkeley.edu/wiki_cider/images/3/32/Seismic_Tomography_Tutorial.pdf)</sup><sup> • </sup><sup>[11](https://doi.org/10.1029/jb089ib07p05953)</sup> The penalty-function technique, which combines data misfit, model smoothness, and path coverage, is widely used at regional and global scales, as is the continuous-regionalization approach of Tarantola and Valette.<sup>[12](http://yaolab.ustc.edu.cn/_upload/tpl/10/f0/4336/template4336/pdf/Liu_Yao_2017_PAGEO.pdf)</sup><sup> • </sup><sup>[2](https://seismo.berkeley.edu/wiki_cider/images/3/32/Seismic_Tomography_Tutorial.pdf)</sup> Second, the phase or group velocity maps at different frequencies are combined, and each location's dispersion curve is inverted for a 1-D \\( V_{S} \\) profile, often starting from a reference model; the resulting profiles assemble into the 3-D model.<sup>[2](https://seismo.berkeley.edu/wiki_cider/images/3/32/Seismic_Tomography_Tutorial.pdf)</sup> Waveform-based implementations extract linear constraints per seismogram and solve the combined system with LSQR plus horizontal and vertical smoothing and norm damping.<sup>[5](https://www.dias.ie/wp-content/uploads/2010/11/lebedevgji2008.pdf)</sup> Because surface waves sense the crust at all periods, crustal corrections are applied a priori, for example using the CRUST2.0 seven-layer crust on a 2° × 2° grid.<sup>[1](https://royalsocietypublishing.org/rspa/article-pdf/doi/10.1098/rspa.2024.0955/2813840/rspa.2024.0955.pdf)</sup><sup> • </sup><sup>[9](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2005JB003677)</sup>\n\n## Origin\n\nThe mathematical groundwork came from George E. Backus's 1964 interpretation of great-circle average phase velocities in the Bulletin of the Seismological Society of America<sup>[13](https://doi.org/10.1785/bssa0540020571)</sup> and from the great-circle Love and Rayleigh wave phase-velocity data of [M. Nafi Toksöz](https://www.edgepedia.org/m-nafi-toksoz) and [Don L. Anderson](https://www.edgepedia.org/don-l-anderson) (1966, [Journal of Geophysical Research](https://www.edgepedia.org/journal-of-geophysical-research)).<sup>[14](https://doi.org/10.1029/jz071i006p01649)</sup> Ichiro Nakanishi and Don L. Anderson inverted worldwide mantle Rayleigh wave group velocities by spherical harmonic expansion in the Bulletin of the Seismological Society of America in 1982,<sup>[15](https://doi.org/10.1785/bssa0720041185)</sup> and John H. Woodhouse and Adam M. Dziewonski introduced waveform-based three-dimensional upper-mantle modeling with the path average approximation in the Journal of Geophysical Research in 1984.<sup>[11](https://doi.org/10.1029/jb089ib07p05953)</sup> Later milestones include Guust Nolet's partitioned waveform inversion (1990, Journal of Geophysical Research),<sup>[16](https://doi.org/10.1029/jb095ib06p08499)</sup> global 40–150 s phase velocity maps by Jeannot Trampert and John H. Woodhouse (1995, Geophysical Journal International),<sup>[17](https://doi.org/10.1111/j.1365-246x.1995.tb07019.x)</sup> the Eurasian group-velocity model of Michael H. Ritzwoller and Anatoli L. Levshin (1998, Journal of Geophysical Research),<sup>[18](https://doi.org/10.1029/97jb02622)</sup> and the ambient-noise tomography of Nikolai M. Shapiro and colleagues (2005, Science), which removed the dependence on earthquake occurrence.<sup>[19](https://doi.org/10.1126/science.1108339)</sup>\n\n## Variants\n\n**Earthquake-based measurements** come in single-station form (each station's dispersion referenced to a model) and two-station form, which measures interstation phase velocity for station pairs aligned with events of magnitude ≥ 5.5 at distances ≥ 20° and azimuthal deviation within 7° of the great-circle path, assuming the wavefield decomposes into plane waves.<sup>[20](https://www.earth-prints.org/server/api/core/bitstreams/c0f487c1-d76d-46f2-a5fa-2a09784208bf/content)</sup> **Ambient-noise tomography** cross-correlates continuous noise records between station pairs, supplying short-period (<20 s) measurements that are difficult from teleseismic earthquake paths; measurements are typically accepted only where signal-to-noise ratio exceeds 10.