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%.      

基于遥测电流的太阳翼在轨振动参数辨识方法

针对传统太阳翼在轨振动特性测试需采用高精度星载设备或额外增设测量装置的问题,建立了太阳翼发电电流与太阳光线入射角之间、太阳翼在轨振动与太阳翼发电电流波动之间的关系。在此基础上提出了仅依靠遥测电流波动信息辨识太阳翼在轨振动固有频率和阻尼比的方法,即：首先通过傅里叶变换获取电流波动信号的幅频响应;结合模态分析结果辨识振动频率及对应阶次信息;通过滤波算法分解各阶次振动,逐一计算对应阻尼比。为验证本方法有效性及误差水平,构造了由多个单自由度衰减振动及随机信号叠加而成的模拟电流波动信号进行仿真分析,结果表明方法有效,误差可接受。在某卫星太阳翼在轨振动参数辨识上的应用实例也表明,本文所提出的方法满足工程应用需求。     

太阳帆航天器三维人工平动点变化特性研究

本文研究了太阳帆航天器在光压因子、锥角和钟角共同作用下的三维人工平动点的变化特性。在光压因子较小的时候,五个平动点会拓展成五个不相连的“人工”平动点面。随着光压因子增大,平动点面SL 3 ,SL 4 和SL5将逐渐扩大并互相融合,最终延展至SL 1 与之融合。而平动点面SL2则始终保持独立的球面,只随着光压因子的增大而扩大但不与其它平动点面发生融合。平动点位置的改变,意味着对应的周期轨道也随之改变,这为平动点周期轨道的转移等任务提供了有效参考。     

动量轮卸载在改进GEO卫星东西轨道保持中的应用

空间外干扰力矩会使在轨GEO三轴卫星动量轮转速发生周期性变化,因此需要进行动量轮卸载。通过对卸载前后卫星轨道根数的比较,发现动量轮卸载可以延长卫星实际的东西轨道保持周期。以动量轮卸载有利卫星轨道保持为研究目的,通过计算和分析,推导出动量轮卸载时转速变化与卫星半长轴变化关系的数学模型,并以实际测量数据为基础,对模型进行了仿真验证,证明了动量轮卸载对改进GEO卫星东西轨道保持的可行性,提出了一种利用动量轮卸载改进GEO卫星东西轨道保持策略的新方法。     

Sq(H) field variations at Sonmiani geomagnetic observatory,Pakistan for solar cycle 24

In this study, Sq(H) field results for Sonmiani geomagnetic observatory (SON), Pakistan are presented first time for solar cycle i.e., Solar Cycle 24. Sonmiani observatory was established in 2008 and was included in the list of INTERMAGNET Magnetic Observatory (IMO) in 2012. The analysis of Sq(H) field is performed to examine diurnal, annual and seasonal behaviour of Sq(H) field at Sonmiani along with Honolulu which is used as reference observatory. Both the observatories lie at the Equatorial Ionisation Anomaly (EIA) crest. In general strong dependency of Sq(H) field on solar cycle has been observed. First peak of SC24 was visible in Sq(H) field at both observatories. However, at HON maximum Sq(H) was observed in 2015 instead of 2014, a year later than the year of solar maximum. Prominent longitudinal difference has been noted between both observatories. At HON, maximum Sq(H) was observed during equinox while at SON it was noted during equinox and summer as a consequence of shift in latitude of Sq focus. Phase shift of Sq(H) at SON followed a general trend, that is maximum Sq(H) shifted to later hours in solar maximum as compared to solar minimum. Whereas, an opposite trend was noted at HON which might be due to coastal effect. In case of seasonal phase shift, at both observatories maximum Sq(H) occurred at later hours in summer than in winter which is opposite to the results obtained by many workers. These points need further investigation and geomagnetic as well as wind, and electric field data of other observatories situated at the EIA crest region is required to interpret the Sq(H) phase shift extensively.     

A study on TEC reduction during the tail phase of the 21st June 2020 annular solar eclipse

Ionospheric response during the annular solar eclipse of June 21, 2020, has been examined in terms of the Total Electron Content (TEC) obtained from six Global Positioning System (GPS) receivers positioned in the Chinese-Taiwanese region. We have shown TEC variation from satellites designated by PRNs (Pseudo-Random Noise code) 2, 6, and 19. PRN wise TEC trend was observed to depend upon satellite-pass trajectory to the receiver's location during the eclipse period. A time lag of ~15–30 min is also observed in maximum TEC decrement after the phase of maximum eclipse. Instead of the percentage of eclipse magnitude, a reduction in TEC is seen more for the station for which the orbital track of respective satellites was in closer view relative to receivers for more hours of eclipse window. Additionally, the eclipse day diurnal variations are compared with the pre-eclipse day TEC trend, and observed results show a clear decrease in TEC values at all chosen stations after the eclipse onset then reached the lowest value a few minutes afterward the maximum eclipse phase.     

