Joint inversions are now commonly used in Earth Sciences. They have been developed to better understand Earth structure since they provide more constraints on the inverted parameters. We propose a new process to simultaneously invert several data sets in order to better image 3-D crustal and upper mantle structures. Our inversion uses 3 kind of data which present a good complementarity : (1) P receiver functions to provide Moho depth variations, (2) teleseismic delay times of P waves to retrieve velocity anomalies in the crust and upper mantle, (3) gravity anomalies to image density variations at lithospheric scale. In our scheme, receiver functions are first inverted. The resulting Moho depths are then interpolated and incorporated as a priori information into the joint inversion of teleseismic delay times and gravity anomalies process. In our new approach, we perform a model space search for Moho variations, P-velocity and density structure to find acceptable fit to the three data sets. In order to preferentially sample the good data fit region, we chose the Neighborhood algorithm of Sambridge to optimistically survey the model space. We model the delay times with a 3-D raytracing using velocity nodes evenly spaced and linked with density nodes via a linear relationship. This relationship can evolve through depth, simulating its pressure dependance. We test our scheme on synthetic examples, and apply the method in a continental rifting region where deformation processes are complex and badly known. This joint inversion thus provides more constraints on the inverted parameters, and allows us to better image crust - mantle interactions in the case of the Hangai dome (Central Mongolia). Indeed, in this area, we expect an asthenospheric upwelling to dynamically support the topography, but we image a density - velocity anomaly in the lower crust. The effects on topography and the origin (composition vs. thermal) of this anomaly are still under debate.
