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.

这项研究将开发一种新的反演算法，应用于三维的全球电子密度随时间变化的图像，以量化的物理过程，驱动的密度分布。 理想的情况是，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结果，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，在实践中，地面仪器和卫星测量很少，因此不可能对物理过程进行评价。 在过去几年中，出现了两个新的发展，提供了一个新的方法来解决这个问题：在应用层析成像方法电离层成像取得了重大进展，和全球电离层数据具有良好的时间和空间分辨率，如总电子含量，现在可以通过互联网定期提供。 研究计划将从考虑离子连续性方程开始。 但不是试图一个数值解，代数矩阵反演将完成，这将纳入观察到的电子密度的时间变化率。 这项工作将分几个步骤进行。 算法的发展首先发生，使用电子密度从第一原理模型作为数值模拟实验室。 然后，同化模式将被用来构建三维电子密度随时间变化的地图。 反演将应用于这些数据集，驱动程序将在仪器齐全的地区推导出来，以便与雷达和法布里-珀罗干涉仪（FPI）的观测结果进行比较。 最后一步是将该算法应用于观测数据集，以获得诸如风暴时间增强密度等现象的驱动因素。 如果成功，这种方法将产生直接估计的中性风，电场，生产，损失和扩散条款。 研究的目标与CEDAR第三阶段文件一致，该文件指出，需要在确定制约热层/电离层对高纬度能量输入的反应的相互关联的过程方面取得进展。 具体来说，调查将集中在三个主要问题：什么是风暴增强密度和源等离子体，似乎饲料密度的物理驱动程序？ 什么是电离层变化的原因，如补丁？ 全球三维电子密度随时间变化的地图是否可以用来约束离子连续性方程，以获得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或同化模型的驱动因素，并验证三维第一性原理模型。 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时间相关的地图。 一名研究生将参与该项目的兼职以及国际合作者，博士。N.米切尔在英国巴斯大学。