SHINE: Understanding the Physical Connection of the in-situ Properties and Coronal Origins of the Solar Wind with a Novel Artificial Intelligence Investigation

了解太阳风对空间气象科学和预报至关重要，因为太阳风等离子体的特性影响地球周围空间环境的局部条件。这些条件在很大程度上是太阳风等离子体携带的速度、结构和磁场的结果。该项目解决了太阳，日光层和行星际环境（SHINE）的目标，即通过利用现代人工智能（AI），机器学习（ML）和大数据分析算法来分析太空和NSF资助的地面日冕观测的研究来了解太阳风。该项目由一位早期职业女性科学家领导，是跨学科的，建立了太阳物理学家和数据科学家之间的合作。该项目是一个为期四年的研究计划，将最先进的AI/ML技术应用于过去、当前和未来任务的太阳风原位测量。目标是对太阳风的类型进行分类，并确定其日冕源区，以了解太阳风的原地特性与其日冕起源之间的物理联系。该团队将使用美国宇航局天基任务的可用观测数据，包括高级成分探测器，风，帕克太阳探测器，太阳能探测器，以及太阳轨道器（SO）1。来自太阳和日光层观测台、日地关系观测台、日出、太阳动力学观测台和太阳观测站的光谱数据将提供太阳风源区的磁场几何形状和基本等离子体诊断。此外，NSF资助的地面日冕图，如CoMP（2011-2018），MK4（1998-2013年），KCor（2013年至今），并在可用时，UCoMP 2将用于提供额外的太阳背景数据和等离子体诊断。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查进行评估，被认为值得支持的搜索.

Understanding the solar wind is crucial to space weather science and forecasting because the properties of the solar wind plasma affect the local conditions in the space environment around Earth. These conditions are largely the result of the speed, structure, and magnetic fields carried by the solar wind plasma. This project addresses the Solar, Heliospheric, and Interplanetary Environment (SHINE) goal of understanding the solar wind, through research that utilizes modern Artificial Intelligence (AI), Machine Learning (ML) and big data analysis algorithms to analyze space-based and NSF-funded ground based coronagraph observations. The project is led by an early career female scientist and is cross-disciplinary, building a collaboration between solar physicists and data scientists. Graduate and undergraduate student researchers from under-represented groups in STEM will be supported.The project is a four-year research program that applies state-of-the-art AI/ML technology to in-situ solar wind measurements from past, current, and future missions. The goal is to classify solar wind types and to determine their coronal source regions, to understand the physical connection between the solar wind’s in-situ properties and their coronal origins. The team will use available observations from NASA space-based missions including the Advanced Composition Explorer, Wind, Parker Solar Probe, Ulysses and when available, Solar Orbiter (SO) 1. Spectroscopic data from the Solar and Heliospheric Observatory, Solar Terrestrial Relations Observatory, Hinode, Solar Dynamics Observatory and SO will provide magnetic field geometry and basic plasma diagnostics of the solar wind source regions. Furthermore, NSF-funded ground based coronagraphs such as CoMP (2011-2018), MK4 (1998-2013), KCor (2013-today) and, when available, UCoMP2 will be used to provide additional solar context data and plasma diagnostics.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.