CEDAR: Obtaining Physical Drivers from Ionospheric Imaging

CEDAR：从电离层成像获取物理驱动因素

• 批准号: 0640955
• 负责人: Gary Bust
• 金额: $ 29.93万
• 依托单位: ATMOSPHERIC & SPACE TECHNOLOGY RESEARCH ASSOCIATES, L.L.C.
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-10-01 至 2010-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0640955&HistoricalAwards=false
• 关键词: CEDAR; Obtaining; Physical; Drivers; Ionospheric

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.

这项研究将开发出一种新型的反转算法，该算法适用于全球电子密度的三维时间依赖性图像，以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对离子连续性方程驱动因素的直接测量，即风，电场，中性和离子组成以及密度以及中性和离子温度。 但是，实际上，地面仪器和卫星测量很少，因此无法评估物理过程。 在过去的几年中，发生了两项发展，这些发展提供了一种解决问题的新方法：在将层析成像方法应用于电离层成像方面已取得了重大进展，现在可以通过互联网常规获得具有良好时间和空间分辨率（例如总电子含量）的全球电离层数据。 研究计划将从考虑离子连续性方程式开始。 但是，将进行代数矩阵倒置，而不是尝试使用数值解，它将结合观察到的电子密度变化时间率。 这项工作将通过几个步骤进行。 该算法的开发首先使用第一原理模型的电子密度作为数值模拟实验室。 然后，同化模型将用于构建电子密度的三维时间依赖性图。 反转将应用于这些数据集，并将驱动器衍生在备受瞩目的区域上，以便将它们与雷达和Fabry-Perot干涉仪（FPIS）的观察结果进行比较。 最后一步是将算法应用于观察数据集，以得出现象的驱动因素，例如风暴时间增强的密度。 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。 该研究的目标与Cedar III期文档一致，该文档指出，在确定控制热层/电离层对高纬度能量输入的相互关联的过程中需要进展。 具体来说，调查将重点放在三个主要问题上：风暴增强的物理驱动因素和似乎可以喂养密度的源血浆是什么？ 电离层变异性（例如斑块）的原因是什么？ 是否可以使用全局的三维时间依赖性图来限制离子连续方程以得出负责观察到的电子密度分布的基础物理驱动器的估计？ 该研究的结果可用于估计机械或同化模型的驱动因素，并验证三维第一原理模型。 该项目中开发的数学技术可以应用于任何地球物理问题，在这些地球物理问题上，物理方程可能与三维时间相关图有关。 一名研究生将兼职参加该项目，以及国际合作者，英国巴斯大学的C. N. Mitchell博士。