Ionospheric response to solar and magnetospheric protons during January 15–22, 2005: EAGLE whole atmosphere model results

We present an analysis of the ionosphere and thermosphere response to Solar Proton Events (SPE) and magnetospheric proton precipitation in January 2005, which was carried out using the model of the entire atmosphere EAGLE. The ionization rates for the considered period were acquired from the AIMOS (Atmospheric Ionization Module Osnabrück) dataset. For numerical experiments, we applied only the proton-induced ionization rates of that period, while all the other model input parameters, including the electron precipitations, corresponded to the quiet conditions. In January 2005, two major solar proton events with different energy spectra and proton fluxes occurred on January 17 and January 20. Since two geomagnetic storms and several sub-storms took place during the considered period, not only solar protons but also less energetic magnetospheric protons contributed to the calculated ionization rates. Despite the relative transparency of the thermosphere for high-energy protons, an ionospheric response to the SPE and proton precipitation from the magnetotail was obtained in numerical experiments. In the ionospheric E layer, the maximum increase in the electron concentration is localized at high latitudes, and at heights of the ionospheric F2 layer, the positive perturbations were formed in the near-equatorial region. An analysis of the model-derived results showed that changes in the ionospheric F2 layer were caused by a change in the neutral composition of the thermosphere. We found that in the recovery phase after both solar proton events and the enhancement of magnetospheric proton precipitations associated with geomagnetic disturbances, the TEC and electron density in the F region and in topside ionosphere/plasmasphere increase at low- and mid-latitudes due to an enhancement of atomic oxygen concentration. Our results demonstrate an important role of magnetospheric protons in the formation of negative F-region ionospheric storms. According to our results, the topside ionosphere/plasmasphere and bottom-side ionosphere can react to solar and magnetospheric protons both with the same sign of disturbances or in different way. The same statement is true for TEC and foF2 disturbances. Different disturbances of foF2 and TEC at high and low latitudes can be explained by topside electron temperature disturbances.     

Bifurcation analysis of ion-acoustic waves for Schrödinger equation in nonextensive Solar wind plasma

Bifurcation analysis of ion-acoustic wave (IAWs) solutions of the nonlinear Schrödinger equation (NLSE) is explored for the first time in an electron-ion (e-i) magnetized solar wind plasma. The existence of ion-acoustic (IA) periodic, superperiodic, kink, antikink, compressive and rarefactive solitary wave solutions are revealed. Special values of Solar wind plasma parameters at a normalized distance from the Sun are considered for numerical simulation. The IA wave solutions are derived analytically. These solutions are analyzed numerically considering the influence of parameters, namely, wave number (k), velocity (V) of traveling wave and nonextensive parameter (q). Computational simulation reveals that only IA periodic wave grows in amplitude as waves moves from the Sun.     

The longitudinal and hemispherical variation of the IRI’s foF2 estimates at ±40° dip angle around 95°E and 130°E sector under fluctuating solar flux conditions

The deviation of the IRI estimates of the monthly mean foF2 in the low mid latitude of 95°E–130°E longitude sector is investigated using simultaneous ground measurements at four stations during 2010–2014. The stations form two conjugate pairs of the same geo-magnetic latitude at two fixed longitudes enabling direct longitudinal and hemispheric comparison. The temporal, spatial, seasonal and solar activity variations of the deviations are discussed with reference to the longitudinal density variation in the transition region between low and midlatitudes. Cases of underestimation/overestimation as well as good estimate are noted. Underestimation (overestimation) in the daytime and overestimation (underestimation) in the nighttime of 95°E (130°E) are common. The longitudinal difference in the measurements suggests negative (positive) foF2 gradient from west to east in daytime (nighttime). In contrast, the IRI predicts flatter or increasing longitudinal profiles from 95°E to 130°E. The local time and longitudinal variation of the IRI deviations can be attributed to the combined role of the longitudinal EIA structure as well as midlatitude zonal wind-magnetic declination effect. The station/season independent deviations relate the role of solar activity representation in the IRI. These deviations may be attributed to the weak IRI response to rapid solar flux fluctuations.