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.

太阳的磁活动的长期和短期变化深远影响了地球和太空气候的空间天气。过去的太阳活动显示了延长的最小值的时期，这些时期仍未得到充分理解。 该项目将解决与太阳活动中大型最小值的原因和特征有关的问题，在这些时期内太阳活动的特征如何变化以及是否可以对这些变化进行建模/预测。该方法结合了黑子数量，同位素时间序列，机器学习技术和数值建模的结合。结果将在太阳能发电机上提供限制，该太阳能发电机在太阳上产生不断变化的磁场，从而导致空间天气。更广泛的影响是提高我们对影响地面，空气和空间技术系统的空间气候和太空天气的理解。该项目支持早期的职业研究人员。总体科学问题是破译时间和空间领域中太阳能磁活动的短期和长期行为的物理，并限制太阳能发电机模型。在年度和十年分辨率下的直接和间接太阳活动指数，例如日光和14C同位素记录，结合机器学习技术和数值模拟，将用于重建过去11,000年的年度日光数，以涵盖全新世。预期的结果包括更好地表征太阳周期的长度，然后再过太阳能最小值。对大型和最大值的性质和发生特征的理解得到了提高；以及对太阳能发电机模型的观察性限制，以破译导致太阳能活动的差异的潜在物理机制。该奖项反映了NSF的法定任务，并认为值得通过基金会的智力优点和更广泛的影响审查标准通过评估来获得支持。