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1.
利用2010年11月至2011年10月IGS提供的全球电子浓度总含量(TEC)数据, 分析太阳活动上升期华南地区(经度110°E, 纬度5°—35°N) 上空电离层赤道异常(EIA)北驼峰的变化特征. 结果显示, 电离层赤道异常北驼峰区TEC峰值I具有明显的季节和半年变化特征; 北驼峰峰值出现的时间T和纬度L的日变化有一个相对较大的变化区间, 其季节和半年变化特征并不明显; 太阳活动对北驼峰变化影响比较明显, 而地磁活动对北驼峰变化影响不明显.   相似文献   

2.
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.   相似文献   

3.
利用昆明低纬度测站(24.7°N,102.9°E,磁纬15.1°N)2016-2019年的观测数据和最新版的国际参考电离层(IRI-2020)模拟结果,对昆明地区电离层总电子含量(TEC)在太阳活动下降年期间的变化特征及与模型输出进行对比研究。结果表明,昆明TEC存在明显的春秋高值、夏冬低值的半年异常;白天高值、夜间低值的日变化特点突出,日峰值出现在06:30-08:00 UT(约13:00-15:00 LT);TEC随太阳活动减弱而明显下降,年平均峰值在2016-2019年分别为48,33,27,24 TECU;日峰值TEC与F10.7存在显著相关,月均值相关系数达到0.86,而与Ap指数则表现为弱相关;IRI-2020能较好地模拟昆明地区TEC的季节变化,但与观测值存在较大差异;均方根偏差值多集中在2~15 TECU,相对偏差百分比值主要在–85%~50%范围变化。对比结果表明IRI-2020的预测精度仍有待提高。  相似文献   

4.
华南地区电离层闪烁的时空分布特征研究   总被引:1,自引:1,他引:0  
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.   相似文献   

5.
利用日本Kokubunji站(139.5°E,35.5°N)1959年1月到2004年12月共46年的F2层临界频率foF2参数,统计分析了Kokubunji站电离层F2层峰值电子浓度NmF2随地磁活动、太阳活动、季节和地方时变化的形态特征.结果表明,总体来看,磁暴期间Kokubunji站电离层响应以正暴为主,其中在太阳高年夏季为负暴,冬季为正暴,春秋季以负暴为主但幅度较小;在太阳低年夏季以正暴为主,冬季为正暴,春秋季以正暴为主.NmF2扰动与ap指数在夏季太阳高年负相关,在冬季无论太阳高年低年均为正相关,春秋季中4月和9月在太阳高年类似夏季,3月和10月在太阳低年类似冬季.电离层最大负相扰动对最大地磁活动的延迟时间约为12~15 h;正相扰动的延迟时间则分别为3 h和10 h.地磁活跃期间地方时黄昏后到午夜前倾向于正相扰动,清晨倾向于负相扰动.   相似文献   

6.
低轨航天器弹道系数估算及热层大气模型误差分析   总被引:1,自引:0,他引:1  
利用低轨(LEO)航天器在轨期间两行轨道根数(TLEs)数据,结合经验大气密度模型NRLMSISE00,反演计算得到其在轨期间的弹道系数B’,以31年B’的平均值代替弹道系数真值,分别通过标准球形目标卫星对比以及物理参数基本相同的非球形目标卫星对比,对弹道系数真值进行了检验;利用不同外形目标卫星弹道系数在不同太阳活动周内的变化规律,结合太阳和地磁活动变化,估计经验大气密度模型的误差分布. 结果表明,利用反演弹道系数31年的平均值来代替真值,其在理论值的正常误差范围内;大气密度模型误差在210~526km高度范围内存在相同的变化趋势,且模型误差随高度增加而增大;在短周期内B’变化与太阳活动指数F10.7存在反相关性;密度模型不能有效模拟2008年出现的大气密度异常低. 以上结果表明,经验大气密度模型结果需要修正,尤其是在太阳活动峰年和谷年,此外,磁暴期间模型误差的修正对卫星定轨和轨道预报等也具有重要意义.   相似文献   

