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Summary The effects of reaction kinetics of bridgmanite and ferropericlase transforming to ringwoodite on elastic properties in upwelling mantle are investigated using data of kinetic experiments and internally self-consistent thermodynamic modelling of density and seismic velocities. The kinetic experiments show inhibited grain growth of ringwoodite. At the initiation of ringwoodite growth, bridgmanite completely transforms to a metastable pyrope-bearing garnet. Ringwoodite then gradually grows from the metastable assemblage of ferropericlase and garnet. The changes in mineralogy result in a low-velocity zone directly above the 660 km seismic discontinuity due to the lower seismic velocities and densities of ferropericlase and garnet compared to ringwoodite and bridgmanite. The modelling of the effects of reaction kinetics and its effect on seismic structure at ∼660 km depth shows more sensitivity to grain size than to temperature and upwelling rate. Modelling 1-D synthetic seismograms of PP (SS) underside reflections off the kinetically inhibited backward reaction to ringwoodite shows advanced traveltimes of underside reflections off ∼660 km depth of 0.2–0.8 s (1.2–1.6 s) for upwelling rates of 50 cm yr–1 and initial grain sizes between 5 and 20 cm due to the low-velocity zone above the 660 km discontinuity. The finite width of the low-velocity layer results in frequency-dependent behaviour of PP and SS underside reflection amplitudes, with higher amplitudes towards shorter periods. The effect on the traveltimes of P-to-s conversions used for receiver function is small (

Shear properties of mantle minerals are vital for interpreting seismic shear wave speeds and therefore inferring the composition and dynamics of a planetary interior. Shear wave speed and elastic tensor components, from which the shear modulus can be computed, are usually measured in the laboratory mimicking the Earth's (or a planet's) internal pressure and temperature conditions. A functional form that relates the shear modulus to pressure (and temperature) is fitted to the measurements and used to interpolate within and extrapolate beyond the range covered by the data. Assuming a functional form provides prior information, and the constraints on the predicted shear modulus and its uncertainties might depend largely on the assumed prior rather than the data. In the present study, we propose a data-driven approach in which we train a neural network to learn the relationship between the pressure, temperature and shear modulus from the experimental data without prescribing a functional form a priori. We present an application to MgO, but the same approach works for any other mineral if there are sufficient data to train a neural network. At low pressures, the shear modulus of MgO is well-constrained by the data. However, our results show that different experimental results are inconsistent even at room temperature, seen as multiple peaks and diverging trends in probability density functions predicted by the network. Furthermore, although an explicit finite-strain equation mostly agrees with the likelihood predicted by the neural network, there are regions where it diverges from the range given by the networks. In those regions, it is the prior assumption of the form of the equation that provides constraints on the shear modulus regardless of how the Earth behaves (or data behave). In situations where realistic uncertainties are not reported, one can become overconfident when interpreting seismic models based on those defined equations of state. In contrast, the trained neural network provides a reasonable approximation to experimental data and quantifies the uncertainty from experimental errors, interpolation uncertainty, data sparsity and inconsistencies from different experiments.

We apply a variety of statistical and machine learning techniques to elucidate the key 1-D and 3-D features of Earth’s lowermost mantle as imaged by seismic tomography. Multiple observables are required to break the trade-off between temperature, composition and mineral phase changes. Using bulk and shear wave speeds we can distinguish lateral and vertical variations in silica content and place a broad constraint on the temperature. Including density allows us to further resolve variations in iron content and place a tighter constraint on the temperature. Globally, the base of the mantle appears to be enriched in SiO2 compared to the overlying mantle. We demonstrate that the large low shear velocity provinces (LLSVPs) are more likely to be enriched in post-perovskite than their surroundings, and that dense piles at the base of the LLSVPs are likely enriched in both iron and silica.&nbsp, The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

SUMMARY Mantle plumes may play a major role in the transport of heat and mass through the Earth, but establishing their existence and structure using seismology has proven challenging and controversial. Previous studies have mainly focused on imaging plumes using waveform modelling and inversion (i.e. tomography). In this study we investigate the potential visibility of mantle plumes using array methods, and in particular whether we can detect seismic scattering from the plumes. By combining geodynamic modelling with mineral physics data we compute ‘seismic’ plumes whose shape and structure correspond to dynamically plausible thermochemical plumes. We use these seismic models to perform a full-waveform simulation, sending seismic waves through the plumes, in order to generate synthetic seismograms. Using velocity spectral analysis and slowness-backazimuth plots, we are unable to detect scattering. However at longer dominant periods (25 s) we see several arrivals from outside the plane of the great circle path, that are consistent with an apparent bending of the wave front around the plume conduit. At shorter periods (15 s), these arrivals are less obvious and less strong, consistent with the expected changes in the waves' behaviour at higher frequencies. We also detect reflections off the iron-rich chemical pile which serves as the plume source in the D″ region, indicating that D″ reflections may not always be due to a phase transformation. We suggest that slowness-backazimuth analysis may be a useful tool to locate mantle plumes in real array data sets. However, it is important to analyse the data at different dominant periods since, depending on the width of the plume, there is probably an optimum frequency band at which the plume is most visible. Our results also show the importance of studying the incoming energy in all directions, so that any apparently out-of-plane arrivals can be correctly interpreted.

