论文标题
耀斑和CME生产太阳活性区的特征
The characteristics of flare- and CME-productive solar active regions
论文作者
论文摘要
太阳耀斑和冠状质量弹出(CMES)对星际空间和地形空间造成直接和不利影响。对产生它们的机制以及有效预测方案的构建的更深入的理解至关重要。耀斑和CME的源区域表现出一些与强剪切的磁性极性反转线相关的常见形态特征,这表明复杂的磁性构型存储了大量的自由磁能和螺旋。这些知识被转变为可以帮助我们有效区分安静,耀斑和CME生产活性区域的参数。但是,Flare和CME预测仍然面临许多挑战。磁场信息在光球处受到约束,仅从一个有利的观察点访问。活动区域的动态行为仍未完全纳入预测中。耀斑和CME的随机性使其预测概率。为了应对这些挑战,已经提出了新的特性来描述活跃区域中磁性能量存储机制的不同方面,并为整个太阳周期提供了参数研究的机会。现在,这种预测因子的清单包括来自流场,过渡区域/冠状光谱,冠状磁场的数据驱动建模以及时间序列动态效应的参数化的信息。向这些方向迈进的进一步工作可能有助于减轻观察高大气层磁场的当前局限性。本文回顾了这些努力,以及将新知识转换为更有效的预测因素并包括新类型数据的重要性。
Solar flares and coronal mass ejections (CMEs) cause immediate and adverse effects on the interplanetary space and geospace. The deeper understanding of the mechanisms that produce them and the construction of efficient prediction schemes are of paramount importance. The source regions of flares and CMEs exhibit some common morphological characteristics associated with strongly sheared magnetic polarity inversion lines, indicative of the complex magnetic configurations that store huge amounts of free magnetic energy and helicity. This knowledge is transformed into parameters that can help us distinguish efficiently between quiet, flare-, and CME-productive active regions. Nonetheless, flare and CME prediction still faces a number of challenges. The magnetic field information is constrained at the photosphere and accessed only from one vantage point of observation; the dynamic behavior of active regions is still not fully incorporated into predictions; the stochasticity of flares and CMEs renders their prediction probabilistic. To meet these challenges, new properties have been put forward to describe different aspects of magnetic energy storage mechanisms in active regions and offer the opportunity of parametric studies for over an entire solar cycle. This inventory of predictors now includes information from flow fields, transition region/coronal spectroscopy, data-driven modeling of the coronal magnetic field, as well as parameterizations of dynamic effects from time series. Further work towards these directions may help alleviate the current limitations in observing the magnetic field of higher atmospheric layers. This paper reviews these efforts as well as the importance of transforming new knowledge into more efficient predictors and including new types of data.