Jiang Chaowei, Feng Xueshang, Guo Yang, Hu Qiang
Institute of Space Science and Applied Technology, Harbin Institute of Technology, Shenzhen 518055, China.
School of Astronomy and Space Science, Nanjing University, Nanjing 210023, China.
Innovation (Camb). 2022 Apr 1;3(3):100236. doi: 10.1016/j.xinn.2022.100236. eCollection 2022 May 10.
Magnetic fields play a fundamental role in the structure and dynamics of the solar corona. As they are driven by their footpoint motions on the solar surface, which transport energy from the interior of the Sun into its atmosphere, the coronal magnetic fields are stressed continuously with buildup of magnetic nonpotentiality in the form of topology complexity (magnetic helicity) and local electric currents (magnetic free energy). The accumulated nonpotentiality is often released explosively by solar eruptions, manifested as solar flares and coronal mass ejections, during which magnetic energy is converted into mainly kinetic, thermal, and nonthermal energy of the plasma, which can cause adverse space weather. To reveal the physical mechanisms underlying solar eruptions, it is vital to know the three-dimensional (3D) structure and evolution of the coronal magnetic fields. Because of a lack of direct measurements, the 3D coronal magnetic fields are commonly studied using numerical modeling, whereas traditional models mostly aim for a static extrapolation of the coronal field from the observable photospheric magnetic field data. Over the last decade, dynamic models that are driven directly by observation magnetograms have been developed and applied successfully to study solar coronal magnetic field evolution as well as its eruption, which offers a novel avenue for understanding their underlying magnetic topology and mechanism. In this paper, we review the basic methodology of the data-driven coronal models, state-of-the-art developments, their typical applications, and new physics that have been derived using these models. Finally, we provide an outlook for future developments and applications of the data-driven models.
磁场在日冕的结构和动力学中起着基础性作用。由于它们由太阳表面的足点运动驱动，这种运动将能量从太阳内部传输到其大气层，日冕磁场不断受到应力作用，以拓扑复杂性（磁螺旋度）和局部电流（磁自由能）的形式积累磁非势性。积累的非势性常常通过太阳爆发而爆发式释放，表现为太阳耀斑和日冕物质抛射，在此期间磁能主要转化为等离子体的动能、热能和非热能，这可能导致不利的空间天气。为了揭示太阳爆发背后的物理机制，了解日冕磁场的三维（3D）结构和演化至关重要。由于缺乏直接测量，通常使用数值模拟来研究三维日冕磁场，而传统模型大多旨在从可观测的光球磁场数据对日冕场进行静态外推。在过去十年中，直接由观测磁图驱动的动态模型已被开发并成功应用于研究太阳日冕磁场演化及其爆发，这为理解其潜在的磁拓扑和机制提供了一条新途径。在本文中，我们回顾了数据驱动日冕模型的基本方法、最新进展、它们的典型应用以及使用这些模型得出的新物理学。最后，我们对数据驱动模型的未来发展和应用进行了展望。
