The Mechanism of the Solar Dynamo Governing Space Climate and Space Weather

太阳发电机调控空间气候和空间天气的机制

• 批准号: 2233852
• 负责人: Fadil Inceoglu
• 金额: $ 15.07万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2026-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2233852&HistoricalAwards=false
• 关键词: Mechanism; Solar; Dynamo; Governing; Space

Long-term and short-term variations in the magnetic activity of the sun profoundly influence space weather on Earth and space climate. Past solar activity shows periods of extended minima, which are still not well understood. This project will address questions related to the cause and characteristics of grand minima in solar activity, how the character of solar activity changes during these periods, and whether these changes can be modeled/predicted. The methodology uses a combination of observations of sunspot numbers, isotope time series, machine learning techniques, and numerical modeling. The results will provide constraints on the solar dynamo that generates the changing magnetic fields on the sun, which causes space weather. The broader impacts will be to improve our understanding of our space climate and space weather that affect our ground-, air- and space-based technological systems. This project supports an early career researcher.The overarching scientific question is to decipher the physics underlying short- and long-term behavior of solar magnetic activity both in temporal and spatial domains, and to constrain the solar dynamo model. Direct and indirect solar activity indices, such as sunspots and 10Be and 14C isotope records at annual and decadal resolutions, combined with machine learning techniques and numerical simulations, will be used to reconstruct annual sunspot numbers throughout the past 11,000 years covering the Holocene. The expected results include better characterization of the length of the solar cycle before, during, and after past grand solar minima; improved understanding of the nature and occurrence characteristics of grand minima and maxima; and observational constraints on solar dynamo models to decipher the underlying physical mechanisms that lead to the observed variations in solar activity.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.

太阳磁活动的长期和短期变化深刻影响着地球的空间天气和空间气候。过去的太阳活动显示出长时间的极小期，但目前仍不清楚。 该项目将解决与太阳活动极小值的原因和特征、太阳活动特征在这些时期如何变化以及这些变化是否可以建模/预测相关的问题。该方法结合了太阳黑子数量的观测、同位素时间序列、机器学习技术和数值建模。研究结果将为太阳发电机提供约束，该发电机在太阳上产生变化的磁场，从而导致太空天气。更广泛的影响将是提高我们对影响我们地面、空中和太空技术系统的太空气候和太空天气的了解。该项目为一名早期职业研究人员提供支持。首要的科学问题是破译太阳磁活动在时间和空间领域的短期和长期行为背后的物理原理，并约束太阳发电机模型。直接和间接太阳活动指数，例如年度和十年分辨率的太阳黑子以及 10Be 和 14C 同位素记录，结合机器学习技术和数值模拟，将用于重建覆盖全新世的过去 11,000 年的年度太阳黑子数量。预期结果包括更好地描述太阳活动极小期之前、期间和之后太阳周期的长度；提高对极小值和极大值的性质和发生特征的理解；以及对太阳发电机模型的观测限制，以破译导致观测到的太阳活动变化的潜在物理机制。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。