Extreme Solar Flare-driven Short-wave Fadeout Observed by SuperDARN ZHO Radar
Extreme Solar Flare-driven Short-wave Fadeout Observed by SuperDARN ZHO Radar
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SuperDARN ZHO 雷达观测到的极端太阳耀斑驱动的短波衰落
DOI：
10.3847/1538-4357/ac6f56
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
K. Zhao
中科院分区：
文献类型：
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作者：
X. Liu;Z. Wang;J. Lu;J. Liu;H. Q. Hu;J. Liu;Z. Hu;M. Wang;K. Zhao
基于中山站超级双极光雷达网（−74.9 MLAT，97.2 MLON）和GOES卫星X射线传感器的观测，我们首次对2010-2019年南半球高纬度地区的日侧电离层短波衰落（SWF）事件进行了统计研究，并提供了SWF的正常特征，发病时间为6分54秒，停电时间分别为 20 分 24 秒，恢复时间为 39 分 36 秒。本作品中的所有 SWF 事件均被选择为由极端耀斑引起。统计分析显示短型和长型 SWF 发作阶段。长事件的爆发/停电相持续时间与耀斑持续时间高度相关（0.79，0.60），SWF主要由耀斑辐射廓线驱动，短爆发事件的软X射线通量上升率高于大多数长爆发事件，这是两类事件差异的主要原因。此外，还需要考虑电离层迟缓对长爆发事件的影响。各相长SWF持续时间与有效峰值X射线通量之间的关系并不明显。然而，积分有效 X 射线通量与长事件的开始/中断阶段持续时间之间的相关性很重要。
Based on the observations from the Super Dual Auroral Radar Network at the Zhongshan Station (−74.9 MLAT, 97.2 MLON) and GOES satellites X-ray sensor, we present the first statistical study of the dayside ionospheric short-wave fadeout (SWF) events on the Southern Hemispheric high latitude from the years 2010–2019 and provide a normal characteristic of SWF with onset of 6 minutes 54 s, blackout of 20 minutes 24 s, and recovery of 39 minutes 36 s, respectively. All the SWF events in this work are selected to be caused by extreme flares. The statistical analysis shows both short-type and long-type SWF onset phases. Onset/blackout phase duration of long events is highly correlated with flare duration (0.79, 0.60), the SWF is mainly driven by the flare radiation profile, and the soft X-ray flux rise rate is higher for short-onset events than for most long-onset events, which is the main reason for the difference between the two types of events. In addition, the effect of ionospheric sluggishness on long-onset events also needs to be considered. The relationship between each phase’s durations of long SWFs and the effective peak X-ray flux is not obvious. However, the correlation between the integrated effective X-ray flux and the onset/blackout phase duration of long events is significant.
日本对中纬度超级双极光雷达网络（SuperDARN）的贡献
DOI：
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发表时间：
2013
期刊：
影响因子：
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作者：
Alan Hase;Hiroshi Mishina;Masaki Wada;松島佳孝，倉敷哲生，廣澤覚;N. Nishitani
通讯作者：
N. Nishitani