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.     

基于长短期记忆神经网络的太阳耀斑短期预报

提出了一个基于长短期记忆神经网络的耀斑预报模型,利用过去24 h太阳活动区的磁场变化时序构建样本,通过长短期记忆神经网络对磁场特征时序演化进行分析,预报未来48 h内是否发生≥M级别耀斑事件。使用的数据集为2010年5月到2017年5月所有活动区样本,选取了SDO/HMI SHARP的10个磁场特征参量。在建模过程中通过XGBoost方法选取权重、增益率和覆盖率均较高的6个特征参量作为输入参数。通过测试对比,模型的虚报率和准确率与传统机器学习模型相近,报准率和临界成功指数分别为0.7483和0.7402,优于传统机器学习模型。模型总体效果优于传统机器学习模型。      

Properties of solar X-ray flares and proton event forecasting

X-ray flares and acceleration processes are in one complex of sporadic solar events (together with CMEs, radio bursts, magnetic field dissipation and reconnection). This supposes the connection (if not physical, but at least statistical) between characteristics of the solar energetic proton events and flares. The statistical analysis indicates that probability and magnitude of the near-Earth proton enhancement depends heavily on the flare importance and their heliolongitude. These relations may be used for elaboration of the forecasting models, which allow us to calculate probability of the solar proton events from the X-ray observations.     

基于PCA方法对太阳活动区主要参量的分析

太阳耀斑与太阳质子事件的发生通常与太阳活动区存在非常密切的关系, 对这种关系的深入分析有助于太阳耀斑和太阳质子事件预报模型的建立. 本文利用主成分分析(Principal Component Analysis, PCA)方法对1997-2010年太阳质子事件所在活动区的主要参量进行分析, 选取的参量包括黑子磁分类、 McIntosh分类、太阳黑子群面积、10.7 cm射电流量、耀斑指数、质子耀斑位置和软X射线耀斑强度. 结果得到81个太阳活动主成分得分值排序(得分值代表每个事件的强弱), 与太阳质子事件峰值流量、太阳黑子年均值以及10.7 cm射电流量年均值的对比显示相似度非常高, 表明主成分得分值一定程度上可以反映太阳活动的强弱规律.      

Flux emergence,flux imbalance,magnetic free energy and solar flares

Emergence of complex magnetic flux in the solar active regions lead to several observational effects such as a change in sunspot area and flux embalance in photospheric magnetograms. The flux emergence also results in twisted magnetic field lines that add to free energy content. The magnetic field configuration of these active regions relax to near potential-field configuration after energy release through solar flares and coronal mass ejections. In this paper, we study the relation of flare productivity of active regions with their evolution of magnetic flux emergence, flux imbalance and free energy content. We use the sunspot area and number for flux emergence study as they contain most of the concentrated magnetic flux in the active region. The magnetic flux imbalance and the free energy are estimated using the HMI/SDO magnetograms and Virial theorem method. We find that the active regions that undergo large changes in sunspot area are most flare productive. The active regions become flary when the free energy content exceeds 50% of the total energy. Although, the flary active regions show magnetic flux imbalance, it is hard to predict flare activity based on this parameter alone.     

1996-2002年太阳耀斑的统计分析

分析了1996-2002年南北半球的太阳黑子相对数和南北半球太阳X射线耀斑级别(简称Imp)≥M1．0的太阳X射线耀斑的特征和不对称性．分析结果表明，南北半球的太阳耀斑活动的程度交替上升，在2001年7月以前北半球的太阳耀斑活动强于南半球，2001年7月开始耀斑活动逐渐以南半球为主．本文还逐月分析了1996—2001年南北半球的耀斑指数．2000年7月为第23周太阳指数最大的一个月，与第23周太阳黑子相对数最大月均值吻合．     

MHD simulation of magnetic field configuration above the active region NOAA 10365

The current sheet (CS) creation before a flare in the vicinity of a singular line above the active region NOAA 10365 is shown in numerical experiments. Such a way the possibility of energy accumulation for a solar flare is demonstrated. These data and results of observation confirm the electrodynamical solar flare model that explains solar flares and CME appearance during CS disruption. The model explains also all phenomena observed in flares. For correct reproduction of the real boundary conditions the magnetic flux between spots should be taken into account. The full system of 3D MHD equations are solved using the PERESVET code. For setting the boundary conditions the method of photospheric magnetic maps is used. Such a method permits to take into account all evolution of photospherical magnetic field during several days before the flare.     

