Space Weather: Advancement and Validation of Real-Time Assimilative Mapping of Ionospheric Electrodynamics (AMIE) for Space Weather Applications

对高纬度电离层电势分布和极光结构的实时了解对于研究和业务空间天气需求都是重要的。该项目将推动电离层电动力学的规范和预测。具体地说，将建立一个新的、时变的高纬度电势经验模型。使用电离层电动力学（AMIE）技术的同化映射将推导出单个电位模式。自1997年以来，已经进行了500多万次AMIE反演，这些反演将构成数据库的核心。已经使用和将要使用的主要数据集是对地球表面磁场变化的测量。其他数据来源将包括来自Sondrestrom和Millstone Hill雷达的非相干散射雷达数据以及来自电离层探测器的电子密度数据。建模的一个新功能是将全天白光图像包含到实时AMIE中。这将极大地帮助实时规范极光的位置、范围和强度。此外，它将允许一个更好的规格的电势通过改进电导。AMIE技术将通过引入自适应网格细化（AMR）来改进。AMR将由极地地球物理数据的间距控制，以便在有多个数据源的区域，AMIE将特征分解到适当的尺度。经验模型将考虑极帽电位降饱和的影响。目前的经验模型没有考虑到饱和效应，这种效应发生在太阳风驱动异常强烈的时候，因此它们预测在这种时期极帽电位会出现不切实际的大下降。为了验证经验模型，将开发一个自动化系统，将实时AMIE模式与DMSP粒子降水和电势数据进行连续比较。然后将实时AMIE结果与经验模型进行比较。结果将公布在一个网站上，供公众查阅。该项目还具有教育/推广和多样性影响。一名来自底特律少数族裔地区的高中科学教师将参与该项目，并将建立一个自动电子邮件系统，当某个特定的夜晚可能看到极光时，订户将收到通知。底特律地区的教师将使用这个工具帮助学生更多地了解近地空间环境。

A realistic timely knowledge of the high latitude ionospheric electric potential pattern and auroral configuration is important for both research and operational space weather needs. This project will advance the state of the art in specification and prediction of the ionospheric electrodynamics. Specifically, a new, time-dependent, empirical model of the high latitude electric potential will be developed. Individual electric potential patterns will be derived using the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) technique. Since 1997, over 5 million AMIE inversions which have been performed and these inversions will form the core of the database. The primary data sets that have been used and will be used are measurements of the variations in the magnetic field at the earth's surface. Additional data sources will include incoherent scatter radar data from the Sondrestrom and Millstone Hill radars and electron density data derived from ionospheric sounders. A new feature of the modeling will be the inclusion of all-sky white light images into real-time AMIE. This will dramatically help the real-time specification of the auroral location, extent, and strength. In addition, it will allow a better specification of the electric potential through the improvement in the conductance. The AMIE technique will be improved by incorporating adaptive mesh refinement (AMR). The AMR will be controlled by the spacing of the polar geophysical data, such that in regions in which there are multiple data sources, AMIE will resolve features to the appropriate scale. The empirical model will include the effect of saturation of the polar cap potential drop. No current empirical model of the potential takes the saturation effect, which occurs when the solar wind driver is exceptionally strong, into account, and they therefore predict unrealistically large polar cap potential drops during such periods. In order to validate the empirical model, an automated system in which real-time AMIE patterns are continuously compared to DMSP particle precipitation and electric potential data will be developed. The real-time AMIE results will then be compared with the empirical model. The results will be posted on a web site for public inspection. The project also has an educational/outreach and diversity impact. A high school science teacher from a predominantly minority region of Detroit will take part in project, and an automated e-mail system will be set up whereby subscribers will be notified when it is likely that aurora may be viewed that particular night. Teachers in the Detroit area will use this tool to help students learn more about the near-Earth space environment.