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.     

Interplanetary shocks and sudden impulses during solar maximum (2000) and solar minimum (1995–1996)

In this work a study is performed on the correlation between fast forward interplanetary shock parameters at 1 Astronomical Unit and sudden impulse (SI) amplitudes in the H-component of the geomagnetic field, for periods of solar activity maximum (year 2000) and minimum (year 1995–1996). Solar wind temperature, density and speed, and total magnetic field, were taken to calculate the static pressures (thermal and magnetic) both in the upstream and downstream sides of the shocks. The variations of the solar wind parameters and pressures were then correlated with SI amplitudes. The solar wind speed variations presented good correlations with sudden impulses, with correlation coefficients larger than 0.70 both in solar maximum and solar minimum, whereas the solar wind density presented very low correlation. The parameter better correlated with SI was the square root dynamic pressure variation, showing a larger correlation during solar maximum (r = 0.82) than during solar minimum (r = 0.77). The correlations of SI with square root thermal and magnetic pressure were smaller than with the dynamic pressure, but they also present a good correlation, with r > 0.70 during both solar maximum and minimum. Multiple linear correlation analysis of SI in terms of the three pressure terms have shown that 78% and 85% of the variance in SI during solar maximum and minimum, respectively, are explained by the three pressure variations. Average sudden impulse amplitude was 25 nT during solar maximum and 21 nT during solar minimum, while average square root dynamic pressure variation is 1.20 and 0.86 nPa^1/2 during solar maximum and minimum, respectively. Thus on average, fast forward interplanetary shocks are 33% stronger during solar maximum than during solar minimum, and the magnetospheric SI response has amplitude 20% higher during solar maximum than during solar minimum. A comparison with theoretical predictions (Tsyganenko’s model corrected by Earth’s induced currents) of the coefficient of sudden impulse change with solar wind dynamic pressure variation showed excellent agreement, with values around 17 nT/nPa^1/2.     

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.     

Solar terrestrial effects of two distinct types

The occurrence frequencies or fluxes of most of the solar phenomena show a 11-year cycle like that of sunspots. However, the average characteristics of these phenomena may not show a 11-year cycle. Among the terrestrial parameters, some related directly to the occurrence frequencies of solar phenomena (for example, ionospheric number densities related to solar EUV fluxes which show 11-year cycle like sunspots) show 11-year cycles, including the double-peak structures near sunspot maxima. Other terrestrial parameters related to average characteristics may not show 11-year sunspot cycles. For example, long-term geomagnetic activity (Ap or Dst indices) is related to the average interplanetary solar wind speed V and the total magnetic field B. The average values of V depend not on the occurrence frequency of ICMEs and/or CIRs as such, but on the relative proportion of slow and high-speed events in them. Hence, V values (and Ap values) in any year could be low, normal or high irrespective of the phase of the 11-year cycle, except that during sunspot minimum, V (and Ap) values are also low. However, 2–3 years after the solar minimum (well before sunspot maximum), V values increase, oscillate near a high level for several years, and may even increase further during the declining phase of sunspot activity, due to increased influence of high-speed CIRs (corotating interplanetary regions). Thus, Ap would have no fixed relationship with sunspot activity. If some terrestrial parameter shows a 11-year cycle, chances are that the solar connection is through the occurrence frequencies (and not average characteristics) of some solar parameter.     

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.     

Solar wind dependence of the Pc1 wave activity

There are a host of factors influencing the excitation of Pc1 geomagnetic pulsations, which are ULF waves in the frequency range between 0.2 and 5 Hz. We have studied carefully the dependence of the pearl-type Pc1 activity at Sodankylä, Finland (L = 5.1) on the plasma density N in front of the magnetosphere, the bulk velocity V of the solar wind, and the intensity B of the IMF. The result is as follows: high values of N and reduced values of V are favorable to appearance of Pc1, whereas the dependence of Pc1 activity on B is practically absent. We also show that the probability of Pc1 occurrence decreases with the interplanetary electric field, and increases with solar wind impact pressure and with the plasma to magnetic pressure ratio “beta”.     

