CSEDI Collaborative Research: Understanding what we see in the lower mantle - mineral physics interpretation of seismic tomographic images

点击翻译按钮获取中文摘要

Earth’s mantle thermal convection drives plate tectonics. It is at the origin of numerous risks for populations (e.g., earthquakes, volcanic eruptions, tsunamis). This process extracts Earth’s internal heat, notably produced by the crystallization of its core. The core is ~3,500 km (~2,200 mi) in radius and consists mostly of iron with some nickel. Its liquid outer shell, the outer core, generates the Earth’s magnetic field. Above the core lies the rocky mantle, a hot layer of mostly solid silicates wrapped into the planet’s crust. The core-mantle boundary (CMB) is located ~2,900 km (1800 mi) beneath the Earth’s surface. It is a complex and critical boundary. There, heat transfer, from the core to the mantle, constrains the geodynamo and powers mantle convection. Deep patterns of mantle flow are observed by refined seismic imaging above the CMB. These structures still challenge interpretations in terms of mineralogy and thermodynamical state. Here, researchers focus on the mantle system. The multidisciplinary team of computational scientists consists of a mineral physicist, two seismologists, an applied mathematician, and a geodynamicist. It introduces innovative approaches to analyze the origin of mantle structures, including machine learning algorithm. The models are constrained with the latest mineral physics data, obtained at the extreme pressures and temperatures prevailing in Earth’s interior. Gradually, the scientists unveil the origins, compositions, and temperatures of the deep mantle structures. Outcomes of the project, i.e., state-of-the-art methods, software, and databases, will benefit the Earth Science community. The project also provides support for an early career female scientist, and training for four graduate students at Columbia University and Princeton University.Here, the researchers use the latest shear (S-) and compressional (P-) wave models obtained by global adjoint tomography, without reference to a 1D spherical model or assumptions of correlations between compressional (VP) and shear velocity (VS) heterogeneities. They also use direct inversion, machine learning algorithms, and the latest mineral physics results on thermoelastic properties of mineral phases undergoing iron spin crossover (ISC). They pay particular attention to the effect of the ISC which disrupts the usual correlation between VS and VP heterogeneities caused by lateral temperature or composition variations. They focus on lower mantle structures, mainly plumes rooted at the CMB and possibly slabs in this region. In the process, they are formatting the mineral physics data on ISCs to make it available through two popular thermochemical and thermoelasticity software/database frameworks – BurnMan and Perple_X – that couple with geodynamic codes. With this software/data infrastructure in place, they run geodynamic simulations to understand the effect of ISC on mantle dynamics. Conversely, results of geodynamic modeling coupled to thermoelasticity data are used to synthesize tomographic images to be compared with observed mantle structures. The know-how generated by this project, i.e., methods, software, databases, and results will be made available through peer-reviewed journals and in specialized web sites, e.g., BurnMan, Perple_X, IRIS, github.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.