Exploring the potential of normal mode seismology for the assessment of geodynamic hypotheses

Fluid dynamics simulations are a powerful tool for understanding processes in the Earth's deep interior. Mantle circulation models (MCMs), for example, provide important insight into the present-day structure of the mantle and its thermodynamic state when coupled with mineralogical models, which is essential information for other fields in the geosciences. The evolution of the heat flux through the core-mantle boundary, for instance, is a prerequisite for geodynamo simulations that aim to model the reversal frequency pattern of the Earth's magnetic field on geologic time scales. However, geodynamical modelling requires extensive knowledge of deep Earth properties and plate motions over time. Uncertainties in these model inputs propagate into the MCMs, which subsequently have to be evaluated with independent data, such as the seismological or geological record. Although state-of-the-art MCMs typically explain statistical properties of seismological data, they do not consistently reproduce the location of features in the mantle.

In this contribution, we explore the effect of varying the absolute position of mantle structure on seismic data by applying first-order modifications to an initial MCM. Normal mode data are particularly well suited for assessing the resulting changes in the location of mantle structure, as they capture its long-wavelength component throughout the entire mantle. In addition, the global sensitivity of normal modes reduces the drawbacks of uneven data coverage. Specifically, we use two different seismic forward modelling approaches, an iterative direct solution method for computing full-coupling spectra and a splitting function calculation that is based on the self-coupling approximation. Our goal is to quantify the effects of a limited number of large-magnitude earthquakes, the adequacy of the self-coupling approximation, and the resolvability of relevant model differences through a comprehensive data analysis. Our synthetic forward modelling framework is moreover well suited for testing the depth sensitivity associated with specific frequency intervals in the spectrum that generally is inferred from seismic 1-D profiles within the splitting function approximation.