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.

中文翻译：

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使用熵测量的 2015 年圣帕特里克节磁暴在群高度的动力学复杂性

非线性时间序列分析技术的不断扩展工具箱最近强调了动力学复杂性对于理解复杂的太阳风-磁层-电离层-热层耦合系统及其组件的行为的重要性。在这里，我们将新的此类方法，主要是一系列熵方法应用于 Swarm 星座测量的地球磁场时间序列。我们展示了源自信息理论的方法的成功应用，以定量研究在 Swarm 高度的上部电离层动态响应的复杂性，重点关注太阳活动周期 24 中最强烈的磁暴，即圣帕特里克节风暴，发生在 2015 年 3 月。这些熵度量首次用于分析在上层电离层飞行的低地球轨道 (LEO) 卫星任务的数据。这些方法可能在改进空间天气临近预报和预报方面具有巨大潜力。