Constraints on thermal state and composition of the Earth's lower mantle from electromagnetic impedances and seismic data

Abstract

[1] Despite the tight constraints put by seismology on the elastic properties of the Earth's lower mantle, its mineralogical composition and thermal state remain poorly known because the interpretation of seismic measurements suffers from the trade-off between temperature, iron content, and mineralogical composition. In order to overcome this difficulty, we complement seismic data with electromagnetic induction data. The latter data are mostly sensitive to temperature and iron content, while densities and acoustic speeds mostly constrain the mineralogy. A 0.5 log unit increase in electrical conductivity can be caused either by a 400 K increase of the temperature or by an increase of iron content from 10% to 12.5%. Acoustic velocity is only marginally sensitive to temperature but it increases by 0.8 km s À1 on average as the perovskite fraction increases from 50% to 100%. Olsen's (1999) apparent resistivities in the period range [15 days, 11 years], and Preliminary reference Earth model (PREM) densities and acoustic speeds are jointly inverted in the depth range [800 km, 2600 km] by using a Monte Carlo Markov Chain method. Given the uncertainties on these data, estimates of perovskite fraction are well constrained over the whole depth range, but information on temperature and iron content is only obtained for depths less than 2000 km, corresponding to the penetration depth of the long-period electromagnetic field. All parameter values are determined with an uncertainty better than 15-20% at the 1s confidence level. The temperature in the uppermost lower mantle (i.e

Robust constraints on average radial lower mantle anisotropy and consequences for composition and texture

“…1). For all five layers the perovskite content has to be lower than ∼75%, in agreement with Deschamps and Trampert (2004), Verhoeven et al (2009), who used PREM velocities, but contradicting piclogitic models of the lower mantle, which have ∼90% perovskite (Murakami et al, 2012). The iron content is higher than 10% in all layers and increases with depth: in the deepest layer the range of accepted X Fe is 14-19%.…”

“…This is due to the elevated density in the deep lower mantle (Fig. 1) and explains the difference with Deschamps and Trampert (2004), Verhoeven et al (2009), who used the density of PREM. In the top four layers, all accepted thermochemical models have temperatures similar to or up to 200 K lower than the Brown-Shankland geotherm (Brown and Shankland, 1981) (Fig.…”

Effect of iron oxidation state on the electrical conductivity of the Earth’s lower mantle

“…Previously temperature and total iron content have been considered to have the greatest influence on lower-mantle electrical conductivity profiles 21 , but our data show that Fe 3þ / SFe could also affect conductivity significantly at mid-mantle depths (1200-1900 km). A companion work has shown that Fe 3þ /SFe could also affect bulk sound velocity in the lower mantle 19 temperature gradient inferred for the lower mantle from such a joint inversion 21 may not be required due to the reduced electrical conductivity of silicate perovskite resulting from the HS-IS transition.…”

“…Electromagnetic induction data offer an important complement to seismic data with respect to lowermantle modelling, because the former are more sensitive to temperature and iron content, whereas the latter better constrain the mineralogy 21 . Laboratory electrical conductivity data of the relevant minerals are an important component of the approach, because they provide critical data on how the chemical and thermal state of the material influences the conductivity.…”

“…A companion work has shown that Fe 3þ /SFe could also affect bulk sound velocity in the lower mantle 19 temperature gradient inferred for the lower mantle from such a joint inversion 21 may not be required due to the reduced electrical conductivity of silicate perovskite resulting from the HS-IS transition. Three-dimensional inversions of electromagnetic data are now possible, and show variations of more than one order of magnitude in electrical conductivity, many of which are correlated with fast and slow regions of seismic tomography models 26 .…”