Array analyses of SmKS waves and the stratification of Earth's outermost core
Array analyses of SmKS waves and the stratification of Earth's outermost core
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DOI：
10.1016/j.pepi.2017.03.006
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发表时间：
2018-03-01
影响因子：
2.3
通讯作者：
Kaneshima, Satoshi
中科院分区：
文献类型：
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作者：
Kaneshima, Satoshi
我们进行阵列分析的SmKS波，以调查Vp结构的地球最外层的核心。对于世界上宽频带地震台网记录到的地震，我们用台阵技术测量了S3 KS和S2 KS、S4 KS和S3 KS、S5 KS和S3 KS之间的时差。地球最外层核心KHOMC的Vp模型很好地拟合了差分时间（Kaneshima和Helffrich，2013）。对于最高质量的数据，还测量S4 KS和S2 KS相对于S2 KS的差分慢度。测量的慢度，具有独特的敏感性的外核心200-400公里以下的CMB，是由KHOMC匹配。这些观测结果巩固了外核顶部存在一层的证据，该层具有比外核大部分明显更陡的Vp梯度。我们用τ-p方法反演了新的SmKS微分时间数据集，并试图改进KHOMC的Vp剖面。KHOMC的基本特征保留后的模型细化。然而，最新估计的地层厚度接近450公里，比KHOMC的厚度要厚。在CMB以下400-800 km的深度，相对于PREM的Vp异常小于0.03 km/s，这与不同Vp模型在深度范围内的一致程度一致。(C)2017爱思唯尔B. V.保留所有权利。
We perform array analyses of SmKS waves in order to investigate the Vp structure of the Earth's outermost core. For earthquakes recorded by broadband seismometer networks in the world, we measure differential travel times between S3KS and S2KS, between S4KS and S3KS, and between S5KS and S3KS by array techniques. The differential times are well fit by a Vp model of the Earth's outermost core, KHOMC (Kaneshima and Helffrich, 2013). Differential slownesses of S4KS and S2KS relative to S2KS are also measured for the highest quality data. The measured slownesses, with unique sensitivity to the outer core 200-400 km below the CMB, are matched by KHOMC. These observations consolidate the evidence for the presence at the top of the outer core of a layer that has a distinctively steeper Vp gradient than the bulk of the outer core. We invert new SmKS differential time data set by a tau-p method and attempt to refine the Vp profile of KHOMC. The essential features of KHOMC are preserved after the model refinement. However, the newly estimated layer thickness is nearly 450 km, which is thicker than that of KHOMC. The Vp anomalies relative to PREM for the depths 400-800 km below the CMB are less than 0.03 km/s, consistent with the degree of agreement between different Vp models for the depth range. (C) 2017 Elsevier B.V. All rights reserved.