<sup>[6](http://jspc-www.colorado.edu/pubs/2007/jgr_na_vers6.pdf)</sup><sup> • </sup><sup>[7](http://ciei.colorado.edu/pubs/2012/Joint_Inversion_Submitted_GJI.pdf)</sup>\n\n**Array methods** track phase fronts across dense arrays. The eikonal tomography paper of Fan-Chi Lin, Michael H. Ritzwoller, and Roel Snieder (2009) takes the gradient of phase traveltime surfaces; its magnitude approximates local slowness and requires no explicit regularization.<sup>[21](https://doi.org/10.1111/j.1365-246x.2009.04105.x)</sup> Helmholtz tomography (Lin and Ritzwoller, 2011) adds amplitude information as a localized finite-frequency correction without building finite-frequency kernels, improving resolution above 50 s and reducing spurious azimuthal anisotropy from backscattering.<sup>[22](https://doi.org/10.1111/j.1365-246x.2011.05070.x)</sup> **Finite-frequency formulations** use 3-D Born sensitivity kernels, such as the Fréchet traveltime kernels of F. A. Dahlen, S.-H. Hung, and Guust Nolet (2000).<sup>[23](https://doi.org/10.1046/j.1365-246x.2000.00070.x)</sup> **Direct 3-D inversion** methods skip the 2-D map step, inverting dispersion for 3-D structure by ray tracing.<sup>[24](https://doi.org/10.1093/gji/ggv080)</sup> **Joint inversion with receiver functions** improves vertical resolution and, unlike [receiver functions](https://www.edgepedia.org/receiver-function) alone, constrains absolute shear velocities.<sup>[25](https://link.springer.com/article/10.1007/s10950-019-09888-1)</sup>\n\nMachine learning has entered the inversion step. DispFormer, a transformer-based network pretrained on synthetic dispersion curves built from LITHO1.0 (1–100 s, crust to about 200 km depth), inverts dispersion curves of arbitrary length for \\( V_{S} \\) profiles in a zero-shot manner without region-specific training.<sup>[26](https://arxiv.org/html/2501.04366v1)</sup> A data-adaptive ensemble extension of the Poisson-Voronoi parameterization of Hongjian Fang, Robert D. van der Hilst, and colleagues (2019) targets direct azimuthal-anisotropy tomography, addressing the strong trade-offs between isotropic velocity and anisotropic parameters in grid-based inversions.<sup>[27](https://doi.org/10.1785/0220190141)</sup><sup> • </sup><sup>[28](https://meetingorganizer.copernicus.org/EGU26/EGU26-7800.html)</sup>\n\n## Applications\n\nRegional group-velocity maps of Eurasia and North Africa were produced at 1° resolution from over 40,000 paths (30,000 Rayleigh and 20,000 Love quality measurements) at 7–100 s periods.<sup>[3](https://www.osti.gov/servlets/purl/877870)</sup> Across the United States, ambient-noise tomography with nearly 200 stations produced 8–70 s Rayleigh wave maps with resolution better than 100 km,<sup>[6](http://jspc-www.colorado.edu/pubs/2007/jgr_na_vers6.pdf)</sup> and eikonal tomography applied to more than 1,000 USArray stations produced isotropic and anisotropic phase velocity maps and a 3-D crustal and uppermost-mantle \\( V_{S} \\) model.<sup>[29](http://phys-geophys.colorado.edu/pubs/2011/ritzwoller%20comptes%20rendus%202011.pdf)</sup> Global models such as S20RTS, built from over 2 million fundamental-mode and overtone measurements plus body-wave traveltimes, image mantle structure at degree-20 scale.<sup>[30](https://www.ipgp.fr/~jpm/PUBLICATIONS/14Bodin_etal_Springer.pdf)</sup>\n\n## Limitations and alternatives\n\n**Crustal corrections** are the leading systematic error. The crustal contribution to apparent wave-speed variations may reach 50% at 150 s period and 100% at 40 s.<sup>[31](https://onlinelibrary.wiley.com/doi/10.1111/ter.12041)</sup><sup> • </sup><sup>[30](https://www.ipgp.fr/~jpm/PUBLICATIONS/14Bodin_etal_Springer.pdf)</sup> **Depth resolution** is limited: fundamental-mode resolution is best in the upper 300 km of the mantle, wave-speed variations within a 30–50 km depth range of the uppermost mantle are unresolvable from long-period data alone, and one-step 3-D inversions show depth leakage, where deeper structure averages over shallower structure.<sup>[30](https://www.ipgp.fr/~jpm/PUBLICATIONS/14Bodin_etal_Springer.pdf)</sup><sup> • </sup><sup>[31](https://onlinelibrary.wiley.com/doi/10.1111/ter.12041)</sup><sup> • </sup><sup>[32](https://seismica.library.mcgill.ca/article/download/1407/2283/18930)</sup> **Ill-posedness** means several velocity profiles fit the same dispersion curve (the equivalence problem), so a priori constraints shape the answer.