基于稀疏地磁数据的中低纬度磁暴感应地电场的算法研究

强磁暴产生的地磁感应电流是诱发电力系统灾害性事故的关键因素,预防与控制地磁感应电流的必要途径是评估其在系统中的水平.掌握磁暴感应地电场的时空分布是评估所在区域电网地磁感应电流的基础,可为研究与防治电网磁暴灾害提供参考.在中国现有稀疏分布的地磁台观测数据基础上,建立了电离层等效球面元电流系统模型,并将其与复镜像法结合,建立了磁暴感应地电场和地磁场的计算模型.利用磁暴期间实测的地磁台站数据进行了计算,算例结果与平面波理论计算结果的对比证明了算法的正确性与有效性.计算结果可直接应用于电力系统的地磁感应电流计算,为分析电力系统磁暴灾害风险提供参考.      

磁暴期间的地磁导航精度分析

地磁导航是无源自主导航技术研究的新方向. 分析了地磁导航的基本原理, 描述了典型磁暴过程, 并针对地磁导航在磁暴环境中的适用性进行了研究. 在采用曲面样条方法对实测地磁场数据建立观测模型的基础上, 结合广义卡尔曼滤波方法讨论了磁暴不同阶段对地磁导航精度造成的影响. 分别采用理论典型磁暴数据以及实测磁暴数据进行仿真, 仿真结果表明, 在磁暴的初相、恢复相的中后时段以及中等强度以下的磁暴全过程仍然可以采用地磁来进行导航定位, 导航精度在200 m以内, 满足飞行器中程制导的精度要求.      

1993年9月12—14日磁暴期间磁层—电离层耦合分析

采用具有明确物理意义的多个地磁指数，以及地面台站链观测的地磁和电离层参数，对一次典型磁暴期内从极光区到赤道附近电离层电流、电场演化发展的耦合过程作了具体分析．结果表明，地磁指数和观测参数能较好地说明磁层－电离层耦合理论结果的主要特征．     

行星际电场与Dst指数

利用ACE卫星的太阳风及行星际磁场观测数据和相应时期的Dst指数，分析了行星际电场的Dst指数的相关关系，讨论了行星际电场作为研究磁层和太阳风相互作用的良好参数的物理机制。结果表明：行星际电场与Dst指数有很好的相关性，并且在强和中等地磁活动基间，存在显著的突变特征曲线；相对于V、V^2Bz、VB^2和ε，行星际电场的突变特征曲线更易识别；弱的扰动磁层背景状况和行星际磁场南向分量及电场晨昏分量的较大波动影响着磁暴的发展，使磁暴主相有多个发展阶段，从而增加磁暴的强度；对主相有多个发展阶段磁暴的研究有待进一步改善。     

冕洞特征参数与地磁暴强度及发生时间统计

地磁暴是空间天气预报的重要对象.在太阳活动周下降年和低年，冕洞发出的高速流经过三天左右行星际传输到达地球并引发的地磁暴占主导地位.目前地磁暴的预报通常依赖于1AU处卫星就位监测的太阳风参数，预报提前量只有1h左右.为了增加地磁暴预报提前量，需要从高速流和地磁暴的源头即太阳出发，建立冕洞特征参数与地磁暴的定量关系.分析了2010年5月到2016年12月的152个冕洞-地磁暴事件，利用SDO/AIA太阳极紫外图像提取了两类冕洞特征参数，分析了其与地磁暴期间ap，Dst和AE三种地磁指数的统计关系，给出冕洞特征参数与地磁暴强度以及发生时间的统计特征，为基于冕洞成像观测提前1～3天预报地磁暴提供了依据.      

低轨道中等能量电子对地磁扰动的响应

低轨道高度上能量电子通量变化与地磁扰动程度密切相关.利用我国资源2号(ZY-2)03星空间环境监测分系统在轨工作期间所获得的能量电子探测数据,以及美国NOAA-15,NOAA-16,NOAA-17三颗卫星中等能量电子探测器自1998年以来积累的太阳同步轨道中等能量电子探测数据,结合地磁活动观测数据,对低轨道高度上中等能量电子对地磁扰动的响应特性进行了统计分析.结果表明,该区域的中等能量电子通量在磁暴、磁层亚暴期间有显著增强,增幅大小与地磁活动程度呈正相关关系,强磁暴期间增幅可达一个数量级左右,在响应时间上存在电子通量变化滞后于磁扰的时间特性.      