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   

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.      

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.      

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.     

Classification and quantification of solar wind driver gases leading to intense geomagnetic storms

Classification and quantification of the interplanetary structures causing intense geomagnetic storms (Dst?≤??100?nT) that occurred during 1997–2016 are studied. The subject of this consists of solar wind parameters of seventy-three intense storms that are associated with the southward interplanetary magnetic field. About 30.14% of the storms were driven by a combination of the sheath and ejecta (S?+?E), magnetic clouds (MC) and sheath field (S) are 26% each, 10.96% by combined sheath and MCs (S?+?C), while 5.48% of the storms were driven by ejecta (E) alone. Therefore, we want to aver that for storms driven by: (1) S?+?E. The Bz is high (≥10?nT), high density (ρ) (>10?N/cm³), high plasma beta (β) (>0.8), and unspecified (i.e. high or low) structure of the plasma temperature (T) and the flow speed (V); (2) MC. The Bz is ≥10?nT, low temperature (T?≤?400,000?K), low ρ (≤10?N/cm³), high V (≥450?km), and low β (≤0.8); (3) The structures of S?+?C are similar to that of MC except that the V is low (V?≤?450?km); (4) S. The Bz is high, low T, high ρ, unspecified V, and low β; and (5) E. Is when the structures are directly opposite of the one driven by MCs except for high V. Although, westward ring current indicates intense storms, but the large intensity of geomagnetic storms is determined by the intense nature of the electric field strength and the Bz. Therefore, great storms (i.e. Dst?≤??200?nT) are manifestation of high electric field strength (≥13?mV/m).     

Solar and interplanetary precursors of geomagnetic storms in solar cycle 23

Estimating the magnetic storm effectiveness of solar and associated interplanetary phenomena is of practical importance for space weather modelling and prediction. This article presents results of a qualitative and quantitative analysis of the probable causes of geomagnetic storms during the 11-year period of solar cycle 23: 1996–2006. Potential solar causes of 229 magnetic storms (Dst ? −50 nT) were investigated with a particular focus on halo coronal mass ejections (CMEs). A 5-day time window prior to the storm onset was considered to track backward the Sun’s eruptions of halo CMEs using the SOHO/LASCO CMEs catalogue list. Solar and interplanetary (IP) properties associated with halo CMEs were investigated and correlated to the resulting geomagnetic storms (GMS). In addition, a comparative analysis between full and partial halo CME-driven storms is established. The results obtained show that about 83% of intense storms (Dst ? −100 nT) were associated with halo CMEs. For moderate storms (−100 nT < Dst ? −50 nT), only 54% had halo CME background, while the remaining 46% were assumed to be associated with corotating interaction regions (CIRs) or undetected frontside CMEs. It was observed in this study that intense storms were mostly associated with full halo CMEs, while partial halo CMEs were generally followed by moderate storms. This analysis indicates that up to 86% of intense storms were associated with interplanetary coronal mass ejections (ICMEs) at 1 AU, as compared to moderate storms with only 44% of ICME association. Many other quantitative results are presented in this paper, providing an estimate of solar and IP precursor properties of GMS within an average 11-year solar activity cycle. The results of this study constitute a key step towards improving space weather modelling and prediction.     

