第23太阳活动周武汉站电离层TEC特征分析

利用武汉站(30.5°N, 114.4°E)1997年1月1日至2007年12月31日电离层TEC、太阳黑子数及地磁指数等资料, 分析了第23周武汉站TEC的周日变化、季节变化、半年变化以及与太阳活动的相关性等特征; 以2006年4月13-17日发生的磁暴为例, 讨论了武汉站TEC对磁暴的响应以及可能的机理. 结果表明,武汉站电离层TEC在太阳活动高、低年均呈典型的周日变化特征; 冬季异常和半年异常特征明显, 且受太阳活动强弱影响; TEC和太阳黑子数年均值相关系数为0.9611; TEC对磁暴的响应可能是由磁层穿透电场和中性风共同作用导致的, 具体影响机制有待深入研究.      

太阳黑子数及Ap指数周期变化特征的小波分析

应用Morlet小波变换方法从多个变化尺度上对1932—2000年的太阳黑子数及Ap指数的变化特征进行分析．(1)太阳黑子数存在准11年、准32年的周期变化特征及Ap指数存在准32年、准11年、准6个月、准27天和准13．9天的周期变化特征；(2)太阳黑子数及Ap指数有着相似的准11年周期变化，但Ap指数极值的出现要比太阳黑子数极值出现滞后1—2年；(3)Ap指数准27天的周期变化在太阳黑子活动高、低年不同，在太阳活动低年，Ap指数有着较稳定的准27天周期变化，但在太阳活动高年，27天的周期变化几乎消失，这种周期变化的消失和出现时间可在Morlet小波变换图中体现出来。     

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。      

太阳活动对电离层TEC变化影响分析ormalsize

为研究太阳活动对电离层TEC变化的影响,从整体到局部分析了2000—2016年的太阳黑子数、太阳射电流量F_10.7指数日均值与电离层TEC的关系,并重点分析了2017年9月6日太阳爆发X9.3级特大耀斑前后15天太阳活动与电离层TEC变化的相关性.结果表明:由2000—2016年的数据整体看来,太阳黑子数、太阳F_10.7指数、TEC两两之间具有很强的整体相关性,但局部相关性强弱不均;此次耀斑爆发前后太阳黑子数、太阳F_10.7指数和TEC具有很强的正相关特性,太阳活动对TEC的影响时延约为2天;太阳活动对全球电离层TEC的影响不同步,从高纬至低纬约有1天的延迟,且对低纬度的影响远大于中高纬度.太阳活动是影响电离层TEC变化的主要原因,但局部也可能存在其他重要影响因素.      

太阳活动对电离层TEC变化影响分析

为研究太阳活动对电离层TEC变化的影响,从整体到局部分析了2000-2016年的太阳黑子数、太阳射电流量F_(10.7)指数日均值与电离层TEC的关系,并重点分析了2017年9月6日太阳爆发X9.3级特大耀斑前后15天太阳活动与电离层TEC变化的相关性.结果表明:由2000-2016年的数据整体看来,太阳黑子数、太阳F_(10.7)指数、TEC两两之间具有很强的整体相关性,但局部相关性强弱不均;此次耀斑爆发前后太阳黑子数、太阳F_(10.7)指数和TEC具有很强的正相关特性,太阳活动对TEC的影响时延约为2天;太阳活动对全球电离层TEC的影响不同步,从高纬至低纬约有1天的延迟,且对低纬度的影响远大于中高纬度.太阳活动是影响电离层TEC变化的主要原因,但局部也可能存在其他重要影响因素.     

基于小波与交叉小波分析的太阳黑子与宇宙线相关性研究

利用小波分析和交叉小波分析方法, 根据太阳黑子数以及Huancayo和Climax两个测站的月均宇宙线数据, 分析了两个测站的月均宇宙线周期变化, 同时利用太阳黑子数R₁₂对Climax站宇宙线流量进行预测研究. 小波分析结果表明, 太阳黑子与宇宙线除存在显著的11年周期外, 太阳活动高年期间还存在1～6个月尺度的周期特性, 在第22太阳周活动高年时还出现了6～8和1～22个月的变化周期; 交叉小波分析结果表明, 在130个月左右的周期上宇宙线与太阳黑子具有显著的负相关性, 并且宇宙线的变化滞后太阳黑子约8个月; 分别采用预测时刻和8个月前的太阳黑子数, 预测相对误差为3.8912%和3.2386%. 本文方法同样适用于估算其他空间天气参量之间的周期和相关性, 提高各种空间天气参量的预测或预报精度.      

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.      

