Highlights about the performances of storm-time TEC modelling techniques for low/equatorial and mid-latitude locations

A statistical evaluation of storm-time total electron content (TEC) modelling techniques over various latitudes of the African sector and surrounding areas is presented. The source of observational TEC data used in this study is the Global Navigation Satellite Systems (GNSS), specifically the Global Positioning Systems (GPS) receiver networks. For each selected receiver station, three different storm-time models based on empirical orthogonal functions (EOF) analysis, non-linear regression analysis (NLRA) and Artificial neural networks (ANN), were implemented. Storm-time GPS TEC data used for both development and validation of the models was selected based on the storm criterion of $\mathit{Dst}?-50$ nT or $K_p?4$ to take into account both coronal mass ejections (CMEs) and co-rotating interaction regions (CIRs) driven storms, respectively. To make an independent test of the models, storm periods considered for validation were excluded from datasets used during the implementation of the models and results are compared with observations, monthly median values, and International Reference Ionosphere (IRI-2016) predictions. Considering GPS TEC as reference, a statistical analysis performed over six storm periods reserved for validation revealed that ANN model is about 10%, 26%, and 58% more accurate than EOF, NLRA, and IRI models, respectively. It was further found that, EOF model performs 15%, and 44% better than NLRA, and IRI models, respectively, while NLRA is 25% better than IRI. On the other hand, results are also discussed referring to the background ionosphere represented by monthly median TEC (MM TEC) and statistics are provided. Moreover, strengths and weaknesses of each model are highlighted.     

一种应用于实时深空干涉测量的电离层时延修正方法

针对"嫦娥4号"中继星任务S频段信标信号的高精度实时干涉测量需求,结合深空测控干涉测量系统采用的稀疏标校工作模式,研究验证了一种面向测控模式实时干涉测量的电离层时延修正方法。首先分析了电磁波经电离层传播的延迟机理及特性;基于深空站历史观测数据,通过自相关函数分析验证了天顶向TEC的周日特性;在此基础上,结合深空干涉测量中心数据处理设备软件系统,讨论了电离层时延修正方法;通过任务期间的实测数据处理分析,验证了所提方法可以将实时测量精度提升1～3 ns,对低仰角跟踪弧段,该技术方法优势更为明显。该方法为后续深入推进深空测控干涉测量系统在任务中的实时应用提供了技术储备。     

Comparison of observed ionospheric vertical TEC over the sea in Indian region with IRI-2016 model

The vertical ionospheric TEC values obtained from GAGAN grid based ionospheric delay correction values over the sea in the Indian equatorial region have been compared with the corresponding values derived from the International Reference Ionosphere model, IRI-2016. The objective of this work is to study the deviation of the vertical TEC derived from the IRI model from ground truths over the sea for different conditions. This will serve the basic intention of assessing the candidature of the IRI model as an alternative ionospheric correction model in navigation receivers in terms of accuracy. We have chosen different solar activity periods, seasons, geomagnetic conditions, locations etc. for our comparison and analysis. The TEC values by the IRI-2016 were compared with the actual measured values for the given conditions and errors were obtained. The measured vertical TEC values at the ionospheric grid points were derived from the GAGAN broadcast ionospheric delay data and used as reference. The IRI model with standard internal functions was used in estimating the TEC at the same ionospheric grid points. The errors in the model derived values are statistically analysed. Broadly, the results show that, for the Indian sector over the sea, the IRI model performs better on quiet days in off equatorial regions, particularly in the northern region. The overall performance degrades for other conditions with the model generally underestimating the true TEC values and most severely in the equatorial region. The performance is worst in this region for the disturbed days of the equinoctial period. The comparison study is also done with the TEC data measured directly by dual frequency GPS receivers. The results were found to be in general agreement with those obtained by comparing the model with GAGAN broadcast data as reference. This study will be useful in considering the IRI-2016 model for real time estimates of TEC as an alternative to the current parametric model in a satellite navigation receiver in absence of other options.     

