Total Electron Content Diurnal and Seasonal Variations and Response to Solar Events at Koudougou Station in Burkina Faso

In this paper, we studied the seasonal behavior of the total electron content (TEC) during a part of solar cycle 24 ascending, maximum and decreasing phases at Koudougou station (Latitude: 12°15'09"N Longitude: 2°21'45"W). Response of TEC to solar recurrent events is presented. The highest values of the TEC in 2014, 2015 and 2016 were recorded on March and October, while in 2013 they were recorded on April and November, corresponding to equinox months. This observation shows that TEC values at the equinoxes are higher than those of solstices. Moreover, the monthly TEC varies in phase with the sunspots number showing a linear dependence of the TEC on solar activity. The ionospheric electron contents are generally very low both before noon and during the night, but quite high at noon and after noon. This pattern of TEC variation is due to the fluctuation of incident solar radiation on the Earth’s equatorial ionosphere. During quiet periods, the number of free electrons generated is lower than that generated during recurrent periods, which shows a positive contribution of recurrent activity to the level of the TEC. Investigations have also highlighted a winter anomaly and equinoctial asymmetry in TEC behavior at Koudougou station.

Total Electron Content during Recurrent and Quiet Geomagnetic Periods at the Koudougou Station in Burkina Faso

In this work, the comparative study of total electron content (TEC) between recurrent and quiet geomagnetic periods of solar cycle 24 at Koudougou station with geographical coordinates 12°15'N;- 2°20'E was addressed. This study aims to analyze how geomagnetic variations influence the behavior of TEC in this specific region. The geomagnetic indices Kp and Dst were used to select quiet and recurrent days. Statistical analysis was used to interpret the graphs. The results show that the mean diurnal TEC has a minimum before dawn (around 0500 UT) and reaches a maximum value around 1400 UT, progressively decreasing after sunset. In comparison, the average diurnal TEC on recurrent days is slightly higher than on quiet days, with an average difference of 7 TECU. This difference increases with the level of geomagnetic disturbance, reaching 21 TECU during a moderate storm. The study also reveals significant monthly variations, with March and October showing the highest TEC values for quiet and recurrent days, respectively. Equinox months show the highest mean values, while solstice months show the lowest. Signatures of semi-annual, winter and equatorial ionization anomalies were observed. When analyzing annual variations, it was found that the TEC variation depends significantly on F10.7 solar flux, explaining up to 98% during recurrent geomagnetic activity and 92% during quiet geomagnetic activity.

Ionospheric vertical total electron content prediction model in low-latitude regions based on long short-term memory neural network

Ionosphere delay is one of the main sources of noise affecting global navigation satellite systems, operation of radio detection and ranging systems and very-long-baseline-interferometry. One of the most important and common methods to reduce this phase delay is to establish accurate nowcasting and forecasting ionospheric total electron content models. For forecasting models, compared to mid-to-high latitudes, at low latitudes, an active ionosphere leads to extreme differences between long-term prediction models and the actual state of the ionosphere. To solve the problem of low accuracy for long-term prediction models at low latitudes, this article provides a low-latitude, long-term ionospheric prediction model based on a multi-input-multi-output, long-short-term memory neural network. To verify the feasibility of the model, we first made predictions of the vertical total electron content data 24 and 48 hours in advance for each day of July 2020 and then compared both the predictions corresponding to a given day, for all days. Furthermore, in the model modification part, we selected historical data from June 2020 for the validation set, determined a large offset from the results that were predicted to be active, and used the ratio of the mean absolute error of the detected results to that of the predicted results as a correction coefficient to modify our multi-input-multi-output long short-term memory model. The average root mean square error of the 24-hour-advance predictions of our modified model was 4.4 TECU, which was lower and better than5.1 TECU of the multi-input-multi-output, long short-term memory model and 5.9 TECU of the IRI-2016 model.

Ionospheric total electron content disturbance associated with May 12, 2008,Wenchuan earthquake

Possible ionospheric disturbances relating to the May 12, 2008, Ms8.0 Wenchuan earthquake were identified by Global Positioning System(GPS)-derived total electron content(TEC), ionosonde observations, the global ionospheric map(GIM), and electron density profiles detected by the Constellation Observation System for Meteorology Ionosphere and Climate(COSMIC).We applied a statistical test to detect anomalous TEC signals and found that a unique enhancement in TEC, recorded at 16 GPS stations, appeared on May 9, 2008. The critical frequency at F2 peak(f0F2), observed by the Chinese ionosondes, and maximal plasma frequency,derived from COSMIC data, revealed a characteristic similar to GPS TEC variations. The GIM showed that the anomalous variations of May 9 were located southeast of the epicenter. Using GPS data from 13 stations near the epicenter, we analyzed the TEC variations of satellite orbit traces during 04:00e11:00 UT. We found that TEC decreased to the east and increased to the southeast of the epicenter during this period. Results showed that the abnormal disturbance on May 9 was probably an ionospheric precursor of the Wenchuan earthquake of May 12, 2008.