In seismic tomography we map the wave speed structure inside the Earth, but we ultimately seek to interpret those images in terms of physical parameters. This is challenging because many parameters can trade‐off with each other to produce a given wave speed. The problem is compounded by the convention of mapping seismic structures as perturbations relative to a 1‐D reference model, rather than absolute wave speeds. Using a full waveform tomography model of Europe as a case study, we quantify the extent to which thermochemical and dynamic properties can be constrained using only S wave speed, expressed in absolute values. The wave speed distributions of this tomography model are compared with 4 million thermochemical models, whose seismic properties are computed via thermodynamic modeling. These models sample the full range of realistic mantle compositions, including variable water and melt contents, and mineral intrinsic anelasticity is taken into account. Intrinsic anelasticity causes waves to travel more slowly at higher temperatures, leading to seismic attenuation, but the sensitivity of the wave speed reduction to temperature is, in turn, controlled by the wave frequency. Global studies of surface waves indicate an anticorrelation between S wave speed and attenuation. We therefore only retain thermochemical models satisfying this anticorrelation. Our study indicates that the frequency dependence of anelasticity, α, depends on temperature or rheology, with α ≈ 0.1 being most appropriate in cold or lithospheric mantle and α ≈ 0.3 in warmer regions (i.e., the asthenosphere). Additionally, the slowest regions require specific compositions and/or a velocity‐weakening mechanism, such as partial melting, elastically accommodated grain boundary sliding, or water., Key Points Knowing the S wave speed precisely with a loose constraint on mantle attenuation places strong constraints on the temperatureThe frequency dependence of anelasticity α is variable: ~0.1 in cold/lithospheric mantle and ~0.3 in warm/asthenospheric mantleEither partial melting or elastically accommodated grain boundary sliding is required to explain the slowest wave speeds at 130 km

We present a full-waveform tomographic model of the crust and upper mantle beneath the Japanese Islands region. This is based on the combination of GPU-accelerated spectral-element wavefield simulations, adjoint techniques, and nonlinear optimization. Our model explains complete seismic waveforms of events not used in the inversion in the period range from 20 to 80 s. Quantitative resolution analysis indicates that resolution lengths within the well-covered areas are around 150 km in the horizontal and around 30 km in the vertical directions. In addition to the high-velocity signatures of known lithospheric slabs in the region, our model reveals a pronounced low-velocity anomaly beneath the volcanic island of Ulleung in the Sea of Japan, reaching −19% around 100 km depth. The Ulleung anomaly originates at or above the Pacific slab, rises vertically upward to the base of the Philippine Sea slab at ∼200 km depth, circumvents it in NW direction, and then significantly strengthens in the uppermost mantle above the Philippine Sea slab. Among the numerous hypotheses for the generation of low-velocity anomalies in subduction systems, those invoking instabilities before or when a slab enters the transition zone seem most likely. The age and fast subduction of the Pacific slab may facilitate the transport of fluids into the transition zone. This may promote the reduction in viscosity and the onset of convective upwelling, aided by ambient mantle flow, such as return flow within the mantle wedge.

In seismic tomography we map the wave speed structure inside the Earth, but we ultimately seek to interpret those images in terms of physical parameters. This is challenging because many parameters can trade‐off with each other to produce a given wave speed. The problem is compounded by the convention of mapping seismic structures as perturbations relative to a 1‐D reference model, rather than absolute wave speeds. Using a full waveform tomography model of Europe as a case study, we quantify the extent to which thermochemical and dynamic properties can be constrained using only S wave speed, expressed in absolute values. The wave speed distributions of this tomography model are compared with 4 million thermochemical models, whose seismic properties are computed via thermodynamic modeling. These models sample the full range of realistic mantle compositions, including variable water and melt contents, and mineral intrinsic anelasticity is taken into account. Intrinsic anelasticity causes waves to travel more slowly at higher temperatures, leading to seismic attenuation, but the sensitivity of the wave speed reduction to temperature is, in turn, controlled by the wave frequency. Global studies of surface waves indicate an anticorrelation between S wave speed and attenuation. We therefore only retain thermochemical models satisfying this anticorrelation. Our study indicates that the frequency dependence of anelasticity, α, depends on temperature or rheology, with α ≈ 0.1 being most appropriate in cold or lithospheric mantle and α ≈ 0.3 in warmer regions (i.e., the asthenosphere). Additionally, the slowest regions require specific compositions and/or a velocity‐weakening mechanism, such as partial melting, elastically accommodated grain boundary sliding, or water., Geochemistry, Geophysics, Geosystems, 19 (10), ISSN:1525-2027

