Solar Wind Magnetosphere Coupling Functions: Practicalities and Physicalities

最近，人们发现了一个数学函数，可以预测太阳风如何在各种近地空间条件下与磁层耦合，以及磁层和电离层中的各种现象。这一发现产生了几个具有重大地球物理意义和实际意义的问题。一种是通过两种不同的方式检查不平衡（快速）日面合并的实例来确定绝对日面磁合并率（而不是比例）。一种方法是使用电离层尖端的纬度与适当的磁场模型进行比较，另一种方法是在一个快速增长的间隔内检查极帽通量的变化。这两种太阳风驱动的预测使得改进地磁活动预测的发展成为可能。这将有可能产生一个更基于物理的、可操作的重要磁指数预测器，如Kp和AE。全球合并速率对行星际磁场锥角的敏感性也将得到更充分的探讨。这笔资金的一部分将用于支持一位年轻的博士后科学家。该项目还将涉及弗吉尼亚理工大学和JHU/APL的科学家之间的合作。这也将为国防气象卫星计划（DMSP）向一般空间科学界分发粒子降水数据提供部分资金。DMSP数据，从原始数据到时间-能量谱再到各种高级数据抽象，被世界各地的研究人员使用。年轻科学家是这个由nsf资助的数据分发系统的重度使用者。

Recently a mathematical function was discovered that predicts how the solar wind couples to the magnetosphere for a wide variety of near-Earth space conditions and for a wide variety of phenomena in the magnetosphere and ionosphere. Several questions of significant geophysical interest and practical consequence arise from this discovery. One is to determine the absolute dayside magnetic merging rate (instead of a proportionality) by examining instances of unbalanced (rapid) dayside merging in two different ways. One method uses the latitude of the ionospheric cusp compared to appropriate magnetic field models, and the other examines changes in polar cap flux over an interval of rapid growth. These two predictors of solar wind driving allow the development of improved geomagnetic activity predictors. This will make it possible to produce a more physics based, operational predictor of important magnetic indices such as Kp and AE. The sensitivity of the global merging rate to the interplanetary magnetic field (IMF) cone angle will also be more fully explored.Part of this funding will support a young,post-doctoral scientist. The project will also involve a collaboration between scientists at the Virginia Tech and JHU/APL. This will also provide partial funding for the distribution of particle precipitation data from the Defense Meteorological Satellite Program (DMSP) to the general space science community. The DMSP data, from raw data to time-energy spectrograms to various high-level data abstractions, are used by researchers around the world. Young scientists are particularly heavy users of this NSF-funded data distribution system.