太阳活动低年广州地区地磁扰动与电离层闪烁的统计特征分析

基于肇庆地磁台的地磁监测数据和广州气象卫星地面站建立的华南地区GPS电离层闪烁监测网的监测数据, 统计分析了2008年7月至2010年7月太阳活动低年期间广州地区地磁扰动与电离层闪烁的关系. 用肇庆台地磁水平分量H的变化量换算出肇庆地磁指数K, 以此来代表广州地区地磁扰动情况.分析结果表明, 磁暴/强地磁扰动对广州地区电离层闪烁的发生总体表现为抑制作用, 电离层闪烁主要发生在低K值期间, 而在K ≥ 4时电离层闪烁的发生呈下降趋势. 电离层闪烁发生率随季节和地磁活动的变化规律表现在, 春季的弱闪烁发生率、夜间中等以上闪烁发生率和夏季中等以上闪烁的发生率明显与地磁活动指数K相关, 即随$K$指数的增大而减小; 在秋季和冬季闪烁发生率与K指数变化无明显关系. 同时还综合分析了地磁与太阳活动的变化对电离层活动的影响, 广州地区闪烁主要发生在太阳活动较低的磁静日期间.      

GISM模型在中国低纬地区的适用性分析

为检验全球电离层闪烁模型（GISM）在中国低纬地区预测的准确性,根据2011年7月至2012年6月期间中国低纬地区三个观测站记录的GPSL1频点的电离层闪烁数据,对GISM模型的预测结果进行了分析.研究表明,在太阳活动高年,该模型能够反映出中国低纬地区闪烁的主要特征.模型预测的闪烁开始时间与观测结果较为一致,而结束时间滞后观测值约1h;模型预测的低纬地区闪烁强度峰值与观测结果基本一致,而在相同累积概率条件下,模型预测的闪烁强度则高于观测值;模型显示闪烁发生概率和闪烁强度随纬度的增加而减小,这一结果与观测结果一致.      

基于IGS电离层TEC格网的扰动特征统计分析

电离层总电子含量（TEC）是研究空间天气特性的重要参量,通过分析电离层TEC,可以了解空间环境的变化特征.利用IGS提供的1999—2016年全球电离层TEC格网数据,按照地磁纬度将全球划分为高、中、中低、低磁纬四个区域,计算不同区域的电离层扰动;利用大量统计数据选取电离层扰动事件的判定阈值,分析电离层扰动与太阳活动、时空之间的关系;计算电离层扰动指数与地磁活动之间的相关系数.结果显示:电离层扰动与太阳活动变化具有较强的正相关特性.在太阳活动低年,电离层扰动事件发生的概率约为1.79%,在太阳活动高年发生扰动的概率约为10.18%.在空间分布上,无论是太阳活动高年还是低年,高磁纬地区发生扰动事件的概率均大于其他磁纬出现扰动事件的概率.计算得到的中磁纬和中低磁纬地区电离层扰动指数与全球地磁指数Ap的相关系数分别为0.57和0.56,说明电离层扰动指数与Ap具有较好的相关关系;高磁纬电离层扰动指数与Ap的相关系数为0.44;低磁纬扰动指数与Ap的相关系数为0.39.以上结果表明,不同区域电离层扰动与全球地磁指数Ap的相关性不同,测定区域地磁指数可能会提高与电离层扰动的相关性.      

海南地区电离层闪烁观测与GISM模式预测的比较分析

为了获得全球电离层闪烁模式GISM在中国低纬地区预测的精度和可靠性,利用海南三亚GPS电离层闪烁监测系统一年的观测数据与模式预测结果进行对比分析.结果表明,在太阳活动低年,GISM能较好地反映海南地区电离层闪烁的季节变化、日变化和空间分布特性;对于季节变化,模式与观测结果在中等强度闪烁条件下较为相符,而在强闪烁和弱闪烁条件下有不同程度的偏差;模式预测的闪烁日变化与实际观测基本一致,但在闪烁发生率出现最大值的时间上模式预测要滞后约1 h左右;在电离层闪烁发生率的空间分布上,模式预测与实际观测较为相符,即海南地区南面电离层闪烁发生率高于北面.      

华南地区电离层闪烁的时空分布特征研究

利用位于赤道异常区的广州(23.17°N, 113.34°E)和茂名(21.45°N, 111.31°E)两台站2011年7月至2012年6月观测到的GPS电离层闪烁数据, 分析比较了这两地电离层闪烁出现的逐月变化及地方时变化和空间分布特征. 结果表明, 中等强度闪烁(S₄ > 0.4)和强闪烁(S₄ > 0.6)的出现均呈现明显季节分布规律, 两站的闪烁活动均表现出春秋强, 冬夏弱的特点, 在时间上主要发生在20:00LT-24:00LT; 从空间分布来看, 两站的闪烁活动在2011年秋季, 闪烁出现的区域比较分散, 而在2012年春季, 主要在两站上空区域出现的闪烁最为频繁.      

