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1.
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   

2.
利用广州台站(23.2°N,113.3°E)的实测数据和IRI-2012模型提供的预测数据,对比分析了2013年广州地区f_0F2的变化特征.结果表明,IRI-2012模型能够较好预测该地区f_0F_2的变化趋势,并且CCIR参数得到的预测值比URSI参数更接近实测值;预测值与实测值存在系统偏差,在11:00 LT-06:00 LT时段,观测值均比预测值大,其他时段则相反.在日落后至午夜前时段,预测值与实测值有较大差距.绝对偏差的极值点通常出现在20:00 LT左右,最大超过4 MHz.相对偏差变化比较明显的时段是午夜后至凌晨;在02:00 LT或04:00 LT及06:00 LT附近,可能会出现双误差峰值点,最大超过0.4;但在σ变化很大的20:00 LT附近,相对偏差却变化不大.夜间增强现象会使得偏差增大,导致预测值不能很好反映实测f_0F2的变化.  相似文献   

3.
提出了一种基于最小二乘的赤道异常区GPS-TEC与系统硬件偏差的反演方法.利用设置在福州、厦门、广州和南宁4个台站的观测数据,可以得到GPS卫星和接收机的硬件偏差以及(20°~28°N,105°~123°E)区域中48个3°×1°网格的TEC(时间分辨率为15 min).应用于2006年观测数据,得到了较稳定的系统硬件偏差,其中卫星硬件偏差值与欧洲定轨中心公布的结果接近,得到的TEC具有合理的日变化和季节变化特征.该反演方法可以应用于赤道异常区电离层的研究.   相似文献   

4.
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   

5.
提出了一种基于无线测定卫星业务(RDSS)系统观测数据提取电离层TEC参数的方法,利用此方法计算分析了2006年5月地面中心地区电离层垂向TEC的日变化趋势.研究结果表明,利用RDSS系统观测数据提取的电离层垂向TEC,在北京时间每日凌晨0400时左右达到最小值,在午后1400时左右达到最大值,符合电离层TEC参数受太阳活动影响较大的物理规律.结果说明研究方法是可行且有效的,文章还对可能存在的误差进行了探讨.   相似文献   

6.
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   

7.
利用人工神经网络提前1h预报电离层TEC   总被引:1,自引:1,他引:0  
提出了一种利用人工神经网络提前1h预报电离层TEC的简便方法. 考虑到实际工程应用要求, 没有使用其他空间天气参数, 而是选择电离层TEC观测数据本身作为输入参数. 输入参数为当前时刻TEC、一阶差分、相对差分和时间, 输出参数为预报时刻TEC. 利用文中介绍的GPS/TEC处理方法解算厦门站2004年电离层TEC观测数据, 对预报方法进行评估, 全年平均相对误差为9.3744%, 预报结果与观测值相关性达到了0.96678. 结果表明, 利用人工神经网络方法提前1h预报电离层TEC有很好的应用前景.   相似文献   

8.
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F10.7、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。   相似文献   

9.
电离层峰值高度HmF2是描述电离层形态的重要参数之一,国际参考电离层模型IRI-2016中融入了大量电离层测高仪和无线电掩星探测数据,用以提升HmF2的预测精度.本文利用太阳活动低年(2007-2010年)气象、电离层和气候卫星联合观测系统COSMIC探测数据描述全球范围内COSMIC HmF2的三维形态变化,对比分析...  相似文献   

