Elements: Spatiotemporal Analysis of Magnetic Polarity Inversion Lines (STEAMPIL)

极端空间天气事件，如太阳耀斑、日冕物质抛射、高能质子事件和地磁风暴，可能会在许多技术复杂的系统中造成大规模破坏，包括无线电通信、电信和导航卫星、电力系统、或空间，甚至商业航空飞行。该项目建立了一个探测和分析网络基础设施，并调查了太阳大气中最明显的特征之一--磁极反转线，这是最强烈喷发活动的热点。分析这些特征使太阳物理学家能够提高对极端空间天气事件的理解，并为空间天气预报员提供所需的预测能力。该项目创建了一个创新和可持续的软件基础设施，用于检测、表征和分析极性反转线。迈向这一目标的第一步是识别极性反转线，并通过图像描述符对这些多方面特征进行定量表征。在随后的阶段，该项目使用先进的机器学习和数据挖掘技术分析这些特征和描述符的时间序列，特别是为了提高空间天气预报能力。这包括分析极性反转线的出现和消失的时空模式，选择和了解与太阳喷发活动有关的这些线的重要形状特征，以及利用已发现的前兆建立喷发预报系统的原型。自动识别和分析极性反转线有几个直接的好处：物理上理解太阳磁场剪切层和从典型的非喷发活动区状态到强烈喷发状态的转变；对太阳喷发的预测做出贡献；产生对自然界剪切层研究有用的描述符和方法。这项由高级网络基础设施办公室颁发的奖项由太阳地球物理计划和美国国家科学基金会地球科学局内的综合和合作教育与研究部联合支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Extreme space weather events such as solar flares, coronal mass ejections, energetic proton events and geomagnetic storms can cause massive disruptions in many technologically complex systems, including radio communications, telecommunication and navigation satellites, electrical power systems, or space and even commercial airline flights. This project builds a detection and analysis cyberinfrastructure, and investigates one of the most distinctive features in the solar atmosphere – magnetic polarity inversion lines, which are hotspots of the most intense eruptive activity. Analyzing these features enables solar physicists to advance understanding of extreme space weather events and provide needed predictive capabilities for space weather forecasters.This project creates an innovative and sustainable software infrastructure to detect, characterize and analyze polarity inversion lines. The first step toward that objective is the identification of polarity inversion lines, and quantitative characterization of these multi-faceted features through image descriptors. In subsequent stages, this project analyzes the time series of these features and descriptors using advanced machine learning and data mining techniques, specifically for improving space weather forecasting capabilities. This includes analyzing the spatiotemporal patterns of emergence and disappearance for polarity inversion lines, selecting and understanding important shape characteristics of these lines pertinent to solar eruptive activity, and creating a prototype eruption forecasting system with discovered precursors. Automatically identifying and analyzing polarity inversion lines has several direct benefits: physically understanding solar magnetic shear layers and the transition from typical non-eruptive active region states to intense, eruptive ones; making contributions to forecasting of solar eruptions; and generating descriptors and measures that can be useful to the study of shear layers in nature.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Solar Terrestrial Physics Program and the Division of Integrative and Collaborative Education and Research within the NSF Directorate for Geosciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.