Investigating Periodicities in Abyssal Hill Morphology of the Atlantic Ocean: Possible Evidence of Mantle Dynamics

研究大西洋深海山形态的周期性：地幔动力学的可能证据

• 批准号: 2341367
• 负责人: John Goff
• 金额: $ 17.05万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2341367&HistoricalAwards=false
• 关键词: Investigating; Periodicities; Abyssal; Hill; Morphology

Non-Technical DescriptionThough covered by the oceans, abyssal hills are the most common landform on earth. They form at the world’s mid-ocean ridge spreading centers and are important records of the plate spreading process. Past studies of abyssal hills have treated them as purely random processes. The statistical parameters of such processes, such as mean, variance, characteristic scale, etc., can be correlated to plate spreading conditions, such as spreading rate, magma supply and crustal thickness. In this way, abyssal hills across the oceans can be used to probe plate dynamics through space and time. Recently, however, some studies have reported the detection of periodic signals embedded within otherwise random abyssal hill profiles. Such a signal could be evidence of previously-unrecognized influence on mid-ocean ridge magma processes, such as climate-driven changes in sea level, or deep-seated modulations of magma delivery. This study will use a new, robust algorithm developed by the lead PI. It detects and quantifies (amplitude, wavelength) periodic signals embedded within a random field. The algorithm will be applied to bathymetric data in the North and South Atlantic Oceans. There, decades-worth of surveys and transits provide abundant data for analysis. Periodic values will first be correlated to past spreading parameters to establish basic relationships. Regional variations in periodic values will then be investigated. This will permit investigating possible deep-earth controls on the formation of periodic signals. The result should establish key constraints in the future modeling of mid-ocean ridges. In addition, the code will be made available to the general public with a user-friendly interface. This will enable non-expert researchers and students in a variety of fields to make use of the algorithm. Technical DescriptionThe existence, or not, of periodicities in abyssal hill morphology has been vigorously debated in recent publications, and some have hypothesized that such periodicities are evidence of external forcing, such as by the impact of Milankovitch cycle-caused sea level fluctuations on the volcanic construction process at mid-ocean ridges (MORs), or internally forced, such as by modulations of mantle upwelling. This project will employ a newly-developed empirically pre-whitening algorithm for detecting and quantifying periodic signals that are embedded in a random field. It will be applied to the abundant archival trackline bathymetry data in the North and South Atlantic Oceans, which samples large and diverse regions of abyssal hills formed at slow-spreading MORs. This will enable testing of a first hypothesis: that temporal periodicities are present in slow-spreading MOR-generated abyssal hills. Preliminary analysis provides initial support, but confidently doing so requires much more than a few anecdotal examples. The existence of periodicities in the seafloor fabric could have significant implications for understanding and modeling MOR dynamics. If periodicities in abyssal hill morphology do exist, what factors of MOR spreading are they responsive to? This question leads us to a second hypothesis: that variations in temporal periodicities exist that are related to spreading properties and mantle conditions at the MOR at the time of formation. It can be tested directly by correlating periodic parameters to paleo-spreading rates, and indirectly by comparing periodic parameters to aperiodic statistical parameters, such as RMS height and characteristic scale, which are themselves correlated with various MOR parameters as noted above. This project will also investigate whether or not there are regional patterns to the periodicities measured, which could be indicative of responsiveness to mantle heterogeneities. For example, recent modeling indicates that periods and amplitudes of crustal thickness-derived seafloor periodicities will be dependent on mantle permeability, a poorly-constrained parameter that is critical for modeling melt transport in the mantle. By modernizing the original code for operation in a Python coding environment, the technique will be accessible to a wider audience, and has the potential to be used in interpreting a wide variety of Earth science and other time series (e.g., climate and weather, oceanographic, etc…). The team will promote the code through social media and develop materials to train interested users. Support of an early career scientist and building capacity in computational geoscience is a further broader impact.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.

非技术描述尽管被海洋覆盖，但深渊山是地球上最常见的地形。它们是在世界中部山脊扩散中心形成的，是板传播过程的重要记录。过去对深渊丘陵的研究将它们视为纯粹的随机过程。此类过程的统计参数，例如平均值，方差，特征量表等，可以与板扩散条件（例如扩散速率，岩浆供应和地壳厚度）相关。这样，可以使用横跨海洋的深渊丘陵来探测板板动力学通过空间和时间。然而，最近，一些研究报告了检测到嵌入在原本随机的深渊山丘中的周期信号。这样的信号可能是对中山山脊岩浆过程的先前未认可的影响的证据，例如气候驱动的海平面变化或岩浆传递的深处调制。研究将使用铅PI开发的一种新的，可靠的算法。它检测和量化（幅度，波长）周期性信号嵌入随机场中。该算法将应用于南大西洋和南大西洋的测深数据。在那里，调查和过境的数十年值提供了全面的数据供分析。周期性值将首先与过去的传播参数相关联，以建立基本关系。然后将研究周期性值的区域变化。这将允许研究有关周期信号形成的可能的深地球控制。结果应在未来的海洋山脊建模中建立关键限制。此外，该代码将通过用户友好的接口向公众提供。这将使各个领域的非专家研究人员和学生能够利用该算法。技术描述在最近出版物中对深渊山山形态的周期性存在的存在，有些人认为，这种周期性是外部强迫的证据，例如，通过米兰科维奇自行车造成的海平面造成的海平面上的海平面波动在火山水平上的影响（morsecean山脊）（mors）或实施式被限制为MOD，例如Modected of Modectuction of Modections of Modections of Mornther。该项目将采用新开发的经验前的旋转算法来检测和量化嵌入随机字段中的周期性信号。它将应用于北大西洋和南大西洋的丰富档案轨道测深数据，该数据在慢速摩尔斯形成的大型和潜水区域的大型和潜水区域。这将实现第一个假设的测试：暂时的周期性存在于缓慢的莫尔生成的深渊丘陵中。初步分析提供了初始支持，但是自信地这样做需要的不仅仅是一些轶事示例。海底织物中周期性的存在可能对理解和建模MOR动态具有重要意义。如果确实存在Abyssal Hill形态中的周期性，那么它们的传播因素会响应哪些因素？这个问题导致我们提出了第二个假设：存在临时周期性的变化，这些变化与形成时在MOR处的传播性质和地幔条件有关。可以通过将周期性参数纠正为古播种速率直接测试，并通过将周期参数与Aperiodic统计参数进行比较，例如RMS高度和特征量表，它们本身与上面指出的各种MOR参数相关。该项目还将调查是否有测量周期性的区域模式，这可能表明对地幔异质性的响应能力。例如，最近的建模表明，地壳厚度衍生的海底周期性的周期和放大器将取决于地幔渗透性，地幔渗透性是一个受约束的较差的参数，这对于对地幔中的熔体转运至关重要。通过在Python编码环境中实现原始操作代码，该技术将被广泛的受众访问，并有可能用于解释各种地球科学和其他时间序列（例如气候和天气，海洋学等）。团队将通过社交媒体宣传代码，并开发材料来培训感兴趣的用户。支持早期职业科学家和计算地球科学的建设能力是广播公司的进一步影响。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估被认为是宝贵的支持。