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.     

Interplanetary shocks and geomagnetic activity during solar maximum (2000) and solar minimum (1995–1996)

Plasma and magnetic field parameter variations through fast forward interplanetary shocks were correlated with the peak geomagnetic activity index Dst in a period from 0 to 3 days after the shock, during solar maximum (2000) and solar minimum (1995–1996). Solar wind speed (V) and total magnetic field (B_t) were the parameters with higher correlations with peak Dst index. The correlation coefficients were higher during solar minimum (r² = 56% for V and 39% for B_t) than during solar maximum (r² = 15% for V and 12% for B_t). A statistical distribution of geomagnetic activity levels following interplanetary shocks was obtained. It was observed that during solar maximum, 36% and 28% of interplanetary shocks were followed by intense (Dst  −100 nT) and moderate (−50  Dst < −100 nT) geomagnetic activity, whereas during solar minimum 13% and 33% of the shocks were followed by intense and moderate geomagnetic activity. It can be concluded that the upstream/downstream variations of V and B_t through the shocks were the parameters better correlated with geomagnetic activity level, and during solar maximum a higher relative number of interplanetary shocks can be followed by intense geomagnetic activity than during solar minimum. One can extrapolate, for forecasting goals, that during a whole solar cycle a shock has a probability of around 50% to be followed by intense/moderate geomagnetic activity.     

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.      

Substorm activity during the main phase of magnetic storms induced by the CIR and ICME events

In this work, the relation of high-latitude indices of geomagnetic activity (AE, Kp) with the rate of storm development and a solar wind electric field during the main phase of magnetic storm induced by the CIR and ICME events is investigated. 72 magnetic storms induced by CIR and ICME events have been selected. It is shown that for the CIR and ICME events the increase of average value of the Kp index (Kp_aver) is observed with the growth of rate of storm development. The value of Kp_aver index correlates with the magnitude of minimum value of Dst index (|Dst_min|) only for the ICME events. The analysis of average values of AE and Kp indices during the main phase of magnetic storm depending on the SW electric field has shown that for the CIR events, unlike the ICME events, the value of AE_aver increases with the growth of average value of the electric field (Esw_aver). The value of Kp_aver correlates with the Esw_aver only for the ICME events. The relation between geomagnetic indices and the maximum value of SW electric field (Esw_max) is weak. However, for the ICME events Kp_aver correlates with Esw_max.     

Geomagnetic activity associated with magnetic clouds,magnetic cloud-like structures and interplanetary shocks for the period 1995–2003

Using nine years (1995–2003) of solar wind plasma and magnetic field data, solar sunspot number, and geomagnetic activity data, we investigated the geomagnetic activity associated with magnetic clouds (MCs), magnetic cloud-like structures (MCLs), and interplanetary shock waves. Eighty-two MCs and one hundred and twenty-two MCLs were identified by using solar wind and magnetic field data from the WIND mission, and two hundred and sixty-one interplanetary shocks were identified over the period of 1995–2003 in the vicinity of Earth. It is found that MCs are typically more geoeffective than MCLs or interplanetary shocks. The occurrence frequency of MCs is not well correlated with sunspot number. By contrast, both occurrence frequency of MCLs and sudden storm commencements (SSCs) are well correlated with sunspot number.     

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%.      

1998年4月下旬至5月上旬地磁暴的日地事件认证

综合运用SOHO／LASCO、SOHO／EIT关于CME的观测结果和WIND飞船关于太阳风的观测记录，识别了1998年4月下旬至5月上旬发生的磁暴的CME源，分析了与5月初强磁暴群相联系的日地事件。结果表明，所用日地扰动事件关系认证的方法是可行的，本文就上述日地事件所涉及的磁暴群与活动区的关系、CME地磁效应的日面东西不对称性以及磁云与高速流的作用等问题进行了讨论。     

Contribution of geometry of interaction between interplanetary and terrestrial magnetic fields into global magnetospheric state and geomagnetic activity

The paper presents results of our study of dependence of geomagnetic activity from geoeffective parameters taking into account mutual orientation of the interplanetary magnetic field, electric field of the solar wind and geomagnetic moment. We attract a reconnection model elaborated by us made allowance for changes of geometry of the solar wind–magnetosphere interaction during annual and diurnal motions of the Earth. We take as our data base the interplanetary magnetic field and solar wind velocity measured at 1 a.u. at ecliptic plane for the period of 1963–2005 and K_p, D_st, a_m indices. Taken as a whole a geoeffective parameter suggested by us explains 95% of observed variations of the indices. Changes of the geometric factor determined by mutual orientation of the solar wind electric field and geomagnetic moment explain larger than 75% of observed statistical variations of D_st and a_m indices. Based on our results we suggest a new explanation of semi-annual and UT variation of geomagnetic activity.     

