结合光球磁场特征物理量的质子事件短期预报

利用描述太阳活动区光球磁场复杂性和非势性特征的三个物理量(纵向磁场最大水平梯度|▽_hB_z |_m, 强梯度中性线长度L, 孤立奇点数目η)建立了质子事件短期预报模型, 验证了磁场特征物理量对质子事件短期预报的有效性. 目前已建立或使用的太阳质子事件短期预报模型中仍然没有正式将磁场特征物理量作为预报因子. 由于太阳质子事件是小概率事件, 其物理产生机制尚不完全清楚, 这些预报模型往往存在虚报率偏高或报准率偏低的问题. 本文试图将原有质子事件模型所用的传统因子与磁场特征物理量结合起来, 利用神经网络方法建立一个更为有效的质子事件短期预报模型. 利用1997--2001年的训练数据集1871个样本建立了输入层为传统预报因子的模型A以及输入层为传统预报因子和磁场特征物理量的模型B. 通过对2002--2003年973个样本的测试数据集进行模拟预报发现, 模型A与B在具有相同质子事件报准率的情况下, 模型B的虚报率明显降低. 这进一步验证了磁场特征物理量在质子事件短期预报中的作用, 进而可以加强对太阳质子事件的实际预报能力.      

利用质子强度变化对太阳质子事件进行短期预报方法初步研究

采用GOSE-10卫星4～9 MeV(P2),9～15 MeV(P3),15～40 MeV(P4),40～80 MeV(P5)能段上的质子通量数据,结合质子能谱,对太阳质子事件发生前各能谱参数的变化特征进行分析,详细介绍利用能谱参数的变化特征及能量E>10 MeV的质子通量数据对太阳质子事件进行预报的新方法,并运用这种方法对2002-2006年期间太阳质子事件进行了预报.预报结果显示,预报提前量最多达到100 h以上,对质子事件的报准率达97.5%,预报方法具备一定的有效性和实用性.      

神经网络方法在太阳质子事件短期预报中的应用

在大量统计结果的基础上,深入研究了太阳质子事件预报机理．总结了质子事件爆发与太阳活动区面积、位置、McIntosh结构、磁结构以及前两天活动区爆发耀斑事件数目之间的关系．然后,在神经网络的基础上建立了太阳质子事件短期预报模型,并对2000年以后12个未参加训练的样本进行测试,结果对事件预报的准确率为83％．此外,我们还利用该模型对2002年1-4月发生的几次质子事件进行了预报试验,结果发现,这期间发生的6次事件都被预报．其中3次质子事件系统预报提前了3天,两次事件预报提前了2天,一次事件提前1天预报．     

基于集成学习的太阳质子事件短期预报方法

太阳质子事件是一种由太阳活动爆发时喷射并传播到近地空间的高能粒子引起的空间天气现象。这些高能粒子会对航天器和宇航员产生严重危害,对太阳质子事件进行准确的短期预报是航天活动灾害预防的重要内容。针对当前主要预报模型中普遍存在的高虚报率问题,提出了一种基于集成学习的太阳质子事件短期预报方法,利用第23个太阳活动周数据,建立了一种集成8种机器学习模型的太阳质子事件短期预报系统。实验结果表明,本文方法在取得了80.95%的报准率的同时,将虚报率降低至19.05%,相比现有的预报系统具有较为明显的优势。      

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.      

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.      

太阳质子事件中短期预报模型研究

太阳质子事件通量的预测对航天器抗辐射加固设计和航天员出舱活动具有非常重要的意义.针对一年以下的航天任务,利用经验统计方法,确认太阳活跃年和太阳平静年期间,1——365天不同时间段内 > 10MeV,> 30MeV和 > 60MeV的太阳质子事件积分通量符合对数正态分布,且通量对数的标准偏差σ和期望值μ随任务期时间的变化满足对数函数形式.以此为基础,构建太阳质子通量的中短期预报模型.该模型能够针对太阳活跃年和太阳平静年,给出一定置信度下1——365天不同时间内 > 10MeV,> 30MeV和 > 60MeV的质子事件通量分布,从而为执行中短期航天任务提供太阳质子事件通量的预测,以规避不必要的风险.      

