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.     

Study of TEC changes during geomagnetic storms occurred near the crest of the equatorial ionospheric ionization anomaly in the Indian sector

GPS satellites data obtained at Bhopal (23.16° N, 77.36° E, geomagnetic latitude 14.23° N) India were analyzed to study the TEC changes during several geomagnetic storms (−300 nT < Dst < −50 nT) occurred in 2005–2007. We had segregated the storms according to the Dst value, i.e. moderate storms (−100 nT < Dst ? −50 nT), strong storms (−150 nT < Dst < −100 nT), and severe storms (Dst less than −150 nT). Total of 21 geomagnetic storms (10 moderate, 9 strong, 2 severe) are considered for the present study. Deviation in vertical total electron content (VTEC) during the main phase of the storm was found to be associated with the prompt penetration of electric field originated due to the under-shielding and over-shielding conditions for almost all geomagnetic storms discussed in this paper. For most of the storms VTEC shows the positive percentage deviation during the main phase while it shows positive as well as the negative deviation during the recovery phase of the storms. The −80% deviation in VTEC was found for geomagnetic storm occurred on July 17, 2005 and the negative trend continued for recovery phase of the storm. This was mainly due to the thermospheric composition changes by Joule heating effect at auroral latitudes that generate electric field disturbance at low latitudes. Traveling ionospheric disturbances (TIDs) were responsible for the formation of wave like nature in VTEC for the storms occurred on May 15, 2005, whereas it was not observed for storm occurred on August 24, 2005.     

Responses of the African equatorial ionization anomaly (EIA) to some selected intense geomagnetic storms during the maximum phase of solar cycle 24

This study investigates the morphology of the GPS TEC responses in the African Equatorial Ionization Anomaly (EIA) region to intense geomagnetic storms during the ascending and maximum phases of solar cycle 24 (2012–2014). Specifically, eight intense geomagnetic storms with Dst ≤ ?100 nT were considered in this investigation using TEC data obtained from 13 GNSS receivers in the East African region within 36–42°E geographic longitude; 29°N–10°S geographic latitude; ± 20°N magnetic latitude. The storm-time behavior of TEC shows clear positive and negative phases relative to the non-storm (median) behavior, with amplitudes being dependent on the time of sudden commencement of the storm and location. When a storm starts in the morning period, total electron content increases for all stations while a decrease in total electron content is manifested for a storm that had its sudden commencement in the afternoon period. The TEC and the EIA crest during the main phase of the storm is significantly impacted by the geomagnetic storm, which experiences an increase in the intensity of TEC while the location and spread of the crest usually manifest a poleward expansion.     

Latitudinal variation of F2-region response to geomagnetic disturbance

The effect of geomagnetic storms on the F2 region was studied by calculating the deviation, ΔfoF2, of foF2 during 40 magnetic storms, ranging from moderate (Dst < −50 nT) to very intense (Dst < −200 nT) of the 21st solar cycle. In order to study the variation of storm-time foF2 with latitude, season and storm strength, ionosonde data were obtained from eight stations spanning a latitudinal range of +60–−60°. The stations chosen lay in a narrow longitudinal range of 140–151°, so that local time difference between the stations is practically negligible. The features exhibited by positive and negative phases were essentially different. The storm time ΔfoF2 clearly exhibited a latitudinal variation and this variation were found to be coupled with the seasonal variation. As for the variation with storm intensity, though ΔfoF2 was found to vary even between two storms of almost equal intensity, the amplitude of a positive or negative phase, |ΔfoF2max| showed a distinct upper limit for each intensity category of storms.     

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.     

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.      

利用支持向量机预测大磁暴期间Dst指数的变化

利用支持向量机（SVM）模型对大磁暴期间Dst指数进行预报研究.以1995-2014年期间的80次大磁暴（Dst≤-100nT）事件共2662组观测数据为研究对象,以对应时间的太阳风参数为模型输入参数,同时建立了神经网络模型和线性机模型进行对比,并利用交叉验证提高预测结果的可靠性.为比较不同模型的预测效果,选用相关系数（CC）、均方根误差（RMS）、磁暴期间Dst指数最小值预测结果的平均绝对误差以及Dst指数最小值出现时间预测结果的平均绝对误差等统计量作为对比参数.结果显示SVM模型的预测效果最好,其中相关系数为0.89,均方根误差为24.27nT,所有磁暴事件的最小Dst值预测平均绝对误差为17.35nT,最小Dst值出现时间的预测平均绝对误差为3.2h.为进一步检验模型对不同活动水平磁暴预报效果的可能差异,将所有磁暴事件分为大磁暴（-200 相似文献   

磁暴数统计特性研究

Dst是一个表征磁暴强度的空间天气指数. 通过统计1957-2008年 发生的中等磁暴(-100<Dst≤ -50nT)和强磁暴(Dst ≤ -100nT)在太阳活动周上升年、极大年、下降年和极小年的时间分布情 况, 分析其随季节变化的统计特性, 进而讨论了引起磁暴的原因. 结果表明, 对于同一太阳活动周, 极大年地磁暴发生次数远大于极小年地磁暴的发生次数, 这与太阳黑子数的变化趋势是一致的; 通常太阳活动周强磁暴出现双峰结构, 而第23周中等磁暴出现双峰结构, 强磁暴则出现三峰结构, 这可能与1999 年强 磁暴发生次数异常少, 使1998年凸显出来的现象有关; 磁暴主要发生在分季, 随着Dst指数的增加, 磁暴发生次数明显增加.      