Application of support vector machine combined with K-nearest neighbors in solar flare and solar proton events forecasting

The support vector machine (SVM) combined with K-nearest neighbors (KNN), called the SVM-KNN method, is new classing algorithm that take the advantages of the SVM and KNN. This method is applied to the forecasting models for solar flares and proton events. For the solar flare forecasting model, the sunspot area, the sunspot magnetic class, and the McIntosh class of sunspot group and 10 cm solar radio flux are chosen as inputs; for the solar proton event forecasting model, the inputs include the longitude of active regions, the flux of soft X-ray, and those for the solar flare forecasting model. Detailed tests are implemented for both of the proposed forecasting models, in which the SVM-KNN and the SVM methods are compared. The testing results demonstrate that the SVM-KNN method provide a higher forecasting accuracy in contrast to the SVM. It also gives an increased rate of ‘Low’ prediction at the same time. The ‘Low’ prediction means occurrence of solar flares or proton events with predictions of non-occurrence. This method show promise for forecasting models of solar flare and proton events.     

太阳发电机理论研究

太阳活动主要是由磁场产生的, 因此, 对太阳磁场性质和起源的研究具有重要意义. 太阳发电机理论主要研究的是太阳上观测到的与太阳活动相关的磁场起源、磁场特征、各种活动现象之间的相关性及其变化规律. 其是太阳物理学中有待解决的最基本、最重要的问题. 根据太阳黑子及太阳周期的相关观测, 介绍了构成发电机的基本要素, 具体描述了各种典型发电机模型, 并对其分别进行评述, 进而探讨了目前存在的问题及发展方向.      

Two energy release processes for CMEs: MHD catastrophe and magnetic reconnection

It remains an open question how magnetic energy is rapidly released in the solar corona so as to create solar explosions such as solar flares and coronal mass ejections (CMEs). Recent studies have confirmed that a system consisting of a flux rope embedded in a background field exhibits a catastrophic behavior, and the energy threshold at the catastrophic point may exceed the associated open field energy. The accumulated free energy in the corona is abruptly released when the catastrophe takes place, and it probably serves as the main means of energy release for CMEs at least in the initial phase. Such a release proceeds via an ideal MHD process in contrast with nonideal ones such as magnetic reconnection. The catastrophe results in a sudden formation of electric current sheets, which naturally provide proper sites for fast magnetic reconnection. The reconnection may be identified with a solar flare associated with the CME on one hand, and produces a further acceleration of the CME on the other. On this basis, several preliminary suggestions are made for future observational investigations, especially with the proposed Kuafa satellites, on the roles of the MHD catastrophe and magnetic reconnection in the magnetic energy release associated with CMEs and flares.     

太阳光球磁场特征物理量在质子事件短期预报中的应用

利用SOHO/MDI全日面纵向磁图, 计算了三个描述太阳活动区磁场复杂性和非势性的特征物理量, 即纵向磁场最大水平梯度Bz, 强梯度中性线长度L, 孤立奇点数目η. 为检验太阳光球磁场特征在质子事件短期预报中是否有效, 采用BP神经网络方法, 建立了基于这三个磁场特征物理量简单的太阳质子事件短期(24h)预报模型. 模 型在对2002年和2003年连续两年的样本检测中, 有很高的准确率(2002年和2003年 分别为90 %, 87.54 %)和较高的 质子事件报准率(2002年和2003年分别为60 %, 75 %),从而为光球磁场特征物理量作为质子事件预报的有效因子提供了依据.      

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．     

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.      

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.      

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.     

Response of the low latitude geomagnetic field to the major proton event of November 2001

A major solar flare eruption occurred at 16:20 UT on 4 November 2001, followed by strong solar radiation storm and proton event recorded by the SOHO and other interplanetary satellites. Coronal mass ejection associated with the flare event triggered an interplanetary shock, which impacted the geomagnetic field after about 33 h. The shock impact was quite intense to produce a SSC magnitude of 80 nT in the low latitude ground magnetic records followed by sharp and deep main phase (Dst −300 nT) in the first stage, following the density (N_p) enhancement. High time resolution digital magnetic field data from the equatorial and low latitude stations in India are analyzed to study the influence of various IP parameters on the intensity and duration of the magnetic storm. A double step storm was found to be in progress caused by the multiple injections. During the period of recovery, after a period of 8 h, a third stage of depression in the ground magnetic field was set in, which corresponded to the southward directed Bz. The energy transfer processes associated with the event is presented.     