磁暴期电离层离子上行能通量的统计关系研究

利用FAST卫星1997-2006年34个磁暴期149个轨道的观测数据,分析不同相位上行通量数量级,研究不同相位离子上行能通量与地磁活动Sym-H指数和Kp指数,以及注入的Poynting通量之间的关系,构造上行通量经验模型.研究结果表明:磁暴主相期间,上行离子能通量可超过108 eV·cm–2·s–1·sr–1·eV...     

利用转移熵研究引起磁暴扰动的太阳风参数重要性排序

磁暴是重要空间天气灾害性事件，能够影响卫星的安全在轨运行和地面电网系统等。目前，对于太阳风–磁层相互作用的研究多集中在分析相关系数的线性关系，而基于信息论的转移熵可以提供强大的无模型有向统计量，可用来分析传统相关性分析和模型假设检测不到的非线性关系。本文利用转移熵的方法，研究了磁暴期间的太阳风驱动参数。利用第23和24太阳活动周的小时精度数据进行长时间尺度分析，发现太阳风向地磁的信息传递呈双峰分布，表现出与太阳活动水平的一致性。利用2010-2018年93个地磁暴期间的分钟精度数据进行短时间尺度分析，结果表明：行星际电场(E)和行星际磁场南向分量(B z)对地磁指数Sym-H在时间延迟为60 min时信息传递较强，而太阳风速度v_{s w}、温度T _sw、数密度D_sw、磁场B和动压P_sw对Sym-H指数的信息传递较弱。上述研究结果能够为太阳风–磁层相互作用的建模提供参数选择及确定预测范围的依据。     

异常SSC事件的行星际原因分析

磁暴急始(SSC)是强烈太阳风动压或行星际激波与磁层相互作用的结果.通常SSC事件的上升时间在4～10 min,我们把上升时间超过15 min的SSC事件称为异常SSC事件.本文利用地磁SYM-H指数鉴别出了5个有地磁观测历史以来发生的上升时间大于15 min的异常SSC事件,并利用Wind,ACE,IMP 8,Goes,Geotail多点卫星太阳风观测数据和地磁观测数据,分析了异常SSC事件的行星际原因.结果表明,异常SSC事件通常都是强烈行星际扰动引起的,5个异常SSC事件有4个对应于行星际激波,有3个对应于多步太阳风动压跃变,有1个对应于行星际电场大幅度变化;由行星际激波产生的异常SSC事件,其上升时间依赖于行星际激波的方向,方向相对于日地连线越偏,上升时间越长;异常SSC事件上升时间与行星际磁场方向关系不明显.      

雷暴电场对LHAASO探测面宇宙线次级粒子能量的影响

采用Monte Carlo方法，通过模拟研究了不同强度雷暴电场对LHAASO探测面宇宙线次级电子能量的影响.在电场作用下，电子的能量分布发生了变化.在低能段总电子数目增加明显，而在高能段电场的影响不明显.当电场强度为1700V·cm-1（大于逃逸电场）时，能量<120MeV的电子被加速，能量<60MeV的总电子数目呈指数增长（增幅高达约2252%），雷暴电场对次级粒子的加速机制与相对论电子逃逸雪崩机制（RREA）相符.当电场强度为1000V·cm-1（小于逃逸电场）时，能量<70MeV的电子被加速，其数目明显增加，但是增幅（约86%）远小于逃逸电场时的幅度.对电场强度小于逃逸电场时的雷暴电场加速宇宙线次级粒子的物理机制进行了讨论.研究结果可为理解LHAASO实验数据特点以及研究雷暴期间宇宙线强度的变化等提供参考.      