利用人工神经网络预报大磁暴

本文采用阈值预报的策略和人工神经网络BP模型,以13个太阳风参量和地磁AE,Dst指数作为输入,以0或1作为输出,提前4h预报大磁暴主相发生的时刻．结果表明,采用神经网络方法的阈值预报可以对灾害性磁暴的发生提前数小时做出比较准确的预报．     

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.     

Classification of solar wind structures and intense geomagnetic storm alarms with self-organizing maps

Intense geomagnetic storms (D_st < −100 nT) usually occur when a large interplanetary duskward-electric field (with Ey > 5 mV m⁻¹) lasts for more than 3 h. In this article, a self-organizing map (SOM) neural network is used to recognize different patterns in the temporal variation of hourly averaged Ey data and to predict intense storms. The input parameters of SOM are the hourly averaged Ey data over 3 h. The output layer of the SOM has a total of 400 neurons. The hourly Ey data are calculated from solar wind data, which are provided by NSSDC OMNIWeb and ACE spacecraft and contain information on 143 intense storms and a fair number of moderate storms, weak storms and quiet periods between September 3, 1966 and June 30, 2002. Our results show that SOM is able to classify solar wind structures and therefore to give timely intense storm alarms. In our SOM, 21 neurons out of 400 are identified to be closely associated with the intense storms and they successfully predict 134 intense storms out of the 143 ones selected. In particular, there are 14 neurons for which, if one or more of them are present, the occurrence probability of intense storms is about 90%. In addition, several of these 14 neurons can predict big magnetic storm (D_st  −180 nT). In summary, our method achieves high accuracy in predicting intense geomagnetic storms and could be applied in space environment prediction.     

Investigation of ionospheric response to two moderate geomagnetic storms using GPS–TEC measurements in the South American and African sectors during the ascending phase of solar cycle 24

The responses of the ionospheric F region using GPS–TEC measurements during two moderate geomagnetic storms at equatorial, low-, and mid-latitude regions over the South American and African sectors in May 2010, during the ascending phase of solar cycle 24, are investigated. The first moderate geomagnetic storm studied reached a minimum Dst value of −64 nT at 1500 UT on 02 May 2010 and the second moderate geomagnetic storm reached a minimum Dst value of −85 nT at 1400 UT on 29 May 2010. In this paper, we present vertical total electron content (VTEC) and phase fluctuations (in TECU/min) from Global Positioning System (GPS) observations from the equatorial to mid-latitude regions in the South American and African sectors. Our results obtained during these two moderate geomagnetic storms from both sectors show significant positive ionospheric storms during daytime hours at the equatorial, low-, and mid-latitude regions during the main and recovery phases of the storms. The thermospheric wind circulation change towards the equator is a strong indicator that suggests an important mechanism is responsible for these positive phases at these regions. A pre-storm event that was observed in the African sector from low- to the mid-latitude regions on 01 May 2010 was absent in the South American sector. This study also showed that there was no generation or suppression of ionospheric irregularities by storm events. Therefore, knowledge about the suppression and generation of ionospheric irregularities during moderate geomagnetic storms is still unclear.     

行星际扰动与不同级别磁暴强度关系的研究

利用1997-2004年间ACE卫星太阳风观测的时均值数据和相应的Dst指数,针对Dstmin≤-50 nT的磁暴,分析了行星际参数(Bz,Ey,v,Pk,|B|,ε'=vxB2zsin4(θ/2))与Dst指数的相关关系.验证了Ey,Bz与Dst指数的良好相关性;按磁暴强度的不同,发现磁暴强度越大,行星际参数与磁暴强度(Dstmin)的相关性就越好.对于中等磁暴(-100 nT＜Dstmin≤-50 nT),行星际参数与磁暴强度的相关系数不高.如果把磁暴分为两个档次,即-150 nT＜Dstmin≤-50 nT的磁暴和Dstmin≤-150 nT的磁暴,计算结果表明,ε'与Dst指数的相关性是最好的.在诸多行星际参数中,就单一因素来说,Ey对磁暴强度影响最大,Bz对磁暴强度影响次之.      

