| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000434270 |
| 005 | | 20200226143542 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781085691253 |
| 035 | |
▼a (MiAaPQ)AAI22585047 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 550 |
| 100 | 1 |
▼a Lai, Hongyu. |
| 245 | 10 |
▼a High-Resolution Imaging of Earth's Lowermost Mantle. |
| 260 | |
▼a [S.l.]:
▼b Arizona State University.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 209 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-03, Section: B. |
| 500 | |
▼a Advisor: Garnero, Edward J. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Arizona State University, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 520 | |
▼a This research investigates the fine scale structure in Earth's mantle, especially for the lowermost mantle, where strong heterogeneity exists. Recent seismic tomography models have resolved large-scale features in the lower mantle, such as the large low shear velocity provinces (LLSVPs). However, differences are present between different models, especially at shorter length scales. Fine scale structures both within and outside LLSVPs are still poorly constrained. The drastic growth of global seismic networks presents densely sampled seismic data in unprecedented quality and quantity. In this work, the Empirical Wavelet construction method has been developed to document seismic travel time and waveform information for a global shear wave seismic dataset. A dataset of 250K high-quality seismic records with comprehensive measurements is documented and made publicly available. To more accurately classify high quality seismic signal from the noise, 1.4 million manually labeled seismic records have been used to train a supervised classification model. The constructed model performed better than the empirical model deployed in the Empirical Wavelet method, with 87% in precision and 83% in recall. To utilize lower amplitude phases such as higher multiples of S and ScS waves, we have developed a geographic bin stacking method to improve signal-to-noise ratio. It is then applied to Sn waves up to n=6 and ScSn wave up to n=5 for both minor and major arc phases. The virtual stations constructed provide unique path sampling and coverage, vastly improving sampling in the Southern Hemisphere. With the high-quality dataset we have gathered, ray-based layer stripping iterative forward tomography is implemented to update a starting tomography model by mapping the travel time residuals along the ray from the surface down to the core mantle boundary. Final updated models with different starting tomography models show consistent updates, suggesting a convergent solution. The final updated models show higher resolution results than the starting tomography models, especially on intermediate-scale structures. The combined analyses and results in this work provide new tools and new datasets to image the fine-scale heterogeneous structures in the lower mantle, which advances our understanding of the dynamics and evolution of the Earth's mantle. |
| 590 | |
▼a School code: 0010. |
| 650 | 4 |
▼a Geophysics. |
| 690 | |
▼a 0373 |
| 710 | 20 |
▼a Arizona State University.
▼b Geological Sciences. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-03B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0010 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15492906
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |