Simulation study on slant-to-vertical deviation in two dimensional TEC mapping over the ionosphere equatorial anomaly

With the rapid increase of GPS/GNSS receivers being deployed and operated in China, real-time GPS data from nearly a thousand sites are available at the National Center for Space Weather, China Meteorology Administration. However, it is challenging to generate a high-quality regional total electron content (TEC) map with the traditional two-dimensional (2-D) retrieval scheme because a large horizontal gradient has been reported over east–south Asia due to the northern equatorial ionization anomaly. We developed an Ionosphere Data Assimilation Analysis System (IDAAS), which is described in this study, using an International Reference Ionosphere (IRI) model as the background and applying a Kalman filter for updated observations. The IDAAS can reconstruct a three-dimensional ionosphere with the GPS slant TEC. The inverse slant TEC correlates well with observations both for GPS sites involved in the reconstruction and sites that are not involved. Based on the IDAAS, simulations were performed to investigate the deviation relative to the slant-to-vertical conversion (STV). The results indicate that the relative deviation induced by slant-to-vertical conversion may be significant in certain instances, and the deviation varies from 0% to 40% when the elevation decreases from 90° to 15°, while the relative IDAAS deviation is much smaller and varies from −5% to 15% without an elevation dependence. Compared with ‘true TEC’ map derived from the model, there is large difference in STV TEC map but no obvious discrepancy in IDAAS map. Generally, the IDAAS TEC map is much closer to the “true TEC” than is STV TEC map is.     

Application of neural networks to South African GPS TEC modelling

The propagation of radio signals in the Earth’s atmosphere is dominantly affected by the ionosphere due to its dispersive nature. Global Positioning System (GPS) data provides relevant information that leads to the derivation of total electron content (TEC) which can be considered as the ionosphere’s measure of ionisation. This paper presents part of a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived TEC. The South African GPS receiver network is operated and maintained by the Chief Directorate Surveys and Mapping (CDSM) in Cape Town, South Africa. Vertical total electron content (VTEC) was calculated for four GPS receiver stations using the Adjusted Spherical Harmonic (ASHA) model. Factors that influence TEC were then identified and used to derive input parameters for the NN. The well established factors used are seasonal variation, diurnal variation, solar activity and magnetic activity. Comparison of diurnal predicted TEC values from both the NN model and the International Reference Ionosphere (IRI-2001) with GPS TEC revealed that the IRI provides more accurate predictions than the NN model during the spring equinoxes. However, on average the NN model predicts GPS TEC more accurately than the IRI model over the GPS locations considered within South Africa.     

Comparison of observed TEC values with IRI-2007 TEC and IRI-2007 TEC with optional foF2 measurements predictions at an equatorial region,Chumphon, Thailand

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.     

TEC variability near northern EIA crest and comparison with IRI model

Monthly median values of hourly total electron content (TEC) is obtained with GPS at a station near northern anomaly crest, Rajkot (geog. 22.29°N, 70.74°E; geomag. 14.21°N, 144.9°E) to study the variability of low latitude ionospheric behavior during low solar activity period (April 2005 to March 2006). The TEC exhibit characteristic features like day-to-day variability, semiannual anomaly and noon bite out. The observed TEC is compared with latest International Reference Ionosphere (IRI) – 2007 model using options of topside electron density, NeQuick, IRI01-corr and IRI-2001 by using both URSI and CCIR coefficients. A good agreement of observed and predicted TEC is found during the daytime with underestimation at other times. The predicted TEC by NeQuick and IRI01-corr is closer to the observed TEC during the daytime whereas during nighttime and morning hours, IRI-2001 shows lesser discrepancy in all seasons by both URSI and CCIR coefficients.     

