Papadimitriou Constantinos, Balasis Georgios, Boutsi Adamantia Zoe, Daglis Ioannis A, Giannakis Omiros, Anastasiadis Anastasios, Michelis Paola De, Consolini Giuseppe
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Metaxa and Vas. Pavlou St., Penteli, 15236 Athens, Greece.
Space Applications & Research Consultancy, SPARC P.C., 10551 Athens, Greece.
Entropy (Basel). 2020 May 19;22(5):574. doi: 10.3390/e22050574.
The continuously expanding toolbox of nonlinear time series analysis techniques has recently highlighted the importance of dynamical complexity to understand the behavior of the complex solar wind-magnetosphere-ionosphere-thermosphere coupling system and its components. Here, we apply new such approaches, mainly a series of entropy methods to the time series of the Earth's magnetic field measured by the Swarm constellation. We show successful applications of methods, originated from information theory, to quantitatively study complexity in the dynamical response of the topside ionosphere, at Swarm altitudes, focusing on the most intense magnetic storm of solar cycle 24, that is, the St. Patrick's Day storm, which occurred in March 2015. These entropy measures are utilized for the first time to analyze data from a low-Earth orbit (LEO) satellite mission flying in the topside ionosphere. These approaches may hold great potential for improved space weather nowcasts and forecasts.
非线性时间序列分析技术的工具库不断扩展，最近凸显了动力学复杂性对于理解复杂的太阳风-磁层-电离层-热层耦合系统及其各组成部分行为的重要性。在此，我们将此类新方法，主要是一系列熵方法，应用于由“蜂群”星座测量的地球磁场时间序列。我们展示了源自信息论的方法在定量研究“蜂群”高度处电离层顶部动力学响应复杂性方面的成功应用，重点关注2015年3月发生的第24太阳活动周最强烈的磁暴，即圣帕特里克节风暴。这些熵度量首次被用于分析来自在电离层顶部飞行的低地球轨道（LEO）卫星任务的数据。这些方法对于改进空间天气临近预报和预报可能具有巨大潜力。
