Joint inversion of 3D crustal structure with ambient noise and earthquake body wave travel time

Surface wave tomography based on the noise correlation function of seismic ambient noise has been widely used in studies of crustal and mantle structure . However, the periods of surface wave dispersions in the ambient noise tomography are typically less than 40 s, which limits its resolution on the lower crust. Travel times of earthquake body waves, such as Sg and SmS, could provide additional constraints to the crustal structure, especially to the lower crust due to the ray paths of SmS traveling through the lower crust twice. Here, we proposed a joint inversion method for 3D crustal structure with ambient noise and earthquake body wave travel time data, with the goal of providing better constraints and resolutions on the whole crust. We constructed the linear equations for joint inversion of crustal S velocity structure with the surface wave dispersion and body wave travel time data, and solved the equations with LSQR algorithm. Different weighting and damping factors, together with smoothing constraints, are adopted for surface wave dispersion and body wave travel time data to fit both dataset simultaneously. Synthetics experiments showed that the joint inversion could resolve the crust structure better than sole tomography of ambient noise or body wave travel time. We conducted the joint inversion around the Yangtze block in the eastern China. Rayleigh wave dispersions are extracted from the seismic ambient noise tomography by Zheng et al (2011) in this area. The body waves (e.g., Sg, SmS, Sn) are coherent to be identified and their travel times are measured with accuracy from high quality waveforms of some recent local earthquakes in this area. In order to minimize the travel time uncertainties, the focal depth and epicenter of these local earthquakes were resolved by depth phases and temporary aftershock observations. The result from joint inversion suggests that the crustal velocity structure, especially the lower crust, was well improved, which not only fits the surface wave dispersions equally well, but also gets good predictions of body wave travel times.