Manifestations of the earthquake preparations in the ionosphere total electron content variations

Recent ionospheric observations report anomalous total electron content (TEC) deviations prior strong earthquakes. We discuss common fetures of the pre-earthquake TEC disturbances on the basis of statistics covering 50 strong seismic events during 2005-2006. The F2-layer ionospheric plasma drift under action of the electric fields of seismic origin is proposed as the main reason of producing TEC anomalies. The origin of such electric fields is discussed in terms of the lithosphere-atmosphere-ionosphere coupling system. This theory is supported by numerical simulations using global Upper Atmosphere Model (UAM). UAM calculations show that the vertical electric current with the density of about 20 - 40 nA/m2 flowing between the Earth and ionosphere over an area of about 200 by 2000 km is required to produce the TEC disturbances with the amplitude of about 30% - 50% relatively to the non-disturbed conditions. Ionosphere responses on the variations of the latitudinal position, direction and configuration of the vertical electric currents have been investigated. We show that not only the vertical component of the ionospheric plasma drift but also horizontal components play an important role in producing pre-earthquake TEC disturbances.

Questions on Optimization of Measurement of Total Electron Content in Ionosphere with GPS

The analysis of existing method for calculation of total content of electrons (TEC) in ionosphere using GPS occultation method does show that due to different values of signal/noise ration in GPS signals ?and , the new method of optimum measurements of relevant frequency components of TEC measured by phase and code methods should be developed. The optimum quantity of measurements of the above-mentioned frequency components is determined taking into account the limitation imposed on general number of necessary measurements.

Near real-time modeling of global ionospheric vertical total electron content using hourly IGS data

The International GNSS Service(IGS) has been providing reliable Global Ionospheric Maps(GIMs) since 1998. The Ionosphere Associate Analysis Centers(IAACs) model the global ionospheric Total Electron Content(TEC) and generate the daily GIM products within the context of the IGS. However, the rapid and final daily GIM products have a latency of at least one day and one week or so, respectively. This limits the value of GIM products in real-time GNSS applications.We propose and develop an approach for near real-time modeling of global ionospheric TEC by using the hourly IGS data. We perform an experiment in a real operating environment to generate near real-time GIM(named BUHG) products for more than two years. Final daily GIM products,Precise Point Positioning(PPP) based VTEC resources, and JASON-3 Vertical TEC(VTEC) measurements are collected for testing the performance of BUHG. The results show that the performance of BUHG is very close to that of the daily GIM products. Also, there is good agreement between BUHG and PPP-derived VTEC as well as with JASON-3 VTEC. It is possible that BUHG would be further improved with an increase in available hourly GNSS data.

Modeling the global ionospheric total electron content with empirical orthogonal function analysis

In the present work we model the global ionospheric total electron content (TEC) with the analysis of empirical orthogonal functions (EOF). The obtained statistical eigen modes, which makeup the modeled TEC, consist of two factors: the eigen vectors mapping TEC patterns at latitude and longitude (or local time LT), and the corresponding coefficients displaying the TEC variations in different time scales, i.e., the solar cycle, the yearly (annual and semiannual) and the diurnal universal time variations. It is found that the EOF analysis can separate the TEC variations into chief processes and the first two modes illustrate the most of the ionospheric climate properties. The first mode contains both the semiannual component which shows the semiannual ionospheric anomaly and the annual component which shows the annual or non-seasonal ionospheric anomaly. The second mode contains mainly the annual component and shows the normal seasonal ionospheric variation at most latitudes and local time sectors. The annual component in the second mode also manifests seasonal anomaly of the ionosphere at higher mid-latitudes around noontime. It is concluded that the EOF analysis, as a statistical eigen mode method, is resultful in analyzing the ionospheric climatology hence can be used to construct the empirical model for the ionospheric climatology.