Evolution of Dst index,cosmic rays and global temperature during solar cycles 20–23

We have studied conditions in interplanetary space, which can have an influence on galactic cosmic ray (CR) and climate change. In this connection the solar wind and interplanetary magnetic field parameters and cosmic ray variations have been compared with geomagnetic activity represented by the equatorial Dst index from the beginning 1965 to the end of 2012. Dst index is commonly used as the solar wind–magnetosphere–ionosphere interaction characteristic. The important drivers in interplanetary medium which have effect on cosmic rays as CMEs (coronal mass ejections) and CIRs (corotating interaction regions) undergo very strong changes during their propagation to the Earth. Because of this CMEs, coronal holes and the solar spot numbers (SSN) do not adequately reflect peculiarities concerned with the solar wind arrival to 1 AU. Therefore, the geomagnetic indices have some inestimable advantage as continuous series other the irregular solar wind measurements. We have compared the yearly average variations of Dst index and the solar wind parameters with cosmic ray data from Moscow, Climax, and Haleakala neutron monitors during the solar cycles 20–23. The descending phases of these solar cycles (CSs) had the long-lasting solar wind high speed streams occurred frequently and were the primary contributors to the recurrent Dst variations. They also had effects on cosmic rays variations. We show that long-term Dst variations in these solar cycles were correlated with the cosmic ray count rate and can be used for study of CR variations. Global temperature variations in connection with evolution of Dst index and CR variations is discussed.     

Storm-time formation of a relativistic electron belt and some relevant phenomena in other magnetospheric plasma domains

An empirical formula relating the strength of a storm given by its |Dst|_max with the L-coordinate of the peak of storm-injected relativistic electrons is one of a few well-confirmed quantitative relations found in the magneto-spheric physics. We successively extended a dataset of the formula’s basic storms with several events of high Dst-amplitude up to the highest observed |Dst|_max = 600 nT. Possible applying of the formula to the predicting of the ring-current plasma-pressure distribution and the lowest westward electrojet position for a storm are discussed. We have also analyzed the 2000–2001 years’ data on relativistic electrons from our instruments installed on EXPRESS-A (geosynchronous orbit; E_e = 0.8–6 MeV), Molniya-3 (h = 500 × 40 000 km, i = 63°; E_e = 0.8–5.5 MeV) and GLONASS (h = 20 000 km, i = 64°; E_e  l MeV) along with other correlated measurements: GOES series (E_e > 2 MeV), geomagnetic indices (Dst, AE, AL) and interplanetary parameters (solar wind, IMF). The goal is to investigate which outer conditions are most responsible for the high/low output of the storm-injected relativistic electrons. For the geosynchronous orbit, two factors are found as the necessary condition of the highest electron output: high and long-lasting substorm activity on a storm recovery phase and high velocity of solar wind. On the contrary, extremely low substorm activity surely observed during whole the storm recovery phase constitutes a sufficient condition of the non-increased after-storm electron intensity. For the first time found cases of the increased after-storm electron intensity observed at the inner L-shells with no simultaneously seen increase in the geosynchronous distances are presented.     

Prediction tests by using “ISF” method for the geomagnetic disturbances

A so-called “ISF” prediction method for geomagnetic disturbances caused by solar wind storms blowing to the Earth is suggested. The method is based on a combined approach of solar activity, interplanetary scintillation (I) and geomagnetic disturbance observations during the period 1966–1982 together with the dynamics of solar wind storm propagation (S) and fuzzy mathematics (F). It has been used for prediction tests for 37 geomagnetic disturbance events during the descending solar activity phase 1984–1985, and was presented in 33rd COSPAR conference. Here, it has been improved by consideration of the three dimensional propagation characteristics of each event, the search for the best radio source and the influence of the southward components of interplanetary magnetic fields on the geomagnetic disturbances. It is used for prediction tests for 24 larger geomagnetic disturbance events that produced space anomalies during the period 1980–1999. The main results are: (1) for the onset time of the geomagnetic disturbance, the relative error between the observation, T_obs, and the prediction, T_pred, ΔT_pred/T_obs  10% for 45.8% of all events, 30% for 78.3% and >30% for only 21.7%; (2) for the magnetic disturbance magnitude, the relative error between the observation, ∑K_p,obs, and the prediction, ∑K_p,pred, Δ∑K_p,pred/∑K_p,obs  10% for 41.6% of all events, 30% for 79% and 45% for 100%. This shows that the prediction method described here has encouraging prospects for improving predictions of large geomagnetic disturbances in space weather events.     