海南地区电离层闪烁监测及初步统计分析

为开展赤道区的电离层闪烁形态特性及相关物理过程的研究,空间中心海南台站建立了一套GPS电离层闪烁监测系统．该系统是利用Plessey GPS Builder-2系统开发的,对软件的源码进行了修改,使其能以高采样率(50／s)同时并行记录11个通道GPS信号强度数据．对2003年7—12月间L-波段电离层闪烁事件的初步统计分析结果表明,电离层闪烁主要发生在日落后到午夜附近,其中9—11月较7—8月闪烁发生和结束的时间明显提前;电离层闪烁发生的频率和强度在9—11月较其他月份明显增强,其中10月达到最大;电离层闪烁的逐日变化具有很强的随机性,闪烁的发生在秋分附近9月底到10月中旬的磁静日期间达到最大;太阳和地磁活动的增强通常会抑制电离层闪烁的发生,这种情形在秋分附近尤为明显．     

中国广州地区电离层闪烁观测结果的初步统计分析

利用在广州站(23o8' N, 113o17' E)建立的GPS电离层闪烁监测系统, 开展了对电离层闪烁的连续观测. 利用这些观测数据, 对广州地区2007年4月至9月及2008年1月至9月电离层闪烁变化特性进行了初步统计分析研究. 分析结果表明, 广州地区闪烁主要发生在太阳活动较低的磁静日期间. 季节变化表现为弱闪烁(0.2相似文献   

太阳活动低年低纬地区VTEC 变化特性分析

利用福州台站(26.1°N, 119.3°E, 磁纬14.4°N)电离层闪烁与TEC监测仪2006-2010年的观测数据, 对该地区垂直总电子含量(VTEC)进行时间变化特性分析. 结果表明, 春秋冬三季的VTEC平均最高值出现在06:00UT, 夏季出现在08:00UT, 所有季节的平均最低值均出现在21:00UT; VTEC变化存在季节异常和弱冬季异常, 春秋季节高, 冬夏季节低, 夏季VTEC比冬季低且最大值出现时间延迟; VTEC在2006-2009年呈现下降的变化趋势, 2010年开始增强, 年际变化与太阳活动及地磁活动变化趋势具有较好的对应关系; VTEC变化与太阳活动存在很好的相关性, 相关系数达到0.5以上, 地磁活动则显示了弱相关的特性; F_10.7与VTEC的相关性随着每天Kp指数总值Σ_kp的增大而减小.      

地磁暴期间北半球高纬度地区电离层变化特征及对精密定位的影响

基于加拿大地区高纬度电离层观测网的电离层闪烁观测数据,分析了2018年8月26日地磁暴事件引发的北半球高纬度地区电离层总电子含量（TEC）异常变化、TEC变化率指数（ROTI）及电离层相位闪烁的变化特征.结果表明:加拿大地区最大异常值约6 TECU,磁暴引发全球电离层TEC异常峰值高达20 TECU;加拿大地区电离层相位闪烁发生率最大增至12.6%,而磁静日期间约为1%;强电离层闪烁期间,电离层相位闪烁指数与ROTI之间具有较强的一致性.对GPS双频精密单点定位（Precise Point Positioning,PPP）结果进行分析发现:无闪烁期间定位误差随测站纬度的增高呈现出增大趋势,但均方根误差小于0.4m;闪烁发生期间各测站的定位误差均显著增大,水平和垂直方向定位误差分别增至约0.9m及1.7m.      

中国南京地区L波段电离层闪烁初步统计分析

利用南京地区2008年11月至2009年10月电离层闪烁监测数据, 统计分析了该地区一年间L波段电离层幅度闪烁发生率的逐日变化、逐月变化、地方时变化和空间分布等特征. 统计结果表明, 在此期间, 南京地区L波段电离层幅度闪烁活动比较平静, 主要以0.14<0.2的闪烁为主, S₄>0.2的闪烁很少发生.不同强度幅度闪烁表现出一致的时间变化和空间分布特征, 2008年11月为最小,2009年6月、8至10月闪烁发生率都有明显的增强, 在10月达到最大, 在8月和10月的S₄>0.2的闪烁主要出现于正午到日落前这段时间; 对于闪烁的空间分布, 单站一年数据统计显示, 测站北向闪烁的发生频率高于南向, 但该统计结果需要更多的数据样本进行进一步的验证.      

A study of L band scintillations during the initial phase of rising solar activity at an Indian low latitude station

The ionospheric scintillation and TEC (Total Electron Content) variations are studied using GPS (Global Positioning System) measurements at an Indian low latitude station Surat (21.16°N, 72.78°E; Geomagnetic: 12.90°N, 147.35°E), situated near the northern crest of the equatorial anomaly region. The results are presented for data collected during the initial phase of current rising solar activity (low to moderate solar activity) period between January 2009 and December 2011. The results show that within a total number of 656 night-time scintillation events, 340 events are observed with TEC depletions, Rate of change of TEC (ROT) fluctuations and enhancement of Rate of change of TEC Index (ROTI). A comparison of night-time scintillation events from the considered period reveal strong correlation amongst the duration of scintillation activity in S₄ index_, TEC depletion, ROT fluctuations and ROTI enhancement in the year 2011, followed by the year 2010 and least in 2009. The statistical analyses of scintillation activity with enhancement of ROTI also show that about 70–96% scintillation activity took place in equinox and winter months. Moreover, from a nocturnal variation in occurrence of scintillation with (S₄ ? 0.2) and enhancement of ROTI with (ROTI ? 0.5), a general trend of higher occurrence in pre-midnight hours of equinox and winter seasons is observed in both indices during the year 2011 and 2010, while no significant trend is observed in the year 2009. The results suggest the presence of F-region ionospheric irregularities with scale sizes of few kilometers and few hundred meters over Surat and are found to be influenced by solar and magnetic activity.     

