基于机器学习的日冕仪图像分类方法研究

日冕物质抛射(Coronal Mass Ejection, CME)的检测是建立CME事件库和实现对CME在行星际传播的预报的重要前提. 通过Visual Geometry Group (VGG) 16卷积神经网络方法对日冕仪图像进行自动分类. 基于大角度光谱日冕仪(Large Angle and Spectrometric Coronagraph Experiment, LASCO) C2的白光日冕仪图像, 根据是否观测到CME对图像进行标记. 将标记分类的数据集用于VGG模型的训练, 该模型在测试集分类的准确率达到92.5%. 根据检测得到的标签结果, 结合时空连续性规则, 消除了误判区域, 有效分类出CME图像序列. 与Coordinated Data Analysis Workshops (CDAW)人工事件库比较, 分类出的CME图像序列能够较完整地包含CME事件, 且对弱CME结构有较高的检测灵敏度. 未来先进天基太阳天文台(Advanced Space-based Solar Observatory, ASO-S)卫星的莱曼阿尔法太阳望远镜将搭载有白光日冕仪(Solar Corona Imager, SCI), 使用此分类方法将该仪器产生的日冕图像按有无CME分类. 含CME标签的图像将推送给中国的各空间天气预报中心, 对CME进行预警.     

基于Faster R-CNN的日冕物质抛射检测方法

日冕物质抛射(Coronal Mass Ejection,CME)是一种强烈的太阳爆发现象,对空间天气和人类生活有巨大的影响,因此,日冕物质抛射检测对预报日冕物质抛射、保障人类的生产生活安全具有重要意义。现有的日冕物质抛射检测多采用人为定义特征和界定阈值等方法。由于人为定义特征不能准确表征日冕物质抛射且具有普适性的阈值难于选择,现有的方法对日冕物质抛射的检测效果有待提高。提出一种基于Faster R-CNN(Faster Region-based Convolutional Neural Networks)的日冕物质抛射检测算法。该方法首先结合CDAW(Coordinated Data Analysis Workshop Data Center),SEEDS(Solar Eruptive Even Detection System)和CACTus(Computer Aoded CME Tracking software package)3个著名的日冕物质抛射目录信息,人工标注了包含9113幅日冕图像的数据集,然后根据日冕物质抛射的图像特征较自然图像少、目标尺寸与自然图像有差异等特点,在特征提取和锚点选择方面对Faster R-CNN进行改进。以2007年6月的日冕物质抛射标注数据为测试集,本文算法检出了全部22个强日冕物质抛射事件和151个弱日冕物质抛射事件中的138个,对日冕物质抛射事件的中心角和角宽度等特征参数的检测误差分别在5°和10°以内。     

对一个太阳风暴及其行星际和地磁效应的研究

对一个爆发于2014年1月7日的太阳风暴进行了研究,通过对太阳活动的多波段遥感观测—来自于太阳动力学天文台(Solar Dynamics Observatory,SDO)以及太阳和日球天文台(Solar and Heliospheric Observatory,SOHO),分析了耀斑和日冕物质抛射(coronal mass ejection,CME)的爆发过程.通过地球同步轨道环境业务卫星(Geostationary Operational Environmental Satellites,GOES)对高能质子以及日地L1点的元素高级成分探测器(Advanced Composition Explorer,ACE)对当地等离子体环境的就位观测,分析了伴随太阳风暴的太阳高能粒子(solar energetic particle,SEP)事件和行星际CME(ICME)及其驱动的激波.通过地面磁场数据分析了该太阳风暴对地磁场的影响.研究结果表明:(1)耀斑脉冲相的开始时刻和CME在日面上的抛射在时序上一致.(2)高能质子主要源于CME驱动的激波加速,并非源于耀斑磁重联过程.质子的释放发生在CME传播到7.7个太阳半径的高度的时刻.(3)穿过近地空间的行星际激波鞘层的厚度和ICME本身的厚度分别为0.22 au和0.26 au.(4)行星际激波和ICME引起了多次地磁亚暴和极光,但没有产生明显的地磁暴.原因在于ICME没有包含一个规则的磁云结构或明显的南向磁场分量.     

