Seismology has revolutionized our understanding of the Earth's interior, but is also limited in its ability to distinguish between variations in different basic characteristics inside the Earth such between elastic properties and density. Constraining such properties is essential to the fundamental understanding of the evolution of the earth, the structure of continents and the processes driving plate tectonics. This project explores the use of a new observable that can complement seismology as a probe of the earth?s interior. Using global position system (GPS) estimates of ground movement, one can now detect the impact of the periodic movement of water mass associated with daily tides as they flex the surface of the earth due to the enormous weight of the moving oceans. Since the amount of flexing is directly controlled by interior properties of the solid earth, we can use these observations coupled with models of the ocean tides to constrain spatial variations in interior properties. This project focuses on both developing these new observation types and using them in models of the structure of the Earth's upper mantle with a particular focus on understanding the outermost 500 km of the Earth in the South American continent.
Earth's ocean tidal load (OTL) response is manifest as horizontal and vertical spatial displacements up to 5-10 cm in amplitude and are regularly measured by GPS receivers with 1 mm accuracy at sub-daily tidal periods. Investigations into OTL response provide a direct means of testing scaling laws and assumptions commonly adopted in seismology to relate seismic velocities to fundamental rock properties, as well as a means of rejecting existing proposed models of the Earth that are inconsistent with the geodetic observations. Furthermore, inferred density and elasticity models can be used to address outstanding questions in geophysics, such as the long-term stability of continental cratons against tectonic deformation. A byproduct of this effort will be the development of computational infrastructure to invert tidal observations in a Bayesian framework.
