Fully funded studentship
Over the last decades, significant progress has been made in the seismic imaging of Earth’s interior. Tomographic images of three-dimensional structures in the mantle inform us about the fate of subducting plates, the location of upwellings and how the mantle flows and cools down over time. However, uncertainties in these images are often not quantified and model amplitudes are not representative of true Earth structure. Consequently, we cannot uniquely constrain the origin of seismic anomalies in the deep mantle, complicating interpretations in terms of compositional heterogeneity and mantle flow patterns.
This project aims to address these issues by utilizing newly developed, computationally fast and versatile inverse methods that can be applied to a wide range of applications. Specifically, we aim to use the SOLA method that retrieves unbiased model amplitudes and provides uncertainty information (Zaroli, 2016; Zaroli, Koelemeijer & Lambotte, 2017).
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