STEREO卫星的CME观测研究进展

简要回顾利用"日地关系天文台"(Solar Terrestrial Relations Observatory,STEREO)卫星的立体观测资料在日冕物质抛射(Coronal Mass Ejection,CME)研究方面已取得的一些重要进展,主要包括(1)通过极紫外成像仪观测到的日冕极紫外暗化来更准确地估计CME质量,研究CME演化的结构特征;(2)利用STEREO卫星日冕仪的双角度观测,在CME立体传播特征方面取得的新进展;(3)STEREO卫星日球成像仪具有广阔的视场范围,可以跟踪研究CME从太阳表面爆发到形成行星际日冕物质抛射(Interplanetary CME,ICME),及其在内日球层和近地空间的演化特征以及运动特征等。同时,也介绍了利用三角测量技术测定CME特征物理量的新方法。     

2003年10月26日至11月3日CME事件的射电初步分析

基于我国的太阳射电宽带频谱仪(0．625～7．600GHz)在2003年10月22日～11月3日观测到8个伴生日冕物质抛射(CME)的太阳射电爆发,结合Nobeyama Radio Polarimeter(NORP)的单频观测、Nobeyama Radioheliograph (NORH)、Siberian Solar Radio Telescope(SSRT)的成像观测以及Culgoora和WAVE／WIND的低频射电频谱观测,对8个射电爆发的射电辐射特征进行了初步分析．试图从中寻找与CME伴生的射电爆发的特征。     

惊天动地的CME

CME是(Coronal Mass Ejection)的缩写,意为日冕物质抛射。 太阳耀斑爆发已经是一个规模巨大的、剧烈的活动现象了。CME则是太阳日冕层中规模比太阳耀斑还大许多倍的活动现象,或者说是尺度最大、最壮观的爆发现象。从物理意义上讲,CME是从太阳向外喷射出的庞大等离子体和磁场结构,是日冕和太阳风     

日冕物质抛射及其驱动激波的多波段和多视角研究

<正>日冕物质抛射(Coronal Mass Ejection, CME)是太阳大气中剧烈的爆发现象之一.其爆发通常能释放大量的能量并抛射大量磁化等离子体. CME所驱动的激波能进一步导致太阳高能粒子事件(Solar Energetic Particle,SEP)的发生,并可能影响航天器和宇航员的安全.因此,研究CME及其驱动激波的形成机制和性质有利于我们更加清晰地了解及监测它们的运动过程,     

卫星黑子衰减触发的喷流事件

详细分析了一次太阳低层大气磁场重联触发的喷流事件.这次喷流发生在2014年8月1日,爆发自美国国家海洋和大气管理局(National Oceanic and Atmospheric Administration, NOAA)活动区12127边缘的一个卫星黑子处.该喷流爆发包括日浪、紫外喷流、极紫外高温和低温喷流.大熊湖太阳天文台(Big Bear Solar Observatory,BBSO)的Goode Solar Telescope (GST)高分辨率氧化钛(TiO)谱线的光球观测显示,喷流爆发过程中,卫星黑子一直衰减.到喷流结束,卫星黑子面积共减少了80%.在此过程中,太阳动力学天文台(Solar Dynamics Observatory, SDO)日球磁场成像仪(Helioseismic and Magnetic Imager, HMI)的视向磁场观测表明,该卫星黑子对应的负极磁场与相邻的正极磁场发生明显对消,产生喷流足部亮点.根据SDO卫星太阳大气成像仪(Atmospheric Imaging Assembly, AIA)的多波段观测,该足部亮点首先出现在紫外1600?波段.待紫外(1600?)喷流从紫外足部亮点顶部向上喷发,在极紫外波段也观测到相应的亮源.随着足点源亮度突然增强,有明显的极紫外低温喷流和日浪从足部亮点侧面喷发.从GST的高分辨率Hα图像上,可见日浪由许多精细纤维组成,这些纤维扎根在足点源的东南侧.根据从光球层过色球层再到日冕层的多波段高分辨率观测,色球中下层的磁场对消触发了这次喷流事件.向上喷发的物质流可以携带能量进入上层大气,并加热上层大气.研究结果表明,低层大气磁重联可能对解决日冕加热问题起重要作用.     

