Spatiotemporal Development and Forecasting of Space Storms

这个项目将应用和扩展两种新方法来解决重铸磁暴的问题。特别是，它将开发基于地面磁指数的极端事件预测工具。它还将开发工具，以准确预测由磁暴产生的地面局部磁场波动。风暴期间和风暴之前的局部预报特别重要，因为磁层-电离层系统的耦合产生了地球空间和地面磁场的变化，其统计性质随当地时间和纬度而变化。该项目将开发基于(1)风暴之间高于（低于）某一阈值的等待时间的统计和(2)量化磁波动的时间变化并纳入太阳风驱动波动的符号动力学方法的风险估计方法。近年来，人们开发了一些工具，可以分析以突然转变和极端事件为特征的数据，比如太空风暴。这些进步是基于动力系统理论和统计物理方法的结合而实现的。越来越多的研究提供证据表明，磁层的行为就像一个复杂的系统，具有突然转变和极端事件，具有独特的统计结构，包括重尾利维型行为。由于这种复杂性，有可能利用数据统计对风暴风险进行概率危害评估。这些预测主要基于小扰动与未来大风暴的关联。该项目将检查驱动器和磁层的非线性行为相互作用产生空间风暴的方式，特别是那些没有明显的总体触发因素的空间风暴。美国社会的日常运转依赖于诸如配电系统和通信卫星群之类的技术。这些技术都容易受到磁暴（也称为太空风暴）的影响。社会对这些技术的依赖日益增加，意味着需要了解和预测磁层的时空波动。除了提高预测重要空间天气现象的能力外，该项目还将包括由本科生进行的有意义的研究。

This project will apply and extend two new approaches to the problem of recasting magnetic storms. In particular it will develop tools for forecasting of extreme events in ground-based magnetic indices. It will also develop tools for accurately predicting local magnetic fluctuations on the ground that are generated by magnetic storms. Local forecasts during and prior to storms are particularly important since coupling of the magnetosphere-ionosphere system produces geospace and ground magnetic variations whose statistical properties vary with both local time and latitude. The project will develop risk estimation methods based on (1) the statistics of the waiting times between storms above (below) a certain threshold, and (2) a symbolic dynamics method which quantifies temporal variations in the magnetic fluctuations and incorporates the solar wind driving fluctuations. Recent years have witnessed the development of tools that allow for the analysis of data that feature sudden transitions and extreme events, like space storms. These advances have been made possible by a combination of approaches based on dynamical systems theory and statistical physics. A growing catalogue of research provides evidence that the magnetosphere behaves like a complex system with sudden transitions and extreme events that have a distinct statistical structure, including heavy-tailed Levy-type behavior. Because of this complex nature it is possible to leverage the data statistics to make probabilistic hazard assessments for storm risk. These are primarily based on the association of small disturbances with future large storms. The project will examine the way in which the nonlinear behavior in the driver and the magnetosphere interact to produce space storms, especially those for which there is no obvious gross trigger. American society relies upon technologies such as power distribution systems and constellations of communications satellites for its daily functioning. These technologies are all susceptible to the effects of magnetic storms (also called space storms). Increased societal dependence on these technologies implies the need to understand and predict spatiotemporal fluctuations in the magnetosphere. In addition to the improved ability to predict important space weather phenomena the project will include meaningful research performed by undergraduate students.