The input from the solar wind (SW) and the accompanying Interplanetary Magnetic Field (IMF) is the defining feature of the solar wind-magnetosphere interactions. One of the most important SW drivers is the solar wind dynamic pressure, and most significantly its sharp changes known as pressure fronts. Sudden enhancements in solar wind dynamic pressure, , have been shown to lead to intensification of the auroral electrojets (and Region 1 field-aligned currents), increase in auroral emissions, and significant enhancement in ionospheric convection and the transpolar potential. Case studies of the interaction between pressure fronts and the terrestrial space environment shed great light on their importance to the structure and dynamics of the system. However, thorough understanding of the interaction requires fully statistical investigations. These statistical studies require a large number of suitable pressure front events. In the past these have been obtained through laborious manual inspection of solar wind data. We present an automated procedure that identifies sudden step enhancements in that satisfy a desired set of limiting step-like characteristics, such as magnitude of the change, sign of the change (positive/negative), and rate of change. The procedure yields a list of suitable events, along with their step features within minutes. The technique is tested for missed events and false positives by direct comparison to manual inspection of the data. Its utility is illustrated by application to the statistical effect of pressure fronts to the transpolar potential as measured by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) technique.

中文翻译：

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用于检测阶梯状太阳风动态压力变化的自动化技术：应用于跨极电位对太阳风动态压力前​​沿的响应

来自太阳风 (SW) 和伴随的行星际磁场 (IMF) 的输入是太阳风-磁层相互作用的定义特征。最重要的 SW 驱动因素之一是太阳风动态压力，最重要的是它的急剧变化称为压力前沿。太阳风动态压力的突然增强，，已被证明会导致极光电射流（和区域 1 场对齐电流）的增强、极光发射的增加以及电离​​层对流和跨极电位的显着增强。压力锋与地球空间环境之间相互作用的案例研究揭示了它们对系统结构和动力学的重要性。然而，对相互作用的透彻理解需要充分的统计调查。这些统计研究需要大量合适的压力前沿事件。过去，这些是通过人工检查太阳风数据获得的。我们提出了一个自动化程序，可以识别在满足一组所需的限制阶跃特征，例如变化的幅度、变化的符号（正/负）和变化率。该过程会在几分钟内生成一个合适的事件列表，以及它们的步骤特征。该技术通过与手动检查数据的直接比较来测试遗漏事件和误报。它的效用通过应用电离层电动力学同化映射 (AMIE) 技术测量的压力前沿对跨极电位的统计效应来说明。