太阳风对流效应对CME渡越时间的影响

基于Gopalswamy预报日冕物质抛射（CME）渡越时间的经验模型,选取1996-2007年间52个与地磁效应Dst<-50nT相关的CME事件以及10个引起特大磁暴（Dst<-200nT）的CME事件,结合ACE卫星在1AU处的太阳风观测资料,分析背景太阳风对流效应对CME到达1AU处渡越时间预报的影响.对于52个CME事件,考虑太阳风对流效应的影响后,预报的标准偏差由16.5h降为11.4h,修正后的误差分布趋向于高斯分布,并且68%事件的预报误差小于15h.对于10个引起特大磁暴的CME事件,考虑太阳风对流效应的影响后,预报的标准偏差由10.6h降低到6.5h,其中6个事件的预报误差小于5h.研究结果表明,对于CME事件,考虑背景太阳风对流效应的影响可以降低预报CME渡越时间的标准偏差,说明太阳风对流效应对预报CME事件渡越时间具有重要作用.      

太阳风速度及日球电流片对CME渡越时间的影响

基于1996-2005年88个引起重大地磁暴的CME(日冕物质抛射)事件、1996-2000年的47个CME事件以及1997-2002年的29个全晕状CME事件,结合ACE卫星在1AU处的太阳风和行星际磁场观测资料以及Wilcox Solar Observatory(WSO)天文台的太阳光球层磁图,分析了背景太阳风速度和日球电流片对CME到达1AU处渡越时间预报误差的影响.结果表明,背景太阳风速度与CME渡越时间误差并没有明显的相关性,在考虑了磁云通量管轴相对黄道面夹角的影响后相关性依然不明显.然而日球电流片对CME渡越时间却有明显的影响,对于初速度较小的异侧CME事件,其渡越时间大于同侧事件;而对于具有较大初速度的CME事件,异侧事件的渡越时间明显小于同侧事件.研究结果表明,CME与太阳风以及日球电流片的相互作用并不是简单的对流相互作用,造成高速CME异侧事件快于同侧事件到达地球的因素非常复杂,有待深入研究.      

CME地磁扰动事件的模糊预报方法

以1997-2003年期间的73个日冕物质抛射(CME)激波扰动事件和模糊数学为基础,提出了一种预报地磁扰动的方法.该方法以CME事件爆发的日面经纬度、相关地磁扰动事件的渡越时间、地磁扰动指数、IPS观测的太阳风速度跃变量为基础,建立了预报CME地磁扰动事件的μθ,μφ,μT,μM,μ△v从属函数,考虑了CME初始速度对激波到达时间的影响.以这5个从属函数为基础并利用模糊数学对1996-2004年期间73个经行星际闪烁(IPS)观测认证的CME激波引起的地磁扰动事件进行了预报实验.实验结果表明,磁扰开始时间预报的相对误差,△Tpre/Tobs≤30%的事件占总事件数的91.78%,而△Tpre/Tobs＞30%的事件占总事件数的12.33%;磁扰幅度(∑Kp)大小的预报,其相对误差△∑Kp/∑Kpobs≤30%的事件占总事件数的60.27%,相对误差≥50%的事件占总事件数的12.33%.这表明该预报方法对空间灾害性事件地磁扰动的定量预报具有很大应用潜力.      

基于经验加速度的低轨卫星轨道预报新方法

研究将定轨过程中的经验加速度应用于地球低轨卫星轨道预报的新方法. 利用GPS伪距观测数据和简化动力学最小二乘批处理方法对地球低轨卫星定 轨, 其中卫星位置、速度及大气阻力系数和辐射光压系数可以直接用于轨道预报. 作为简化动力学最重要特征的经验加速度呈现准周期、余弦曲线特点, 可通过 傅里叶级数拟合建模. 确定性动力学模型与补偿大气阻力模型误差的切向经验 加速度级数拟合模型组成增强型动力学模型用于提高轨道预报精度. 应用 GRACE-A星载GPS伪距观测数据和IGS超快星历定轨并进行轨道预报, 结果表明 轨道预报初值位置精度达到0.2m, 速度精度达到1×10-4m·s-1, 预报3天位置精度优于60m, 比只利用确定性动力学模型进行预报精度平 均提高2.3倍. 先定轨后预报的模式可用在星上自主精确导航系统中.      