Responses of ionospheric foF2 to geomagnetic activities in Hainan

Responses of low-latitude ionospheric critical frequency of F2 layer to geomagnetic activities in different seasons and under different levels of solar activity are investigated by analyzing the ionospheric foF2 data from DPS-4 Digisonde in Hainan Observatory during 2002–2005. The results are as follows: (1) the response of foF2 to geomagnetic activity in Hainan shows obvious diurnal variation except for the summer in low solar activity period. Generally, geomagnetic activity will cause foF2 to increase at daytime and decrease at nighttime. The intensity of response of foF2 is stronger at nighttime than that at daytime; (2) seasonal dependence of the response of foF2 to geomagnetic activity is very obvious. The negative ionospheric storm effect is the strongest in summer and the positive ionospheric storm effect is the strongest in winter; (3) the solar cycle has important effect on the response of foF2 to geomagnetic activity in Hainan. In high solar activity period, the diurnal variation of the response of foF2 is very pronounced in each season, and the strong ionospheric response can last several days. In low solar activity period, ionospheric response has very pronounced diurnal variation in winter only; (4) the local time of geomagnetic activities occurring also has important effect on the responses of foF2 in Hainan. Generally, geomagnetic activities occurred at nighttime can cause stronger and longer responses of foF2 in Hainan.     

海口站电离层闪烁强度功率谱分析与建模应用

基于中国海口站(20.00°N, 110.33°E)获取的2013全年UHF 频段电离层闪烁信号强度数据, 利用Welch算法, 分析给出了四类典型电离层闪 烁强度功率谱. 利用功率谱时序图分析方法, 发现电离层不均匀体存在东西向水 平周期性变化结构. 提取全年功率谱指数p, 通过统计分析发现谱指数p存在规律变化, 据此建立一个谱指数经验模型, 该谱指数模型已用于中国低纬 区域电离层闪烁发生预报概率模型(CMSOP), 进而对海口站UHF频段电离层闪烁发生 概率观测数据和预报结果进行了对比分析.      

磁鞘等离子体密度统计建模

利用理想磁流体LFM模型的模拟数据,基于非参数统计方法对2004年11月14日03:00UT-07:00UT磁暴恢复相期间磁鞘等离子体平均密度进行建模.分析磁鞘等离子体平均密度与上游太阳风参数、行星际磁场参数及地磁扰动参数的统计关系,建立基于数据降维的经验模型.结果表明,电离层扰动强度因子、太阳风-磁层耦合强度因子和日地空间因果链耦合强度因子是影响磁鞘等离子体平均密度的三个主要方面.磁暴恢复相期间电离层上行离子是磁层环电流和磁尾等离子体的重要离子来源.建模分析过程表明,利用经验模型对空间物理过程开展建模,数据的严重多重共线性通常会导致模型的精度较差.而利用SIR和LPR建立的磁鞘等离子体平均密度随相关参数变化的经验模型可以有效解决该问题,具有较好的预测精度,统计特征显著.      

Multi-wavelength coordinated observations of ionospheric irregularity structures from an anomaly crest location during unusual solar minimum of the 24th cycle

The present paper reports coordinated ionospheric irregularity measurements at optical as well as GPS wavelengths. Optical measurements were obtained from Tiny Ionospheric Photometer (TIP) sensors installed onboard the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites. GPS radio signals were obtained from a dual frequency GPS receiver operational at Calcutta (22.58°N, 88.38°E geographic; geomagnetic dip: 32.96°; 13.00°N, 161.63°E geomagnetic) under the SCIntillation Network Decision Aid (SCINDA) program. Calcutta is located near the northern crest of Equatorial Ionization Anomaly (EIA) in the Indian longitude sector. The observations were conducted during the unusually low and prolonged solar minima period of 2008–2010. During this period, four cases of post-sunset GPS scintillation were observed from Calcutta. Among those cases, simultaneous fluctuations in GPS Carrier-to-Noise ratios (C/N_o) and measured radiances from TIP over a common ionospheric volume were observed only on February 2, 2008 and September 25, 2008. Fluctuations observed in measured radiances (maximum 0.95 Rayleigh) from TIP due to ionospheric irregularities were found to correspond well with C/N₀ fluctuations on the GPS links observed from Calcutta, such effects being noted even during late evening hours of 21:00–22:00 LT from locations around 40° magnetic dip. These measurements indicate the existence of electron density irregularities of scale sizes varying over several decades from 135.6 nm to 300–400 m well beyond the northern crest of the EIA in the Indian longitude sector during late evening hours even in the unusually low solar activity conditions.     

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.     

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.