Global P wave tomography of Earth's lowermost mantle from partition modeling

摘要

[1] Determining the scale-length, magnitude, and distribution of heterogeneity in the lowermost mantle is crucial to understanding whole mantle dynamics, and yet it remains a much debated and ongoing challenge in geophysics. Common shortcomings of current seismically derived lowermost mantle models are incomplete raypath coverage, arbitrary model parameterization, inaccurate uncertainty estimates, and an ad hoc definition of the misfit function in the optimization framework. In response, we present a new approach to global tomography. Apart from improving the existing raypath coverage using only high-quality cross-correlated waveforms, the problem is addressed within a Bayesian framework where explicit regularization of model parameters is not required. We obtain high-resolution images, complete with uncertainty estimates, of the lowermost mantle P wave velocity structure using a hand-picked data set of PKPab-df, PKPbc-df, and PcP-P differential travel times. Most importantly, our results demonstrate that the root mean square of the P wave velocity variations in the lowermost mantle is approximately 0.87%, which is 3 times larger than previous global-scale estimates.