多方向μ介子通量一致性特征研究

通过地面μ介子望远镜可以探测不同方向到达的宇宙线通量,得到从外空间入射的宇宙线受到不均匀结构的调制情况,判断CME的特征.通过分析,发现大地磁暴前Nagoya台站东向和南向的探测数据存在固定的2h时间差,认为这是由两个入射方向的宇宙线粒子先后穿越CME结构引起的.分别计算了两个方向相同时间和南向相位后移2h后通量探测数据的相关系数,以及两种情形下通量差的变化幅度,定量描述了CME接近地球过程中两个方向通量的相关特征.通过比较发现,CME接近地球过程中,经过相位变换的两个方向的相关系数明显高于未经变换的情况,经过相位变换的两个方向的通量差幅度明显小于未经变换的情况;CME到达地球后,两种情形的相关系数和通量差幅度则趋于相同.对2003-2005年K_p=9的地磁暴事件的分析均发现了这种现象.对2006年12月14日大地磁暴前的μ介子通量特征进行了分析,也完全符合上述特征.      

基于MapReduce的CME参数识别模型并行计算技术

日冕物质抛射（Coronal Mass Ejection,CME）参数识别模型是太阳风预报过程的重要组成部分.在空间环境预报业务中,为提高太阳风预报的准确率,需要提高CME参数识别的精度.模型以计算任务串行的方式运行,运算效率低导致模型运算时间长,不能满足这种需求.CME参数识别模型的物理运算过程相互不独立,其在单节点上的运行方式不能满足并行化要求.基于MapReduce的并行计算框架,改进了CME参数识别模型的计算流程,提出CDMR（CME detection under MapReduce）方法,实现了CME参数识别模型的并行计算,并对比分析CME参数识别模型在串行计算和MapReduce并行计算下的运行时间,提高了模型的识别精度和计算效率.      

太阳质子事件预报和射电Ⅰ型噪暴

太阳是一个异常活跃的天体,其爆发过程会对地球周围空间环境产生重要影响. 通常,单个高能质子即足以引起飞行器中微电子器件出现异常,因此太阳质子事件预报是空间天气预报的重要内容. 关于预报模型的参数选择尚有值得改进之处. 研究认为,Ⅰ型噪暴与日冕加热磁重联具有密切关系,可以作为预报参数. 通过两个典型太阳爆发事件的详细资料分析,说明了Ⅰ型噪暴与质子事件及CME的相关性.      

全晕CME与太阳质子事件的关系

日冕物质抛射（CME）是太阳质子事件的重要源头.CME的速度和源区位置是太阳质子事件产生的重要因素.通过统计最近5年全晕CME与太阳质子事件的关系发现,速度大且源区位置距离日面上连接地球磁力线足点近的全晕CME更易引发太阳质子事件,其中速度大于1200km…-1、角距离60°以内的样本引发太阳质子事件的概率最高.对3个未引发太阳质子事件的高速全晕CME进行了详细分析,发现CME的主体爆发方向和行星际磁场环境的变化也影响太阳质子事件的产生.因此,在太阳质子事件的实际预报中,综合CME爆发速度、源区位置、主体抛射方向和行星际环境等多个因素才能给出更准确的事件预报结果.      

X级以上耀斑与地磁效应关系研究

统计研究了2010年1月至2012年12月期间所有与耀斑爆发相伴生的日冕物质抛射(CME) 引发的地磁暴事件. 结果表明, 对于CME源区其主要分布在日面 45°E-45°W, 占总数的78.95%, 且西半球比东半球多, 即源区位于西半球的CME易产生地磁效应; X级耀斑与地磁效应的关联性更高, 60.0%的 X级耀斑在其爆发后的2～3天内观测到地磁暴, 而其他级别的耀斑与地磁效应的关联性低得多, 均不足10%; 通过对此期间日面爆发的所有X级耀斑研究分析后发现, 对于源区位于日面东经45°E-45°W 的X级耀斑, 若在其爆发过程中没有大尺度日面扰动, 则无伴生CME且后续产生地磁效应的可能性很低. 由此提出一种通过分析日面观测数据进行地磁暴预报的方法.      

用银河宇宙线判定几个引起特大磁暴CME的运动方向

利用位于南北极尖区位置的McMurdo和Thule台站的宇宙线强度的观测数据，分析了几个引起特大磁暴CME的来向．分析结果表明，所选的与4个特大磁暴相关的CME基本是朝正对磁层顶的方向运动并与磁层作用的．通过对引起第23周两个特大磁暴的CME特征分析对照，发现CME的来向是影响磁暴强弱的一个因素．同样条件下，运动方向偏向地球一侧的CME引起的磁暴比正对地球的CME引起的磁暴要弱。     

CME引起的地磁暴穿越时间

日冕物质抛射(CME)从发生至引起地磁暴最大值的时间间隔称为穿越时间.本文选取1997-2015年89个CME-Dst事件,分析CME速度、能量、耀斑类型等对穿越时间的影响;采用非线性拟合以及支持向量机(SVM)非线性回归技术,建立基于1997-2009年62个CME-Dst事件的CF模型和SVM模型,并利用其余27个CME-Dst事件对模型预报效果分别进行检验.结果表明,CF模型和SVM模型的预报准确率均达到85.2%,其中CF模型的平均绝对值误差为13.77 h,而SVM模型为13.88 h.与ECA模型结果(准确率为77.8%,平均绝对值误差为14.55 h)进行对比发现,CF模型和SVM模型的准确率更高而误差更小.CF模型和SVM模型能够提前1~5天较好地预报地磁暴爆发时间.     