Assessment of improvement of the IRI model over Ethiopia for the modeling of the variability of TEC during the period 2013–2016

This paper discusses the monthly and seasonal variation of the total electron content (TEC) and the improvement of performance of the IRI model in estimating TEC over Ethiopia during the solar maximum (2013–2016) phase employing as reference the GPS derived TEC data inferred from four GPS receivers installed in different regions of Ethiopia; Assosa (geog 10.05°N, 34.55°E, Geom. 7.01°N), Ambo (8.97°N, 37.86°E, Geom. 5.42°N), Nazret (8.57°N, 39.29°E, Geom. 4.81°N) and Arba Minch (6.06°N, 37.56°E, Geom. 2.62°N). The results reveal that, in the years 2013–2016, the highest peak GPS-derived diurnal VTEC is observed in the March equinox in 2015 over Arba Minch station. Moreover, both the arithmetic mean GPS-derived and modelled VTEC values, generally, show maximum and minimum values in the equinoctial and June solstice months, respectively in 2014–2015. However, in 2013, the minimum and maximum arithmetic mean GPS-derived values are observed in the March equinox and December solstice, respectively. The results also show that, even though overestimation of the modelled VTEC has been observed on most of the hours, all versions of the model are generally good to estimate both the monthly and seasonal diurnal hourly VTEC values, especially in the early morning hours (00:00–03:00?UT or 03:00–06:00?LT). However, it has also been shown that the IRI 2007 and IRI 2012 versions generally perform best in matching the diurnal GPS derived TEC values as compared to that of the IRI 2016 version. In addition, the IRI 2012 version with IRI2001 option for the topside electron density shows the highest overestimation of the VTEC as compared to the other options. None of the versions of the IRI model are proved to be able to capture the effects of geomagnetic storms.     

Vertical TEC variations and model during low solar activity at a low latitude station,Xiamen

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.     

GPS derived TEC and foF2 variability at an equatorial station and the performance of IRI-model

The ionosphere induces a time delay in transionospheric radio signals such as the Global Positioning System (GPS) signal. The Total Electron Content (TEC) is a key parameter in the mitigation of ionospheric effects on transionospheric signals. The delay in GPS signal induced by the ionosphere is proportional to TEC along the path from the GPS satellite to a receiver. The diurnal monthly and seasonal variations of ionospheric electron content were studied during the year 2010, a year of extreme solar minimum (F10.7 = 81 solar flux unit), with data from the GPS receiver and the Digisonde Portable Sounder (DPS) collocated at Ilorin (Geog. Lat. 8.50°N, Long. 4.50°E, dip −7.9°). The diurnal monthly variation shows steady increases in TEC and F2-layer critical frequency (foF2) from pre-dawn minimum to afternoon maximum and then decreases after sunset. TEC show significant seasonal variation during the daytime between 0900 and 1900 UT (LT = UT + 1 h) with a maximum during the March equinox (about 35 TECU) and minimum during the June solstice (about 24 TECU). The GPS-TEC and foF2 values reveal a weak seasonal anomaly and equinoctial asymmetry during the daytime. The variations observed find their explanations in the amount of solar radiation and neutral gas composition. The measured TEC and foF2 values were compared with last two versions of the International Reference Ionosphere (IRI-2007 and IRI-2012) model predictions using the NeQuick and CCIR (International Radio Consultative Committee) options respectively in the model. In general, the two models give foF2 close to the experimental values, whereas significant discrepancies are found in the predictions of TEC from the models especially during the daytime. The error in height dependent thickness parameter, daytime underestimation of equatorial drift and contributions of electrons from altitudes above 2000 km have been suggested as the possible causes.     

Changes in total electron content (TEC) during the annular solar eclipse of 15 January 2010

The solar eclipse of 15 January 2010 was an annular eclipse of the Sun with a maximum magnitude of 0.96 at 1.62°N, 69.29°E. To study the effect of this solar eclipse on the ionosphere the GPS data recorded at three different Indian stations Varanasi (Geographic latitude 25°, 16′N, longitude 82°, 59′E), Hyderabad (Geographic latitude 17°, 20′N, longitude 78°, 30′E) and Bengaluru (Geographic latitude 12°, 58′N, longitude 77°, 33′E) have been used to retrieve ionospheric total electron content (TEC). The ionospheric response to this rare event has been studied in terms of GPS-derived TEC observed at all the three Indian stations. A significant reduction in TEC reflected by all PRNs at all the three stations has been observed. The magnitude of the reduction in VTEC compared to quiet mean VTEC depends on latitude as well as longitude. The amount of reduction observed from different satellites (PRN) is different and depends on the location of the satellite from the solar eclipse path.     

