不同太阳活动条件下电离层形态对估算GPS系统硬件延迟的影响

利用两个中纬度台站GPS观测数据提取的GPS卫星硬件延迟,分析了不同太阳活动情况下估算的硬件延迟稳定性和统计特征,结合同期电离层观测数据,研究了电离层状态对硬件延迟估算结果的影响.研究结果表明,基于太阳活动高年(2001年)GPS观测数据估算的硬件延迟稳定性要低于太阳活动低年GPS观测数据的估算结果,利用2001年GPS数据估算的卫星硬件延迟年标准偏差(RMS)平均值约为1TECU,而2009年GPS数据估算的卫星硬件延迟年标准偏差平均值约为0.8TECU.通过对2001年和2009年北京地区电离层F₂层最大电子密度(N_mF₂)变化性分析,结合GPS硬件延迟估算方法对电离层时空变化条件的要求,认为硬件延迟稳定性与太阳活动强度的联系是由不同太阳活动条件下电离层变化的强度差异引起的.      

大耀斑期间向日面电离层总电子含量的响应个例分析

利用2001年4月15日1336UT耀斑爆发期间向日面GPS观测数据提取的总电子含量的时间变化曲线。分析了向日面电离层对这次耀斑的响应特点．结果表明，耀斑期间向日面电离层出现了总电子含量突增事件．最大总电子含量增加量约为2．6TECU，在0600LT和1800LT都观测到了总电子含量突增，世增加幅度仅为0．5-1TECU．在高纬地区，由于电离层闪烁，从TEC时间变化曲线提取不出来总电子含量增加值．从各卫星星下点处的TEC增加量和各星下点处的太阳天顶角的关系可以看到，TEC增加量与太阳天顶角有关，太阳天顶角越大，TEC增幅越小。另外，从总电子含量时间变化率曲线上还观测到了时间同步的小尺度扰动，通过与耀斑期间硬X射线辐射通量的比较，发现两者有明显的相关性，电离层中的这种扰动与耀斑期间的硬X射线或远紫外辐射有关．     

2009年6至7月华南地区电离层TEC扰动研究

电离层TEC（Total Electron Content）扰动与多种扰动源相关联．2009年6至7月期间存在地震和日全食的扰动源．利用广州地区GPS监测网在2009年6至7月连续监测到的TEC数据,通过采用前15天数据的滑动窗口对数据进行处理,从时间序列和空间分布两方面分析了华南地区电离层TEC扰动特征．结果显示,2009年6至7月华南地区电离层TEC扰动和该时期发生的地震以及日全食事件可能有关联;2009年7月多个地震发生引起的电离层扰动特征为,震前出现的是正异常,发震当天或震后有可能是正异常,也有可能是负异常;7月22日日全食当天TEC扰动为正异常,推测该正异常是地磁活动、地震活动及日全食综合效应的结果．     

2009年7月22日日全食期间电离层总电子含量变化研究

利用中国区域内五个GPS台站(一个台站处于日全食区域、四个台站处于日偏食区域)观测数据, 研究2009年7月22日日全食期间电离层总电子含量(TEC)的变化, 结果表明, 日全食期间, 电离层TEC值经历了下降和恢复的过程, 最小TEC相对于最大食偏的时间延迟约为1～10min; 台站测得最小TEC的星下点(IPP)越靠近日全食带TEC下降量越大, 在日食期间武汉站(114.35°E, 30.53°N) TEC相对于各参考日期的TEC, 其平均下降量最大, 达到4.58TECU.      

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.      

磁暴期间电离层扰动的GPS台网观测分析

给出了一种利用GPS台网观测获取TEC快速变化的计算方法，并将该方法用于东亚一澳大利亚扇区的GPS台网观测数据，分析了2000年7月14—18H大磁暴期间的电离层响应，揭示出电离层暴期间赤道异常峰的压缩和移动等特性．计算结果表明，在站点分布不均匀、原始观测数据不足且随时间跳变等多种不利因素的影响下，这种新的算法仍能保持很好的计算稳定性，并能快速地提取给定时空范围内的三维TEC短时变化的特征，适用于研究电离层暴等情况下引起的TEC扰动．     

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.      

