期刊文献+

On the Nature of the P-Wave Velocity Gradient in the Inner Core beneath Central America 被引量:2

On the Nature of the P-Wave Velocity Gradient in the Inner Core beneath Central America
原文传递
导出
摘要 We conduct an experiment to investigate whether linearity in the observed velocity gradient in the volume of the inner core sampled by the PKP ray paths beneath Central America is a robust approximation. Instead of solving an optimization problem, we approach it within the Bayesian inference. This is an ensemble approach, where model specification is relaxed so that in- stead of only one solution, groups of reasonable models are acceptable. Furthermore, in transdimen- sional Bayesian inference used here, the number of basis functions needed to model observations is by itself an unknown. Our modeling reveals that in the ensemble of models, the most likely are those containing only 2 nodes (linear trend). Thus our result justifies the assumption used for the deter- mination of inner core rotation with respect to the rest of the mantle that the observed gradient is constant in its nature (linear). Recent observations in seismology suggest that it is likely that the spa- tial variability in elastic parameters is a widespread phenomenon in the inner core. Future array observations will further constrain spatial extent and magnitude of velocity changes and show whether there is a significant difference between these observations in the two quasi-hemispheres of the inner core. We conduct an experiment to investigate whether linearity in the observed velocity gradient in the volume of the inner core sampled by the PKP ray paths beneath Central America is a robust approximation. Instead of solving an optimization problem, we approach it within the Bayesian inference. This is an ensemble approach, where model specification is relaxed so that in- stead of only one solution, groups of reasonable models are acceptable. Furthermore, in transdimen- sional Bayesian inference used here, the number of basis functions needed to model observations is by itself an unknown. Our modeling reveals that in the ensemble of models, the most likely are those containing only 2 nodes (linear trend). Thus our result justifies the assumption used for the deter- mination of inner core rotation with respect to the rest of the mantle that the observed gradient is constant in its nature (linear). Recent observations in seismology suggest that it is likely that the spa- tial variability in elastic parameters is a widespread phenomenon in the inner core. Future array observations will further constrain spatial extent and magnitude of velocity changes and show whether there is a significant difference between these observations in the two quasi-hemispheres of the inner core.
出处 《Journal of Earth Science》 SCIE CAS CSCD 2013年第5期699-705,共7页 地球科学学刊(英文版)
基金 Calculations were performed on the Terrawulf Ⅱ cluster,a computational facility supported through the AuScope Australian Geophysics Observing System(AGOS) Auscope Ltd.is funded under the National Collaborative Research Infrastructure Strategy(NCRIS)and the Education Investment Fund(EIF3),both Australian Commonwealth Government programmes
关键词 solid earth physics deep geophysics. solid earth physics, deep geophysics.
  • 相关文献

参考文献30

  • 1Bayes, T., 1763. An Essay towards Solving a Problem in the Doctrine of Chances. Phyl. Trans., 53: 370-418, doi: 1 0.1 098/rst1.1763.0053.
  • 2Bodin, T., Sambridge, M., Tkalcic, H., et al., 2012. Transdimensional Inversion of Receiver Functions and Surface Wave Dispersion. J. Geophys. Res., 117(B2), doi: 10.1 I l1/j.1365-246X.2011.05326.x.
  • 3Breger, L., Tkalcic, H., Romanowicz, B., 2000. The Effect ofD" on PKP(AB-DF) Travel Time Residuals and Possible Implications for Inner Core Structure. Earth Planet. Sci. Lett., 175: 133-143.
  • 4Calvet, M., Chevrot, S., Souriau, A., 2006. P-Wave Propagation in Transversely Isotropic Media II. Application to Inner Core Anisotropy: Effects of Data Averaging, Parametrization and a Priori Information. Phys. Earth Planet. Inter., 156:21-40.
  • 5Creager, K. C., 1997. Inner Core Rotation Rate from Small-Scale Heterogeneity and Time-Varying Travel Times. Science, 278: 1284--1288.
  • 6Denison, D. G. T., Holmes, C., Mallick, B., et al., 2002. Bayesian Methods for Nonlinear Classification and Regression. John Wiley & Sons, Hoboken.
  • 7Deguen, R., Alboussiere, T., Brito, D., 2007. On the Presence and Structure of a Mush at the Inner Core Boundary of the Earth. Phys. Earth Planet. Inter., 274: 1887-1891.
  • 8Garcia, R., Tkalcic, H., Chevrot, S., 2006. A New Global PKP Data Set to Study Earth's Core and Deep Mantle. Phys. Earth Planet. Int., 159: 15-31.
  • 9Gallagher, K., Bodin, T., Sambridge, M., et al., 2011. Inference of Abrupt Changes in Noisy Geochemical Records Using Bayesian Transdimensional Change Point Models. Earth Planet. Sci. Lett., 311: 182-194.
  • 10Green, P., 1995. Reversible Jump MCMC Computation and Bayesian Models Selection. Biometrika, 82: 711-732 Green, P., 2003. Trans-dimensional Markov Chain Monte Carlo.

同被引文献12

引证文献2

二级引证文献17

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部