7.
用特征向量分析法对第23太阳活动周天津静海磁场强度水平分量H的时均值进行研究,分析行星际磁场扇形结构的地磁效应(简称扇形效应)对中低纬地磁场H分量日变化的贡献.研究结果表明,中低纬扇形效应为3~11nT,在太阳活动高年扇形效应达到最大值(约11nT),低年达到最小值(约3nT).太阳活动高年扇形效应引起的地磁H分量值变化与太阳活动低年的情况相反,但是扇形效应在夏季对地磁H分量的影响较小.太阳活动高年扇形效应日均值的增减与上升年的相反,与下降年相同,夏季扇形效应平均增量最小且无规律.春、夏和秋三个季节的扇形效应最大值都出现在太阳活动高年,冬季的扇形效应在太阳活动峰年两年后才出现最大值(约11nT).在太阳活动低年(或高年),当扇形磁场背离(或指向)太阳时,夏季扇形效应白天引起地磁H分量增大(或减小),夜间导致地磁H分量减小(或增大),其他季节全天都会导致地磁H分量减小(或增大).用特征向量推断行星际磁场扇形极性的符合率在春夏秋三个季节高达60%,在冬季为55%.   相似文献   

8.
通过分析2008年8月至2009年7月昆明站(25.6°N, 103.8°E) 中频(MF)雷达观测数据, 研究了太阳活动低年电离层D区电子密度的季节变化特性,发现D区电子密度主要呈现半年变化特征, 即在春秋季电子密度较大, 而在夏冬季则较小, 这与国际参考电离层(IRI)预测的年变化趋势不一致, 但与昆明站电离层测高仪的最低回波频率fmin的观测结果相符. 同时比较了D区电子密度半年变化与纬向风半年变化的关系, 发现二者之间保持了非常一致的变化趋势并对这种一致性的内在原因进行了分析.   相似文献   

9.
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.   相似文献   

10.
何语璇  刘勇  张强 《空间科学学报》2020,40(6):1074-1083
基于Polar卫星1996-2008年的表面电压数据,研究了卫星在低轨区域出现正高电位(异常事件)与太阳活动的关系及其发生位置的磁地方时(MLT)分布.研究表明:太阳辐射与异常事件发生次数呈正相关,太阳活动越活跃,异常事件出现次数越多,但不会影响航天器表面电位;异常事件发生占比呈现明显季节性变化,在太阳活动高年,冬季和夏季次数较多,春季和秋季次数较少,在太阳活动低年,每月次数均维持在较低水平,而一个月内异常事件次数没有明显规律;在分布上南北半球表现出相似性,异常事件均不会发生在地磁纬度50°-60°区域,极区和昏侧发生次数较多,而不同的是异常事件在南半球发生得更多更集中;虽然太阳活动与航天器在低高度时表面出现正高电位的次数呈正相关,但即使在太阳活动峰年,航天器异常事件发生率也不超过10%.   相似文献   

11.
GPS-derived vertical TEC recorded at Xiamen (24.5°N, 118.1°E, geomagnetic latitude 13.2°N), China, during year 2006 is analyzed for the first time and compared to that predicted by ionosphere model SPIM recommend by ISO. A manifest seasonal anomaly is found with the high value during equinoctial season and low value during summer and winter season. Relative standard deviation for VTEC shows high value at around midnight and before sunrise. The correlation analysis exhibits that the variation of VTEC has a very weak relation with geomagnetic and solar activities (Dst, AP, SSN and F10.7). Comparative results reveal that the SPIM overestimates the observed VTEC at most of the time.  相似文献   

12.
Variability of vertical TEC recorded at Fuzhou (26.1°N, 119.3°E, geomagnetic latitude 14.4°N), Xiamen (24.5°N, 118.1°E, geomagnetic latitude 13.2°N), Nanning (22.8°N, 108.3°E, geomagnetic latitude 11.4°N), China, during the low solar activity in 2006–2007 have been analyzed and discussed. Remarkable seasonal anomaly was found over three stations with the highest value during spring and the lowest value during summer. The relative standard deviation of VTEC is over 20% all the time, with steady and smooth variation during daytime while it has a large fluctuation during nighttime. The biggest correlation coefficient was found in the VTEC-sunspot pair with a value of over 0.5. It seems that solar activity has a better correlation ship than geomagnetic activity with the variation of VTEC and better correlations are found with more long-term data when comparing our previous study. The results of comparing observation with model prediction in three sites reveal again that the SPIM model overestimates the measured VTEC in the low latitude area.  相似文献   

