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\begin{document}

\title{Bayesian inference of mantle viscosity from whole-mantle density models}



\author[1]{Maxwell Rudolph}%
\author[2]{Pritwiraj Moulik}%
\author[2]{Ved Lekic}%
\affil[1]{University of California, Davis}%
\affil[2]{University of Maryland}%


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  \date{May 28, 2024}


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\begin{abstract}
The long-wavelength geoid is sensitive to Earth's mantle density
structure as well as radial variations in mantle viscosity. We present a
suite of inversions for the radial viscosity profile using whole-mantle
models that jointly constrain the variations in density, shear- and
compressional-wavespeeds using full-spectrum tomography. We use a
Bayesian approach to identify a collection of viscosity profiles
compatible with the geoid, while enabling uncertainties to be
quantified. Depending on tomographic model parameterization and data
weighting, it is possible to obtain models with either positive- or
negative-buoyancy in the large low shear velocity provinces (LLSVPs). We
demonstrate that whole-mantle density models in which density and
\$V\_S\$ variations are correlated imply an increase in viscosity below
the transition zone, often near
\textasciitilde{}1000\textasciitilde{}km. Many solutions also contain a
low-viscosity channel below 650\textasciitilde{}km. Alternatively,
models in which density is less-correlated with \$V\_S\$ -- which better
fit normal mode data -- require a reduced viscosity region in the lower
mantle. This feature appears in solutions because it reduces the
sensitivity of the geoid to buoyancy variations in the lowermost mantle.
The variability among the viscosity profiles obtained using different
density models is indicative of the strong non-linearities in modeling
the geoid and the limited resolving power of the geoid kernels. We
demonstrate that linearized analyses of model resolution do not
adequately capture the posterior uncertainty on viscosity. Joint and
iterative inversions of viscosity, wavespeeds, and density using seismic
and geodynamic observations are required to reduce bias from prior
assumptions on viscosity variation and scalings between material
properties.%
\end{abstract}%



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