Interpreting the Paleomagnetic Field Using Stochastic Models

使用随机模型解释古磁场

基本信息

批准号：
1644644
负责人：
Bruce Buffett
金额：
$ 27万
依托单位：
University of California-Berkeley
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-01-01 至 2020-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1644644&HistoricalAwards=false
关键词：
Interpreting Paleomagnetic Field Using Stochastic

项目摘要

Earth's magnetic field is an important aspect of our planet's habitability, yet the long-term behavior of the magnetic field is poorly understood. Historical observations provide a valuable source of information, but the duration of this record is just too short to draw meaningful conclusions. Instead, we must rely on paleomagnetic observations to build a more complete understanding. Unfortunately, the link between paleomagnetic observations and the underlying dynamics is neither simple nor direct. A promising new strategy will be developed using stochastic models to quantify the time dependence of the dipole field. This approach is ideally suited for the task because it focuses on the observed part of the field (i.e. the dipole), while treating the unobserved part of the magnetic field in a statistical fashion. The expected outcome of this work is two-fold. First, the stochastic models will enable the investigators to make quantitative predictions for many properties of the magnetic field, including the rates of reversal in the dipole polarity as well as the duration of short disruptions in the magnetic field (often called excursions). Second, the stochastic models are amenable to physical interpretation, which means that the team can make important advances in connecting paleomagnetic observations to physical processes deep inside the planet. Engagement of graduate and senior undergraduate students in the project will promote skills in physical modeling, data analysis, statistics, and high-performance computing.The proposed work identifies four main tasks. The first step is to construct stochastic models using observations of the dipole field over the past two million years. Predictions for the power spectrum of dipole fluctuations can be related to physical properties, like the electrical conductivity of the core or the overturn time for convection. The second task will address the autocovariance of the observed dipole fluctuations. Turbulent motions in Earth's core drive random fluctuations in the dipole field, so detailed estimates of the autocovariance offer unique insights into the mechanisms of dipole generation. The third task deals with the duration of polarity transitions with the aim of identifying timescales and processes at work during reversals. Finally, the investigators will quantitatively assess the relative occurrence of short chrons under the hypothesis that they represent polarity transitions when the initial state is not fully established in a stable polarity. At each stage they will assess the success or failure of the models by making detailed comparisons with available observations.

地球的磁场是我们星球可居住性的重要方面，但磁场的长期行为却鲜为人知。历史观察结果提供了宝贵的信息来源，但是该记录的持续时间太短了，无法得出有意义的结论。取而代之的是，我们必须依靠古磁观测来建立更完整的理解。不幸的是，古磁观测与基础动力学之间的联系既不简单也不是直接的。有希望的新策略将使用随机模型来量化偶极场的时间依赖性。这种方法非常适合该任务，因为它专注于观察到的场（即偶极子），同时以统计方式处理磁场的未观察到的部分。这项工作的预期结果是两个方面。首先，随机模型将使研究人员能够对磁场的许多特性做出定量预测，包括偶极极性中的逆转速率以及磁场中短时间干扰的持续时间（通常称为偏移）。其次，随机模型可以适合物理解释，这意味着团队可以在将古磁观测与地球内部深处的物理过程联系起来方面做出重要进展。研究生和高级本科生参与该项目将促进物理建模，数据分析，统计和高性能计算方面的技能。拟议的工作确定了四个主要任务。第一步是在过去的200万年中使用偶极场观察到的随机模型。偶极波动功率谱的预测可能与物理特性有关，例如核心的电导率或对流的推翻时间。第二个任务将解决观察到的偶极波动的自动振动。地球核心驱动偶极场中的动荡动作，因此对自动助力的详细估计为偶极子产生机理提供了独特的见解。第三个任务涉及极性转变的持续时间，目的是识别逆转过程中工作时间和过程。最后，研究者将在假设中代表极性转变时定量评估短期基础的相对出现，而当初始状态在稳定的极性中未完全确定。在每个阶段，他们将通过与可用观察结果进行详细比较来评估模型的成功或失败。