Taiwan’ Chi-Chi Earthquake Precursor Detection Using Nonlinear Principal Component Analysis to Multi-Channel Total Electron Content Records

This research uses eigenvalue characteristics of nonlinear principal component analysis (NLPCA) and principal component analysis (PCA) to investigate total electron content (TEC) anomalies associated with Taiwan's Chi-Chi earthquake of 21 September 1999 (LT) (Mw=7.6).The transforms are used for ionospheric TEC from 01 August to 20 September 1999 (local time) using data from 13 GPS receivers.The data were collected at 22°N-26°N Lat.and 120°E-122°E Long..Applying the NLPCA to the multi-channel total electron content records of GPS receivers,the earthquake-associated TEC anomalies were represented by large principal eigenvalues of NLPCA (>0.5 in a normalized set) on 14 August and 17,18,and 20 September,with allowance given for the Dst index,which was quiet for the study period.Comparisons were then made with other researchers who also found TEC anomalies on September 17,18,and 19 associated with the Chi-Chi earthquake,which cannot be detected by PCA.Consideration is also given for reported ground level geomagnetic field activity that occurred between mid-August and late October,leading up to and including the Chi-Chi and Chia-Yi earthquakes,which are associated with the same series of faults.It is possible that Aug.14 is representative of an earthquake-associated TEC anomaly.This is an interesting result given how much earlier than the earthquake it occurred.

Analysis of Anomalous Enhancement in TEC and Electron Density in the China Region Prior to the 17 March 2015 Geomagnetic Storm Based on Ground and Space Observations

Total Electron Content(TEC)and electron density enhancement were observed on the day before 17 March 2015 great storm in the China Region.Observations from ground-and space-based instruments are used to investigate the temporal and spatial evolution of the pre-storm enhancement.TEC enhancement was observed from 24°N to 30°N after 10:00 UT at 105°E,110°E and 115°E longitudes on March 16.The maximum magnitude of TEC enhancement was more than 10 TECU and the maximal relative TEC enhancement exceeded 30%.Compared with geomagnetic quiet days,the electron density of Equatorial Ionization Anomaly(EIA)northern peak from Swarm A/C satellites on March 16 was larger and at higher latitudes.NmF2 enhanced during 11:30—21:00 UT at Shaoyang Station and increased by 200%at~16:00 UT.However,TEC and electron density enhancement were not accompanied by a significant change of hmF2.Most research has excluded some potential mechanisms as the main driving factors for storm-time density enhancements by establishing observational constraints.In this paper,we observed pre-storm enhancement in electron density at different altitudes and Equatorial Electrojet(EEJ)strength results derived from ground magnetometers observations suggest an enhanced eastward electric field from the E region probably played a significant role in this event.

Assessment of International GNSS Service Global Ionosphere Map products over China region based on measurements from the Crustal Movement Observation Network of China

The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.

基于注意力机制LSTM的电离层TEC预测

电离层总电子含量(Total Electron Content,TEC)的监测与预报是空间环境研究的重要内容,对卫星通讯和导航定位等有重要意义.TEC值影响因素较多,很难确定精确物理模型来对其进行预测.本文设计了基于注意力机制的LSTM模型(Att-LSTM),采用过去24小时TEC观测数据对未来TEC进行预测.选择北半球东经100°上,每2.5°纬度选择一个位置,共计36个位置来验证本文提出模型的性能,并与主流的深度学习模型如DNN、RNN、LSTM进行对比实验.取得了如下成果:(1)在选定的36个地区未来2小时单点预测上,基于本文的Att-LSTM模型的TEC预测性能明显优于其他对比模型;(2)讨论了纬度对Att-LSTM预测未来2小时TEC值时性能的影响,发现在北纬0°到60°之间,Att-LSTM预测性能随着纬度的升高而略有降低,在北纬62.5°~87.5°之间,模型预测性能出现扰动,预测效果略差;(3)讨论了磁暴期和磁静期模型的预测性能,发现无论是磁暴期还是磁静期,本文模型预测性能均较好;(4)还讨论了对未来多时点预测效果,实验结果表明,本文所提出的模型对未来2、4个小时的预测拟合度R-Square均超过0.95,预测结果比较可靠,对未来6、8、10个小时预测拟合度最高为0.7934,预测拟合度R-Square下降迅速,预测结果不可靠.