2008—2009年电离层对重现型地磁活动的响应

利用2008—2009年的GPS TEC数据,分析了电离层对冕洞引起的重现型地磁活动的响应. 结果表明,在太阳活动低年,电离层TEC表现出与地磁 ap指数（采用全球3h等效幅度指数ap来表征）和太阳风速度相似的9天和13.5天短周期变化,表明TEC的这种短周期特性主要与重现型地磁活动相关. 地磁纬度和地方时分析表明,夜间高纬地区正负相扰动明显,中低纬地区则以正相扰动为主,较大的TEC变幅主要发生在南北半球高纬地区,夜间南半球高纬地区TEC变化相对ap指数变化有相位延迟. 白天中低纬地区正负相扰动明显,TEC短周期变化与ap指数变化相位基本一致. 2008年TEC的9天和13.5天周期变化幅度大于2009年.      

武汉地区电离层电子浓度总含量的统计经验模式研究

由武汉电离层观象台一个太阳黑子周期（1980-1990年）的实测电离层电子浓度总含量（TEC）资料，统计分析得出了武汉地区的一个TEC经验模式，模式很好地再现了武汉地区的TEC观测值，其预测误差在太阳活动高年稍太，低年较小；在春秋两季稍大，冬夏两季较小；在当地时间白天和傍晚稍大，夜间和早晨较小。此外，与国际参考电离层模式IRI的计算结果比较，本模式预测的TEC值更接近于实际观测结果，同时，本文也初步探讨了TEC的半年变化特征和冬季异常现象。     

太阳活动变化分析

利用Morlet小波变换方法对太阳黑子相对数进行了分析,对太阳活动变化得出了一些有意义的结果.太阳活动存在10.7 a和101 a的变化周期,以10.7 a周期最为显著.太阳活动强弱变化存在一定的阶段性,在1950年发生了气候突变,之后太阳活动明显加强,未来一段时间太阳活动较弱.      

Variation of ionospheric total electron content at crest of equatorial anomaly in China from 1997 to 2004

The periodic variation of TEC data at Xiamen station (geographic coordinate: 24.4°N, 118.1°E; geomagnetic coordinate: 13.2°N, 187.4°E) at crest of equatorial anomaly in China from 1997 to 2004 is analyzed. The characteristic of TEC association with solar activity and geomagnetic activity are also analyzed. The method of continuous wavelet, cross wavelet and wavelet coherence transform methods have been used. Analysis results show that long-term variations of TEC at Xiamen station are mainly controlled by the variations of solar activities. Several remarkable components including 128–256 days, 256–512 days and 512–1024 days exist in TEC variations. The TEC data at Xiamen station is in anti-phase with geomagnetic Dst index in semiannual time-scale, but this response only exists during high solar activity. Diurnal variation of TEC is studied for different seasons. Some features like the semiannual anomaly and winter anomaly in TEC have been reported.     

Analysis of ionospheric TEC response to solar and geomagnetic activities at different solar activity stages

Studying the relationship of total electron content (TEC) to solar or geomagnetic activities at different solar activity stages can provide a reference for ionospheric modeling and prediction. On the basis of solar activity indices, geomagnetic activity parameters, and ionospheric TEC data at different solar activity stages, this study analyzes the overall variation relationships of solar and geomagnetic activities with ionospheric TEC, the characteristics of the quasi-27-day periodic oscillations of the three variables at different stages, and the delayed TEC response of solar activity by conducting correlation analysis, Butterworth band-pass filtering, Fourier transform, and time lag analysis. The following results are obtained. (1) TEC exhibits a significant linear relationship with solar activity at different solar activity stages. The correlation coefficients |R| are arranged as follows: |R|_EUV > |R|_F10.7 > |R|sunspot number. No significant linear relationship exists between TEC and geomagnetic activity parameters (|R| < 0.35). (2) TEC, solar activity indices, and geomagnetic activity parameters have a period of 10.5 years. The maximum amplitudes of the Fourier spectrum for TEC and solar activity indices are nearly 27 days and those of geomagnetic activity parameters are nearly 27 and 13.5 days. (3) The deviations of the quasi-27-day significant periodic oscillation of TEC and solar activity indices are consistent. (4) No evident relationship exists between the quasi-27-day periodic oscillation of TEC and geomagnetic activity parameters. (5) The delay time of TEC for the 10.7 cm solar radio flux and extreme ultraviolet is always consistent, whereas that for sunspot number varies at each stage.     

Variability study of ionospheric total electron content at crest of equatorial anomaly in China from 1997 to 2007

The variation of TEC data at Wuhan station (geographic coordinate: 30.5°N, 114.4°E; geomagnetic coordinate: 19.2°N, 183.8°E) at crest of equatorial anomaly in China from January 1997 to December 2007 were analyzed. Variability with solar activity, annual, semiannual, diurnal and seasonal variation were also analyzed. The MSIS00 model and ISR model were used to analyze the possible mechanisms of the variabilities found in the results. The TEC data in 1997 and 2001 deduced from another crest station Xiamen (geographic coordinate: 24.4°N, 118.1°E; geomagnetic coordinate: 13.2°N, 187.4°E) were used to contrast. Analysis results show that long-term variations of TEC at Xiamen station are mainly controlled by the variations of solar activities. Typical diurnal variation behaves as a minimum of the TEC in the pre-dawn hours around 05:00–06:00LT and a maximum on the afternoon hours around 13:00–15:00LT. Some features like the semiannual anomaly and winter anomaly in TEC have been reported. The anomaly may be the result of common action of the electric field over the magnetic equatorial and the [O/N₂] at the crest station.     

