DI009-03
How much and where? Exploring Excess Density within the LLSVPs by reconciling Stoneley Mode and Earth Tide Observations.

Wednesday, 9 December 2020: 10:38
Virtual
Harriet C. P. Lau, University of California, Berkeley, Department of Earth and Planetary Science, Berkeley, CA, United States, Alex Robson, University of California Berkeley, Berkeley, CA, United States, Paula Koelemeijer, Royal Holloway University of London, Egham, United Kingdom and Barbara A Romanowicz, Univ California Berkeley, Berkeley, CA, United States
Abstract:
The so-called LLSVPs (Large Low Shear Velocity Provinces) have long been a source of discussion within the mantle geochemical, seismological and geodynamical communities. Several topics of debate include the very reason that LLSVPs exist, their detailed morphology, and their stability, which all hold key implications for the long term evolution of the mantle. Recent efforts have highlighted interesting features in the deep mantle that offer some indirect hints to their origin, e.g., discoveries of new mineral phases, the sharp sidedness, the presence of ULVZs situated in similar locations at the base of the mantle.
In this talk, we focus on one aspect of the story: the density distribution within the LLSVPs. In recent years, two studies concluded seemingly contradictory pictures of LLSVP density using two entirely new datasets: (1) earth tide data (as measured by GPS); and (2) Stoneley mode splitting function data. While the tidal study favored a mantle with relatively dense LLSVPs, the latter favored the opposite. We will present preliminary results where we have combined both tidal data and Stoneley mode splitting data, and have augmented these with normal mode spectra focussing on Stoneley mode peaks using full-band normal mode coupling theory. In doing so, we have taken full advantage of the differences in mantle depth sensitivity between each data type to explore what density depth distributions can satisfy both datasets. We have found several density distributions, where density anomalies are confined to a thin basal layer, are able to satisfy both data sets.