Collaborative Research: Inferring High Latitude Convection Patterns Using SuperDARN, DMSP and ACE

将利用超级DARN和DMSP沿着的电离层对流观测以及ACE太阳风观测来建立一个新的高纬度对流模型。该方法将使用数据插值正交函数（DINOFs）。DINEOF是一种基于数据的技术，它确定了一组有限的基函数及其演变，最好地描述了数据集。基函数将用于研究极冠对流和太阳风之间的相互作用。 该技术可将两个电离层数据集合并起来，并将填补数据记录中的空白，而不像目前那样使用面元平均法。该方法是严格的，并提供误差估计。该模型将提供两半球对流的时空特征，对磁层和电离层的研究具有一定的参考价值。这是一个年轻的研究人员刚刚开始他的职业生涯，并将支持在得克萨斯大学达拉斯博士后研究员。弗吉尼亚理工大学将资助一名研究生。

Observations of ionospheric convection from SuperDARN and DMSP along with ACE solar wind observations will be used to develop a new high-latitude convection model. The approach will be to use Data Interpolating Orthogonal Functions (DINEOFs). DINEOFs are a data-based technique that determines a limited set of basis functions and their evolution that best describes a data set. The basis functions will be used to study the interaction between polar cap convection and the solar wind. The technique allows the two ionospheric data sets to be combined and will fill gaps in the data record without using bin-averaging as is presently done. The approach is rigorous and provides error estimates. The resulting model will provide spatial and temporal characteristics of the convection for both hemispheres.This model will be valuable to other magnetospheric and ionospheric researchers. It is from a young researcher just starting his career and will support a post-doctoral researcher at the University of Texas at Dallas. A graduate student will be supported at Virginia Tech.