Converging motion of conjugate flaring kernels during two large solar flares

In this paper, we analyze the footpoint motion of two large solar flares using observations made by the Transition Region and Coronal Explorer (TRACE) and Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). The two flares are the M5.7 flare of March 14, 2002 and the X10 flare of October 29, 2003. They are both classical two-ribbon flares as observed in TRACE 1600 or 171 Å images and have long-duration conjugate hard X-ray (HXR) footpoint emission. We use the ‘center-of-mass’ method to locate the centroids of the UV/EUV flare ribbons. The results are: (1) The conjugate UV/EUV ribbons and HXR footpoints of the two flares show a converging (inward) motion during the impulsive phase. For the two flares, the converging motion lasts about 3 and 10 min, respectively. The usual separation (outward) motion for the flare ribbons and footpoints take place only after the converging motion. (2) During the inward and the outward motion, the conjugate ribbons and footpoints of the two events exhibit a strong unshear motion. In obtaining above results, TRACE UV/EUV and RHESSI HXR data show an overall agreement. The two events demonstrate that the magnetic reconnection for the flares occurs in highly sheared magnetic field. Furthermore, the results support the magnetic model constructed by Ji et al. [Ji, H., Huang, G., Wang, H. Astrophys. J. 660, 893–900, 2007], who proposed that the contracting motion of flaring loops is the signature of the relaxation of sheared magnetic fields.     

Prediction of expected global climate change by forecasting of galactic cosmic ray intensity time variation in near future based on solar magnetic field data

A method of prediction of expected part of global climate change caused by cosmic ray (CR) by forecasting of galactic cosmic ray intensity time variation in near future based on solar activity data prediction and determined parameters of convection-diffusion and drift mechanisms is presented. This gave possibility to make prediction of expected part of global climate change, caused by long-term cosmic ray intensity variation. In this paper, we use the model of cosmic ray modulation in the Heliosphere, which considers a relation between long-term cosmic ray variations with parameters of the solar magnetic field. The later now can be predicted with good accuracy. By using this prediction, the expected cosmic ray variations in the near Earth space also can be estimated with a good accuracy. It is shown that there are two possibilities: (1) to predict cosmic ray intensity for 1–6 months by using a delay of long-term cosmic ray variations relatively to effects of the solar activity and (2) to predict cosmic ray intensity for the next solar cycle. For the second case, the prediction of the global solar magnetic field characteristics is crucial. For both cases, reliable long-term cosmic ray and solar activity data as well as solar magnetic field are necessary. For solar magnetic field, we used results of two magnetographs (from Stanford and Kitt Peak Observatories). The obtained forecasting of long-term cosmic ray intensity variation we use for estimation of the part of global climate change caused by cosmic ray intensity changing (influenced on global cloudiness covering).     

Evidence of the radio-quiet hard X-ray precursor of the 13 December 2006 solar flare

We report multi-wavelength investigation of the pre-impulsive phase of the 13 December 2006 X-class solar flare. We use hard X-ray data from the anticoincidence system of spectrometer onboard INTEGRAL (ACS) jointly with soft X-ray data from the GOES-12 and Hinode satellites. Radio data are from Nobeyama and Learmonth solar observatories and from the Culgoora Solar Radio Spectrograph. The main finding of our analysis is a spiky increase of the ACS count rate accompanied by surprisingly gradual and weak growth of microwave emission and without detectable radio emission at meter and decimeter wavelengths about 10 min prior to the impulsive phase of the solar flare. At the time of this pre-flare hard X-ray burst the onset of the GOES soft X-ray event has been reported, positive derivative of the GOES soft X-ray flux started to rise and a bright spot has appeared in the images of the Hinode X-ray telescope (XRT) between the flare ribbons near the magnetic inversion line close to the sources of thermal and non-thermal hard X-ray emission observed by Reuven Ramaty High-Energy Solar Spectroscopic Imager (RHESSI) during the flare. These facts we consider as evidences of solar origin of the increased pre-flare ACS count rate. We briefly discuss a possible cause of the pre-flare emission peculiarities.     

太阳质子耀斑的一个统计性质

本文研究太阳质子耀斑相对于太阳光球大尺度平均磁场中性线的分布, 给出一个新得到的质子耀斑的统计性质。研究太阳质子事件及其源耀斑的统计性质, 是太阳物理和空间物理学的重要前沿课题。从太阳活动预报及地球空间环境预报研究的角度看, 一个重要的问题是质子耀斑在