基于PSP观测的行星际Ⅲ型射电爆发的研究进展

与太阳射电爆发相比,通常认为频率较低的行星际射电爆发产生于远离低日冕的行星际空间.地球电离层的截止导致地基设备无法对其进行观测.美国国家航空航天局(National Aeronautics and Space Administration, NASA)发射的帕克太阳探测器(Parker Solar Probe, PSP)是迄今为止距离太阳最近的空间探测器.其搭载的射电频谱仪能够对10 k Hz–19.17 MHz频段范围内的射电辐射进行观测. PSP能够靠近甚至可能穿越行星际III型射电爆发的辐射源区,因此使用PSP对行星际射电爆发进行观测具有前所未有的优势.简要介绍了目前为止使用PSP的射电观测数据对行星际III型射电爆发的多方面研究,包括爆发的发生率、偏振、散射、截止频率、可能的辐射机制和相关的辐射源区等方面的研究进展,并讨论了其未来的研究前景.     

暗条和日冕极紫外波的三维动力学演化研究

<正>探索三维空间内的各种太阳爆发活动是近年来人们普遍关注的一个热点课题.其主要原因在于爆发活动的三维演化反映了其真实的物理过程,对于认识各种活动现象的发生和演化规律十分重要.暗条爆发和日冕物质抛射(CME)是两种重要的太阳活动现象.日冕极紫外(EUV)波是CME的一种伴生现象,对日冕EUV波的研究为完整地理解CME提供了重要的线索.由于先前的数据都来源于单一视角     

Automatic Detection and Tracking of Coronal Mass Ejections in Coronagraph Time Series

We present the current capabilities of a software tool to automatically detect coronal mass ejections (CMEs) based on time series of coronagraph images: the solar eruptive event detection system (SEEDS). The software developed consists of several modules: preprocessing, detection, tracking, and event cataloging. The detection algorithm is based on a 2D to 1D projection method, where CMEs are assumed to be bright regions moving radially outward as observed in a running-difference time series. The height, velocity, and acceleration of the CME are automatically determined. A threshold-segmentation technique is applied to the individual detections to automatically extract an approximate shape of the CME leading edge. We have applied this method to a 12-month period of continuous coronagraph images sequence taken at a 20-minute cadence by the Large Angle and Spectrometric Coronagraph (LASCO) instrument (using the C2 instrument only) onboard the Solar and Heliospheric Observatory (SOHO) spacecraft. Our automated method, with a high computational efficiency, successfully detected about 75% of the CMEs listed in the CDAW CME catalog, which was created by using human visual inspection. Furthermore, the tool picked up about 100% more small-size or anomalous transient coronagraph events that were ignored by human visual inspection. The output of the software is made available online at . The parameters of scientific importance extracted by the software package are the position angle, angular width, velocity, peak, and average brightness. Other parameters could easily be added if needed. The identification of CMEs is known to be somewhat subjective. As our system is further developed, we expect to make the process significantly more objective.     

The ARTEMIS Catalog of LASCO Coronal Mass Ejections

The LASCO-C2 coronagraph aboard the SOHO solar observatory has been providing a continuous flow of coronal images since 1996. Synoptic maps for each Carrington rotation have been built from these images, and offer a global view of the temporal evolution of the solar corona, particularly the occurrence of transient events. Coronal Mass Ejections (CMEs) present distinct signatures thus offering a novel approach to the problem of their identification and characterization. We present in this article an automated method of detection based on their morphological appearance on synoptic maps. It is based on adaptive filtering and segmentation, followed by merging with high-level knowledge. The program builds a catalog which lists the CMEs detected for each Carrington Rotation, together with their main estimated parameters: time of appearance, position angle, angular extent, average velocity and intensity. Our final catalog LASCO-ARTEMIS (Automatic Recognition of Transient Events and Marseille Inventory from Synoptic maps) is compared with existing catalogs, CDAW, CACTUS and SEEDS. We find that, likewise the automated CACTUS and SEEDS catalogs, we detect many more events than the CDAW catalog which is based on visual detection. The total number of detected CMEs strongly depends upon the sensitivity to small, faint and numerous events.     

