CEDAR: Obtaining Physical Drivers from Ionospheric Imaging

这项研究将开发一种新的反演算法，应用于全球电子密度的三维随时间变化的图像，以便量化驱动密度分布的物理过程。理想情况下，电离层科学家将获得离子连续性方程驱动因素的直接全球测量，即风、电场、中性和离子组成和密度以及中性和离子温度。然而，实际上地面仪器和卫星测量非常少，因此不可能对物理过程进行评估。在过去几年中，出现了两项发展，为解决这一问题提供了新的途径：在将层析成像方法应用于电离层成像方面取得了重大进展，现在可以通过因特网定期获得具有良好时间和空间分辨率的全球电离层数据，如总电子含量。研究计划将从考虑离子连续性方程开始。但不是尝试数值解，而是进行代数矩阵求逆，其中将包含观察到的电子密度变化的时间速率。这项工作将分几个步骤进行。该算法的开发是首先进行的，使用第一原理模型中的电子密度作为数值模拟实验室。然后，将使用同化模型来构建电子密度的三维随时间变化的地图。反演将应用于这些数据集，并将在仪器良好的区域推导出驱动程序，以便将它们与雷达和法布里-珀罗涉仪(FPI)的观测结果进行比较。最后一步是将算法应用于观测数据集，以得出风暴时间密度增强等现象的驱动因素。如果成功，这种方法将产生中性风、电场、生产、损失和扩散项的直接估计。这项研究的目标与Cedar第三阶段文件一致，该文件指出，需要在确定管理热层/电离层对高纬度能量输入反应的相互关联的过程方面取得进展。具体地说，调查将集中在三个主要问题上：风暴密度增加的物理驱动因素是什么，以及似乎为密度提供来源的等离子体？电离层变化的原因是什么，如斑块？电子密度的全球三维时间相关图能否被用来约束离子连续性方程，以得出对观测到的电子密度分布负责的潜在物理驱动因素的估计？研究结果可用于估计机械模型或同化模型的驱动因素，并验证三维第一原理模型。在这个项目中开发的数学技术可以应用于任何地球物理问题，其中物理方程可以与三维随时间变化的地图相关。一名研究生将兼职参与该项目，英国巴斯大学的国际合作者C·N·米切尔博士也将参与。

This investigation will develop a novel inversion algorithm to be applied to three-dimensional time-dependent images of global electron density in order to quantify the physical processes that are driving the density distribution. Ideally, ionospheric scientists would obtain direct global measurements of the drivers of the ion continuity equation, namely the winds, electric fields, neutral and ion composition and densities, and neutral and ion temperatures. However, in practice there are so few ground-based instrument and satellite measurements that evaluation of the physical processes is not possible. In the past few years, two developments have occurred which offer a new way to approach the problem: significant advances have been made in applying tomographic methods to ionospheric imaging, and global ionospheric data with good time and spatial resolution, such as total electron content, are now routinely available through the internet. The research plan will start with consideration of the ion continuity equation. But rather than attempt a numerical solution, an algebraic matrix inversion will be done which will incorporate observed time rates of change of the electron densities. The work will be performed in several steps. The development of the algorithm occurs first, using electron densities from a first-principles model as a numerical simulation lab. Then an assimilative model will be used to construct three-dimensional time-dependent maps of electron densities. The inversion will be applied to these datasets, and the drivers will be derived over well-instrumented regions so that they may be compared with observations from radars and Fabry-Perot interferometers (FPIs). The final step is to apply the algorithm to observational datasets to derive the drivers of phenomena such as storm-time enhanced densities. If successful, this approach will yield direct estimates of the neutral winds, electric fields, production, loss, and diffusion terms. The goals of the research are consistent with the CEDAR Phase III Document which stated that progress is needed in identifying the interrelated processes governing the thermosphere/ionosphere response to high latitude energy inputs. Specifically, the investigation will focus on three main questions: What are the physical drivers of storm enhanced densities and the source plasma that appears to feed the densities? What are the causes of ionospheric variability such as patches? Can global three-dimensional time-dependent maps of electron density be used to constrain the ion continuity equation to derive estimates of the underlying physical drivers responsible for the observed electron density distributions? The results of the research could be used to estimate the drivers of mechanistic or assimilative models and to validate three-dimensional first principles models. The mathematical techniques developed in this project can be applied to any geophysical problem where a physical equation can be related to three-dimensional time-dependent maps. A graduate student will participate in the project part-time as well as an international collaborator, Dr. C. N. Mitchell at the University of Bath, United Kingdom.