GPS derived ionospheric TEC response to geomagnetic storm on 24 August 2005 at Indian low latitude stations

Results pertaining to the response of the low latitude ionosphere to a major geomagnetic storm that occurred on 24 August 2005 are presented. The dual frequency GPS data have been analyzed to retrieve vertical total electron content at two Indian low latitude stations (IGS stations) Hyderabad (Geographic latitude 17°20′N, Geographic longitude 78°30′E, Geomagnetic latitude 8.65°N) and Bangalore (Geographic latitude 12°58′N, Geographic longitude 77°33′E, Geomagnetic latitude 4.58°N). These results show variation of GPS derived total electron content (TEC) due to geomagnetic storm effect, local low latitude electrodynamics response to penetration of high latitude convection electric field and effect of modified fountain effect on GPS–TEC in low latitude zone.     

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.     

A morphological study of GPS-TEC data at Agra and their comparison with the IRI model

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.     

Evaluation of the improvement of IRI-2016 over IRI-2012 at the India low-latitude region during the ascending phase of cycle 24

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.     

用Kriging方法构建中纬度区域电离层TEC地图

提出了中国中北部及周边(30°N～55°N,70°E～140°E范围内)区域电离层电子浓度总含量(TEC)地图(简称CNC TEC Map)的Kriging算法.比较了目前被广泛使用的电离层模型(Klobuchar,IRI和JPLGIM)与真实的TEC分布的符合情况;比较了常数漂移(普通Kriging方法)、线性漂移和二次漂移的Kriging方法;在三种不同的时间分辨率(5min,30min和120min)下,比较了Kriging算法、就近插值算法和多项式回归算法(5阶)绘制CNC TEC Map的效果.结果显示在本文研究区域内常用的电离层模型与真实TEC分布存在较大的区别;使用普通Kriging方法就可以较好的表示华北地区TEC分布;Kriging方法的结果优于其余两种插值算法,尤其是当时间分辨率提高到5 min时,Kriging算法的优势比较明显.      

IRI 2001/90 TEC predictions over a low latitude station

Total electron content (TEC) over Tucumán (26.9°S, 294.6°W) measured with Faraday technique during the high solar activity year 1982, is used to check IRI 2001 TEC predictions at the southern crest of the equatorial anomaly region. Comparisons with IRI 90 are also made. The results show that in general IRI overestimates TEC values around the daily minimum and underestimates it the remaining hours. Better predictions are obtained using ground ionosonde measurements as input coefficients in the IRI model. The results suggest that for hours of maximum TEC values the electron density profile is broader than that assumed by the model. The main reason for the disagreement would be the IRI shape of the electron density profile.     

GPS scintillation and TEC gradients at equatorial latitudes in April 2006

We use observations of ionospheric scintillation at equatorial latitudes from two GPS receivers specially modified for recording, at a sampling rate of 50 Hz, the phase and the amplitude of the L1 signal and the Total Electron Content (TEC) from L1 and L2. The receivers, called GISTM (GPS Ionospheric Scintillation and TEC Monitor), are located in Vietnam (Hue, 16.4°N, 107.6°E; Hoc Mon, 10.9°N, 106.6°E). These experimental observations are analysed together with the tomographic reconstruction of the ionosphere produced by the Multi-Instrument Data Analysis System (MIDAS) for investigating the moderate geomagnetic storm which occurred on early April 2006, under low solar activity. The synergic adoption of the ionospheric imaging and of the GISTM measurements supports the identification of the scale-sizes of the ionospheric irregularities causing scintillations and helps the interpretation of the physical mechanisms generating or inhibiting the appearance of the equatorial F layer irregularities. In particular, our study attributes to the turning of the IMF (Interplanetary Magnetic Field) between northward and southward direction an important role in the inhibition of the generation of spread F irregularities resulting in a lack of scintillation enhancement in the post-sunset hours.     

基于BDS/GPS和经验模型的区域电离层建模

基于北斗卫星导航系统（BDS）和全球定位系统（GPS）实测电离层穿刺点（IPP）数据,结合国际参考电离层（IRI）经验模型历史数据,提出一种对区域二维电离层总电子含量（TEC）进行高精度建模的方法.针对缺乏穿刺点的区域内短时间电离层建模时精度较低且各时段穿刺点空间分布不同的问题,该方法使用IRI模型在建模区域内均匀添加虚拟穿刺点数据,并根据与实测穿刺点的距离,使用构造的权重计算公式赋予其动态权重值,通过加权最小二乘法进行球谐模型参数解算.与欧洲定轨中心（CODE）发布的全球电离层图（GIM）进行数据比对发现,相对于只使用BDS/GPS实测穿刺点数据的建模方法,利用本文建模方法计算获得的垂直总电子含量（VTEC）值对缺乏实测穿刺点的区域精度有明显的提升.      

