流星突发通信信道日变化预测模型

流星突发通信不同于传统的通信, 其是低速率通信, 具有突发、不连续、不定时的特性. 因此, 流星余迹通信的复杂性要求有必要对其通信信道进行建模. 在流星通信链路中, 流星的辐射分布、可用流星率和占空比是影响流星通信信道性能的重要参数. 流星辐射分布在不同季节不同时间都各不相同, 因此准确预测流星通信链路在不同时间的流星辐射分布, 从而改变大圆路径上天线的指向, 对提高通信速率显得非常重要. 同时, 准确预测流星突发通信链路上的可用流星率和占空比, 有助于准确预测并建立流星突发信道模型. 本文分析研究了偶发流星辐射分布建模的发展, 建立了偶发流星日心空间和地心空间的几何关系, 得到了流星突发通信信道参数预测模型. 并将预测模型应用于流星通信链路, 预测结果与通信链路观测结果比较一致, 为流星通信系统的建立提供了技术支持.      

Towards a scientific understanding of the risk from extreme space weather

Like all natural hazards, space weather exhibits occasional extreme events over timescales of decades to centuries. Historical events provoked much interest, and sometimes alarm, because bright aurora becomes visible at mid-latitudes. However, they had little economic impact because the major technologies of those eras were not sensitive to space weather. This is no longer true. The widespread adoption of advanced technological infrastructures over the past 40 years has created significant sensitivity. So these events now have the potential to disrupt those infrastructures – and thus have profound economic and societal impact. However, like all extreme hazards, such events are rare, so we have limited data on which to build our understanding of the events. This limitation is uniquely serious for space weather since it is a global phenomenon. Many other natural hazards (e.g. flash floods) are highly localised, so statistically significant datasets can be assembled by combining data from independent instances of the hazard recorded over a few decades. Such datasets are the foundation on which reliable risk assessment methodologies are built. But we have a single instance of space weather so we would have to make observations for many centuries in order to build a statistically significant dataset. We show that it is not practicable to assess the risk from extreme events using simple statistical methods. Instead we must exploit our knowledge of solar-terrestrial physics to find other ways to assess these risks. We discuss three alternative approaches: (a) use of proxy data, (b) studies of other solar systems, and (c) use of physics-based modelling. We note that the proxy data approach is already well-established as a technique for assessing the long-term risk from radiation storms, but does not yet provide any means to assess the risk from severe geomagnetic storms. This latter risk is more suited to the other approaches, but significant research is needed to make progress. We need to develop and expand techniques to monitoring key space weather features in other solar systems (stellar flares, radio emissions from planetary aurorae). And to make progress in modelling severe space weather, we need to focus on the physics that controls severe geomagnetic storms, e.g. how can dayside and tail reconnection be modulated to expand the region of open flux to envelop mid-latitudes?     

“嫦娥三号”探测器软着陆自主导航与制导技术

"嫦娥三号"探测器首次实现了我国航天器在地外天体软着陆,制导导航与控制技术是软着陆任务成功的关键。针对高安全和高可靠软着陆任务的要求,设计了包含接力避障的软着陆飞行程序,提出了单波束分时修正与多波束融合修正的自主导航方法和自适应动力显式制导、无迭代多项式粗避障制导以及内外环结合的精避障制导等方法。实际在轨飞行结果表明,导航算法提供了高精度的状态估计,制导算法实现了高精度状态控制和有效避障机动,确保了软着陆落月的安全性和可靠性。     

Statistical study of the time delay of ionospheric TEC storms to geomagnetic storms in Taoyuan,Taiwan

We have studied the time delay of ionospheric storms to geomagnetic storms at a low latitude station Taoyuan (25.02°N, 121.21°E), Taiwan using the Dst and TEC data during 126 geomagnetic storms from the year 2002 to 2014. In addition to the known local time dependence of the time delay, the statistics show that the time delay has significant seasonal characteristics, which can be explained within the framework of the seasonal characteristics of the ionospheric TEC. The data also show that there is no correlation between the time delay and the intensity of magnetic storms. As for the solar activity dependence of the time delay, the results show that there is no relationship between the time delay of positive storms and the solar activity, whereas the time delay of negative storms has weakly negative dependence on the solar activity, with correlation coefficient −0.41. Especially, there are two kinds of extreme events: pre-storm response events and long-time delay events. All of the pre-storm response events occurred during 15–20 LT, manifesting the Equator Ionospheric Anomaly (EIA) feature at Taoyuan. Moreover, the common features of the pre-storm response events suggest the storm sudden commencement (SSC) and weak geomagnetic disturbance before the main phase onset (MPO) of magnetic storms are two main possible causes of the pre-storm response events. By analyzing the geomagnetic indices during the events with long-time delay, we infer that this kind of events may not be caused by magnetic storms, and they might belong to ionospheric Q-disturbances.     