Large geomagnetic storms of extreme solar event periods in solar cycle 23

During extreme solar events such as big flares or/and energetic coronal mass ejections (CMEs) high energy particles are accelerated by the shocks formed in front of fast interplanetary coronal mass ejections (ICMEs). The ICMEs (and their sheaths) also give rise to large geomagnetic storms which have significant effects on the Earth’s environment and human life. Around 14 solar cosmic ray ground level enhancement (GLE) events in solar cycle 23 we examined the cosmic ray variation, solar wind speed, ions density, interplanetary magnetic field, and geomagnetic disturbance storm time index (D_st). We found that all but one of GLEs are always followed by a geomagnetic storm with D_st  −50 nT within 1–5 days later. Most(10/14) geomagnetic storms have D_st index  −100  nT therefore generally belong to strong geomagnetic storms. This suggests that GLE event prediction of geomagnetic storms is 93% for moderate storms and 71% for large storms when geomagnetic storms preceded by GLEs. All D_st depressions are associated with cosmic ray decreases which occur nearly simultaneously with geomagnetic storms. We also investigated the interplanetary plasma features. Most geomagnetic storm correspond significant periods of southward B_z and in close to 80% of the cases that the B_z was first northward then turning southward after storm sudden commencement (SSC). Plasma flow speed, ion number density and interplanetary plasma temperature near 1 AU also have a peak at interplanetary shock arrival. Solar cause and energetic particle signatures of large geomagnetic storms and a possible prediction scheme are discussed.     

Statistical analysis of the occurrence rate of geomagnetic storms during solar cycles 20–24

This study examines the occurrences rate of geomagnetic storms during the solar cycles (SCs) 20–24. It also investigates the solar sources at SCs 23 and 24. The Disturbed storm time (Dst) and Sunspot Number (SSN) data were used in the study. The study establishes that the magnitude of the rate of occurrences of geomagnetic storms is higher (lower) at the descending phases (minimum phases) of solar cycle. It as well reveals that severe and extreme geomagnetic storms (Dst < -250 nT) seldom occur at low solar activity but at very high solar activity and are mostly associated with coronal mass ejections (CMEs) when occurred. Storms caused by CME + CH-HSSW are more prominent during the descending phase than any other phase of the solar cycle. Solar minimum features more CH-HSSW- associated storms than any other phase. It was also revealed that all high intensity geomagnetic storms (strong, severe and extreme) are mostly associated with CMEs. However, CH-HSSW can occasionally generate strong storms during solar minimum. The results have proven that CMEs are the leading cause of geomagnetic storms at the ascending, maximum and the descending phases of the cycles 23 and 24 followed by CME + CH-HSSW. The results from this study indicate that the rate of occurrence of geomagnetic storms could be predicted in SC phases.     

Dayside ionospheric uplift during strong geomagnetic storms as detected by the CHAMP,SAC-C,TOPEX and Jason-1 satellites

Ionosphere response to severe geomagnetic storms that occurred in 2001–2003 was analyzed using data of global ionosphere maps (GIM), altimeter data from the Jason-1 and TOPEX satellites, and data of GPS receivers on-board CHAMP and SAC-C satellites. This allowed us to study in detail ionosphere redistribution due to geomagnetic storms, dayside ionospheric uplift and overall dayside TEC increase. It is shown that after the interplanetary magnetic field turns southward and intensifies, the crests of the equatorial ionization anomaly (EIA) travel poleward and the TEC value within the EIA area increases significantly (up to ∼50%). GPS data from the SAC-C satellite show that during the main phase of geomagnetic storms TEC values above the altitude of 715 km are 2–3 times higher than during undisturbed conditions. These effects of dayside ionospheric uplift occur owing to the “super-fountain effect” and last few hours while the enhanced interplanetary electric field impinged on the magnetopause.     

The solar wind control of the equatorial ionosphere dynamics during geomagnetic storms

The interplanetary magnetic field, geomagnetic variations, virtual ionosphere height h′F, and the critical frequency foF2 data during the geomagnetic storms are studied to demonstrate relationships between these phenomena. We study 5-min ionospheric variations using the first Western Pacific Ionosphere Campaign (1998–1999) observations, 5-min interplanetary magnetic field (IMF) and 5-min auroral electrojets data during a moderate geomagnetic storm. These data allowed us to demonstrate that the auroral and the equatorial ionospheric phenomena are developed practically simultaneously. Hourly average of the ionospheric foF2 and h′F variations at near equatorial stations during a similar storm show the same behavior. We suppose this is due to interaction between electric fields of the auroral and the equatorial ionosphere during geomagnetic storms. It is shown that the low-latitude ionosphere dynamics during these moderate storms was defined by the southward direction of the B_z-component of the interplanetary magnetic field. A southward IMF produces the Region I and Region II field-aligned currents (FAC) and polar electrojet current systems. We assume that the short-term ionospheric variations during geomagnetic storms can be explained mainly by the electric field of the FAC. The electric fields of the field-aligned currents can penetrate throughout the mid-latitude ionosphere to the equator and may serve as a coupling agent between the auroral and the equatorial ionosphere.     