2020年7月22日阿拉斯加7.8级地震同震电离层扰动分析

利用全球导航卫星系统(GNSS)、电离层测高仪和地震仪数据,从振幅及波形、时空分布、传播速度与方向、时频域等角度对2020年阿拉斯加7.8级地震同震电离层扰动(Co-seismic ionospheric disturbances,CIDs)特性进行探究.卫星G03、G04和G09在地震西部探测到3类CIDs,最大扰动幅度约0.1 TECU (1 TECU=10^(16) el/m~2),并且均沿着地震断层破裂延伸方向(西南方向)传播;而在地震北部与东部未发现CIDs.根据CIDs的速度及中心频率将其分为三类,第一类为高速传播的CIDs(速度约为2.93 km·s^(-1)),中心频率约11 mHz,符合瑞利波激发的电离层扰动特征;第二类CIDs的传播速度约为1.69 km·s^(-1)和1.55 km·s^(-1),中心频率约4.5 mHz和4.7 mHz,符合声波引起的电离层扰动频率;第三类CIDs速度约为0.98 km·s^(-1)和1.11 km·s^(-1),中心频率约2.9 mHz,可能为声波引起的另一类电离层扰动.同时,利用CIDs时空数据估计的CIDs扰动源位置与震中较为接近,进一步说明电离层扰动由地震激发.通过对GNSS站及地震仪位移的分析,估计了地震瑞利波沿西南方向传播速度与第一类CIDs较为吻合,验证了第一类CIDs由瑞利波激发,且断层的垂直位移是引起电离层扰动的重要因素.测高仪观测到电离层临界频率(f_(0)F_(2))发生显著波动,探测到CIDs的传播速度约1.02 km·s^(-1),传播速度和方向与卫星G03、G04探测的CIDs较为吻合,推断其属于第三类CIDs.

阿拉斯加2021年8.2级地震同震电离层扰动特征及对比分析

为分析2021年7月29日阿拉斯加8.2级地震引起的电离层响应,利用地震附近的全球导航卫星系统(Global Navigation Satellite System,GNSS)观测数据估算电离层总电子含量(Ionospheric Total Electron Content,TEC)及同震电离层扰动(Coseismic Ionospheric Disturbances,CIDs).从多角度对CIDs的时空分布特征进行分析,并与阿拉斯加2018年7.9级走滑型地震以及2020年7.8级逆断层地震引起的CIDs对比.在地震西南方向探测到两类CIDs,最大扰动振幅约0.8 TECU(1 TECU=1016 el/m^(2)),并且在西南方向距离震中约1094 km的测高站EA653探测到CIDs.在震中西北、东北和北方向探测到传播速度相近的CIDs.根据CIDs的速度和频率大小将CIDs分为两类,第一类CIDs的传播速度为1.87 km·s^(-1),频率约为3.8 mHz,可能由地震声波引起,扰动量级最大;第二类CIDs的传播速度为0.85~1.09 km·s^(-1),中心频率约在3.0 mHz或者5.7 mHz附近,为地震声波引起的另一类电离层扰动.逆断层地震引起的CIDs比走滑型地震更加显著,表明地震引起的垂直地表运动在CIDs的形成中起主要作用.三次地震在西南方向均引起显著的CIDs,与地震破裂方向较为一致,该地区大地震引起的CIDs可能具有较为明显的方向性,具体形成机制有待于进一步研究.

基于GPS TEC的2022年1月15日汤加火山喷发激起的电离层行扰分析

2022年1月15日南太平洋汤加海底火山发生剧烈喷发,是近30年来最大规模的火山爆发,产生的强烈大气波动为开展火山喷发电离层扰动研究提供了难得的机会。本文利用GPS数据探测火山附近、新西兰、澳大利亚和中国地区的电离层扰动,从波形、频率、传播速度和时空分布等角度分析汤加火山喷发电离层行扰(TIDs)的特征,并利用电离层测高站、海平面监测站和大气压监测站的观测数据进一步验证TIDs的传播特征。研究结果发现,汤加火山喷发在其附近区域、新西兰、澳大利亚和中国地区引起了3类TIDs。在火山附近东、西、南、北方向上均探测到第一类TIDs, TIDs的传播速度为617~972 m/s,该类TIDs极有可能由火山喷发产生的声波引起。汤加火山喷发仅在火山附近东、西方向引起第二类TIDs,其传播速度分别为472 m/s和418 m/s,可能由声波传播过程中衍生的声重力波或者混合波引起,形成机理有待进一步研究。汤加火山喷发在新西兰、澳大利亚和中国地区引发了第三类TIDs,其传播速度为328~352 m/s,该类TIDs与Lamb波密切相关。

一种多频多系统周跳探测与修复方法

为满足多频多系统精密单点定位(PPP)数据预处理的实际需求,提出了一种周跳探测与修复方法。针对多频多系统PPP数据处理中各卫星的信号数量不同,利用最小二乘模糊度降相关平差(LAMBDA)原理构建模糊度组合。通过仅使用相位观测值估计的倾斜电子总量(STEC)探测不敏感周跳和漏判周跳。对于周跳修复,将伪距和载波相位的观测值在历元间作差求得周跳的浮点解和协方差阵,然后应用LAMBDA算法搜索周跳整数解并进行修复。通过静态、动态以及磁暴环境下周跳探测和修复实验,验证了所提方法的有效性,多频条件下周跳修复的正确率达到100%。