Automatic Detection and Classification of Coronal Mass Ejections

We present an automatic algorithm to detect, characterize, and classify coronal mass ejections (CMEs) in Large Angle Spectrometric Coronagraph (LASCO) C2 and C3 images. The algorithm includes three steps: (1) production running difference images of LASCO C2 and C3; (2) characterization of properties of CMEs such as intensity, height, angular width of span, and speed, and (3) classification of strong, median, and weak CMEs on the basis of CME characterization. In this work, image enhancement, segmentation, and morphological methods are used to detect and characterize CME regions. In addition, Support Vector Machine (SVM) classifiers are incorporated with the CME properties to distinguish strong CMEs from other weak CMEs. The real-time CME detection and classification results are recorded in a database to be available to the public. Comparing the two available CME catalogs, SOHO/LASCO and CACTus CME catalogs, we have achieved accurate and fast detection of strong CMEs and most of weak CMEs.     

The 2015 Summer Solstice Storm: One of the Major Geomagnetic Storms of Solar Cycle 24 Observed at Ground Level

We report on the 22?–?23 June 2015 geomagnetic storm that occurred at the summer solstice. There have been fewer intense geomagnetic storms during the current solar cycle, Solar Cycle 24, than in the previous cycle. This situation changed after mid-June 2015, when one of the largest solar active regions (AR 12371) of Solar Cycle 24 that was located close to the central meridian, produced several coronal mass ejections (CMEs) associated with M-class flares. The impact of these CMEs on the Earth’s magnetosphere resulted in a moderate to severe G4-class geomagnetic storm on 22?–?23 June 2015 and a G2 (moderate) geomagnetic storm on 24 June. The G4 solstice storm was the second largest (so far) geomagnetic storm of Cycle 24. We highlight the ground-level observations made with the New-Tupi, Muonca, and the CARPET El Leoncito cosmic-ray detectors that are located within the South Atlantic Anomaly (SAA) region. These observations are studied in correlation with data obtained by space-borne detectors (ACE, GOES, SDO, and SOHO) and other ground-based experiments. The CME designations are taken from the Computer Aided CME Tracking (CACTus) automated catalog. As expected, Forbush decreases (FD) associated with the passing CMEs were recorded by these detectors. We note a peculiar feature linked to a severe geomagnetic storm event. The 21 June 2015 CME 0091 (CACTus CME catalog number) was likely associated with the 22 June summer solstice FD event. The angular width of CME 0091 was very narrow and measured \({\sim}\, 56^{\circ }\) degrees seen from Earth. In most cases, only CME halos and partial halos lead to severe geomagnetic storms. We perform a cross-check analysis of the FD events detected during the rise phase of Solar Cycle 24, the geomagnetic parameters, and the CACTus CME catalog. Our study suggests that narrow angular-width CMEs that erupt in a westward direction from the Sun–Earth line can lead to moderate and severe geomagnetic storms. We also report on the strong solar proton radiation storm that began on 21 June. We did not find a signal from this SEP at ground level. The details of these observations are presented.     

Velocity Distribution of CMEs After Projection Correction

The observed CME (coronal mass ejection) is its projection on the sky plane, and this leads to certain discrepancies between the observational and true parameters of the CME. For example, the observed velocity is generally smaller than the true velocity. The method of making projection correction for the CME velocity based on the conical model is utilized to analyze the velocity distributions of the 1691 CMEs which are only correlated to flares (called the class FL CMEs for short) and the 610 CMEs which are only correlated to filament eruptions (called the class FE CMEs for short) before and after the projection correction. These CMEs were observed with the Large Angle and Spectrometric Coronograph on the Solar and Heliospheric Observatory from September 1996 to September 2007 (close to a solar cycle). The obtained results are as follows: (1) before and after the projection correction the velocity distribution of FL CMEs is quite similar to that of FE CMEs, and before and after the projection correction the mean velocities of the two classes of CMEs are almost the same; (2) before and after the projection correction, the natural logarithm distribution of the FL CME velocities is also very similar to that of the FE CME velocities.     