10.
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...  相似文献   

11.
This work presents an analysis of the Total Electron Content (TEC) derived from the International GNSS Service (IGS) receivers at Malindi (mal2: 2.9oS, 40.1oE, dip −26.813o), Kasarani (rcmn: 36.89oE, 1.2oS, dip −23.970o), Eldoret (moiu: 35.3oE, 0.3oN, dip −21.037o) and GPS-SCINDA (36.8oE, 1.3oS, dip −24.117o) receiver located in Nairobi for the period 2009–2011. The diurnal, monthly and seasonal variations of the GPS derived TEC (GPS-TEC) and effects of space weather on TEC are compared with TEC from the 2007 International Reference Ionosphere model (IRI-TEC) using the NeQuick option for the topside electron density. The diurnal peaks in GPS-TEC is maximum during equinoctial months (March, April, October) and in December and minimum in June solstice months (May, June, July). The variability in GPS-TEC is minimal in all seasons between 0:00 and 04:00 UT and maximum near noon between 10:00 and 14:00 UT. Significant variability in TEC at post sunset hours after 16:00 UT (19:00 LT) has been noted in all the seasons except in June solstice. The TEC variability of the post sunset hours is associated with the occurrence of the ionization anomaly crest which enhances nighttime TEC over this region. A comparison between the GPS-TEC and IRI-TEC indicates that both the model and observation depicts a similar trend in the monthly and seasonal variations. However seasonal averages show that IRI-TEC values are higher than the GPS-TEC. The IRI-TEC also depicts a double peak in diurnal values unlike the GPS-TEC. This overestimation which is primarily during daytime hours could be due to the model overestimation of the equatorial anomaly effect on levels of ionospheric ionization over the low latitude regions. The IRI-TEC also does not show any response to geomagnetic activity, despite the STORM option being selected in the model; the IRI model generally remains smooth and underestimates TEC during a storm. The GPS-TEC variability indicated by standard deviation seasonal averages has been presented as a basis for extending the IRI-model to accommodate TEC-variability.  相似文献   

12.
The Total Electron Content (TEC) from four locations in the Indian sector namely, Trivandrum (8.47°N, 76.91°E, Geomag.0.63°S, 0.3° dip), Waltair (17.7° N, 83.3°E, Geomag. 6.4°N, 20° dip), Bhopal (23.28°N, 77.34°E, Geomag.14.26°N, 33.2° dip), and Delhi (28.58°N, 77.21°E, Geomag.19.2°N, 43.4° dip) during a low sunspot year of 2004 are used to study the variabilities of the TEC. The day time TEC values are higher over Waltair and Bhopal compared to those at Trivandrum and Delhi. Considerable day-to-day variations in the diurnal values of TEC are observed at the anomaly crest locations. The observed GPS-TEC has been compared with the IRI-2007 model derived TEC considering three different options (IRI-2001, IRI-2001 corrected and Ne-Quick) available in the model for the topside electron density. The TEC derived with Ne-Quick and IRI-01 corrected options show better agreement with GPS-TEC while the TEC from IRI-01 method shows larger deviations. From the correlation analysis carried out between TEC value at 1300 h LT and solar indices parameters namely sunspot number (SSN), F10.7 and EUV, it is observed that the correlation is more during equinoctial months and less during summer months. The correlation coefficients observed over the anomaly locations, Bhopal and Delhi are lower compared to those at Trivandrum and Waltair.  相似文献   

13.
We have compared the TEC obtained from the IRI-2012 model with the GPS derived TEC data recorded within southern crest of the EIA in the Eastern Africa region using the monthly means of the 5 international quiet days for equinoxes and solstices months for the period of 2012 – 2013. GPS-derived TEC data have been obtained from the Africa array and IGS network of ground based dual-frequency GPS receivers from four stations (Kigali (1.95°S, 30.09°E; Geom. Lat. 11.63°S), Malindi (2.99°S, 40.19°E; Geom. Lat. 12.42°S), Mbarara (0.60°S, 30.74°E; Geom. Lat. 10.22°S) and Nairobi (1.22°S, 36.89°E; Geom. Lat. 10.69°S)) located within the EIA crest in this region. All the three options for topside Ne of IRI-2012 model and ABT-2009 for bottomside thickness have been used to compute the IRI TEC. Also URSI coefficients were considered in this study. These results are compared with the TEC estimated from GPS measurements. Correlation Coefficients between the two sets of data, the Root-Mean Square Errors (RMSE) of the IRI-TEC from the GPS-TEC, and the percentage RMSE of the IRI-TEC from the GPS-TEC have been computed. Our general results show that IRI-2012 model with all three options overestimates the GPS-TEC for all seasons and at all stations, and IRI-2001 overestimates GPS-TEC more compared with other options. IRI-Neq and IRI-01-corr are closely matching in most of the time. The observation also shows that, GPS TEC are underestimated by TEC from IRI model during noon hours, especially during equinoctial months. Further, GPS-TEC values and IRI-TEC values using all the three topside Ne options show very good correlation (above 0.8). On the other hand, the TEC using IRI-Neq and IRI-01- corr had smaller deviations from the GPS-TEC compared to the IRI-2001.  相似文献   