Comparison of GPS-TEC measurements with NeQuick2 and IRI model predictions in the low latitude East African region during varying solar activity period (1998 and 2008–2015)

This paper examines the performances of NeQuick2, the latest available IRI-2016, IRI-2012 and IRI-2007 models in describing the monthly and seasonal mean total electron content (TEC) over the East African region. This is to gain insight into the success of the various model types and versions at characterizing the ionosphere within the equatorial ionization anomaly. TEC derived from five Global Positioning System (GPS) receivers installed at Addis Ababa (ADD, 5.33°N, 111.99°E Geog.), Asab (ASAB, 8.67°N, 116.44°E Geog.), Ambo (ABOO, 5.43°N, 111.05°E Geog.), Nairobi (RCMN, ?4.48°N, 108.46°E Geog.) and Nazret (NAZR, 4.78°N, 112.43°E Geog.), are compared with the corresponding values computed using those models during varying solar activity period (1998 and 2008–2015). We found that different models describe the equatorial and anomaly region ionosphere best depending on solar cycle, season and geomagnetic activity levels. Our results show that IRI-2016 is the best model (compared to others in terms of discrepancy range) in estimating the monthly mean GPS-TEC at NAZR, ADD and RCMN stations except at ADD during 2008 and 2012. It is also found that IRI-2012 is the best model in estimating the monthly mean TEC at ABOO station in 2014. IRI show better agreement with observations during June solstice for all the years studied at ADD except in 2012 where NeQuick2 better performs. At NAZR, NeQuick2 better performs in estimating seasonal mean GPS-TEC during 2011, while IRI models are best during 2008–2009. Both NeQuick2 and IRI models underestimate measured TEC for all the seasons at ADD in 2010 but overestimate at NAZR in 2009 and RCMN in 2008. The periodic variations of experimental and modeled TEC have been compared with solar and geomagnetic indices at ABOO and ASAB in 2014 and results indicate that the F10.7 and sunspot number as indices of solar activity seriously affects the TEC variations with periods of 16–32?days followed by the geomagnetic activity on shorter timescales (roughly periods of less than 16?days). In this case, NeQuick2 derived TEC shows better agreement with a long term period variations of GPS-TEC, while IRI-2016 and IRI-2007 show better agreement with observations during short term periodic variations. This indicates that the dependence of NeQuick2 derived TEC on F10.7 is seasonal. Hence, we suggest that representation of geomagnetic activity indices is required for better performance over the low latitude region.     

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.     

磁暴期间全球TEC扰动特性分析

磁暴期间白天电离层总电子含量（TEC）大幅度扰动.TEC扰动与磁暴发生时的世界时（UT）有关.利用7年的数据对TEC对磁暴的响应进行统计研究.结果显示,磁暴期间白天TEC增大明显,且在午后TEC的增大比例有一个高峰.在18:00UT-04:00UT,南美地区与其他地区相比TEC增长较大,这可能与白天的光照有关.为了研究TEC变化与磁暴的关系,结合同样时间段的Dst指数,把TEC数据分为磁暴日（Dst<-100nT）和平静日（Dst>-50nT）.研究发现,将TEC前移2h,低纬日侧地区TEC增大值随着世界时的变化与Dst变化的负相关性较好,相关系数为-0.75.在中纬度地区,将TEC扰动前移1h,相关系数为-0.61.这可能是行进式大气扰动携带着赤道向的子午风,由极区向低纬传播引起.可以认为,TEC的变化可能是由磁暴引起的.在高纬地区,TEC增大值随着世界时的变化与Dst变化的相关性较差.这可能是由于太阳高度角较低,光辐射通量较小,导致电子密度的增加不明显.      

Time series modeling and analysis of trends of daily averaged ionospheric total electron content

A 10.7 cm solar radio flux F10.7, geomagnetic planetary equivalent amplitude (Ap index), and period variations were considered in this paper to construct a linear model for daily averaged ionospheric total electron content (TEC). The correlation coefficient of the modeled results and International GNSS Service (IGS) observables was approximately 0.97, which implied that the model could accurately reflect the realistic variation characteristics of the daily averaged TEC. The influences of the different factors on TEC and its characteristics at different latitudes were examined with this model. Results show that solar activity, annual and semiannual cycles are the three most important factors that affect daily averaged TEC. Solar activity is the primary determinant of TEC during periods with high solar activity, whereas periodic factors primarily contribute to TEC during periods with minimum solar activity. The extent of the influences of the different factors on TEC exhibits obvious differences at varying latitudes. The magnitude of the semiannual variation becomes less significant with the increase in latitude. Furthermore, a geomagnetic storm causes an increase in TEC at low latitudes and a decrease at high latitudes.