Relationship between substorm activity and the interplanetary medium parameters during the main phase of strong magnetic storms

In the present paper dependences of substorm activity on the solar wind velocity and southward component (Bz) of interplanetary magnetic field (IMF) during the main phase of magnetic storms, induced by the CIR and ICME events, is studied. Strong magnetic storms with close values of Dst_min?≈??100?±?10?nT are considered. For the period of 1979–2017 there are selected 26 magnetic storms induced by the CIR and ICME (MC?+?Ejecta) events. It is shown that for the CIR and ICME events the average value of the AE index (AE_aver) at the main phase of magnetic storm correlates with the solar wind electric field. The highest correlation coefficient (r?=?0.73) is observed for the magnetic storms induced by the CIR events. It is found that the AE_aver for magnetic storms induced by ICME events, unlike CIR events, increases with the growth of average value of the southward IMF Bz module. The analysis of dependence between the AE_aver and average value of the solar wind velocity (Vsw_aver) during the main phase of magnetic storm shows that in the CIR events, unlike ICME, the AE_aver correlates on the Vsw_aver.     

Long-term changes in indices of geomagnetic activity at the auroral station Sodankylä

Here we compare the traditional analog measure of geomagnetic activity, Ak, with the more recent digital indices of IHV and Ah based on hourly mean data, and their derivatives at the auroral station Sodankylä. By this selection of indices we study the effects of (i) analog vs. digital technique, and (ii) full local-time vs. local night-time coverage on quantifying local geomagnetic activity. We find that all other indices are stronger than Ak during the low-activity cycles 15–16 suggesting an excess of very low scalings in Ak at this time. The full-day indices consistently depict stronger correlation with the interplanetary magnetic field strength, while the night-time indices have higher correlation with solar wind speed. The Ak index correlates better with the digital indices of full-day coverage than with any night-time index. However, Ak depicts somewhat higher activity levels than the digital full-day indices in the declining phase of the solar cycle, indicating that, due to their different sampling rates, the latter indices are less sensitive to high-frequency variations driven by the Alfvén waves in high-speed streams. On the other hand, the night-time indices have an even stronger response to solar wind speed than Ak. The results strongly indicate that at auroral latitudes, geomagnetic indices with different local time coverage reflect different current systems, which, by an appropriate choice of indices, allows studying the century-scale dynamics of these currents separately.     

Ionospheric storm due to solar Coronal mass ejection in September 2017 over the Brazilian and African longitudes

Coronal mass ejection (CME) occurs when there is an abrupt release of a large amount of solar plasma, and this cloud of plasma released by the Sun has an intrinsic magnetic field. In addition, CMEs often follow solar flares (SF). The CME cloud travels outward from the Sun to the interplanetary medium and eventually hits the Earth’s system. One of the most significant aspects of space weather is the ionospheric response due to SF or CME. The direction of the interplanetary magnetic field, solar wind speed, and the number of particles are relevant parameters of the CME when it hits the Earth’s system. A geomagnetic storm is most geo-efficient when the plasma cloud has an interplanetary magnetic field southward and it is accompanied by an increase in the solar wind speed and particle number density. We investigated the ionospheric response (F-region) in the Brazilian and African sectors during a geomagnetic storm event on September 07–10, 2017, using magnetometer and GPS-TEC networks data. Positive ionospheric disturbances are observed in the VTEC during the disturbed period (September 07–08, 2017) over the Brazilian and African sectors. Also, two latitudinal chains of GPS-TEC stations from the equatorial region to low latitudes in the East and West Brazilian sectors and another chain in the East African sector are used to investigate the storm time behavior of the equatorial ionization anomaly (EIA). We noted that the EIA was disturbed in the American and African sectors during the main phase of the geomagnetic storm. Also, the Brazilian sector was more disturbed than the African sector.     

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).     

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.     

