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

切实、及时地了解高纬度电离层电势模式和极光配置对于空间气象的研究和业务需要都很重要。这一项目将促进电离层电动力学的描述和预测的最新水平。具体地说，将开发一个新的、与时间相关的高纬度电势的经验模型。将使用电离层电动力学同化映射(AMIE)技术得出单独的电势模式。自1997年以来，已进行了500多万次AMIE倒置，这些倒置将构成数据库的核心。已经使用和将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仪的电子密度数据。建模的一个新功能将是将全天空白光图像包含到实时AMIE中。这将极大地帮助实时指定极光的位置、范围和强度。此外，通过改善电导，它将允许更好地规范电势。AMIE技术将通过结合自适应网格细化(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中，AMIE将以适当的比例解析要素。经验模型将考虑极帽电位降饱和的影响。目前的电势经验模型都没有考虑到饱和效应，这是在太阳风驱动异常强烈时发生的，因此他们预测在这样的时期内极冠电势下降得不切实际。为了验证经验模型，将开发一个自动化系统，在该系统中，实时AMIE模式与DMSP粒子降水和电位数据进行连续比较。然后将实时AMIE结果与经验模型进行比较。选举结果将公布在网站上，供公众查阅。该项目还具有教育/外联和多样性的影响。来自底特律以少数民族为主的地区的一名高中理科教师将参加该项目，并将建立一个自动电子邮件系统，当可能在特定晚上看到极光时，将通知订阅者。底特律地区的教师将使用这一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.