Dust storms detection over the Indo-Gangetic basin using multi sensor data

Dust storms are common during the summer season over the Indo-Gangetic basin and are considered to be a major health hazard to millions of people living in the basin. In countries like India, there is no early warning made for dust outbreaks and as a result the day-to-day life is affected by these dust events. In this paper, efforts have been made to utilize multi sensor data to study the characteristics of dust storms. Moderate Resolution Imaging Spectroradiometer and Multiangle Imaging SpectroRadiometer images clearly show dust storm events over the Indo-Gangetic basin. The Total Ozone Mapping Spectroradiometer (TOMS) Aerosol Index and the Advanced Microwave Sounding Unit (AMSU) data over the western end of the Indo-Gangetic basin have been analyzed. These data show characteristic behavior of brightness temperature and Aerosol Index due to dust, which change significantly as dust migrates towards east over Kanpur. The TOMS Aerosol Index and the AMSU brightness temperature (T_b) show a characteristic anti-correlation, which confirms the presence of a dust storm over Indo-Gangetic basin.     

Time delay of ionospheric TEC storms to geomagnetic storms and pre-storm disturbance events in East Asia

Using the TEC data at Beijing (39.61°N, 115.89°E)/Yakutsk (62.03°N, 129.68°E) stations of East Asia regions and relevant geomagnetic data from 2010 to 2017, we have studied the time delay of ionospheric storms to geomagnetic storms and compare it with our previous results of Taoyuan (25.02°N, 121.21°E) station (Zhang et al., 2020). The data shows a well-known local time dependence of the time delay, and seasonal dependences are different at these stations. In addition, there is no correlation between the time delay and the magnetic storm intensity /solar activity, except the time delay of negative storms has weakly negative dependence on the solar activity. Comparing with the results of Taoyuan station which is located at EIA region in East Asia, we find that the time delay increases nonlinearly as the latitude decreases due to different ionospheric backgrounds at these places. Moreover, the pre-storm disturbance events are found to have similar statistical characteristics as the pre-storm enhancement in Europe middle latitudes (Bure?ová and La?tovi?ka, 2007). By subtracting the common features of the pre-storm disturbance events, we preliminarily infer that auroral activity might be main driver of the pre-storm disturbance events.     

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.     

中低纬电离层不同季节地磁暴响应的事例分析

利用中国中低纬台站漠河（53.5°N,122.3°E）、北京（40.3°N,116.2°E）、武汉（30.5°N,114.2°E）和三亚（18.3°N,109.6°E）的电离层观测数据,对比分析了4个台站电离层参数在2015年不同季节4个地磁扰动事件期间的变化特征.结果表明,4个磁暴事件期间电离层的响应特征并不完全一致,有着明显的季节特征,春季、夏季和秋季电离层以负相扰动为主,冬季以正相扰动为主.分析发现,中性成分O/N₂的降低与电离层负相扰动有关,但三亚地区的负相扰动还与扰动发电机电场相关.正相扰动的机制在不同事件中并不相同,穿透电场可能是引起春季磁暴事件期间电离层短时正暴效应的原因,而冬季长时间的正暴效应则是扰动电场和中性风共同作用的结果.      

