Statistical Spectrum Estimation and Solar Gravity Modes

我们建议继续研究太阳正常模式与空间等离子体传播之间的联系，以及这些模式对地球的影响。我们1995年对这些模式的发现，从对科学数据的好奇，到手机系统的通话中断，再到最近，在地球磁层的高能电子中发现了太阳引力模式（g模式）。这与理论和模拟相结合，正在逐渐改变人们对太空等离子体传播方式的看法，以及对日地耦合的看法。未来几年的一项主要任务将是继续进行基础科学研究，包括改进我们对模式的统计特征，它们的传播特性，以及更深入地研究将它们耦合到各种地面系统中的机制。例如，我们知道这些模式是蜂窝电话系统中很大一部分掉线的原因，但不知道大气或电离层物理学的原因。我预计，g模式的工作将最终导致空间天气预报的改进，其应用范围从地质勘探、空中交通管制到电网稳定。同时，我计划继续完善统计和分析工具，使这种变革性研究成为可能。由于更好的数据分析方法，特别是估计光谱和相干的多锥度方法，科学和工程上的发现才有可能。对学生进行这些统计方法的培训将有助于将这些新工具推广到加拿大的工业中，他们可以期望对依赖于时间序列数据可靠性的广泛应用进行改进。这些领域包括手术安排、财务预测、减少石油管道腐蚀以及改善北极地区的通信。

We propose to continue studying the connection between normal modes of the Sun, propagation in space plasmas, and the effects of these modes on Earth. Our 1995 discovery of these modes has snowballed from a curiosity in scientific data, to dropped calls on cellular phone systems, and most recently, to the identification of a solar gravity mode (g-mode) in high-energy electrons in Earth's magnetosphere. This, combined with theory and simulations, is gradually changing peoples' views of how propagation in space plasmas works and, with it, views of solar-terrestrial coupling. A major task of the next few years will be to continue the basic scientific research including refinements in our statistical characterization of the modes, their propagation properties, and more intensive study of the mechanisms that couple them into various terrestrial systems. For example, we know that these modes are responsible for a large fraction of the dropped calls in cellular phone systems, but do not know the atmospheric or ionospheric physics responsible. I anticipate that the work on g-modes will lead to eventual improvements in space weather forecasts with applications ranging from geological prospecting, to air traffic control, to stability of power grids.Simultaneously, I plan to continue refining the statistical and analytic tools that make such transformative research possible. The scientific and engineering discoveries have only been possible because of better data analysis methods, in particular the multitaper method of estimating spectra and coherences.Training students in these statistical methods will help spread these new tools into Canadian industry, where they can be expected to make improvements to a wide range of applications which depend upon the reliability of time series data. These areas are as diverse as surgical scheduling, financial forecasting, reducing corrosion in oil pipelines, and better communication in the Arctic.