2009年7月22日日全食电离层效应观测

首次利用廊坊中频雷达和武汉、嘉兴、廊坊等三站GPS对2009年7月22日日全食电离层效应进行了观测．日食期间,中频雷达D层78km高度上电子密度减小了约67％,电子密度为200cm^-3的高度上升了近10km,GPS／TEC减小了1TECU左右,其变化的最大相位与日食最大相位几乎同步;日食后,观测到周期为2个多小时的电离层扰动现象．     

磁暴期间中国中低纬电离层不规则体与扰动分析

2017年9月8日发生了一次强磁暴，Kp指数最大值达到8.利用区域电离层格网模型（Regional Ionosphere Map，RIM）和区域ROTI（Rate of TEC Index）地图，分析了磁暴期间中国及其周边地区电离层TEC扰动特征和低纬地区电离层不规则体的产生与发展情况，同时利用不同纬度IGS（International GNSS Service）测站BJFS（39.6°N，115.9°E），JFNG（30.5°N，114.5°E）和HKWS（22.4°N，114.3°E）的GPS双频观测值，获取各测站的ROTI和DROT（Standard Deviation of Differential ROT）指数变化趋势.结果表明:此次磁暴发生期间电离层扰动先以正相扰动为主，主要发生在中低纬区域，dTEC（differential TEC）最大值达到14.9TECU，随后电离层正相扰动逐渐衰减，在低纬区域发生电离层负相扰动，dTEC最小值达到-7.2TECU；在12:30UT-13:30UT时段，中国南部低纬地区发生明显的电离层不规则体事件；相比BJFS和JFNG两个测站，位于低纬的HKWS测站的ROTI和DROT指数变化更为剧烈，这表明电离层不规则体结构存在纬度差异.      

一种基于白谱法的电离层天气扰动指数

基于一种电离层扰动提取方法——白谱法,利用IGS提供的电离层TEC网格数据,获得电离层J_s指数、J_r指数和J_p指数,分别反映单站、纬度圈（沿经度积分）及行星际尺度下的电离层天气扰动状态.在2015年3月的一次磁暴过程中,J_s指数、J_r指数及J_p指数均很好地反映出电离层响应地磁暴的过程,磁暴前后J_p指数与Dst指数相关系数达到-0.72;J_s图从二维角度很好地表征了电离层天气的扰动过程.在此基础上,统计分析了2011——2014年J_p指数与Dst指数的相关性,结果表明:限定J_p≥2,J_p指数与对应时间Dst指数的相关系数为-0.67;限定J_p≥3,二者相关系数更高,达到-0.87.通过分析不同J_p指数阈值下不同等级磁暴的次数,发现J_p指数可以很好地反映磁暴下的电离层整体扰动,为指示电离层天气状态提供了可能的参数.      

Ionospheric anomalies observed over South Korea preceding the Great Tohoku earthquake of 2011

We investigated the ionospheric anomalies observed before the Tohoku earthquake, which occurred near the northeast coast of Honshu, Japan on 11 March, 2011. Based on data from a ground-based Global Positioning System (GPS) network on the Korean Peninsula, ionospheric anomalies were detected in the total electron content (TEC) during the daytime a few days before earthquake. Ionospheric TEC anomalies appeared on 5, 8 and 11 March. In particular, the ionospheric disturbances on 8 March evidenced a remarkable increase in TEC. The GPS TEC variation associated with the Tohoku earthquake was an increase of approximately 20 total electron content units (TECU), observed simultaneously in local and global TEC measurements. To investigate these pre-earthquake ionospheric anomalies, space weather conditions such as the solar activity index (F10.7) and geomagnetic activity indices (the Kp and Dst indices) were examined. We also created two-dimensional TEC maps to visual the spatial variations in the ionospheric anomalies preceding the earthquake.     