Statistical study of the time delay of ionospheric TEC storms to geomagnetic storms in Taoyuan,Taiwan

We have studied the time delay of ionospheric storms to geomagnetic storms at a low latitude station Taoyuan (25.02°N, 121.21°E), Taiwan using the Dst and TEC data during 126 geomagnetic storms from the year 2002 to 2014. In addition to the known local time dependence of the time delay, the statistics show that the time delay has significant seasonal characteristics, which can be explained within the framework of the seasonal characteristics of the ionospheric TEC. The data also show that there is no correlation between the time delay and the intensity of magnetic storms. As for the solar activity dependence of the time delay, the results show that there is no relationship between the time delay of positive storms and the solar activity, whereas the time delay of negative storms has weakly negative dependence on the solar activity, with correlation coefficient −0.41. Especially, there are two kinds of extreme events: pre-storm response events and long-time delay events. All of the pre-storm response events occurred during 15–20 LT, manifesting the Equator Ionospheric Anomaly (EIA) feature at Taoyuan. Moreover, the common features of the pre-storm response events suggest the storm sudden commencement (SSC) and weak geomagnetic disturbance before the main phase onset (MPO) of magnetic storms are two main possible causes of the pre-storm response events. By analyzing the geomagnetic indices during the events with long-time delay, we infer that this kind of events may not be caused by magnetic storms, and they might belong to ionospheric Q-disturbances.     

The impact of coronal mass ejection on the horizontal geomagnetic fields and the induced geoelectric fields

This work investigates the influence of coronal mass ejection (CME) on the time derivatives of horizontal geomagnetic and geoelectric fields, proxy parameters for identifying GICs. 16 events were identified for the year 2003 from the CORONAS-PHOTON spacecraft. Five of the events (May 29, June 9, October 28, October 29, and November 4) were extensively discussed over four magnetic observatories, were analyzed using the time derivatives of the horizontal geomagnetic (dH/dt) and geoelectric (E_H) fields obtained from data of the INTERMAGNET network. It was observed that energy distributions of the wavelet power spectrum of the horizontal geoelectric field are noticed at the nighttime on both 29 May and 9 June 2003 across the stations. Daytime and nighttime intensification of energy distribution of the wavelet power spectrum of the horizontal geoelectric field are observed on both 28 and 29 October 2003 due to strong westward electrojet. The 4 November 2003 event depicts daytime amplification of energy distributions of the wavelet power spectrum across the stations. The highest correlation magnitude is obtained in the event of 4 November 2003 between dH/dt and E_H relationships during the intense solar flare of class X 17.4. We observed that the correlation magnitude between dH/dt and E_H increases with increase in CME activity. We concluded that the response of the surface impedance model for different stations plays a key role in determining the surface electric field strength, due to large electric field changes at different stations.     

Storm-time atmospheric density modeling using neural networks and its application in orbit propagation

Upper atmospheric densities during geomagnetic storms are usually poorly estimated due to a lack of clear understanding of coupling mechanisms between the thermosphere and magnetosphere. Consequently, the orbit determination and propagation for low-Earth-orbit objects during geomagnetic storms have large uncertainties. Artificial neural networks are often used to identify nonlinear systems in the absence of rigorous theory. In the present study, an attempt has been made to model the storm-time atmospheric density using neural networks. Considering the debate over the representative of geomagnetic storm effect, i.e. the geomagnetic indices ap and Dst, three neural network models (NNM) are developed with ap, Dst and a combination of ap and Dst respectively. The density data used for training the NNMs are derived from the measurements of the satellites CHAMP and GRACE. The NNMs are evaluated by looking at: (a) the mean residuals and the standard deviations with respect to the density data that are not used in training process, and (b) the accuracy of reconstructing the orbits of selected objects during storms employing each model. This empirical modeling technique and the comparisons with the models NRLMSIS-00 and Jacchia-Bowman 2008 reveal (1) the capability of neural networks to model the relationship between solar and geomagnetic activities, and density variations; and (2) the merits and demerits of ap and Dst when it comes to characterizing density variations during storms.