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Global P wave tomography of Earth's lowermost mantle from partition modeling
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...
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Published in: | Journal of geophysical research. Solid earth 2013-10, Vol.118 (10), p.5467-5486 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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.
Key Points
Mantle heterogeneity is three times stronger than previous results
P‐wave velocity perturbations are mapped in lowermost mantle
Transdimensional, hierarchical Bayesian inversion of differential travel times |
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ISSN: | 2169-9313 2169-9356 |
DOI: | 10.1002/jgrb.50391 |