Validation of CME Detection Software (CACTus) by Means of Simulated Data,and Analysis of Projection Effects on CME Velocity Measurements

In the context of space weather forecasting, an automated detection of coronal mass ejections (CMEs) becomes more and more important for efficiently handling a large data flow which is expected from recently-launched and future solar missions. In this paper we validate the detection software package “CACTus” by applying the program to synthetic data from our 3D time-dependent CME simulations instead of observational data. The main strength of this study is that we know in advance what should be detected. We describe the sensitivities and strengths of automated detection, more specific for the CACTus program, resulting in a better understanding of CME detection on one hand and the calibration of the CACTus software on the other hand, suggesting possible improvements of the package. In addition, the simulation is an ideal tool to investigate projection effects on CME velocity measurements.     

Propagation Characteristics of CMEs Associated with Magnetic Clouds and Ejecta

We have investigated the characteristics of magnetic cloud (MC) and ejecta (EJ) associated coronal mass ejections (CMEs) based on the assumption that all CMEs have a flux rope structure. For this, we used 54 CMEs and their interplanetary counterparts (interplanetary CMEs: ICMEs) that constitute the list of events used by the NASA/LWS Coordinated Data Analysis Workshop (CDAW) on CME flux ropes. We considered the location, angular width, and speed as well as the direction parameter, D. The direction parameter quantifies the degree of asymmetry of the CME shape in coronagraph images, and shows how closely the CME propagation is directed to Earth. For the 54 CDAW events, we found the following properties of the CMEs: i) the average value of D for the 23 MCs (0.62) is larger than that for the 31 EJs (0.49), which indicates that the MC-associated CMEs propagate more directly toward the Earth than the EJ-associated CMEs; ii) comparison between the direction parameter and the source location shows that the majority of the MC-associated CMEs are ejected along the radial direction, while many of the EJ-associated CMEs are ejected non-radially; iii) the mean speed of MC-associated CMEs (946 km?s^?1) is faster than that of EJ-associated CMEs (771 km?s^?1). For seven very fast CMEs (≥?1500 km?s^?1), all CMEs with large D (≥?0.4) are associated with MCs and the CMEs with small D are associated with EJs. From the statistical analysis of CME parameters, we found the superiority of the direction parameter. Based on these results, we suggest that the CME trajectory essentially determines the observed ICME structure.     

Validation of the CME Geomagnetic Forecast Alerts Under the COMESEP Alert System

Under the European Union 7th Framework Programme (EU FP7) project Coronal Mass Ejections and Solar Energetic Particles (COMESEP, http://comesep.aeronomy.be ), an automated space weather alert system has been developed to forecast solar energetic particles (SEP) and coronal mass ejection (CME) risk levels at Earth. The COMESEP alert system uses the automated detection tool called Computer Aided CME Tracking (CACTus) to detect potentially threatening CMEs, a drag-based model (DBM) to predict their arrival, and a CME geoeffectiveness tool (CGFT) to predict their geomagnetic impact. Whenever CACTus detects a halo or partial halo CME and issues an alert, the DBM calculates its arrival time at Earth and the CGFT calculates its geomagnetic risk level. The geomagnetic risk level is calculated based on an estimation of the CME arrival probability and its likely geoeffectiveness, as well as an estimate of the geomagnetic storm duration. We present the evaluation of the CME risk level forecast with the COMESEP alert system based on a study of geoeffective CMEs observed during 2014. The validation of the forecast tool is made by comparing the forecasts with observations. In addition, we test the success rate of the automatic forecasts (without human intervention) against the forecasts with human intervention using advanced versions of the DBM and CGFT (independent tools available at the Hvar Observatory website, http://oh.geof.unizg.hr ). The results indicate that the success rate of the forecast in its current form is unacceptably low for a realistic operation system. Human intervention improves the forecast, but the false-alarm rate remains unacceptably high. We discuss these results and their implications for possible improvement of the COMESEP alert system.