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

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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.