14.
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   

15.
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.  相似文献   

16.
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.  相似文献   

17.
太阳活动低年低纬地区VTEC 变化特性分析   总被引:2,自引:0,他引:2  
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; F10.7与VTEC的相关性随着每天Kp指数总值Σkp的增大而减小.   相似文献   

18.
This paper investigated the performance of the latest International Reference Ionosphere model (IRI-2016) over that of IRI-2012 in predicting total electron content (TEC) at three different stations in the Indian region. The data used were Global Positioning System (GPS) data collected during the ascending phase of solar cycle 24 over three low-latitude stations in India namely; Bangalore (13.02°N Geographic latitude, 77.57°E Geographic longitude), Hyderabad (17.25°N Geographic latitude, 78.30°E Geographic longitude) and Surat (21.16°N Geographic latitude, 72.78°E Geographic longitude). Monthly, the seasonal and annual variability of GPS-TEC have been compared with those derived from International Reference Ionosphere IRI-2016 and IRI-2012 with two different options of topside electron density: NeQuick and IRI01-corr. It is observed that both versions of IRI (i.e., IRI-2012 and IRI-2016) predict the GPS-TEC with some deviations, the latest version of IRI (IRI-2016) predicted the TEC similar to those predicted by IRI-2012 for all the seasons at all stations except for morning hours (0500 LT to 1000?LT). This shows that the effect of the updated version is seen only during morning hours and also that there is no change in TEC values by IRI-2016 from those predicted by IRI-2012 for the rest of the time of the day in the Indian low latitude region. The semiannual variations in the daytime maximum values of TEC are clearly observed from both GPS and model-derived TEC values with two peaks around March-April and September-October months of each year. Further, the Correlation of TEC derived by IRI-2016 and IRI-2012 with EUV and F10.7 shows similar results. This shows that the solar input to the IRI-2016 is similar to IRI 2012. There is no significant difference observed in TEC, bottom-side thickness (B0) and shape (B1) parameter predictions by both the versions of the IRI model. However, a clear improvement is visible in hmF2 and NmF2 predictions by IRI-2016 to that by IRI-2012. The SHU-2015 option of the IRI-2016 gives a better prediction of NmF2 for all the months at low latitude station Ahmedabad compare to AMTB 2013.  相似文献   

19.
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.  相似文献   

20.
The temporal and seasonal variations of Total Electron Content (TEC) are studied at Agra (Geographic Lat. 27.17°N, Long. 78.89°E, Dip: 41.4°), India, which is in the equatorial anomaly region, for a period of 12 months from 01 January to 31 December, 2007 using a Global Positioning System (GPS) receiver. The mean TEC values show a minimum at 0500 h LT (LT = UT + 5.5 h) and a peak value at about 1400 h LT. The lowest TEC values are observed in winter whereas largest values are observed in equinox and summer. Anomalous variations are found during the period of magnetic disturbances. These results are compared with the TEC derived from IRI-2007 using three different options of topside electron density, NeQuick, IRI01-corr, and IRI-2001. A good agreement is found between the TEC obtained at Agra and those derived from IRI models.  相似文献   

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