The Role of Electric Fields in Space Weather

研究磁层对太阳风动力强迫的反应对于预测这种驱动对空间和地面技术系统的影响特别有意义。在这方面，一个诊断特别差的参数是由磁重联驱动的电场。虽然我们了解基本过程，但我们仍然不了解增强的电场对磁层所有区域的影响，例如为其他过程提供种子种群以产生更高能量的粒子、造成影响航天器轨道的密度变化等。该项目将主要侧重于分析各种不同系统从空间和地面测量的电场测量结果，还将涉及在提高我们的预测能力方面使用数值模拟。数据分析将基于(一)欧空局飞行任务群；(二)多国飞行任务组的现有数据集；以及(三)由北半球多个观测站的数据组成的SuperDARN数据集。虽然有几种数据分析方法可以产生全球速度场，从而产生电场，但学生将研究最合适的方法，将来自磁层不同位置的这些不同项目的数据汇集在一起。这将需要(1)确定选择感兴趣区间的标准；(2)使用这些标准来确定这些区间；(3)从每个数据集中确定最合适的数据产品的格式。随后的建模将包括一组试运行，以调查模型对电场变化的敏感度，包括时间和空间。

The investigation of the response of the magnetosphere to the dynamic forcing by the solar wind is of particular interest in forecasting the impact of this driving on technological systems, both space and earth based. A particularly poorly diagnosed parameter in this respect is the electric field which is driven by magnetic reconnection. While we understand the fundamental processes we remain ignorant of the impact of enhanced electric fields in all areas of the magnetospheres, for example providing seed populations for other processes to create higher energy particle, creating changes in the density which affect spacecraft orbits, etc. The project will investigate the impact of the electric field measured in the ionosphere on technological system. The project will primarily focus on the analysis of measurements of electric fields measured by a variety of different systems from both space and ground and will also touch upon the use of numerical simulation in terms of improving our predictive capability. The data analysis will be based on existing data sets from (i) the ESA mission SWARM; (ii) the Cluster mission) and finally (iii) SuperDARN data set which consists of data from multiple observatories in the northern hemisphere. Although several data analysis methods exist to produce the global velocity field, and hence electric field, the student will investigate the most appropriate ways to bring together data from these different projects which come from different locations in the magnetosphere. This will require (i) determining the criteria for selecting intervals of interest; (ii) using these criteria to identify those intervals; (iii) and determining the format of the data products most appropriate from each data set. The subsequent modeling will consist of a set of trial runs to investigate the sensitivity of the model to the electric field variations, both in time and space.