13.
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.  相似文献   

14.
This study presents the time variations of the total electron content in the South East Asian equatorial ionization anomaly. The time variation of the TEC is analyzed through the period 2006–2011 by using a latitudinal chain of GPS stations extending in the northern and southern hemisphere. The data shows that the shape of the diurnal variation of the TEC depends on the latitude: a plateau is observed at the stations near the equator and a Gaussian at the station distant from the equator. We observe a semiannual pattern in all the stations with maxima at equinox. In both hemispheres, the amplitude of the crest is larger in spring than autumn from 2006 to 2008 and smaller in spring than in autumn from 2009 to 2011. We also observe an asymmetry between the amplitude and the position of the two crests of ionization. There is a very high level of correlation between the amplitude of the TEC at the two crests and the sunspot number: ∼0.88. During the deep solar minimum 2008–2009, the amplitude of crests of ionization becomes small during several months in summer and winter. The results show that both crests move significantly equatorward in winter than other seasons and there is a tendency for both crests to appear earlier in winter and later in summer.  相似文献   

15.
利用广州站(23.2°N, 113.3°E) GPS双频接收机监测的电离层TEC数据和IRI-2007模型不同电离层输入参数计算得到的TEC预测值, 对比分析了太阳活动低年(2008年)广州地区TEC的变化特征. 结果表明, TEC观测值周日变化在16:00LT左右达到最大值, 而IRI-TEC最大值出现时间较GPS-TEC提前1h左右. TEC季节变化在春秋分较高, 两至季节较低, 表现出明显的半年特性和季节依赖性, 并出现冬季异常现象. IRI-TEC与GPS-TEC在白天具有较好的一致性, 夜间偏差较大. 不同电离层输入参数得到的TEC预测值也相差较大, 选用顶部电子密度参数NeQuick、底部厚度参数B0 Table并用URSI系数计算F2层峰值参数时, 能较好地反映TEC观测值的变化特征. 在对磁暴的响应上, 预测值无明显变化, 观测值则有比较明显的表现. 通过对比, 初步分析了利用IRI-2007模型预测TEC在广州地区的适用性, 并给出了合理的参数选择方案.   相似文献   

16.
Diurnal, seasonal and latitudinal variations of Vertical Total Electron Content (VTEC) over the equatorial region of the African continent and a comparison with IRI-2007 derived TEC (IRI-TEC), using all three options (namely; NeQuick, IRI01-corr and IRI-2001), are presented in this paper. The variability and comparison are presented for 2009, a year of low solar activity, using data from thirteen Global Positioning System (GPS) receivers. VTEC values were grouped into four seasons namely March Equinox (February, March, April), June Solstice (May, June, July), September Equinox (August, September, October), and December Solstice (November, December, January). VTEC generally increases from 06h00 LT and reaches its maximum value at approximately 15h00–17h00 LT during all seasons and at all locations. The NeQuick and IRI01-corr options of the IRI model predict reasonably well the observed diurnal and seasonal variation patterns of VTEC values. However, the IRI-2001 option gave a relatively poor prediction when compared with the other options. The post-midnight and post-sunset deviations between modeled and observed VTEC could arise because NmF2 or the shape of the electron density profile, or both, are not well predicted by the model; hence some improvements are still required in order to obtain improved predictions of TEC over the equatorial region of the Africa sector.  相似文献   

17.
This paper presents an analysis of the Total Electron Content (TEC) derived from the International GNSS Service receiver (formerly IGS) at Malindi (2.9°S, 40.1°E), Kenya for the periods 2004–2006 during the declining phase of solar cycle 23. The diurnal, monthly and seasonal variations of the TEC are compared with TEC from the latest International Reference Ionosphere model (IRI-2007). The GPS–TEC exhibits features such as an equatorial noon time dip, semi-annual variations, Equatorial Ionization Anomaly and day-to-day variability. The lowest GPS–TEC values are observed near the June solstice and September equinox whereas largest values are observed near the March equinox and December solstice. The mean GPS–TEC values show a minimum at 03:00 UT and a peak value at about 10:00 UT. These results are compared with the TEC derived from IRI-2007 using the NeQuick option for the topside electron density (IRI–TEC). Seasonal mean hourly averages show that IRI-2007 model TEC values are too high for all the seasons. The high prediction primarily occur during daytime hours till around midnight hours local time for all the seasons, with the highest percentage deviation in TEC of more 90% seen in September equinox and lowest percentage deviation in TEC of less than 20% seen in March equinox. Unlike the GPS–TEC, the IRI–TEC does not respond to geomagnetic storms and does overestimate TEC during the recovery phase of the storm. While the modeled and observed data do correlate so well, we note that IRI-2007 model is strongly overestimating the equatorial ion fountain effect during the descending phase of solar cycle, and this could be the reason for the very high TEC estimations.  相似文献   

18.
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.  相似文献   

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