Storm time spatial variations in TEC during moderate geomagnetic storms in extremely low solar activity conditions (2007–2009) over Indian region

The total electron content (TEC) measurements from a network of GPS receivers were analyzed to investigate the storm time spatial response of ionosphere over the Indian longitude sector. The GPS receivers from the GPS Aided Geo Augmented Navigation (GAGAN) network which are uniquely located around the ∼77°E longitude are used in the present study so as to get the complete latitudinal coverage from the magnetic equator to low mid-latitude region. We have selected the most intense storms but of moderate intensity (−100 nT < Dst < −50 nT) which occurred during the unusually extremely low solar activity conditions in 2007–2009. Though the storms are of moderate intensity, their effects on equatorial to low mid-latitude ionosphere are found to be very severe as TEC deviations are more than 100% during all the storms studied. Interesting results in terms of spatial distribution of positive/negative effects during the main/early recovery phase of storms are noticed. The maximum effect was observed at crest region during two storms whereas another two storms had maximum effect near the low mid-latitude region. The associated mechanisms like equatorial electrodynamics and neutral dynamics are segregated and explained using the TIMED/GUVI and EEJ data during these storms. The TEC maps are generated to investigate the storm time development/inhibition of equatorial ionization anomaly (EIA).     

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.     

Mean winds of the mesosphere and lower thermosphere (60–110 km): A global distribution from radar systems (MF,Meteor, VHF)

During the last decade a large number of radars (～12) have been developed, which have produced substantial quantities of tidally-corrected mean winds data. The distribution of the radars is not global, but many areas are well covered: the Americas with Poker Flat (65°N), Saskatoon (52°N), Durham (43°N), Atlanta (34°N), Puerto Rico (18°N); Europe with Kiruna (68°), Garchy (47°N) and Monpazier (44°N); and Oceania with Christchurch (44°S), Adelaide (35°S), Townsville (20°S), and Kyoto (35°N). Zonal and meridional wind height-time cross-sections from $\text{60}\text{80}$ km (MF/Meteor Radar) to ～110 km have been prepared for the last 5–6 years. They are compared with cross-sections from CIRA-72 for zonal winds, and Groves (1969) for meridional winds.It is shown that while CIRA-72 is still a useful model for many purposes, significant differences exist between it and the new radar data. The latter demonstrate important seasonal, latitudinal, longitudinal and hemispheric variations. The new meridional cross-sections are of great value. The common features with Groves (1969) are the equatorward cells in summer near 85 km; however their strength (～10 ms^?1) and size are less. Systematic and somewhat different variations emerge at higher (?52°N) and middle (35–44°) latitudes.     

第21～24太阳周4类空间天气事件爆发特征统计分析

对第21～24太阳周不同等级的太阳X射线耀斑事件、太阳质子事件、地磁暴事件及高能电子增强事件的爆发频次特征进行统计,结果表明:太阳周耀斑爆发的总数量与该太阳周的黑子数峰值呈正比,耀斑总数、X级耀斑事件数与峰值的相关系数分别为0.974,0.997;太阳质子事件主要发生在峰年前后1～2年,约占总发生次数的80%,峰值通量大于10pfu （1 pfu=1 cm-2·sr-1·s-1）的质子事件中,84%伴有耀斑爆发,并且主要伴随M或X级耀斑,少量伴随C级耀斑,峰值通量大于1000pfu的质子事件中,98%伴随M或X级耀斑,并且以X级耀斑为主;第21,22,23和24太阳周发生地磁暴最频繁的时间分别在1982,1991,2003年和2015年,分别滞后黑子数峰值时间3年、2年、2年和1年;72%的高能电子增强事件发生在太阳周下降期,24%的高能电子增强事件发生在太阳周上升期.      

月球软着陆过程高精度自主导航避障方法

针对未知地形和障碍会危及着陆安全的问题,给出了一种月球软着陆过程高精度自主导航避障方法,主要包括基于IMU配以测距测速修正的自主绝对导航、障碍识别与目标着陆点选取、针对目标着陆点的相对导航与相对避障控制等算法。该方法在保证着陆精度的同时也大大降低了着陆过程遇到障碍的风险,提高了系统的安全性,已成功应用于实际工程任务。     

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     

Solar wind low-energy energetic ion enhancements: A tool to forecast large geomagnetic storms

