Sensitivity of surface wave and gravity data to velocity and density structure in the mantle – insights from transdimensional inversion

Determining the thermochemical structure of the mantle is crucial for understanding its evolution and dynamics. Temperature variations have long been known as important driving forces of mantle convection; however compositional differences can also influence dynamics. Additionally, compositional differences can act as indicators left behind by processes operating in the past. Both aspects have played a role in the ongoing discussions on the Large Low Shear Wave Velocity Provinces (LLSVP), the proposed Bridgmanite Enriched Ancient Mantle Structures (BEAMS) and the fate of subducted oceanic crust.

A prerequisite for determining compositional differences in terms of major oxides with geophysical techniques is a joint determination of several geophysical properties. A single geophysical property (density, velocity) could almost always be explained by temperature or composition variations alone – except in pathological edge cases. The geophysical signature of composition lies in the pointwise relation between properties. This pointwise relation can be distorted by spectral filtering or inversion smoothing and damping.

In this contribution, I parametrize the mantle as a collection of discrete spatial anomalies in terms of seismic velocity and density. Surface wave phase speed and satellite gravity data are used to constrain the anomalies. A transdimensional Monte Carlo Markov Chain method is used to generate ensembles of solutions that try to balance model complexity and data fit. An important aspect of this setup is that the two data sets used are complementary: While satellite gravity data are available (nearly) globally with homogeneous quality, coverage of phase speed data depends on the spatial distribution of seismic stations and large earthquakes. Conversely, the gravity field lacks true depth sensitivity, which surface wave data can provide by combining several frequencies.

I will present synthetic investigations that aim at determining how accuracy and coverage affect the simultaneous recoverability of seismic velocity and density.