利用ACE卫星数据对太阳质子事件预警方法的研究

通过分析GOES和ACE卫星大于10MeV能量段的5min平均质子通量数据,发现两者有很好的相关性,最佳相关系数显示,GOES通量数据较ACE卫星数据有数十分钟至几小时的时间延迟.这为利用ACE数据进行质子事件预警提供了依据.本文提出一种利用ACE卫星大于10MeV能量段的通量数据对质子事件进行预警的方法.该方法在2001年8月7日至2012年2月20日这11年多时间的试验中,表现出较高的报准率(76.3%)和较低的虚报率(14.7%),预警提前时间在数十分钟至几小时不等.该方法的结果与美国国家海洋和大气管理局(NOAA)空间天气预测中心(SWPC)使用的预警模型对比,具有更高的报准率,较低的虚报率,在预警时间提前量方面两者相当.      

太阳质子事件警报

采用人工神经网络预报方法,利用太阳耀斑的日面位置、X射线辐射的峰值流量及其上升时间、2695MHz和8800MHz微波辐射的半积分流量等5个物理参量,提出了一个新的太阳质子事件警报方案,预报太阳质子事件的发生及其流量和时间．该方案在本文检验中达到93．75％的预报准确率．     

一种新的太阳质子事件警报方法的探讨

本文分析了第21太阳活动周后半期的太阳质子耀斑硬X射线辐射资料, 发现它们的峰值流量、积分流量、上升沿斜率、X光子的最高能量和持续时间等物理参数之间有着不同于非质子耀斑的相关性。据此, 本文采用模糊聚类分析法, 对21太阳活动周期间(1980.2—1986.2)的质子事件进行预报试验。其报准率为88.5%, 虚报率为53.1%, 漏报率为11.5%。本文提供了基于X射线辐射特征的太阳质子事件警报的新途径和方法。      

Relation between solar wind velocity and properties of its source region

Different kinds of coronal holes are sources of different kind of solar winds. A successful solar wind acceleration model should be able to explain all those solar winds. For the modeling it is important to find a universal relation between the solar wind physical parameters, such as velocity, and coronal physical parameters such as magnetic field energy. To clarify the physical parameters which control the solar wind velocity, we have studied the relation between solar wind velocity and properties of its source region such as photospheric/coronal magnetic field and the size of each coronal hole during the solar minimum. The solar wind velocity structures were derived by using interplanetary scintillation tomography obtained at Solar-Terrestrial Environment Laboratory, Japan. Potential magnetic fields were calculated to identify the source region of the solar wind. HeI 1083 nm absorption line maps obtained at Kitt Peak National Solar Observatory were used to identify coronal holes. As a result, we found a relation during solar minimum between the solar wind velocity and the coronal magnetic condition which is applicable to different kind of solar winds from different kind of coronal holes.     

Correlation between solar flare productivity and photospheric vector magnetic fields

Studying the statistical correlation between the solar flare productivity and photospheric magnetic fields is very important and necessary. It is helpful to set up a practical flare forecast model based on magnetic properties and improve the physical understanding of solar flare eruptions. In the previous study ([Cui, Y.M., Li, R., Zhang, L.Y., He, Y.L., Wang, H.N. Correlation between solar flare productivity and photospheric magnetic field properties 1. Maximum horizontal gradient, length of neutral line, number of singular points. Sol. Phys. 237, 45–59, 2006]; from now on we refer to this paper as ‘Paper I’), three measures of the maximum horizontal gradient, the length of the neutral line, and the number of singular points are computed from 23990 SOHO/MDI longitudinal magnetograms. The statistical relationship between the solar flare productivity and these three measures is well fitted with sigmoid functions. In the current work, the three measures of the length of strong-shear neutral line, total unsigned current, and total unsigned current helicity are computed from 1353 vector magnetograms observed at Huairou Solar Observing Station. The relationship between the solar flare productivity and the current three measures can also be well fitted with sigmoid functions. These results are expected to be beneficial to future operational flare forecasting models.     