低纬(海南)地区电离层偶发E层的潮汐类周期研究

基于低纬(海南)台站(19.5°N,109.1°E)电离层测高仪在2004年观测到的偶发E层(Es)临界频率(f₀E_s)和虚高(h'E_s)数据,利用谱分析方法,给出了中国低纬地区Es层在全年和不同季节内的短周期变化特性.对全年数据谱分析表明,Es层除具有非常强的24h周期外,还具有显著的12h和8h周期.对不同季节内两个参数的谱分析进一步表明,8h周期主要出现在f₀E_s参数的春秋分季和夏末及在h'E_s参数的几乎所有季节;6h周期主要出现在f₀E_s参数的11-12月.海南低纬Es层中具有显著的6h和8h周期特性,特别是这两个周期还能同时出现在冬季,这是以往研究中不曾发现的新结果.初步分析认为,Es层的6h和8h周期极可能是分别由1/4日和1/3日潮汐所造成的.      

Pre-earthquake ionospheric anomalies before three major earthquakes by GPS-TEC and GIM-TEC data during 2015–2017

The dual-frequency satellite-based measurements from Global Positioning System (GPS) may provide feasible ways of studying and potentially detecting of earthquake (EQ) related anomalies in the ionosphere. In this paper, GPS based Total Electron Content (TEC) data are studied for three major M?>?7.0 EQs in Nepal and Iran-Iraq border during 2015–2017 by implementing statistical procedures on temporal and spatial scale. Previous studies presented different time interval of pre-seismic ionospheric anomalies, however, this study showed that EQs ionospheric precursors may occur within 10?days. Furthermore, the ionospheric anomalies on the suspected day occurred during UT?=?08:00–12:00?h before the main shock. The Global Ionospheric Map TEC (GIM-TEC) data retrieved over the epicenter of M7.8 (Nepal EQ) showed a significant increase of 6 TECU on April 24, 2015 (one day before the main shock), which is recorded by the ground GPS station data of Islamabad (station lies within the EQ preparation zone). Furthermore, the spatial GIM-TEC result imply significant anomalies over the epicenter during the time interval between UT?=?08:00–12:00?h (LT?=?13:00–17:00). For M7.3 (Nepal EQ), the TEC anomalies were detected on May 10, 2015 (2?days before the event) in the temporal data. The spatial TEC data imply the huge clouds over the epicenter at about UT?=?08:00–12:00?h on May 10, 2015, that may be associated with this EQ in the quiet geomagnetic storm conditions. Similarly, temporal and spatial TEC showed anomaly on November 3, 2017, during UT?=?08:00–12:00 (9?days before the Iran-Iraq border EQ) after implementing the statistical method on it. Conversely, there exists a short-term but low magnitude TEC anomaly synchronized with a geomagnetic storm on November 7–8, 2017 (4 to 5?days prior to M7.3 Iran-Iraq border EQ). The diurnal and hourly GIM-TEC and VTEC data also imply the execution of ionospheric anomalies within 10?days prior to all events. All these positive anomalies in TEC may be due to the existence of a huge energy from the epicenter during the EQ preparation period.     

基于因果卷积与LSTM网络的电离层总电子含量预报

电离层总电子含量（TEC）不仅是分析电离层形态的关键参数之一,同时为导航及定位等空间应用系统消除电离层附加时延提供重要支撑。由于电离层TEC的时空变化特征,本文融合因果卷积和长短时记忆网络,以太阳活动指数F_10.7、地磁活动指数Dst和电离层TEC历史数据作为特征输入,构建深度学习模型,实现提前24 h预报电离层TEC。进一步利用2005－2013年连续9年的CODE TEC数据,全面评估了模型在北京站（40°N,115°E）、武汉站（30.53°N,114.36°E）和海口站（20.02°N,110.38°E）的预报性能。结果显示不同太阳活动条件下三个站的TEC值与真实测量值的相关系数都大于0.87,均方根误差大都集中在0～1 TECU以内,且模型预报精度与纬度、太阳、地磁活动程度、季节变化相关。与仅由长短时记忆网络构成的预报模型相比,本实验模型均方根误差降低了15%,为电离层TEC预报模型的实际应用提供了参考。      

Comparison of observed TEC values with IRI-2007 TEC and IRI-2007 TEC with optional foF2 measurements predictions at an equatorial region,Chumphon, Thailand