Seasonal variability of GPS-VTEC and model during low solar activity period (2006–2007) near the equatorial ionization anomaly crest location in Chinese zone

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.     

Seasonal variations of storm-time TEC at European middle latitudes

Global Navigation Satellite System (GNSS) measurements of the Total Electron Content (TEC) from local (Dourbes, 50.1°N, 04.6°E) and European IGS (International GNSS Service) stations were used to obtain the TEC changes during the geomagnetic storms of the latest solar activity cycle. A common epoch analysis, with respect to geomagnetic storm intensity, season, and latitude, was performed on data representing nearly 300 storm events. In general, the storm-time behaviour of TEC shows clear positive and negative phases, relative to the non-storm (median) behaviour, with amplitudes that tend to increase during more intense storms. The most pronounced positive phase is observed during winter, while the strongest and yet shortest negative phase is detected during equinox. Average storm-time patterns in the TEC behaviour are deduced for potential use in ionosphere prediction services.     

Temporal extrapolation of TEC using WNN during 2007–2018 and comparison against GIM,IRI2016 and Kriging

In this paper, a new method of temporal extrapolation of the ionosphere total electron content (TEC) is proposed. Using 3-layer wavelet neural networks (WNNs) and particle swarm optimization (PSO) training algorithm, TEC time series are modeled. The TEC temporal variations for next times are extrapolated with the help of training model. To evaluate the proposed model, observations of Tehran GNSS station (35.69°N, 51.33°E) from 2007 to 2018 are used. The efficiency of the proposed model has been evaluated in both low and high solar activity periods. All observations of the 2015 and 2018 have been removed from the training step to test the proposed model. On the other hand, observations of these 2 years are not used in network training. According to the F10.7, the 2015 has high solar activity and the 2018 has quiet conditions. The results of the proposed model are compared with the global ionosphere maps (GIMs) as a traditional ionosphere model, international reference ionosphere 2016 (IRI2016), Kriging and artificial neural network (ANN) models. The root mean square error (RMSE), bias, dVTEC = |VTEC_GPS ? VTEC_Model| and correlation coefficient are used to assess the accuracy of the proposed method. Also, for more accurate evaluation, a single-frequency precise point positioning (PPP) approach is used. According to the results of 2015, the maximum values of the RMSE for the WNN, ANN, Kriging, GIM and IRI2016 models are 5.49, 6.02, 6.34, 6.19 and 13.60 TECU, respectively. Also, the maximum values of the RMSE at 2018 for the WNN, ANN, Kriging, GIM and IRI2016 models are 2.47, 2.49, 2.50, 4.36 and 6.01 TECU, respectively. Comparing the results of the bias and correlation coefficient shows the higher accuracy of the proposed model in quiet and severe solar activity periods. The PPP analysis with the WNN model also shows an improvement of 1 to 12 mm in coordinate components. The results of the analyzes of this paper show that the WNN is a reliable, accurate and fast model for predicting the behavior of the ionosphere in different solar conditions.     

Towards a GPS-based TEC prediction model for Southern Africa with feed forward networks

In this paper, first results from a national Global Positioning System (GPS) based total electron content (TEC) prediction model over South Africa are presented. Data for 10 GPS receiver stations distributed through out the country were used to train a feed forward neural network (NN) over an interval of at most five years. In the NN training, validating and testing processes, five factors which are well known to influence TEC variability namely diurnal variation, seasonal variation, magnetic activity, solar activity and the geographic position of the GPS receivers were included in the NN model. The database consisted of 1-min data and therefore the NN model developed can be used to forecast TEC values 1 min in advance. Results from the NN national model (NM) were compared with hourly TEC values generated by the earlier developed NN single station models (SSMs) at Sutherland (32.38°S, 20.81°E) and Springbok (29.67°S, 17.88°E), to predict TEC variations over the Cape Town (33.95°S, 18.47°E) and Upington (28.41°S, 21.26°E) stations, respectively, during equinoxes and solstices. This revealed that, on average, the NM led to an improvement in TEC prediction accuracy compared to the SSMs for the considered testing periods.