行星际南向磁场事件与强磁暴

利用１９７８－１９８８年期间的太阳风和地磁资料对行星际磁场（ＩＭＦ）南向分量Ｂｓ事件（即Ｂｓ〉１０ｎＴ及其所驱动的错向电场ＶＢｓ〉５ｍＶ／ｍ、持续时间△Ｔ〉３ｈ的事件）与弱磁暴（Ｄｓｔ≤－１００ｎＴ）关系进行了分析。结果表明,１００％的Ｂｓ事件能能引起磁暴的发生,但其中只有８４％为强磁暴;强磁暴的发生都与较强的ＩＭＦ Ｂｓ活动密切相关,但只有６８％的强磁共伴随Ｂｓ事件而发生;Ｂｓ事件与强磁暴并不是     

Geomagnetic storm effects on the occurrences of ionospheric irregularities over the African equatorial/low-latitude region

The study investigated the effects of intense geomagnetic storms of 2015 on the occurrences of large scale ionospheric irregularities over the African equatorial/low-latitude region. Four major/intense geomagnetic storms of 2015 were analyzed for this study. These storms occurred on 17th March 2015 (?229?nT), 22nd June 2015 (?204?nT), 7th October 2015 (?124?nT), and 20th December 2015 (?170?nT). Total Electron Content (TEC) data obtained from five African Global Navigation Satellite Systems (GNSS) stations, grouped into eastern and western sectors were used to derive the ionospheric irregularities proxy indices, e.g., rate of change of TEC (ROT), ROT index (ROTI) and ROTI daily average (ROTI_AVE). These indices were characterized alongside with the disturbance storm time (Dst), the Y component of the Interplanetary Electric Field (IEFy), polar cap (PC) index and the H component of the Earth’s magnetic field from ground-based magnetometers. Irregularities manifested in the form of fluctuations in TEC. Prompt penetration of electric field (PPEF) and disturbance dynamo electric field (DDEF) modulated the behaviour of irregularities during the main and recovery phases of the geomagnetic storms. The effect of electric field over both sectors depends on the local time of southward turning of IMF Bz. Consequently, westward electric field inhibited irregularities during the main phase of March and October 2015 geomagnetic storms, while for the June 2015 storm, eastward electric field triggered weak irregularities over the eastern sector. The effect of electric field on irregularities during December 2015 storm was insignificant. During the recovery phase of the storms, westward DDEF suppressed irregularities.     

第23太阳活动周中等地磁暴行星际源的统计分析

统计了第23太阳活动周(1996--2006年)发生的183次中等强度地磁暴(-100 nT < Dst ≤ -50 nT)的行星际源,分析了中等磁暴的年分布状况以及引起中等磁暴的不同行星际结构在太阳活动周中的分布特征,同时,与强磁暴行星际源的分布状况做了对比分析,主要的统计分析结果如下. (1)共转相互作用区CIR与行星际日冕物质抛射ICME在中等磁暴中具有同等重要的作用,且在ICME中,具有磁云结构和非磁云结构的ICME在引起中等磁暴的能力方面也基本相同,但带有鞘层结构的ICME在引起中等磁暴中具有更重要的作用. (2)中等磁暴在极大年(2001年)和下降年(2003年)发生次数最多,与地磁活动的双峰年对应,在极小年(1996和2006年)发生次数最少,与地磁活动低年对应,在其他年份分布较平均. (3)中等磁暴在太阳活动极大年主要由ICME引起,在上升年和下降年CIR在其中起主要作用,且下降年基本是上升年的两倍,而对于强磁暴而言,ICME始终是最重要的行星际源.      

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.      

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。     

On the mid-latitude ionospheric storm association with intense geomagnetic storms

The bulk association between ionospheric storms and geomagnetic storms has been studied. Hemispheric features of seasonal variation of ionospheric storms in the mid-latitude were also investigated. 188 intense geomagnetic storms (Dst ≤ 100 nT) that occurred during solar cycles 22 and 23 were considered, of which 143 were observed to be identified with an ionospheric storm. Individual ionospheric storms were identified as maximum deviations of the F2 layer peak electron density from quiet time values. Only ionospheric storms that could clearly be associated with the peak of a geomagnetic storm were considered. Data from two mid-latitude ionosonde stations; one in the northern hemisphere (i.e. Moscow) and the other in the southern hemisphere (Grahamstown) were used to study ionospheric conditions at the time of the individual geomagnetic storms. Results show hemispheric and latitudinal differences in the intensity and nature of ionospheric storms association with different types of geomagnetic storms. These results are significant for our present understanding of the mechanisms which drive the changes in electron density during different types of ionospheric storms.     

中纬度地磁暴期间热层垂直风响应机制的模拟

基于TIMEGCM模型,研究了2005年9月10日中纬度地磁暴期间热层(100～650 km)水平风场变化对垂直风的影响.通过连续性方程诊断分析了暴时引起垂直风场变化的机制,结果表明:250 km以上的垂直风场取决于水平风场的变化,而250 km以下的垂直风场由较高高度的垂直风拉动;在地磁暴初相开始时,经向风场相比纬向...