Turbulence,complexity, and solar flares

The issue of predicting solar flares is one of the most fundamental in physics, addressing issues of plasma physics, high-energy physics, and modelling of complex systems. It also poses societal consequences, with our ever-increasing need for accurate space weather forecasts. Solar flares arise naturally as a competition between an input (flux emergence and rearrangement) in the photosphere and an output (electrical current build up and resistive dissipation) in the corona. Although initially localised, this redistribution affects neighbouring regions and an avalanche occurs resulting in large scale eruptions of plasma, particles, and magnetic field. As flares are powered from the stressed field rooted in the photosphere, a study of the photospheric magnetic complexity can be used to both predict activity and understand the physics of the magnetic field. The magnetic energy spectrum and multifractal spectrum are highlighted as two possible approaches to this.     

太阳宁静区色球磁场观测

利用中国科学院北京天文台怀柔太阳磁场望远镜,对日面中心宁静区光球和色球磁场进行了长时间的积分观测。通过对光球、色球以及色球不同层次的长时间积分的观测发现,网络磁元从光球到色球扩展不大,并且部分内网络磁元升到了色球。这些结果对描述太阳磁场的两大模型提出了挑战。      

Solar activity prediction studies and services in NAOC

Solar activity prediction services started in 1960’s in National Astronomical Observatories, Chinese Academy of Sciences (NAOC). As one of the members of the International Space Environment Service (ISES), Regional Warning Center of China (RWC-China) was set up in 1990’s. Solar Activity Prediction Center (SAPC), as one of the four sub-centers of RWC-China, is located in NAOC. Solar activity prediction studies and services in NAOC cover short-term, medium-term, and long-term forecast of solar activities. Nowadays, certain prediction models, such as solar X-ray flare model, solar proton event model, solar 10 cm radio flux model, have been established for the practical prediction services. Recently, more and more physical analyses are introduced in the studies of solar activity prediction, such as the magnetic properties of solar active regions and magnetic structure of solar atmosphere. Besides traditional statistics algorithms, Machine Learning and Artificial Intelligence techniques, such as Support Vector Machine (SVM) method, are employed in the establishment of forecast models. A Web-based integrated platform for solar activity data sharing and forecast distribution is under construction.     

Observational study of magnetic chirality of solar active regions

We present the evolution of magnetic field and relationship with the magnetic (current) helicity in solar active regions from a series of photospheric vector magnetograms obtained at Huairou Solar Observing Station near Beijing, and also longitudinal magnetograms by MDI of SOHO, white light and 171 Å images by TRACE and soft X-ray images by Yohkoh.The conclusions in the analysis of the formation process of complex and delta magnetic configuration in some super active regions are the following: (1) The magnetic shear and gradient provide the non-potentiality of the magnetic field of active regions reflecting the existence of electric current. (2) Some of large-scale delta active regions could be due to the emergence of highly sheared non-potential magnetic flux bundles from the subatmosphere with amount of magnetic helicity, in addition to the emergence of twisted magnetic ropes. (3) We also present some results on the study of the magnetic (current) helicity in solar active regions.     

一个基于观测的太阳风背景模型

建立由太阳光球磁场和日冕偏振亮度等观测约束的单流体太阳风模型,包括日冕和太阳风的等离子体密度、速度和磁场,温度还有待于以后处理.这里采用高山观测台(HAO)MKⅢ的日冕偏振亮度(pB)在1.36Rs上的观测概图,根据Guhathakurta在1996年发展的日冕电子密度反演模型确定日冕的电子密度分布.同时采用Wilcox太阳观测台(WSO)的光球磁场视向分量的观测概图作为底部边界,根据Zhao等在1994年发展的水平电流-电流片(HCCS)模型得到全球磁场.Phillips在1995年及McComas在2003年分别用Ulysses第一次和第二次跨极飞行的观测发现,归一化到1 AU的太阳风动量流密度除了在10°～30°的纬度范围内略低以外几乎不变.根据这一结论,结合已经得到的密度数据,就可以得到日冕和太阳风的速度.将上面的模型应用于1918卡林顿自转周稳态太阳风的研究,结果与太阳活动极小期的观测基本相符,但是与观测相比较低速高密度区偏大,因此密度模型还有待改进.