Bayesian inversion for the filtered flow at the Earth's Core Mantle Boundary

Abstract

The inverse problem which consists of determining the flow at the Earth's Core Mantle Boundary according to an outer core magnetic field and secular variation model, has been investigated through a Bayesian formalism. To circumvent the issue arising from the truncated nature of the available fields, we combined two modelization methods. In the first step, we applied a filter on the magnetic field to isolate its large scales by reducing the energy contained in its small scales, we then derived the dynamical equation, referred as filtered frozen flux equation, describing the spatio-temporal evolution of the filtered part of the field. In the second step, we proposed a statistical parametrization of the filtered magnetic field in order to account for both its remaining unresolved scales and its large scale uncertainties. These two modelization techniques were then included in the Bayesian formulation of the inverse problem. To explore the complex posterior distribution of the velocity field resulting from this development, we numerically implemented an algorithm based on Markov Chain Monte Carlo methods. After evaluating our approach on synthetic data and comparing it to previously introduced methods, we applied it on real data for the single epoch 2005.0.