In this research, as part of working towards improving the IRI over equatorial region, the total electron content (TEC) derived from GPS measurements and IRI-2007 TEC predictions at Chumphon station (10.72°N, 99.37°E), Thailand, during 2004–2006 is analyzed. The seasonal variation of the IRI-2007 TEC predictions is compared with the TEC from the IRI-2007 TEC model with the option of the actual F2 plasma frequency (foF2) measurements as well as the TEC from the GPS and International GNSS service (IGS). The Chumphon station is located at the equatorial region and the low latitude of 3.22°N. For a declining phase of the solar cycle (2004–2006), the study shows that the IRI-2007 TEC underestimates the IRI-2007 TEC with the foF2 observation at the nighttime by about 5 TECU. The maximum differences are about 15 TECU during daytime and 5 TECU during nighttime. The overestimation is more evident at daytime than at nighttime. When compared in terms of the root-mean square error (RMSE), we find that the highest RMSE between GPS TEC and IRI 2007 TEC is 14.840 TECU at 1230 LT in 2004 and the lowest average between them is 1.318 TECU at 0630 LT in 2006. The noon bite-out phenomena are clearly seen in the IRI-2007 TEC with and without optional foF2 measurements, but not on the GPS TEC and IGS TEC. The IRI TEC with optional foF2 measurements gives the lowest RMSE values between IRI TEC predicted and TEC measurement. However, the TEC measurements (GPS TEC and IGS TEC) are more correct to use at Chumphon station.     

Application of BDS-GEO for studying TEC variability in equatorial ionosphere on different time scales

The Earth's ionosphere and especially its equatorial part is a highly dynamical medium. Geostationary satellites are known to be a powerful tool for ionospheric studies. Recent developments in BDS-GEO satellites allow such studies on the new level due to the best noise pattern in TEC estimations, which corresponds to those of GPS/GLONASS systems. Here we used BDS-GEO satellites to demonstrate their capability for studying equatorial ionosphere variability on different time scales. Analyzing data from the equatorial SIN1 IGS station we present seasonal variations in geostationary slant TEC for the periods of high (October 2013 - October 2014) and low (January 2017 - January 2018) solar activity, which show semi-annual periodicity with amplitudes about 10 TECU during solar maximum and about 5 TECU during the solar minimum. The 27-day variations are also prominent in geostationary slant TEC variations, which correlates quite well with the variations in solar extreme UV radiation. We found semi-annual pattern in small scale ionospheric disturbances evaluated based on geostationary ROTI index: maximal values correspond to spring and fall equinoxes and minimum values correspond to summer and winter solstices. The seasonal asymmetry in ROTI values was observed: spring equinox values were almost twice as higher than fall equinox ones. We also present results on the 2017 May 28–29 G3 geomagnetic storm, when ～30 TECU positive anomaly was recorded, minor and final major sudden stratospheric warmings in February and March 2016, with positive daytime TEC anomalies up to 15–20 TECU, as well as the 2017 September 6 X9.3 solar flare with 2 TECU/min TEC rate. Our results show the large potential of geostationary TEC estimations with BDS-GEO signals for continuous monitoring of space weather effects in low-latitude and equatorial ionosphere.     

Ionospheric anomalies of local earthquakes detected by GPS TEC measurements using data from Tashkent and Kitab stations

This paper reports the ionospheric anomalies observed during strong local earthquakes (M?5.0) which occurred mostly in and around Uzbekistan in seismically active zones, during years 2006 to 2009 within approximately 1000 km distance from the observing GPS stations located in Tashkent and Kitab, Uzbekistan. The solar and geomagnetic conditions were quiet during occurrence of the selected strong earthquakes. We produce Total Electron Content (TEC) time series over both sites and apply them to detect anomalous TEC signals preceding or accompanying the local earthquakes. The results show anomalous increase or decrease of TEC before or during the earthquakes. In general the anomalies occurred 1–7 days before the earthquakes as ionospheric electromagnetic precursors. To identify the anomalous values of TEC we calculated differential TEC (dTEC). dTEC is obtained by subtracting monthly averaged diurnal vTEC from the values of observed vTEC at each epoch. This procedure removes normal diurnal variations of vTEC. The present results are in good agreement with the previous observations on ionospheric earthquake precursors reported by various researchers.