Modeling solar proton access to geostationary spacecraft with geomagnetic cutoffs

Solar energetic particle (SEP) cutoffs at geosynchronous orbit are sensitive to moderate geomagnetic activity and undergo daily variations due to the day–night asymmetry of the magnetosphere. At geosynchronous orbit, cutoff rigidity also has a large directional dependence, with the highest cutoff rigidity corresponding to ions arriving from magnetic east and lowest cutoff rigidity corresponding to ions incident from the west. Consequently, during geomagnetically quiet periods, the SEP flux observed by an eastward facing particle detector is significantly lower than observed by a westward facing particle detector. During geomagnetically disturbed periods the cutoff is suppressed allowing SEPs access well inside of geosynchronous, so that the east–west SEP flux ratio approaches unity. Variations in the east–west SEP flux ratio observed by GOES Energetic Particle Sensors (EPS) have recently been reported by Rodriguez et al. (2010). In NOAA’s operational processing of EPS count rates into differential fluxes, the differential flux is treated as isotropic and flat over the energy width of the channel. To compare modeled SEP flux with GOES EPS observations, the anisotropy of the flux over the EPS energy range and field of view must be taken into account. A technique for making direct comparisons between GOES EPS observations and SEP flux modeled using numerically computed geomagnetic cutoffs is presented. Initial results from a comparison between modeled and observed flux during the 6–11 December 2006 SEP event are also presented. The modeled cutoffs reproduce the observed flux variations well but are in general too high.     

地磁扰动期间低轨目标轨道预报的误差修正

针对地磁扰动期间大气密度变化造成的低轨目标较大的轨道预报误差,提出一种根据POES卫星观测的极光能量注入数据改进短期轨道预报的方法。分析表明CHAMP卫星的沿迹大气密度及轨道衰减与极光能量注入具有较好的相关性。通过线性回归方法,建立轨道半长轴衰减及阻力调制系数的修正公式,并使用修正后的阻力调制系数取代两行元(TLE)中的该系数带入SGP4模型进行位置预报。该方案考虑了外推过程中地磁扰动引起的大气密度响应,能更准确地反映外推过程中大气阻力对轨道的影响。将其应用到2008年CHAMP卫星和国际空间站的轨道预报中,结果表明,半长轴和位置的预报误差可分别降低50%和30%左右。进一步对不同年份、不同轨道高度的目标进行了预报误差修正的分析,验证了该方法的普适性。     

伺服机构恒压变量泵压力脉动分析

对某运载火箭整箭测试中一级伺服机构出现压力脉动的原因进行了分析。根据伺服机构变量泵原理,认为引起压力脉动的主要因素是变量泵调节机构。建立了变量泵的仿真模型,讨论了变量调节机构灵敏度和管路结构等其他因素对变量柱塞泵输出压力脉动的影响,以及压力脉动对控制元件和执行元件的影响。结果表明:变量泵的低频小幅值压力脉动对整个伺服系统的控制元件和执行元件均无影响。伺服机构能正常稳定地工作,保证运载火箭的飞行可靠性。     

Mid-latitude thermospheric zonal winds during the equinoxes

The diurnal variation of the mid-latitude upper thermosphere zonal winds during equinoxes has been studied using data recently generated from CHAMP measurements from 2002 to 2004 using an iterative algorithm. The wind data was separated into two geomagnetic activity levels, representing high geomagnetic activity level (Ap > 8) and low geomagnetic activity level (Ap ? 8). The data were further separated into two solar flux levels; with F10.7 > 140 for high and F10.7 ? 140 for low. Geomagnetic activity is a correlator just as significant as solar activity. The response of mid-latitude thermospheric zonal winds to increases in geomagnetic disturbances and solar flux is evident. With increase in geomagnetic activity, midday to midnight winds are generally less eastward and generally more westward after the about midnight transitions. The results show that east west transitions generally occurred about midnight hours for all the situations analyzed. The west to east transition occurs from 1400–1500 MLT. Enhanced westward averaged zonal wind speeds going above 150 ms⁻¹ are observed in the north hemisphere mid-latitude about sunrise hours (∼0700–1100 MLT). Nighttime winds in the north hemisphere are in good agreement with previous single station ground observations over Millstone Hill. Improved ground observations and multi satellite observations from space will greatly improve temporal coverage of the Earth’s thermosphere.     

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.     

