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Abstract To quantitatively convert upper mantle seismic wave speeds measured into temperature, density, composition, and corresponding and uncertainty, we introduce theWhole‐rockInterpretativeSeismicToolboxForUltramaficLithologies (WISTFUL). WISTFUL is underpinned by a database of 4,485 ultramafic whole‐rock compositions, their calculated mineral modes, elastic moduli, and seismic wave speeds over a range of pressure (P) and temperature (T) (P = 0.5–6 GPa,T = 200–1,600°C) using the Gibbs free energy minimization routine Perple_X. These data are interpreted with a toolbox of MATLAB® functions, scripts, and three general user interfaces:WISTFUL_relations, which plots relationships between calculated parameters and/or composition;WISTFUL_geotherms, which calculates seismic wave speeds along geotherms; andWISTFUL_inversion, which inverts seismic wave speeds for best‐fit temperature, composition, and density. To evaluate our methodology and quantify the forward calculation error, we estimate two dominant sources of uncertainty: (a) the predicted mineral modes and compositions, and (b) the elastic properties and mixing equations. To constrain the first source of uncertainty, we compiled 122 well‐studied ultramafic xenoliths with known whole‐rock compositions, mineral modes, and estimatedP‐Tconditions. We compared the observed mineral modes with modes predicted using five different thermodynamic solid solution models. The Holland et al. (2018,https://doi.org/10.1093/petrology/egy048) solution models best reproduce phase assemblages (∼12 vol. % phase root‐mean‐square error [RMSE]) and estimated wave speeds. To assess the second source of uncertainty, we compared wave speed measurements of 40 ultramafic rocks with calculated wave speeds, finding excellent agreement (V_pRMSE = 0.11 km/s). WISTFUL easily analyzes seismic datasets, integrates into modeling, and acts as an educational tool. 

We constrain the viscosity of the lower crust through a joint inversion of seismic P-wave (Vp) and S-wave (Vs) velocities. Previous research has demonstrated robust relationships between seismic velocity and crustal composition, as well as between the composition and viscosity of the lower crust. Here we extend these analyses, showing seismic velocity can be used as a robust indicator of crustal viscosity. First, we use the Gibbs free energy minimization routine Perple_X to calculate equilibrium mineral assemblages for a global compilation of crustal rocks at various pressures and temperatures. Second, we use a rheological mixing model that combines single-phase flow laws for major crust-forming minerals to calculate bulk viscosity from the predicted mineral assemblages incorporating the effects of strain rate, temperature, pressure, and water activity. We apply our method to regional seismic and heat flow data across East Asia in order to separate the relative variations in mid-crustal viscosity associated with composition and temperature. In some regions, temperature variations are the dominant influence on viscosity; e.g., we predict a 3 order of magnitude increase in viscosity between the low heat flow Sichuan Basin and higher heat flow surrounding regions. These viscosity variations are consistent with those previously inferred to produce the different topographic gradients in these areas [1]. However in constant heat flow regions, compositional variations exert the primary influence on viscosity; e.g., the North China Craton and the Yangtze Craton are predicted to have compositionally-controlled viscosities ranging from 1022–1023 Pa×s. Finally, the regional Vp/Vs ratios in the Tibetan Plateau cannot be explained by thermal and/or compositional variations alone, possibly indicating the presence of melt, which would lead to additional viscosity reductions. [1] Clark & Royden, Geology, 2000.