两冕流间CME事件数值模拟的改进

通过偶极子场和六极子场适当叠加，改进猜解磁场，使猜解磁场在太阳南北极符号相反，然后采用理想磁流体力学方程组(MHD)，由猜解磁场与太阳风流动相互作用计算出稳态自洽解，得到定性上与观测比较接近的具有两个冕流的背景结构．在两个冕流间采用具有同心圆磁场位形的触发模型触发CME事件，研究CME的日冕传播特征．模拟结果表明，CME被约束在两冕流间传播，CME闭磁场位形和磁云横截面磁场位形相似，可以解释1AU处观测磁云的部分特征；在CME附近，存在压力和Lorentz力起主要作用的区域，这可以为分析1AU处CME事件的观测数据提供帮助．     

CME dynamics using coronagraph and interplanetary ejecta data

In this work, we present a study of the coronal mass ejection (CME) dynamics using LASCO coronagraph observations combined with in-situ ACE plasma and magnetic field data, covering a continuous period of time from January 1997 to April 2001, complemented by few extreme events observed in 2001 and 2003. We show, for the first time, that the CME expansion speed correlates very well with the travel time to 1 AU of the interplanetary ejecta (or ICMEs) associated with the CMEs, as well as with their preceding shocks. The events analyzed in this work are a subset of the events studied in Schwenn et al. (2005), from which only the CMEs associated with interplanetary ejecta (ICMEs) were selected. Three models to predict CME travel time to Earth, two proposed by Gopalswamy et al. (2001) and one by Schwenn et al. (2005), were used to characterize the dynamical behavior of this set of events. Extreme events occurred in 2001 and 2003 were used to test the prediction capability of the models regarding CMEs with very high LASCO C3 speeds.     

Determining CME parameters by fitting heliospheric observations: Numerical investigation of the accuracy of the methods

Transients in the heliosphere, including coronal mass ejections (CMEs) and corotating interaction regions can be imaged to large heliocentric distances by heliospheric imagers (HIs), such as the HIs onboard STEREO and SMEI onboard Coriolis. These observations can be analyzed using different techniques to derive the CME speed and direction. In this paper, we use a three-dimensional (3-D) magneto-hydrodynamic (MHD) numerical simulation to investigate one of these methods, the fitting method of  and . Because we use a 3-D simulation, we can determine with great accuracy the CME initial speed, its speed at 1 AU and its average transit speed as well as its size and direction of propagation. We are able to compare the results of the fitting method with the values from the simulation for different viewing angles between the CME direction of propagation and the Sun-spacecraft line. We focus on one simulation of a wide (120–140°) CME, whose initial speed is about 800 km s⁻¹. For this case, we find that the best-fit speed is in good agreement with the speed of the CME at 1 AU, and this, independently of the viewing angle. The fitted direction of propagation is not in good agreement with the viewing angle in the simulation, although smaller viewing angles result in smaller fitted directions. This is due to the extremely wide nature of the ejection. A new fitting method, proposed to take into account the CME width, results in better agreement between fitted and actual directions for directions close to the Sun–Earth line. For other directions, it gives results comparable to the fitting method of Sheeley et al. (1999). The CME deceleration has only a small effect on the fitted direction, resulting in fitted values about 1–4° higher than the actual values.     

Pseudo-automatic characterization of the morphological and kinematical properties of coronal mass ejections using a texture-based technique

