Professor David Waltham (Department of Earth Sciences, Royal Holloway, University of London)
Dr Sophie Lambrotte (School and Observatory for Earth Sciences, University of Strasbourg)
Dr Christophe Zaroli (School and Observatory for Earth Sciences, University of Strasbourg)
Similar as on the Earth’s surface, intriguing landscapes are present deep inside our planet. To image these landscapes and gain critical insights into the dynamic processes that have shaped the evolution of our planet, surface recordings of seismic waves generated by earthquakes are typically used. Particularly, it is crucial to image the landscape of the core-mantle boundary (CMB). At this boundary, dynamic processes interact that are vital for life on Earth – with mantle flow driving plate tectonics and outer core flow sustaining our protective magnetic field.
Despite many studies over the last 50 years, no consensus exists on the amplitude or pattern of CMB topography. In addition, there is a discrepancy between models based on observations of high-frequency travelling waves or long-period standing waves (Koelemeijer, 2020), which provide information on different scale lengths. Besides, it was recently recognised that robust estimates of CMB topography can help solve the debate regarding the origin of large structures in Earth’s lowermost mantle (Deschamps et al., 2017).
This PhD project aims to image the dynamic topography of the CMB by using high-resolution data combined with novel seismic data processing methods. By using a new inverse method (Zaroli, 2016), the developed CMB topography models will have amplitudes that truly reflect real Earth structure and be accompanied by full uncertainty information. Crucially, new and existing observations of both travelling and standing seismic waves will be incorporated. Combining insights from both data types within one framework is vital for building a consistent CMB topography model (Koelemeijer, 2020). The candidate will compare the resulting models to predictions based on geodynamic simulations of mantle flow, with the aim to constrain the characteristics of lower mantle structure and to further our understanding of this enigmatic region inside the Earth.
The candidate will receive training in data analysis, computational and inverse methods as well as general research and communication skills. The candidate will benefit from being part of the DEEPSCAPE group at Royal Holloway and interaction with collaborators abroad.
This project is suited for candidates with strong quantitative skills, notably in mathematical analyses and programming (e.g. geophysics or physics degree/background).