利用神经网络预报电离层f0F2

由中国武汉电离层台站和澳大利亚Hobart台站的电离层F2层临界频率(f0F2)的资料,利用三层前向反馈神经网络(BP网络),提出一种提前24h预测f0F2的方法,该方法以前5天观测的f0F2数据拟合的5个系数以及太阳活动参数作为输入,以当天24 h的f0F2作为输出对网络进行训练,训练好的网络可以实现对f0F2提前24 h的预报.预测结果显示,利用神经网络预测的f0F2与实际观测结果变化趋势较一致,并且比IRI的计算结果更加准确.误差分析表明,在南半球Hobart(-42.9°,147.3°)台站比中国武汉站(30.4°,114.3°)的结果要好,在低年比高年要好,在冬夏季节比春秋季节稍好.本文说明利用神经网络对电离层参量进行预报是一种切实可行的方法.     

地磁场与电离层异常现象及其与地震的关系

利用中国地磁台网与电离层台站资料,总结了大地震前出现的地磁低点位移、地磁日变异常及电离层f0F2(F2层临界频率)异常现象.对比研究了1997年11月8日玛尼7.5级与2001年11月14日昆仑山口西8.1级地震前磁场与电离层异常分布及特征.结果显示,两次巨大地震前磁场与电离层短临异常时空分布特征有较好的一致性,震中周围出现日变异常、拉萨台出现电离层f0F2明显异常;震前约1个月出现地磁低点位移,其突变分界线通过震中地区.      

电离层暴时经验模型STORM在中国区域的适应性研究

利用中国区域内9个垂测站1976---1987年一个太阳活动周期的电离层暴时f0F2数据, 统计分析了电离层暴事件的等级, 以及不同等级的电离层暴随季节和地磁纬度的分布特征. 研究发现, 中小型电离层暴在春秋季发生的概率较大, 不同季节的发生次数与地磁纬度具有明显的关系. 利用STORM模型对电离层暴时f0F2和大型及特大型电离层暴时f0F2的预测值与月中值进行了比较. 结果表明, 除了冬季误差增大外, 发生电离层暴时STORM模型能够有效地改善月中值模型. 增加中国的暴时数据, 并提高对冬季的暴时参数f0F2的预测是改善STORM模型的重要因素. 建立合适的暴时指数来预测f0F2是未来研究的重点.      

夜间135.6 nm气辉反演的电离层f0F2与测高仪观测比较研究

在夜间电离层，气辉135.6 nm谱线主要由F层的O⁺和电子的辐射复合过程以及O⁺和O^–的中性复合过程激发，该谱线强度和电离层峰值电子密度Nm F₂存在很强的相关性。利用夜气辉135.6 nm辐射强度与F₂层峰值电子密度Nm F₂的平方成正比的物理模型，建立了在不同经纬度、地方时、季节和太阳活动下均适用的反演算法。通过DMSP卫星上搭载的紫外光谱成像仪(SSUSI)实际观测的135.6 nm气辉辐射强度来反演相应时空的电离层F₂层临界频率f₀F₂，并将其与地基测高仪探测结果做了综合对比。结果表明，在太阳活动高年(2013年)，相对误差小于等于20%的数据占比93.0%，平均相对误差约为7.08%；在太阳活动低年(2017年)，相对误差小于等于20%的数据占比80.8%，平均相对误差约为12.64%。最后，对该算法在太阳活动高低年的反演精度差异进行了分析。     

利用F_(10.7)短期预报电离层F_0F_2

通过对电离层历史数据和太阳射电流量F10.7的回归分析,提出了一种单站电离层f0F2的短期预报方法,以F10.7的流动平均值fc为输入,以未米3天的f0F2为输出,分别利用中国地区8个台站的数据进行检验,分析不同太阳活动水平、季节以及地方时预报误差的分布特征.结果表明,该方法能有效地预测未来1～3天的f0F2.该方法还可应用于其他电离层参量的短期预报.     

