Longitudinal dependence of the forecast accuracy of the ionospheric total electron content in the equatorial zone

The longitudinal dependence of the behavior of ionospheric parameters has been the subject of a number of works where significant variations are discovered.This also applies to the prediction of the ionospheric total electron content(TEC),which neural network methods have recently been widely used.However,the results are mainly presented for a limited set of meridians.This paper examines the longitudinal dependence of the TEC forecast accuracy in the equatorial zone.In this case,the methods are used that provided the best accuracy on three meridians:European(30°E),Southeastern(110°E)and American(75°W).Results for the stations considered are analyzed as a function of longitude using the Jet Propulsion Laboratory Global Ionosphere Map(JPL GIM)for 2015.These results are for 2 h ahead and 24 h ahead forecast.It was found that in this case,based on the metric values,three groups of architectures can be distinguished.The first group included long short-term memory(LSTM),gated recurrent unit(GRU),and temporal convolutional networks(TCN)models as a part of unidirectional deep learning models;the second group is based on the recurrent models from the first group,which were supplemented with a bidirectional algorithm,increasing the TEC forecasting accuracy by 2-3 times.The third group,which includes the bidirectional TCN architecture(BiTCN),provided the highest accuracy.For this architecture,according to data obtained for 9 equatorial stations,practical independence of the TEC prediction accuracy from longitude was observed under the following metrics(Mean Absolute Error MAE,Root Mean Square Error RMSE,Mean Absolute Percentage Error MAPE):MAE(2 h)is 0.2 TECU approximately;MAE(24 h)is 0.4 TECU approximately;RMSE(2 h)is less than 0.5 TECU except Niue station(RMSE(2 h)is 1 TECU approximately);RMSE(24 h)is in the range of 1.0-1.7 TECU;MAPE(2 h)<1%except Darwin station,MAPE(24 h)<2%.This result was confirmed by data from additional 5 stations that formed latitudinal chains in the equatorial part of the three meridians.The complete correspondence of the observational and predicted TEC values is illustrated using several stations for disturbed conditions on December 19-22,2015,which included the strongest magnetic storm in the second half of the year(min Dst=-155 nT).

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, MsS.0 Wenchuan earthquake were identified by Global Positioning System （GPS）-derived total electron content （TEC）, ion- osonde 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 fre- quency at F2 peak （foF2）, 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 04：00-11：00 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 ionosphenc precursor of the Wenchuan earthquake of May 12, 2008.

Performance of GPS slant total electron content and IRI-Plas-STEC for days with ionospheric disturbance

Total Electron Content （TEC） is an important observable parameter of the ionosphere which forms the main source of error for space based navigation and positioning systems. Since the deployment of Global Navigation Satellite Systems （GNSS）, cost-effective esti- mation of TEC between the earth based receiver and Global Positioning System （GPS） sat- ellites became the major means of investigation of local and regional disturbance for earthquake precursor and augmentation system studies. International Reference Iono- sphere （IRI） extended to plasmasphere （IRI-Plas） is the most developed ionospheric and plasmaspheric climatic model that provides hourly, monthly median of electron density distribution globally. Recently, IONOLAB group {www.ionolab.org） has presented a new online space weather service that can compute slant TEC （STEC） on a desired ray path for a given date and time using IRI-Plas model （IRI-Plas-STEC）. In this study, the performance of the model based STEC is compared with GPS-STEC computed according to the estimation method developed by the IONOLAB group and includes the receiver bias as IONOLAB-BIAS （IONOLAB-STEC）. Using Symmetric Kullback-Leibler Distance （SKLD）, Cross Correlation （CC） coefficient and the metric norm （L2N） to compare IRI-Plas-STEC and IONOLAB-STEC for the month of October 2011 over the Turkish National Permanent GPS Network （TNPGN- Active）, it has been observed that SKLD provides a good indicator of disturbance for both earthquakes and geomagnetic storms.

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.

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） （M_w=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.

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.

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.

Climatological analysis and modeling of the ionospheric global electron content

In this paper, we calculate the ionospheric global electron content (GEC) from the GPS TEC data along the geographic longitude 120°E during the period of 1996-2004, and investigate the relationship be- tween GEC and 10.7 cm solar radio flux F10.7 and its seasonal dependence with partial correlation analysis. Our results show that GEC is closely correlated with solar activity index F10.7 and is also re- lated with annual and semiannual variations. An empirical GEC model driven by those factors is then to examine the influences of different solar activity proxies for the model input. The results suggest that GEC mainly depends on solar activity and the seasonal variations; the latter is also modulated by solar activity. Furthermore, the magnitude of semiannual variation is a little greater than that of annual varia- tion. Our empirical GEC model is proved to be better than the model proposed by Afraimovich et al.

Metal Induced Inhibition of Photosynthesis,Photosynthetic Electron Transport Chain and ATP Content of Anabaena doliolum and Chlorella vulgaris:Interaction with Exogenous ATP

This study demonstrates a concentration dependent inhibition of carbon fixation, O2 evolution, photosynthetic electron transport chain and ATP content of A. doliolum and C. vulgaris by Cu, Ni and Fe. Although the mode of inhibition of photosynthetic electron transport chain of both the algae was similar, PS II depicted greater sensitivity to the test metals used. The toxicity in both organisms was Cu > Ni > Fe. A. doliolum was, however, more sensitive to Cu and Ni, and C. vulgaris to Fe. Toxicity was generally dependent on metal uptake, which in turn was dependent on their concentrations in the external medium. A partial restoration of nutrient uptake, carbon fixation, and enzyme activities following supplementation of exogenous ATP suggests that ATP regulates toxicity through chelation.

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.