Predicting the occurrence of large geomagnetic storms more than an hour in advance is an important, yet difficult task. Energetic ion data show enhancements in flux that herald the approach of interplanetary shocks, usually for many hours before the shock arrival. We present a technique for predicting large geomagnetic storms (Kp  7) following the arrival of interplanetary shocks at 1 AU, using low-energy energetic ions (47–65 keV) and solar wind data measured at the L1 libration point. It is based on a study of the relationship between energetic ion enhancements (EIEs) and large geomagnetic storms by Smith et al. [Smith, Z., Murtagh, W., Smithtro, C. Relationship between solar wind low-energy energetic ion enhancements and large geomagnetic storms. J. Geophys. Res. 109, A01110, 2004. doi:10.1029/ 2003JA010044] using data in the rise and maximum of solar cycle 23 (February 1998–December 2000). An excellent correlation was found between storms with Kp  7 and the peak flux of large energetic ion enhancements that almost always (93% of time in our time period) accompany the arrival of interplanetary shocks at L1. However, as there are many more large EIEs than large geomagnetic storms, other characteristics were investigated to help determine which EIEs are likely to be followed by large storms. An additional parameter, the magnitude of the post-shock total magnetic field at the L1 Lagrangian point, is introduced here. This improves the identification of the EIEs that are likely to be followed by large storms. A forecasting technique is developed and tested on the time period of the original study (the training data set). The lead times, defined as the times from the arrival of the shock to the start of the 3-h interval of maximum Kp, are also presented. They range from minutes to more than a day; the average for large storms is 7 h. These times do not include the extra warning time given when the EI flux cross the high thresholds ahead of the shock. Because the data-stream used in the original study is no longer available, we extended the original study (1998–2000) to 2001, in order to: (a) investigate EIEs in 2001; (b) present a validation of the technique on an independent data set; (c) compare the results based on the original (P1) energy channel to those of the replacement (P1′) and (d), determine new EIE thresholds for forecasting geomagnetic storms using P1′ data. The verification of this P1′ training data set is also presented, together with lead times.     

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.     

中等磁暴太阳周分布的统计研究

依据实际观测的中等磁暴数据,统计分析了中等磁暴的太阳周分布.分析结果表明,在一个太阳活动周内,每年中等磁暴随时间的变化出现多个峰值,其中,最大峰值均出现在太阳活动周的下降段,即中等磁暴的峰值比太阳黑子数平滑年均值的峰值要滞后,滞后的时间为2～3年.超过70%的中等磁暴出现在太阳活动周的下降段,这表明绝大多数中等磁暴出现在太阳活动周的下降段.通过对中等磁暴平滑月均值与太阳黑子数平滑月均值相位差的计算分析发现,中等磁暴峰值出现的时间比太阳黑子数峰值出现的时间要滞后,不同太阳活动周中等磁暴峰值出现的时间与太阳黑子数峰值时间滞后的程度不同.      

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.     

Present day challenges in understanding the geomagnetic hazard to national power grids

Power grids and pipeline networks at all latitudes are known to be at risk from the natural hazard of geomagnetically induced currents. At a recent workshop in South Africa, UK and South African scientists and engineers discussed the current understanding of this hazard, as it affects major power systems in Europe and Africa. They also summarised, to better inform the public and industry, what can be said with some certainty about the hazard and what research is yet required to develop useful tools for geomagnetic hazard mitigation.     

宇宙线变化特征在强地磁暴预报中的应用

利用宇宙线中子探测数据定性分析了地面宇宙线多台站之间的相互联系以及大磁暴与宇宙线之间的响应关系. 以Irkutsk和Oulu宇宙线台站为例, 运用小波去噪技术提高数据的稳定性. 结果表明, 相同世界时条件下, 两站宇宙线通量相关性在事件发生时较高; 而相同地方时条件下, 相关性则在平静期较高. 进一步采用相同地方时条件对不同宇宙线台站的通量在平静期和扰动期的相对变化进行分析, 选取2004年7月强地磁暴典型事例进行直观分析, 发现大地磁暴前Irkutsk和Oulu台站的宇宙线相对通量发生明显差异, 可以尝试作为强地磁暴宇宙线先兆特征. 通过对2001年3月至2005年5月的强磁暴和中强磁暴进行统计, 得到与强地磁暴相关的适当宇宙线相对差异阈值. 将得到的阈值对2005年9月至2011年12月所有强磁暴及中强磁暴进行验证, 总成功率达到87.5%, 误报率为35.7%, 结果较好.