<sup>[8](https://gfzpublic.gfz-potsdam.de/rest/items/item_243803_1/component/file_243802/content?download=true)</sup> **Finite-frequency effects** such as wavefront healing, which reduces a 0.33 s delay to 0.17 s before the wave reaches the receiver, bias ray-theoretical inversions; eikonal tomography does not account for wave interference, wavefront healing, or backscattering.<sup>[1](https://royalsocietypublishing.org/rspa/article-pdf/doi/10.1098/rspa.2024.0955/2813840/rspa.2024.0955.pdf)</sup><sup> • </sup><sup>[22](https://doi.org/10.1111/j.1365-246x.2011.05070.x)</sup>\n\nCompared with teleseismic body-wave tomography, which retrieves only relative wave speeds and vertically smears anomalies because rays traverse the upper mantle nearly vertically, Rayleigh wave tomography constrains absolute \\( V_{S} \\) and depth extent more reliably in the upper several hundred kilometers.<sup>[31](https://onlinelibrary.wiley.com/doi/10.1111/ter.12041)</sup><sup> • </sup><sup>[33](https://www.geol.umd.edu/facilities/seismology/wp-content/uploads/2013/02/Ritsema_Lekic_2020.pdf)</sup> Receiver functions locate discontinuities but suffer a trade-off between discontinuity depth and overburden velocity; surface waves constrain absolute velocities but resolve fine structure poorly because of their wide sensitivity kernels, which is why the two are often inverted jointly.<sup>[25](https://link.springer.com/article/10.1007/s10950-019-09888-1)</sup>\n\n## References\n\n1. [A high-resolution discourse on seismic tomography (Royal Society A, 2024/2025 review)](https://royalsocietypublishing.org/rspa/article-pdf/doi/10.1098/rspa.2024.0955/2813840/rspa.2024.0955.pdf)\n2. [Seismic Tomography Tutorial (Berkeley CIDER)](https://seismo.berkeley.edu/wiki_cider/images/3/32/Seismic_Tomography_Tutorial.pdf)\n3. [A variable resolution surface wave dispersion study of Eurasia, North Africa, and surrounding regions (Pasyanos et al., OSTI report)](https://www.osti.gov/servlets/purl/877870)\n4. [Rayleigh-wave dispersion data selection and model fine-tuning based on uncertainty estimation | Scientific Reports](https://www.nature.com/articles/s41598-025-30603-3)\n5. [Global upper-mantle tomography with the automated multimode inversion of surface and S-wave forms (Lebedev, Nolet et al., GJI 2008)](https://www.dias.ie/wp-content/uploads/2010/11/lebedevgji2008.pdf)\n6. [Broad-band ambient noise surface wave tomography across the United States (Bensen et al., JGR 2008)](http://jspc-www.colorado.edu/pubs/2007/jgr_na_vers6.pdf)\n7. [Joint inversion of surface wave dispersion and receiver functions: A Bayesian Monte-Carlo approach (Shen et al., 2012)](http://ciei.colorado.edu/pubs/2012/Joint_Inversion_Submitted_GJI.pdf)\n8. [Surface wave testing review (Foti et al., GFZ repository copy)](https://gfzpublic.gfz-potsdam.de/rest/items/item_243803_1/component/file_243802/content?download=true)\n9. [Global upper-mantle structure from finite-frequency surface-wave tomography (Zhou et al., 2006, JGR)](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2005JB003677)\n10. [Surface Wave Tomography (D. L. Anderson, 1984, NASA CASI copy of Eos article)](https://ntrs.nasa.gov/api/citations/19840009660/downloads/19840009660.pdf)\n11. [John H. Woodhouse, Adam M. Dziewonski (1984). Mapping the upper mantle: Three‐dimensional modeling of earth structure by inversion of seismic waveforms. Journal of Geophysical Research Atmospheres.](https://doi.org/10.1029/jb089ib07p05953)\n12. [Surface Wave Tomography with Spatially Varying Smoothing Based on Continuous Model Regionalization (Liu & Yao, 2017)](http://yaolab.ustc.edu.cn/_upload/tpl/10/f0/4336/template4336/pdf/Liu_Yao_2017_PAGEO.pdf)\n13. [George E. Backus (1964). Geographical interpretation of measurements of average phase velocities of surface waves over great circular and great semi-circular paths. Bulletin of the Seismological Society of America.](https://doi.org/10.1785/bssa0540020571)\n14. [M. Nafi Toksöz, Don L. Anderson (1966). Phase velocities of long-period surface waves and structure of the upper mantle: 1. Great-Circle Love and Rayleigh wave data. Journal of Geophysical Research Atmospheres.](https://doi.org/10.1029/jz071i006p01649)\n15. [Ichiro Nakanishi, Don L. Anderson (1982). Worldwide distribution of group velocity of mantle Rayleigh waves as determined by spherical harmonic inversion. Bulletin of the