Collaborative Research: Improved Ionospheric Source Models for Imaging Upper Mantle/Transition Zone Resistivity

地球磁场的日变化主要是由于在我们上方的电离层中流动的电流，高度约为100-150公里，其次是由于我们下方导电地球内部深处感应的电流。这是一个合作项目，将固体地球和电离层科学家聚集在一起，努力更好地了解和区分这两个电流源。这项工作的一个主要动机是提高对更小和更微妙的内部成分的理解，从而提高成像地球深处(200-700公里)电导率变化的能力。这些深度的岩石的电导率对少量水都高度敏感，因此这些图像最终将有助于估计地球深处的水的数量和分布，并提高对地球深层水循环的了解。这些结果将对一些科学领域产生重要影响，包括地球的动态和演化以及海洋的演化。这项研究的关键一步是显著改进磁场的外部电离层分量的模型。这种磁场模型在地磁学和空间物理学的基础科学和应用科学研究中有许多潜在的重要应用。最终，它们将在需要精确磁场知识的具有直接社会意义的应用中发挥作用，包括导航、太阳电池阵的定向和对自然资源的地球物理勘探。结合最近关于地幔矿物电导率的实验室结果，改进的地幔电导率成像将提供有关地幔中水的宝贵新信息，可能对地幔流变学以及地球动力学和地球化学演化产生深远影响。有关地球深层电阻率的信息几乎完全来自对地球表面长期地磁变化的观测--电离层和磁层电流系统产生的外场和导电地球感应电流产生的内场的总和。每天0.5-10周(CPD)的频率与穿过大气层并进入过渡带的成像最相关，这些变化大多起源于100-150公里高度的电离层发电机区域。这些电离层电流依赖于时空变化的热层中性风和电离层电导率分布。为了可靠地解释指示地球电导率变化的相对微妙的感应信号，必须适当地考虑这些空间复杂的电离层磁场信号。该项目通过电磁感应成像专家和电离层物理和建模专家之间的合作来解决这一具有挑战性的问题。将利用历史和现代的大量地面地磁阵列数据，同时估计外部源和内部电导率变化的空间结构。提议的方法有两个新的组成部分。首先，采用稳健的主成分分析(PCA)方法对原始数据进行约简。这种主成分分析方案大大减少了数据的数量(从而减少了所需的独立源参数的数量)，并允许合并来自不同时代的数据，从而显著增加了数据覆盖率。其次，通过使用一个成熟的基于物理的电离层电流数值模式--Thermosphere-Ionosphere-Mesosphere-Electrodynamics通用环流模式(TIME-GCM)，对源模型进行了严格的约束。除了该团队立即应用于改进的电磁感应成像之外，这些努力可能会为电离层和更广泛的地磁界带来重大好处。例如，该项目包括时间-GCM输出与大量地面地磁数据之间的详细比较，从而洞察这一数值模式的优点和缺点。更广泛地说，为将地面数据纳入电离层磁场的时间相关模型而开发的方法将有利于对地球磁场的一系列基础和应用研究。

Daily variations of Earth's magnetic field result primarily from electric currents flowing above us in the ionosphere, at heights of about 100-150 km, with a secondary component due to currents induced below us in the deep interior of the electrically conducting Earth. This is a collaborative project, bringing solid Earth and ionospheric scientists together in an effort to better understand and separate the two current sources. A primary motivation for this effort is to improve understanding of the smaller and subtler internal component, and thence improve the ability to image electrical conductivity variations deep (200-700 km) in the Earth. Conductivity of rocks at these depths is highly sensitive to even small amounts of water, so these images will ultimately allow estimates the amount and distribution of water in the deep Earth, and improve understanding of deep Earth water cycles. These results will have important implications to a number of scientific fields, including the dynamics and evolution of the Earth and evolution of the oceans. The crucial step in this study is to significantly improve models of the external ionospheric component of the magnetic field. Such magnetic field models have many potentially important applications to basic and applied scientific research in geomagnetism and space physics. Ultimately they will be useful in applications of direct societal relevance where the knowledge of an accurate magnetic field is required, including navigation, orientation of solar arrays, and geophysical exploration for natural resources.In conjunction with recent laboratory results on electrical conductivity of mantle minerals, improved imaging of electrical conductivity in Earth's mantle will provide valuable new information about water in the mantle, with potentially profound implications for mantle rheology, and for the dynamics and geochemical evolution of the Earth. Information about deep Earth resistivity comes almost exclusively from observations of long-period geomagnetic variations observed on Earth's surface--the sum of external fields due to ionospheric and magnetospheric current systems, and internal fields due to currents induced in the conducting Earth. Frequencies of 0.5-10 cycles per day (cpd) are most relevant to imaging through the aesthenosphere and into the transition zone, and these variations mostly have their origin in the ionospheric dynamo region at 100-150 km height. These ionospheric currents depend on the spatial and temporal varying thermospheric neutral wind and the ionospheric conductivity distribution. To reliably interpret the relatively subtle induced signals indicative of Earth conductivity variations, these spatially complex ionospheric magnetic field signals must be properly accounted. This project attacks this challenging problem through collaboration between specialists in EM induction imaging and experts in ionospheric physics and modeling. Spatial structure of external source and internal conductivity variations will be estimated simultaneously, using a large collection of ground-based geomagnetic array data from both historical and modern eras. There are two novel components to the proposed approach. First, a robust Principal Components Analysis (PCA) scheme is used for initial data reduction. This PCA scheme massively reduces the number of data (and thus the number of independent source parameters required), and allows data from different eras to be merged, thus significantly increasing data coverage. Second, the source modeling is tightly constrained through the use of a mature physics based numerical model for ionospheric currents, the Thermosphere-Ionosphere-Mesosphere-Electrodynamics general Circulation Model (TIME-GCM). In addition to the team's immediate application to improved EM induction imaging, these efforts may provide significant benefits to the ionospheric and broader geomagnetic communities. For example, the project includes detailed comparison between TIME-GCM outputs and a large collection of ground geomagnetic data, providing insight into strengths and weaknesses of this numerical model. More broadly, approaches developed for incorporating ground-based data into time dependent models of ionospheric magnetic fields will benefit a range of basic and applied studies of Earth's magnetic field.