Moderate geomagnetic storms of January 22–25, 2012 and their influences on the wave components in ionosphere and upper stratosphere-mesosphere regions

Moderate geomagnetic storms occurred during January 22–25, 2012 period. The geomagnetic storms are characterized by different indices and parameters. The SYM-H value on January 22 increased abruptly to 67 nT at sudden storm commencement (SSC), followed by a sharp decrease to −87 nT. A second SSC on January 24 followed by a shock on January 25 was also observed. These SSCs before the main storms and the short recovery periods imply the geomagnetic storms are CME  -driven. The sudden jump of solar wind dynamic pressure and IMF _Bz$B_z$ are also consistent with occurrence of CMEs. This is also reflected in the change in total electron content (TEC) during the storm relative to quiet days globally. The response of the ionospheric to geomagnetic storms can also be detected from wave components that account for the majority of TEC variance during the period. The dominant coherent modes of TEC variability are diurnal and semidiurnal signals which account upto 83% and 30% of the total TEC variance over fairly exclusive ionospheric regions respectively. Comparison of TEC anomalies attributed to diurnal (DW1) and semidiurnal (SW2) tides, as well as stationary planetary waves (SPW1) at 12 UTC shows enhancement in the positive anomalies following the storm. Moreover, the impact of the geomagnetic storms are distinctly marked in the daily time series of amplitudes of DW1, SW2 and SPW1. The abrupt changes in amplitudes of DW1 (5 TECU) and SW2 (2 TECU) are observed within 20°S–20°N latitude band and along 20°N respectively while that of SPW1 is about 3 TECU. Coherent oscillation with a period of 2.4 days between interplanetary magnetic field and TEC was detected during the storm. This oscillation is also detected in the amplitudes of DW1 over EIA regions in both hemispheres. Eventhough upward coupling of quasi two day wave (QTDWs) of the same periodicity, known to have caused such oscillation, are detected in both ionosphere and upper stratosphere, this one can likely be attributed to the geomagnetic storm as it happens after the storm commencement. Moreover, further analysis has indicated that QTDWs in the ionosphere are strengthened as a result of coherent oscillation of interplanetary magnetic field with the same frequency as QTDWs. On the otherhand, occurrences of minor SSW and geomagnetic storms in quick succession complicated clear demarcation of attribution of the respective events to variability of QTDWs amplitudes over upper stratosphere.     

Seasonal variations of storm-time TEC at European middle latitudes

Global Navigation Satellite System (GNSS) measurements of the Total Electron Content (TEC) from local (Dourbes, 50.1°N, 04.6°E) and European IGS (International GNSS Service) stations were used to obtain the TEC changes during the geomagnetic storms of the latest solar activity cycle. A common epoch analysis, with respect to geomagnetic storm intensity, season, and latitude, was performed on data representing nearly 300 storm events. In general, the storm-time behaviour of TEC shows clear positive and negative phases, relative to the non-storm (median) behaviour, with amplitudes that tend to increase during more intense storms. The most pronounced positive phase is observed during winter, while the strongest and yet shortest negative phase is detected during equinox. Average storm-time patterns in the TEC behaviour are deduced for potential use in ionosphere prediction services.     

Evaluation of the STORM model storm-time corrections for middle latitude

This paper presents results from the Storm-Time Ionospheric Correction Model (STORM) validation for selected Northern and Southern Hemisphere middle latitude locations. The created database incorporated 65 strong-to-severe geomagnetic storms, which occurred within the period 1995–2007. This validation included data from some ionospheric stations (e.g., Pruhonice, El Arenosillo) that were not considered in the development or previous validations of the model. Hourly values of the F2 layer critical frequency, foF2, measured for 5–7 days during the main and recovery phases of each selected storm were compared with the predicted IRI 2007 foF2 with the STORM model option activated. To perform a detailed comparison between observed values, medians and predicted foF2 values the correlation coefficient, the root-mean-square error (RMSE), and the percentage improvement were calculated. Results of the comparative analysis show that the STORM model captures more effectively the negative phases of the summer ionospheric storms, while electron density enhancement during winter storms and the changeover of the different storm phases is reproduced with less accuracy. The STORM model corrections are less efficient for lower-middle latitudes and severe geomagnetic storms.     

Magnetospheric physics in China: 2008—2010

In the past two years, most of the works on magnetospheric physics were made by using the data of Double Star Program and Cluster missions. However some works were still conducted by computer simulation or using the data from other space missions and ground geomagnetic observations. This paper briefly review these previous works based on papers selected from the 28 publications from April 2008 to April 2010. The subjects covered various sub-branches of magnetospheric physics, including geomagnetic storm, magnetospheric substorm and etc.      

采用强制降噪和多尺度融合的地磁导航方法

针对地磁数据测量易受各种噪声和干扰影响,导致地磁匹配导航精度、概率和可靠性降低的问题,提出了一种采用小波强制降噪和多尺度融合的地磁匹配导航方法。该方法利用地磁数据高频部分易受噪声干扰影响而低频部分稳定性好、各尺度下的匹配结果具有相对独立性的特点,将含噪地磁基准图和实时图进行多尺度分解,在所选的多个尺度下经强制降噪后分别进行匹配,并融合各尺度下的匹配结果表决产生最终的导航结果。地磁匹配导航仿真实验结果表明该方法可有效提高导航的精度、概率和可靠性。