Constraining ocean-mantle dynamics by improving shear-wave splitting with ocean bottom seismometers

横波分裂是一种提供地幔如何流动信息的工具。然而，这种技术很难用于在占地球表面近70%的海底收集数据。本项目实现了一种处理海洋数据集的新方法。关于是什么驱动地幔流动以及岩浆如何到达火山的假说将得到检验。一名本科生将帮助进行数据分析，该方法将被广泛使用。横波分裂观测为岩石圈-软流圈系统的地球动力学提供了一级约束。这个项目将调查三个科学问题。1)是地球表面板块的运动还是内部对流力量驱动了海洋软流层的流动？2)地幔柱驱动构造板块下的径向流动模式，还是岩石圈-软流圈系统的力量捕获了地幔柱？3)洋中脊下产生的熔体是否被剪切分离成条带，或者熔体是否不与背景应变场相互作用？由于使用海底地震仪进行SWS观测所面临的挑战，目前很难解决这些问题。针对传统方法在海洋环境中面临的复杂的深度变化各向异性和低信噪比两个关键挑战，提出了一种新的方法。在诺梅尔特遗址和加拉帕戈斯群岛的初步结果显示，与更传统的方法相比，有了重大改进。该方法将被转换为Julia编程语言，供社区使用。本建议实施的方法通过增加返回良好SWS结果的数据集的数量，增加了国内和国际海底地震仪实验的回报。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Shear-wave splitting is a tool that provides information about how the mantle flows. However, this technique is difficult for data collected on the seafloor which is nearly 70% of the Earth’s surface. This project implements a new approach for oceanic datasets. Hypotheses will be tested about what drives mantle flow and how magmas reach volcanoes. An undergraduate student will help with data analysis and the method will be released for wide use.Observations of shear-wave splitting (SWS) provide a first-order constraint on the geodynamics of the lithosphere-asthenosphere system. This project will investigate three science questions. 1) Do the motions of the plates on the Earth’s surface or internal convective forces drive flow in the oceanic asthenosphere? 2) Do mantle plumes drive a radial pattern of flow beneath tectonic plates, or are plumes captured by forces in the lithosphere-asthenosphere system? 3) Does the melt generated beneath mid-ocean ridges get segregated by shear into bands, or does the melt not interact with the background strain field? Addressing these questions at present is made difficult by the challenges involved in making SWS observations with ocean-bottom seismometers. A method is proposed to address two key challenges faced by traditional methods in oceanic environments – complex depth-varying anisotropy and low signal-to-noise ratios. Preliminary results at both the NoMelt site and Galapagos Archipelago show major improvements relative to more traditional approaches. The methodology will be converted to the Julia programming language for use by the community. The methodology implemented by this proposal increases the return from ocean-bottom seismometer experiments - both domestic and international - by increasing the number of datasets that return good SWS results.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.