中性风和垂直漂移对低纬F区电离层影响初析

利用二维低纬电离层－等离子体层时变理论模式,模拟太阳活动高年春分条件下垂直漂移和中性风强度改变对低纬F区电离层参量的影响.模式在所考察的磁子午面内求解等离子体输运方程,给出离子浓度和速度随纬度、高度、地方时的变化.模式计算结果显示,调整垂直漂移和中性风强度对低纬F区电离层电子浓度的影响与电离层所处磁纬、垂直漂移和中性风作用时段等有关,呈现出一些新特点.结果对分析不同条件下垂直漂移和中性风对低纬F区电离层影响具有一定的指导意义.      

电离层数字测高仪被动接收观测模式研究

利用CADI(Canadian Advanced Digital Ionosonde)电离层数字测高仪平台,实现了新的电离层数字测高仪被动接收观测模式.利用新开发的观测模式,在观测台站开展了一系列实验观测研究,经过信号处理和信息提取,获得了电离层特征参量f0F2回归方程,高频信道背景噪声分布,电离层D层对电波的吸收等电离层探测信息.实验观测结果表明,所获取的f0F2与主动探测结果相关性在0.84以上,高频信道背景噪声分布以及电离层D层吸收状况与电离层实际分析结果相吻合.     

武汉地区电离层TEC和NmF2及板厚的季节变化

通过利用武汉电离层观测站(114.4°E,30.6°N)1980-1990年对E8T-Ⅱ卫星信标的法拉第旋转测量的TEC(电子浓度总含量)数据,以及由测高仪测量的1980-1990年间的f0F2(F2层临界频率)数据,研究了武汉地区TEC,NmF2(最大电子浓度)和板厚的季节变化,同时比较了IRI和武汉单站模式在预测NmF2季节性方面的有效性.武汉单站模式在预测NmF2季节性变化方面优于IRI模式.      

我国电离层基本参量与国际参考模式的比较

本文利用我国满洲里、北京、武昌、重庆和广州等台站电离层观测记录,对各层临界频率的实测值(月中值)与IRI-86的计算值进行了分析比较.|发现两者存在着显著而系统的偏离.E层和F₁层偏离较小F₂层偏离较大,其相对值有时超过60%.总的来说,f₀F₂的相对偏离:夜间大,白天小冬季大,夏季小太阳活动低年大,高年小随着纬度降低偏离增大模式值普遍大于实测值.      

地磁扰动期间日本Kokubunji站电离层的扰动特征分析

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.      

电离层f_0F_2参数提前24小时预测

利用中国9个垂测站(海口、广州、重庆、拉萨、兰州、北京、乌鲁木齐、长春、满洲里)一个太阳周(1976-1986年)的数据资料,采用三层前向反馈神经网络(BP网络)实现了电离层F2层临界频率(f0F2)参数提前24h预测.通过对f0F2参数的时间序列及其与日地活动之间进行相关分析,确定f(t)(当前时刻f0F2)、经过变换的F10.7指数等5个参数作为神经网络的输入参数,并通过同时段训练法获得不同时刻的预测值,本文与自相关分析法进行了预测性能比较.结果表明,上述方法构建的神经网络可以达到较高的预测精度.针对暴时数据,对神经网络算法进行了改进,提高了神经网络法对暴时数据的适用性.     

基于相空间重构的f_0F_2一步预测算法研究

利用低纬度地区某垂测站2005年3月和4月两个月,f0F2参数共5856个数据样奉,对提前15min的一步预测算法进行了研究.基于混沌时间序列的相空间重构方法,以相近邻点轨迹具有相似性为预测理论基础,采用k最近邻点的方法对下一时刻的,f0F2进行预测.对邻点个数的选取采用了训练法和自适应选择法,对选出的邻点采用平均法和自回归两种方法进行处理,并对几种不同方法的预测结果进行了比较.结果证明,基于相空间重构的一步预测算法预测精度较高,并且容易实现,运算速度高,适用于电离层参数准实时预报.     

