Data Services Products: EMC-NEUS -Vs2018 3-D shear-wave isotropic model for the northeastern United States from full-wave ambient noise tomography

Summary

NEUS-Vs2018 (Yang and Gao, 2018) is a 3-D shear-wave isotropic model for the northeastern United States from full-wave ambient noise tomography with resolvable depths down to 120 km.

Description

Name NEUS-Vs2018
Title 3-D shear-wave isotropic model for the northeastern United States from full-wave ambient noise tomography
Type 3-D Tomography Earth Model
Sub Type Shear-wave velocity (km/s)
Year 2018
Short Description   NEUS-Vs2018 is a 3-D shear-wave isotropic model for the northeastern United States from full-wave ambient noise tomography with resolvable depths down to 120 km. It is based on an empirical Green’s function data set extracted from cross-correlation between station pairs. The tomography method involves 3-D wave propagation simulation. The travel-time different between the synthetics and the observed empirical Green’s functions are inverted based on finite-frequency sensitivity kernels to get velocity perturbations. The velocity model is updated iteratively.
Authors:  
Xiaotao Yang
Department of Geosciences
University of Massachusetts Amherst
627 North Pleasant Street, Amherst, MA 01003

Haiying Gao
Department of Geosciences
University of Massachusetts Amherst
627 North Pleasant Street, Amherst, MA 01003

Previous Model None
Reference Model The reference velocity model consists of two parts: a global shear-velocity model for the top 70 km (Shapiro and Ritzwoller, 2002) and the North American upper mantle model at greater depths (Bedle and van der Lee, 2009).
 
Model Download YangAndGao-NEUS-Vs2018.nc (see metadata ), is the netCDF file for the model
 
Model Homepage
Depth Coverage From 0 km to 120 km
Area Northeastern United States (latitude: 38.5° to 47.5°, longitude: -76° to -67°)
 
Data Set Description The data set includes the shear velocity model on an inversion grid of longitude and latitude with spacing of 0.015° in both directions. No smoothing or interpolation applied. Vertical grid spacing increases with depth.
 
Model Resolution As tested and validated by previous applications of full-wave tomographic imaging (e.g., Gao, 2018; Zhang and Shen, 2008), Rayleigh waves are most sensitive to P-wave velocity at shallow depths (< 15 km) and to S-wave velocity at greater depths. Although P-wave velocity model is also provided for all depth, interpretation of P velocities deeper than 15 km and shallower than 5 km is discouraged. The model provided here is from the inversion result of the 6th iteration without smoothing or interpolation. When interpreting the velocity model, it is recommended that the user smooth the model based on the best resolution at the corresponding depth, as shown in Yang and Gao (2018) and in Figure 2 on this page. The checkerboard amplitude and pattern of P-wave velocity perturbations can be well recovered at depths of 5 km, 12 km, and 17 km with horizontal scales of approximately 26 km, 40 km, and 53 km, respectively. For the deeper crust and uppermost mantle, our checkerboard resolution tests can resolve shear velocity perturbations with horizontal scales ranging from 26 km (at 17 km depth) to 53 km (at 43 km depth). Within the mantle lithosphere, seismic features with horizontal scales of 60-100 km can be well resolved.

Average P- and S-wave velocities at multiple layers
Average P- and S-wave velocities at multiple layers from full-wave ambient noise tomography
model: NEUS-Vs2018 (after Yang and Gao, 2018).

3D checkerboard resolution tests for the velocity models
3D checkerboard resolution tests for the velocity models. The velocity perturbation varies
within ±10% in the input models (after supplementary Figure S6 in Yang and Gao, 2018).

Citations and DOIs

To cite the original work behind this Earth model:

  • Yang, X., H. Gao (2018). Full-Wave Seismic Tomography in the Northeastern United States: New Insights into the Uplift Mechanism of the Adirondack Mountains, Geophysical Research Letters, 45, https://doi.org/10.1029/2018GL078438

To cite IRIS DMC Data Products effort:

  • Trabant, C., A. R. Hutko, M. Bahavar, R. Karstens, T. Ahern, and R. Aster (2012), Data Products at the IRIS DMC: Stepping Stones for Research and Other Applications, Seismological Research Letters, 83(5), 846–854, https://doi.org/10.1785/0220120032.

DOI for this EMC webpage:

References

Credits

Model contributed by Xiaotao Yang

Timeline

2018-07-03
online

Contact

Categories

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