This data set consists of multi-scale and high-resolution seismic wave velocity, attenuation, anisotropy, interface and stress field model of the crust, lithosphere and upper mantle beneath the Sichuan-Yunnan area. The velocity and attenuation models are mainly obtained by applying waveform adjoint tomography, double difference tomography and ambient noise tomography methods. The anisotropic models are mainly obtained by applying shear wave splitting, receiver functions and ambient noise methods. The interface structure is mainly obtained by receiver functions. The stress field model is mainly restrained by GPS velocity field and focal mechanism. Some of the used seismic waveform are from published data, and some are obtained from deployed seismic stations. The model data set can be used for further study on valuable scientific issues such as the mechanism of the occurrence of large earthquakes and the tectonic evolution of the lithosphere beneath the Chuandian Block, and the dynamic mechanism of the eastward extrusion of the Tibetan Plateau.

File naming and required software

File naming: the model data set is stored in text format, and each file is named as "serial number _topic number _model name".
Data reading method: all data files in the data set can be opened directly by text program.

Data Citations Data citation guideline What's data citation?

Cite as:

Pei, S. (2022). Multi-scale and high-resolution structure underneath the Sichuan-Yunnan area. A Big Earth Data Platform for Three Poles, DOI: 10.11888/SolidEar.tpdc.272529. CSTR: 18406.11.SolidEar.tpdc.272529. (Download the reference： RIS | Bibtex )

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Support Program

The study on multi-scale and high-resolution structures, deformation patterns and background of large earthquakes preparation and occurrence beneath the Chuandian Block (No:2017YFC1500300)

Copyright & License

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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)