ULF wave index as magnetospheric and space-weather parameters

Waves in the Ultra Low Frequency (ULF) band owe their existence to solar wind turbulence and transport momentum and energy from the solar wind to the magnetosphere and farther down. Therefore an index based on ULF wave power could better characterize solar wind–magnetosphere interaction than K_P, Dst, AE, etc. indices which described mainly quasi-study state condition of the system. We have shown that the ULF wave index accurately characterize relativistic electron dynamics in the magnetosphere as these waves are closely associated with circulation, diffusion and energization of relativistic electrons in the magnetosphere. High speed solar wind streams also act as a significant driver of activity in the Earth’s magnetosphere co-rotating interaction region and are responsible for geomagnetic activities. In the present paper, we have analyzed various cases related with very weak (quiet) days, weak days, storm days and eclipse events and discussed the utility of the ULF wave index to explain the magnetospheric dynamics and associated properties. We have tried to explain that the ULF wave index can equally be useful as a space weather parameter like the other indices.     

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.     

Forecasting of DST variations from polar cap indices using neural networks

The 15-min averaged polar cap (PC) index was used as an input parameter for the Dst variation forecasting. The PC index is known to describe well the principal features of the solar wind as well as the total energy input to the magnetosphere. This allowed us to design a neural network able to forecast the Dst variations from 1 to 4 h ahead. 1998 PC and Dst data sets were used for training and testing and 1997 data sets was used for validation proposes. From the 15 moderate and strong geomagnetic storms observed during 1997, nine were successfully forecasted. In three cases the observed minimum Dst value was less than the predicted one, and only in three cases the neural network was not able to reproduce the features of the geomagnetic storm.     

Low-latitude geomagnetic response to the interplanetary conditions during very intense magnetic storms

The variations in the horizontal and declination components of the geomagnetic field in response to the interplanetary shocks driven by fast halo coronal mass ejections, fast solar wind streams from the coronal hole regions and the dynamic pressure pulses associated with these events are studied. Close association between the field-aligned current density (j_∥) and the fluctuations in the declination component (ΔD_ABG) at Alibag is found for intense storm conditions. Increase in the dawn-dusk interplanetary electric field (E_y) and ΔD_ABG are generally in phase. However, when the magnetospheric electric field is directed from dusk to dawn direction, a prominent scatter occurs between the two. It is suggested that low-latitude ground magnetic data may serve as a proxy for the interplanetary conditions in the solar wind.     

The Earth’s magnetosphere response to interplanetary medium conditions on January 21–22, 2005 and on December 14–15, 2006

The Earth’s magnetosphere response to interplanetary medium conditions on January 21–22, 2005 and on December 14–15, 2006 has been studied. The analysis of solar wind parameters measured by ACE spacecraft, of geomagnetic indices variations, of geomagnetic field measured by GOES 11, 12 satellites, and of energetic particle fluxes measured by POES 15, 16, 17 satellites was performed together with magnetospheric modeling based in terms of A2000 paraboloid model. We found the similar dynamics of three particle populations (trapped, quasi-trapped, and precipitating) during storms of different intensities developed under different external conditions: the maximal values of particle fluxes and the latitudinal positions of the isotropic boundaries were approximately the same. The main sources caused RC build-up have been determined for both magnetic storms. Global magnetospheric convection controlled by IMF and substorm activity driven magnetic storm on December 14–15, 2006. Extreme solar wind pressure pulse was mainly responsible for RC particle injection and unusual January 21, 2005 magnetic storm development under northward IMF during the main phase.     

利用BP神经网络预测AE指数

采用的预报模式是一种全连接的BP网络模型,利用太阳风及行星际磁场的观测数据预报AE指数.神经网络输入选用ACE卫星数据,取5 min平均值,通过比较,选用4个预报参量.构造了预报参量时续为20 min,40 min和60 min依次递增的三个网络,分别进行训练和预测,并对行星际参量对AE指数影响的时续性进行了探讨.预报结果表明,全连接BP神经网络在AE指数的短期预报中是比较有效的,同时还提出了需要进一步改进的环节.      

行星际日冕物质抛射地磁效应研究的支持向量机方法初步研究

行星际日冕物质抛射（Interplanetary Coronal Mass Ejection,ICME）与地球磁层相互作用并带来地磁暴等地磁扰动.从Richardson和Cane提供的近地球ICME列表中筛选出ICME事件集,基于ICME扰动期间的行星际等离子体与磁场数据提取出特征.通过计算各特征的费舍尔分值（Fisher Score）,对这些特征进行选择,发现行星际磁场南北向分量持续时间小于-10nT且激波等扰动所带来的ICME扰动开始时,太阳风速度的增量等特征与ICME事件的地磁效应密切相关.这与现有的传统统计研究结果一致.以这些特征为基础,训练得到的径向基函数支持向量机能够以0.78±0.08的准确率判断ICME事件是否会产生中等及以上强度的地磁暴（Dst ≤-50nT）.