利用神经网络预报中国地区电离层f0F2

利用神经网络技术并考虑太阳和地磁活动对电离层的影响,提出了一种提前5 h预报中国地区电离层临界频率f0F2的方法.网络输入包括时间、季节、地理纬度、太阳天顶角、最近一天的12个观测值(F-23,F-22,F-21,F-20,F-19,F-18,F-5,F-4,F-3,F-2,F-1,F0)和前30天滑动平均值(A-24,A-23,A-22,A-4,A-3A-2,A-1,A0),网络输出分别为未来5 h的f0F2值F+1,F+2,F+3,F+4,F+5.选取乌鲁木齐、长春、重庆和广州站1958-1968年间的数据训练网络,利用中国9个电离层站的历史数据检验网络,根据均方根误差衡量网络性能的好坏.结果表明,神经网络的预报结果能较好地符合实测数据.这说明利用神经网络实现中国地区电离层f0F2的时空预报是可行的.     

NeQuick 2 and IRI Plas VTEC predictions for low latitude and South American sector

Using vertical total electron content (VTEC) measurements obtained from GPS satellite signals the capability of the NeQuick 2 and IRI Plas models to predict VTEC over the low latitude and South American sector is analyzed. In the present work both models were used to calculate VTEC up to the height of GPS satellites. Also, comparisons between the performance of IRI Plas and IRI 2007 have been done. The data correspond to June solstice and September equinox 1999 (high solar activity) and they were obtained at nine stations. The considered latitude range extends from 18.4°N to ?64.7°N and the longitude ranges from 281.3°E to 295.9°E in the South American sector. The greatest discrepancies among model predictions and the measured VTEC are obtained at low latitudes stations placed in the equatorial anomaly region. Underestimations as strong as 40?TECU [1?TECU?=?10¹⁶?m^?2] can be observed at BOGT station for September equinox, when NeQuick2 model is used. The obtained results also show that: (a) for June solstice, in general the performance of IRI Plas for low latitude stations is better than that of NeQuick2 and, vice versa, for highest latitudes the performance of NeQuick2 is better than that of IRI Plas. For the stations TUCU and SANT both models have good performance; (b) for September equinox the performances of the models do not follow a clearly defined pattern as in the other season. However, it can be seen that for the region placed between the Northern peak and the valley of the equatorial anomaly, in general, the performance of IRI Plas is better than that of NeQuick2 for hours of maximum ionization. From TUCU to the South, the best TEC predictions are given by NeQuick2.The source of the observed deviations of the models has been explored in terms of CCIR foF2 determination in the available ionosonde stations in the region. Discrepancies can be also related to an unrealistic shape of the vertical electron density profile and or an erroneous prediction of the plasmaspheric contribution to the vertical total electron content. Moreover, the results of this study could be suggesting that in the case of NeQuick, the underestimation trend could be due to the lack of a proper plasmaspheric model in its topside representation. In contrast, the plasmaspheric model included in IRI, leads to clear overestimations of GPS derived TEC.     

Correction of B2bot for NeQuick during low solar activity at Hainan station

This work is a continuation of the previous article and it focuses on low solar activity and modeling effort. NeQuick model uses Epstein layer formalism to model each part of the profile. We study the diurnal and seasonal variations of B2_bot, ΔB2 (B2_best − B2_NeQuick2) and R (B2_best/B2_{NeQuick 2}) at Hainan station during low solar activity. The results show it is possible to improve the B2_bot parameter of the NeQuick model at that region during low solar activity. Then, we use a function ?(t) with LT in different seasons to correct the B2_bot formula of NeQuick 2. The correction shows that (1) By the correction formula, the B2_bot of NeQuick is improved. The maximum standard deviation is improved for 9 km. (2) The correction formula is more effective in summer than in equinox and winter and performs better during early morning hours than during the rest of the day.     

Comparing TOPEX TEC measurements with IRI predictions

TEC values obtained from TOPEX satellite were compared with the International Reference Ionosphere (IRI) 2001 model estimates. The present work also shows results of the IRI model with the option of a new topside electron density distribution (NeQuick model). TOPEX TEC measurements, which include years of high and middle to low solar activity (2000 and 2004), were analyzed by binning the region covered by the satellite (±66°) every five degrees of modip. In general, there is good agreement between IRI predictions and Topex measurements. Cases with large disagreements are observed at low and high latitudes during high solar activity. Comparing the model predictions using the default IRI2001 model and the NeQuick topside option show that the default IRI 2001 version represents the observed data in a more realistic way, but appears to be less reliable at high and low latitudes in some cases.     

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.