SHINE: Characterizing the Coronal Origins of Slow Solar Wind using Heavy Ion Composition and Spectroscopic Observations
SHINE: Characterizing the Coronal Origins of Slow Solar Wind using Heavy Ion Composition and Spectroscopic Observations
批准号:
1621686
负责人:
Jimmie Raines
金额:
$37.06万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2021-08-31
中文摘要
低速太阳风(Slow-speed Solar Wind,SSW)是在1 Au的黄道面上席卷地球的太阳风中最主要的成分,它对地球空间环境和地球高层大气的形成和决定起着重要作用,而地球高层大气是大多数人造卫星所在的地方。 然而,尽管所有的努力致力于调查SSW,这种类型的风的两个基本问题仍然没有答案:(1)SSW起源于日冕;(2)如何做日冕等离子体的属性决定SSW的原位重离子成分? 这个为期3年的SHINE项目旨在描述SSW的日冕起源,以回答这两个重要的科学问题。 项目小组将利用两种完全不同的技术研究SSW:当地风等离子体特性的现场测量和遥感光谱或成像观测。当结合在一起时,这两种技术可以成为一种强大的工具,使研究人员能够充分利用其潜力来研究SSW的起源。 该项目将使太阳能研究界受益,并发挥重要的教育作用。 通过使用两种完全不同的测量技术,这一项目将成为两个不同的太阳物理学界(现场界和遥感界)之间的桥梁,这两个不同的太阳物理学界一直平行工作,相互作用有限,因此将激发新一轮的交叉合作。 这项研究将在密歇根大学安阿伯分校进行,在那里它将通过大学的UROP计划支持本科教育,并通过与我们系的研究生合作支持研究生教育。 该项目还将支持一名年轻的女博士后,从而帮助她在STEM学科中建立女性职业生涯。 该项目的研究和EPO议程支持AGS部门在发现,学习,多样性和跨学科研究方面的战略目标。这个为期3年的SHINE项目旨在描述太阳风的起源。 为了实现这一目标,项目小组将利用ACE/SWICS和SWEPAM、ESTO/SWICS、SWOOPS和Wind/SWE的现场测量数据,并将分析与SOHO/MDI、SDO/HMI和Hinode/SOT的遥感数据相结合。 现场太阳风观测将根据其日冕起源类型而不是其现场性质进行分类。 将使用回溯方法来确定太阳上的相应源区。 将利用谱线强度确定太阳风源区的物理特性。 该研究项目与NSF的SHINE计划直接相关,因为它将提供有关太阳风起源的重要知识。 这类知识对于准确建模和预测从太阳表面到地球及其以外的空间气象条件至关重要。
英文摘要
As the most dominant component of the solar wind that engulfs the Earth on the ecliptic plane at 1 AU, the Slow-speed Solar Wind (SSW) plays a substantial role in shaping and determining the Geospace environment and the Earth's upper atmosphere where most of the man-made satellites are located. However, despite all the efforts devoted to investigating the SSW, two fundamental questions about this type of wind remain unanswered: (1) where does the SSW originate in the corona; and, (2) how do the coronal plasma properties determine the in-situ heavy ion composition of the SSW? This 3-year SHINE project is aimed at characterizing the coronal origins of the SSW in order to answer these two important science questions. The project team will study the SSW, utilizing two completely different techniques: in-situ measurements of local wind plasma properties, and remote-sensing spectral or imaging observations. When combined together, these two techniques can become a formidable tool that allows the investigators to fully exploit their potential to study the origin of the SSW. This project will benefit the solar research community and serve important educational functions. By using two completely different measurement techniques, this project will serve as a bridge between two different solar physics communities that have been working in parallel with limited interaction: the in-situ community and the remote sensing community, and will thus stimulate a new wave of cross collaborations. The research will be carried out at the University of Michigan at Ann Arbor, where it will support undergraduate education through the University's UROP program and graduate education through collaboration with the graduate students in our department. The project will also support a young female postdoc, thus helping her establish a career as a woman in STEM disciplines. The research and EPO agenda of this project supports the Strategic Goals of the AGS Division in discovery, learning, diversity, and interdisciplinary research.This 3-year SHINE project is aimed at characterizing the origin of the solar wind. In order to achieve this goal, the project team will utilize in-situ measurements from ACE/SWICS and SWEPAM, Ulysses/SWICS, SWOOPS and Wind/SWE and combine the analysis with remote-sensing data from SOHO/MDI, SDO/HMI and Hinode/SOT. The in-situ solar wind observations will be classified based on their coronal origin types rather then their in-situ properties. Back-tracking methods will be used to identify the corresponding source regions on the Sun. The physical properties of the solar wind source regions will be determined using spectral line intensities. This research project is directly relevant to the NSF's SHINE program, because it will provide important knowledge about the origin of the solar wind. Such knowledge is critical for accurate modeling and prediction of the space weather conditions from the solar surface to the Earth and beyond.
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