The white light coronagraphs onboard SOHO (LASCO-C2 and -C3) and most recently STEREO (SECCHI -COR1 and -COR2) have detected a myriad of coronal mass ejections (CME). They are a key component of space weather and under certain conditions they can become geo-effective, hence the importance of their kinematic characterization to help predict their effects. However, there is still a lot of debate on how to define the event boundaries for space weather purposes, which in turn makes it difficult to agree on their kinematic properties. That lack of agreement is reflected in both the manual and automated CME catalogs in existence. To contribute to a more objective definition and characterization of white-light coronagraph events, Goussies et al. (2010) introduced recently the concept of “texture of the event”. Based on that property, they developed a supervised segmentation algorithm to allow the automatic tracking of dynamic events observed in the coronagraphs field of view, which is called CORonal SEgmentation Technique (CORSET). In this work, we have enhanced the capabilities of the algorithm by adding several new functionalities, namely the automatic computation of different morphological and kinematic parameters. We tested its performance on 57 well-studied limb CME events observed with the LASCO coronagraphs between 1997 and 2001, and compared the parameters obtained with those from three existent CME lists: two of them obtained from an observer-based detection and tracking method (i.e., two manual catalogs), and the other one based on the automated detection and characterization of the CME events (i.e., a fully automated catalog). We found that 51 events could be tracked and quantified in agreement with the CME definition. In general terms, the position angle, and the radial and expansion speeds are in agreement with the manual catalogs used for comparison. On the other hand, some discrepancies between CORSET and the automated catalog were found, which can be explained by the different delimitation of the CME angular extent.     

Study of CME transit speeds for the event of 07-NOV-2004

Several methods for CME speed estimation are discussed. These include velocity derivation based on the frequency drifts observed in metric and decametric radio wave data using a range of coronal density models. Coronagraph height–time plots allow measurement of plane-of-sky and expansion speeds. These in turn can enable propagation speeds to be derived from a range of empirical relations. Simple geometric e.g., cone, models can provide propagation velocity estimates for suitable halo or partial halo events. Interplanetary scintillation observations allow speed estimates at large distances from the Sun detecting in particular the deceleration of the faster CMEs. Related interplanetary shocks and the arrival times and speeds of the associated magnetic clouds at Earth can also be considered. We discuss the application of some of these methods to the transit to Earth of a complex CME that originated earlier than 16:54 U.T. on 07-NOV-2004. The difficulties in making velocity estimates from radio observations, particularly under disturbed coronal conditions, are highlighted.     

1997年1月空间天气事件的三维MHD模拟

以1997年1月空气天气事件期间的观测为依据，在构造了比较接近真实的背景太阳风基础上，进一步利用三维时变的MHD模式，模拟了CME（日冕物质抛射）激发的扰动在行星际空间的传播过程，对地球空间环境的影响及行星际磁场南向分量Bz在1AU的时间经历。模拟结果与WIND卫星的测量进行了比较。结果表明，模拟与观测得到的扰动得到地球的时间、地球空间环境各量的变化及Bz的时间经历基本一致。     

基于机器学习方法对23太阳活动周质子事件的研究

在耀斑伴随日冕物质抛射(CME)事件编目数据的基础上,进行太阳质子事件(SPE)匹配,构建研究数据集.利用Apriori算法挖掘SPE与耀斑级别、耀斑发生日面位置以及CME角宽度和速度的关联关系.结果 表明:X级耀斑、全晕CME、高速(＞1000 km.s-1) CME和日面西半球耀斑是最可能伴随质子事件的4种特征,其...     

Orientations of LASCO Halo CMEs and their connection to the flux rope structure of interplanetary CMEs

Coronal mass ejections (CMEs) observed near the Sun via LASCO coronographic imaging are the most important solar drivers of geomagnetic storms. ICMEs, their interplanetary, near-Earth counterparts, can be detected in situ, for example, by the Wind and ACE spacecraft. An ICME usually exhibits a complex structure that very often includes a magnetic cloud (MC). They can be commonly modelled as magnetic flux ropes and there is observational evidence to expect that the orientation of a halo CME elongation corresponds to the orientation of the flux rope. In this study, we compare orientations of elongated CME halos and the corresponding MCs, measured by Wind and ACE spacecraft. We characterize the MC structures by using the Grad–Shafranov reconstruction technique and three MC fitting methods to obtain their axis directions. The CME tilt angles and MC fitted axis angles were compared without taking into account handedness of the underlying flux rope field and the polarity of its axial field. We report that for about 64% of CME–MC events, we found a good correspondence between the orientation angles implying that for the majority of interplanetary ejecta their orientations do not change significantly (less than 45 deg rotation) while travelling from the Sun to the near-Earth environment.     

应用BP神经网络针对高通量质子事件的通量数值预报

质子事件的爆发与太阳软X射线辐射有着很强的相关性,利用GOES卫星的1～8 (A)波段和0.5～4 (A)波段的软X射线数据,选取一些特征参量验证该相关性并应用到质子事件短期预报中.在当前质子事件传输物理机制不完全明确的情况下,在现有的预报质子事件有无的模型基础上,利用BP神经网络,根据软X射线通量水平等预测事件质子峰值通量水平,再对训练后的网络进行检验,检验预测所得结果与实际探测值误差小于一个量级,具备一定实用意义.