Seismological Society of America.](https://doi.org/10.1785/bssa0720041185)\n16. [Guust Nolet (1990). Partitioned waveform inversion and two‐dimensional structure under the network of autonomously recording seismographs. Journal of Geophysical Research Atmospheres.](https://doi.org/10.1029/jb095ib06p08499)\n17. [Jeannot Trampert, John H. Woodhouse (1995). Global phase velocity maps of Love and Rayleigh waves between 40 and 150 seconds. Geophysical Journal International.](https://doi.org/10.1111/j.1365-246x.1995.tb07019.x)\n18. [Michael H. Ritzwoller, Anatoli L. Levshin (1998). Eurasian surface wave tomography: Group velocities. Journal of Geophysical Research Atmospheres.](https://doi.org/10.1029/97jb02622)\n19. [Nikolai M. Shapiro and colleagues (2005). High-Resolution Surface-Wave Tomography from Ambient Seismic Noise. Science.](https://doi.org/10.1126/science.1108339)\n20. [SeisLib: surface-wave tomography software paper](https://www.earth-prints.org/server/api/core/bitstreams/c0f487c1-d76d-46f2-a5fa-2a09784208bf/content)\n21. [Fan-Chi Lin, Michael H. Ritzwoller, Roel Snieder (2009). Eikonal tomography: surface wave tomography by phase front tracking across a regional broad-band seismic array. Geophysical Journal International.](https://doi.org/10.1111/j.1365-246x.2009.04105.x)\n22. [Fan-Chi Lin, Michael H. Ritzwoller (2011). Helmholtz surface wave tomography for isotropic and azimuthally anisotropic structure. Geophysical Journal International.](https://doi.org/10.1111/j.1365-246x.2011.05070.x)\n23. [F. A. Dahlen, S.-H. Hung, Guust Nolet (2000). Fréchet kernels for finite-frequency traveltimes-I. Theory. Geophysical Journal International.](https://doi.org/10.1046/j.1365-246x.2000.00070.x)\n24. [Hongjian Fang and colleagues (2015). Direct inversion of surface wave dispersion for three-dimensional shallow crustal structure based on ray tracing: methodology and application. Geophysical Journal International.](https://doi.org/10.1093/gji/ggv080)\n25. [Reliable workflow for inversion of seismic receiver function and surface wave dispersion data: a “13 BB Star” case study (Journal of Seismology)](https://link.springer.com/article/10.1007/s10950-019-09888-1)\n26. [DispFormer: Pretrained Transformer for Flexible Dispersion Curve Inversion from Global Synthesis to Regional Applications (arXiv, January 2025)](https://arxiv.org/html/2501.04366v1)\n27. [Hongjian Fang and colleagues (2019). Parsimonious Seismic Tomography with Poisson Voronoi Projections: Methodology and Validation. Seismological Research Letters.](https://doi.org/10.1785/0220190141)\n28. [Direct Surface-Wave Tomography of Azimuthal Anisotropy Using a Data-Adaptive Ensemble Approach (EGU26-7800 abstract)](https://meetingorganizer.copernicus.org/EGU26/EGU26-7800.html)\n29. [Ambient noise tomography with a large seismic array (Ritzwoller et al., Comptes Rendus Geoscience 2011)](http://phys-geophys.colorado.edu/pubs/2011/ritzwoller%20comptes%20rendus%202011.pdf)\n30. [Interpreting Radial Anisotropy (Bodin et al., Springer chapter, IPGP-hosted)](https://www.ipgp.fr/~jpm/PUBLICATIONS/14Bodin_etal_Springer.pdf)\n31. [Caveats on tomographic images (Tectonophysics)](https://onlinelibrary.wiley.com/doi/10.1111/ter.12041)\n32. [Towards surface-wave tomography with 3D resolution and uncertainty (SEISMICA)](https://seismica.library.mcgill.ca/article/download/1407/2283/18930)\n33. [Heterogeneity of Seismic Wave Velocity in Earth's Mantle (Ritsema & Lekic, 2020, Annual Reviews, author-hosted PDF)](https://www.geol.umd.edu/facilities/seismology/wp-content/uploads/2013/02/Ritsema_Lekic_2020.pdf)\n\n---\n*Topic: Encyclopedia › Physical world and mathematics › Earth sciences › Earth systems and geophysics › Seismic tomography*\n\n*Initially written Sep 29, 2026 · Reviewed: Sep 30, 2026 · Edited: Sep 30, 2026 · Last review: Sep 30, 2026*\n\n*Copyright 2026 EdgeChat AI, a subsidiary of Biostate AI.*\n\nLicense: Edgepedia Community License 1.0, https://www.edgepedia.org/edgepedia/license\n",
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 "speakable": "Rayleigh wave tomography is a seismological imaging method that measures Rayleigh wave dispersion along earthquake–station paths and inverts it for 3-D shear-wave velocity models of the crust and upper mantle."
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