跨多个卡林顿自转周期观测到的长寿命活动区的统计概览
Statistical Overview of Long-Lived Active Regions Observed Across Multiple Carrington Rotations
AI总结：
该研究定义并统计了跨至少两个卡林顿自转周期的长寿命太阳活动区，发现其占2011-2019年NOAA活动区的13%，面积更大、磁通量更多，产生C级及以上耀斑的概率是普通活动区的3-6倍，为空间天气预报提供支撑。
摘要：
太阳活动区（ARs）的研究对一系列基础科学以及空间天气的实际应用都具有核心重要性。活动区的浮现和生命周期是两个备受关注的研究方向，但缺乏一致的全日面观测使得对活动区的长期研究十分困难。本文介绍了一项识别并表征长寿命活动区（LLARs）的研究结果，长寿命活动区被定义为至少在两个连续的卡林顿自转周期中被观测到、且进入衰减阶段后未发生显著连续磁流浮现的活动区。\n这类活动区占2011年至2019年间NOAA识别的所有活动区的13%，其分布与年度太阳黑子数高度吻合。这表明长寿命活动区与常规活动区由相同的基本驱动过程产生。与其他活动区相比，长寿命活动区的面积往往显著更大、包含的磁通量更多，但两类活动区的磁复杂度分布相似。\n然而最引人注目的结果是，长寿命活动区成为GOES C级及以上太阳耀斑源的概率是其他活动区的3-6倍。这凸显了研究长寿命活动区的形成机制、以及如何在其浮现阶段识别它们的重要性，以期改进空间天气预报。这些发现对活动区加热时空模式的进一步影响将在后续研究中探讨。
英文摘要：
The study of solar active regions (ARs) is of central importance to a range of fundamental science, as well as the practical applications of space weather. Active region emergence and life cycles are two areas of particular interest, yet the lack of consistent full-Sun observations has made long-term studies of active regions difficult. Here, we present results from a study to identify and characterize long-lived active regions (LLARs), defined as those which were observed during at least two consecutive Carrington rotations and which did not undergo significant successive flux emergence once the decay phase began. Such active regions accounted for 13% of all NOAA-identified ARs between 2011 and 2019, and their distribution closely follows the annual sunspot number. This implies that LLARs are produced by the same basic driving processes as regular ARs. LLAR areas tend to be significantly larger and contain more magnetic flux compared to other ARs, but the two categories have similar magnetic complexity distributions. The most striking result, however, is that LLARs are 3-6 times more likely than other ARs to be the source of a solar flare of GOES class C or greater. This highlights the importance of studying what makes a LLAR and how to identify them at emergence with a view towards improved space weather forecasting. The further implications of these findings for AR heating spatial and temporal patterns will be explored in an upcoming study.
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