Mantle plumes may play a major role in the transport of heat and mass through the Earth, but establishing their existence and structure using seismology has proven challenging and controversial. Previous studies have mainly focused on imaging plumes using waveform modelling and inversion (i.e. tomography). In this study we investigate the potential visibility of mantle plumes using array methods, and in particular whether we can detect seismic scattering from the plumes. By combining geodynamic modelling with mineral physics data we compute ‘seismic’ plumes whose shape and structure correspond to dynamically plausible thermochemical plumes. We use these seismic models to perform a full-waveform simulation, sending seismic waves through the plumes, in order to generate synthetic seismograms. Using velocity spectral analysis and slowness-backazimuth plots, we are unable to detect scattering. However at longer dominant periods (25 s) we see several arrivals from outside the plane of the great circle path, that are consistent with an apparent bending of the wave front around the plume conduit. At shorter periods (15 s), these arrivals are less obvious and less strong, consistent with the expected changes in the waves' behaviour at higher frequencies. We also detect reflections off the iron-rich chemical pile which serves as the plume source in the D″ region, indicating that D″ reflections may not always be due to a phase transformation. We suggest that slowness-backazimuth analysis may be a useful tool to locate mantle plumes in real array data sets. However, it is important to analyse the data at different dominant periods since, depending on the width of the plume, there is probably an optimum frequency band at which the plume is most visible. Our results also show the importance of studying the incoming energy in all directions, so that any apparently out-of-plane arrivals can be correctly interpreted., Geophysical Journal International, 219 (Supplement_1), ISSN:0956-540X, ISSN:1365-246X

The physical and chemical properties of the Earth’s mantle govern the cause of natural disasters, such as earthquakes and volcanoes. Since we do not have direct access to mantle materials, their properties are often inferred from laboratory measurements and surface observations (e.g. seismic data from earthquake recordings). This thesis addresses some key problems we face while utilising these data to constrain the thermal and chemical properties of the mantle. Firstly, we propose a data-driven approach based on machine learning to explain the laboratory measurements and quantify their uncertainties in the absence of an adequate physical model. Our results show that although conventional approaches based on fitting the measurements to an assumed model may appear better constrained, they could potentially provide biased results. Secondly, we use the data-driven approach to explore which thermochemical parameters can be constrained (and to what extent) with limited seismic observables- wave speeds and density. Our results show that these observables constrain temperature and major chemical parameters (silicon, magnesium, and iron), and they indicate the presence of thermochemical heterogeneities at the lowermost mantle. The dense and slow piles at the bottom of the lower mantle seen in seismic data can be explained by an enrichment in silica and iron content- characteristic feature of enstatite chondrites. The inferred heterogeneities have profound implications for the dynamics of the mantle and outer core. The methodology developed in this thesis is extremely efficient. It can easily incorporate additional observables and thus, has wide applications in the seismology and mineral physics community.

Equation-of-state (EOS) modeling, whereby the seismic properties of a specified thermochemical structure are constructed from mineral physics constraints, and compared with global seismic data, provides a potentially powerful tool for distinguishing between plausible mantle structures. However, previous such studies at lower mantle depths have been hampered by insufficient evaluation of mineral physics uncertainties, overestimation of seismic uncertainties, or biases in the type of seismic and/or mineral physics data used. This has led to a wide, often conflicting, variety of models being proposed for the average lower mantle structure. In this study, we perform a thorough reassessment of mineral physics and seismic data uncertainties. Uncertainties in both the type of EOS, and mineral elastic parameters, used are taken into account. From this analysis, it is evident that the seismic variability due to these uncertainties is predominantly controlled by only a small subset of the mineral parameters. Furthermore, although adiabatic pyrolite cannot be ruled out completely, it is problematic to explain seismic velocities and gradients at all depth intervals with such a structure, especially in the interval 1660-2000 km. We therefore consider a range of alternative thermal and chemical structures, and map out the sensitivity of average seismic velocities and gradients to deviations in temperature and composition. Compositional sensitivity is tested both in terms of plausible end-member compositions (e.g., MORB, chondrite), and via changes in each of the five major mantle oxides, SiO2, MgO, FeO, CaO, and Al2O3. Fe enrichment reduces both P and S velocities significantly, while Si enrichment (and Mg depletion) increases P and S velocities, with a larger increase in P than in S. Using purely thermal deviations from adiabatic pyrolite, it remains difficult to explain simultaneously all seismic observations. A superadiabatic temperature gradient does improve the seismic fit in the lowermost mantle, but should be accompanied by concurrent bulk chemistry changes. Our results suggest that the most plausible way to alter bulk chemistry in the lowermost mantle, simultaneously fitting density, bulk velocity and shear velocity constraints, is an increasing contribution of a hot, basalt-enriched component with depth. Copyright 2009 by the American Geophysical Union.

Geophysical Journal International, 175 (2), ISSN:0956-540X, ISSN:1365-246X