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     

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.      

第23太阳活动周行星际磁场扇形结构对中低纬地磁场的影响

用特征向量分析法对第23太阳活动周天津静海磁场强度水平分量H的时均值进行研究,分析行星际磁场扇形结构的地磁效应（简称扇形效应）对中低纬地磁场H分量日变化的贡献.研究结果表明,中低纬扇形效应为3～11nT,在太阳活动高年扇形效应达到最大值（约11nT）,低年达到最小值（约3nT）.太阳活动高年扇形效应引起的地磁H分量值变化与太阳活动低年的情况相反,但是扇形效应在夏季对地磁H分量的影响较小.太阳活动高年扇形效应日均值的增减与上升年的相反,与下降年相同,夏季扇形效应平均增量最小且无规律.春、夏和秋三个季节的扇形效应最大值都出现在太阳活动高年,冬季的扇形效应在太阳活动峰年两年后才出现最大值（约11nT）.在太阳活动低年（或高年）,当扇形磁场背离（或指向）太阳时,夏季扇形效应白天引起地磁H分量增大（或减小）,夜间导致地磁H分量减小（或增大）,其他季节全天都会导致地磁H分量减小（或增大）.用特征向量推断行星际磁场扇形极性的符合率在春夏秋三个季节高达60%,在冬季为55%.      

The bimodal magnetosphere and ring current, radiation belt, and tail transducers

It has generally been assumed that a geomagnetic storm is entirely driven by external forces—e.g., solar wind E_y = V_x × B_z, V_x, V²_x (where the components of the electric field, E, the magnetic field, B, and velocity, V, are given in GSE coordinates)—which would imply that particle injections in the ring current (RC) or outer radiation belts should be highly correlated. However the data from ISTP are showing that the magnetosphere can have at least two very different responses to the same solar wind (SW) conditions: a classic, enhanced RC with Dst response, or a 1000-fold increase in the outer radiation belt MeV electrons (ORBE). August 29, October 14 and 23, 1996 are examples of Dst storms, whereas April 15, 1996 and January 10, 1997 are examples of MeV storms. It is this second response that is so deadly to some geosynchronous spacecraft, whereas geomagnetic storms are categorized by the first response. Neither of these appear to be correlated to the SW conditions driving substorms. Why should the SW energy appear in the radiation belts or the ring current independently? We hypothesize that the RC couples to the electric power available (E_y), the ORBE couple to the mechanical power available (V_x), and the Tail couples to the magnetic energy (B_z) available in the SW. The transducer for RC may be subauroral parallel potentials, the transducer for ORBE may be the cusp, while the Tail substorm transducer is yet a third independent mechanism for extracting SW energy. Evidence for this theory comes from the novel POLAR satellite that traverses the cusp, the plasmasheet and the radiation belts.     

利用行星际监测数据进行地磁暴预报

利用全连接神经网络方法应用于地磁Dst指数的预报中.对ACE卫星探测的太阳风和行星际磁场及其变化对未来几小时的Dst指数的影响进行了统计分析,发现在这些行星际实测参数中,对Dst指数作用较为明显的是太阳风速度、太阳风质子密度和行星际磁场南向分量,同时,当前Dst指数实测值对今后几小时的Dst指数已有很强的制约作用.在统计分析的基础上,建立了全连接神经网络预报模型.由于采用了全连接神经网络结构,模式能够反映出太阳风、行星际磁场等参数与地磁Dst指数参数的复杂联系,可以自动建立输入参量的最佳组合方式,提高了预报精度.通过利用大量实测数据对神经网络模式进行训练,最终建立了利用优选的ACE卫星行星际监测数据提前2 h对Dst指数进行预报.通过检测,预报的误差为14.3%.