基于滑窗初始点dSTEC定权的全球实时电离层综合

自2017年起,国际GNSS服务组织(IGS)部分电离层分析中心先后提供全球实时电离层校正服务。针对实际应用中单一分析中心实时电离层产品存在的可靠性差问题,本文提出了基于滑窗初始点差分斜向总电子含量(dSTEC)定权的全球实时电离层综合方法。以中国科学院(CAS)、法国空间研究中心(CNES)、西班牙加泰罗尼亚理工大学(UPC)及武汉大学(WHU)实时产品为基础,实现了实时全球电离层地图(RT-GIM)产品的例行综合。从电离层延迟误差修正、单频标准单点定位(SF-SPP)及单频精密单点定位(SF-PPP) 3个方面,分析2022年2月15日至2022年3月15日综合RT-GIM产品的应用性能。以IGS事后GIM为参考,本文综合RT-GIM与UPC综合RT-GIM对应的RMS为分别为3.30和3.20 TECU,二者精度相当;以定位残差95%分位数为统计量,与IGS事后GIM产品相比,综合RT-GIM对应的SF-SPP及SF-PPP精度分别低7.7%和4.9%;与北斗三号广播电离层模型BDGIM相比,综合RT-GIM对应的SF-SPP及SF-PPP精度分别提升了15.9%和9.5%。自2022年起,CAS综合RT-GIM产品已例行提交至IGS。

Remote sensing ionospheric variations due to total solar eclipse, using GNSS observations

For years great interest has been taken in the effects of physical phenomena on ionosphere structure. A total solar eclipse was visible in North America on August 21 st, 2017. This event offered a great opportunity for remote sensing the ionospheric behavior under the eclipse condition. In this study we investigated the effects of total solar eclipse on variations of Total Electron Content(TEC), and consequently deviations on regional models of Vertical TEC(VTEC), as well as variations in ionospheric scintillation occurrence. Although variations of TEC due to total solar eclipse are studied thoroughly by many authors, but the effect of solar eclipse on ionospheric scintillation has never been considered before. Our study is based on measurements from a high-rate GPS network over North America on the day of eclipse, a day before and after its occurrence, on the other hand, GPS measurements from groundbased stations on similar days were used to model TEC on the day of event, and also one day before and after it. The results of this study demonstrate that solar eclipse reduced scintillation occurrence at the totality region up to 28 percent and TEC values showed a decrease of maximum 7 TECU. Considering TEC models, our study showed apparent variations in the regional models, which confirms previous studies on ionospheric responses to eclipse as well as theoretical assumptions.

An artificial neural network model in predicting VTEC over central Anatolia in Turkey

This research investigates the capability of artificial neural networks to predict vertical total electron content(VTEC)over central Anatolia in Turkey.The VTEC dataset was derived from the 19 permanent Global Positioning System(GPS)stations belonging to the Turkish National Permanent GPS NetworkActive(TUSAGA-Aktif)and International Global Navigation Satellite System Service(IGS)networks.The study area is located at 32.6°E-37.5°E and 36.0°N-42.0°N.Considering the factors inducing VTEC variations in the ionosphere,an artificial neural network(NN)with seven input neurons in a multi-layer perceptron model is proposed.The KURU and ANMU GPS stations from the TUSAGA-Aktif network are selected to implement the proposed neural network model.Based on the root mean square error(RMSE)results from 50 simulation tests,the hidden layer in the NN model is designed with 41 neurons since the lowest RMSE is achieved in this attempt.According to the correlation coefficients,absolute and relative errors,the NN VTEC provides better predictions for hourly and quarterly GPS VTEC.In addition,this paper demonstrates that the NN VTEC model shows better performance than the global IRI2016 model.Regarding the spatial contribution of the GPS network to TEC prediction,the KURU station performs better than ANMU station in fitting with the proposed NN model in the station-based comparison.

Ionospheric Responses to a Total Solar Eclipse Deduced by the GPS Beacon Observations

The total electron content (TEC) data during the total eclipse of March 9, 1997 were collected, which were observed by means of nine GPS receivers located at the eastern Asia. The responses of total TEC to the eclipse were analyzed. The results show that: 1) the eclipse led to apparent decrement in TEC that lasted for six to eight hours; 2) the maximum decrement occurred after the middle of the eclipse with time delays varying from twenty minutes to about three hours; 3) the maximum absolute deviations of TEC on the eclipse day do not show a simple and consistent relationship to the maximum solar obscuration.