Ionospheric total electron content response to annular solar eclipse on June 21, 2020

The effects of physical events on the ionosphere structure is an important field of study, especially for navigation and radio communication. The paper presents the spatio-temporal ionospheric TEC response to the recent annular solar eclipse on June 21, 2020, which spans across two continents, Africa and Asia, and 14 countries. This eclipse took place on the same day as the June Solstice. The Global Navigation Satellite System (GNSS) based TEC data of the Global Ionosphere Maps (GIMs), 9 International GNSS Service (IGS) stations and FORMOSAT-7/COSMIC-2 (F7/C2) were utilized to analyze TEC response during the eclipse. The phases of the TEC time series were determined by taking the difference of the observed TEC values on eclipse day from the previous 5-day median TEC values. The results showed clear depletions in the TEC time series on June 21. These decreases were between 1 and 9 TECU (15–60%) depending on the location of IGS stations. The depletions are relatively higher at the stations close to the path of annular eclipse than those farther away. Furthermore, a reduction of about ?10 TECU in the form of an equatorial plasma bubble (EPB) was observed in GIMs at ~20° away from the equator towards northpole, between 08:00–11:00 UT where its maximum phase is located in southeast Japan. Additionally, an overall depletion of ~10% was observed in F7/C2 derived TEC at an altitude of 240 km (hmF2) in all regions affected by the solar eclipse, whereas, significant TEC fluctuations between the altitudes of 100 km ? 140 km were analyzed using the Savitzky-Golay smoothing filter. To prove TEC depletions are not caused by space weather, the variation of the sunspot number (SSN), solar wind (V_SW), disturbance storm-time (Dst), and Kp indices were investigated from 16th to 22nd June. The quiet space weather before and during the solar eclipse proved that the observed depletions in the TEC time series and profiles were caused by the annular solar eclipse.     

A method of estimating GPS instrumental biases with a convolution algorithm

This paper presents a method of deriving the instrumental differential code biases (DCBs) of GPS satellites and dual frequency receivers. Considering that the total electron content (TEC) varies smoothly over a small area, one ionospheric pierce point (IPP) and four more nearby IPPs were selected to build an equation with a convolution algorithm. In addition, unknown DCB parameters were arranged into a set of equations with GPS observations in a day unit by assuming that DCBs do not vary within a day. Then, the DCBs of satellites and receivers were determined by solving the equation set with the least-squares fitting technique. The performance of this method is examined by applying it to 361?days in 2014 using the observation data from 1311 GPS Earth Observation Network (GEONET) receivers. The result was crosswise-compared with the DCB estimated by the mesh method and the IONEX products from the Center for Orbit Determination in Europe (CODE). The DCB values derived by this method agree with those of the mesh method and the CODE products, with biases of 0.091?ns and 0.321?ns, respectively. The convolution method's accuracy and stability were quite good and showed improvements over the mesh method.     

Comparison of GPS derived TEC with the TEC predicted by IRI 2012 model in the southern Equatorial Ionization Anomaly crest within the Eastern Africa region

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.     

Statistical study of the time delay of ionospheric TEC storms to geomagnetic storms in Taoyuan,Taiwan

We have studied the time delay of ionospheric storms to geomagnetic storms at a low latitude station Taoyuan (25.02°N, 121.21°E), Taiwan using the Dst and TEC data during 126 geomagnetic storms from the year 2002 to 2014. In addition to the known local time dependence of the time delay, the statistics show that the time delay has significant seasonal characteristics, which can be explained within the framework of the seasonal characteristics of the ionospheric TEC. The data also show that there is no correlation between the time delay and the intensity of magnetic storms. As for the solar activity dependence of the time delay, the results show that there is no relationship between the time delay of positive storms and the solar activity, whereas the time delay of negative storms has weakly negative dependence on the solar activity, with correlation coefficient −0.41. Especially, there are two kinds of extreme events: pre-storm response events and long-time delay events. All of the pre-storm response events occurred during 15–20 LT, manifesting the Equator Ionospheric Anomaly (EIA) feature at Taoyuan. Moreover, the common features of the pre-storm response events suggest the storm sudden commencement (SSC) and weak geomagnetic disturbance before the main phase onset (MPO) of magnetic storms are two main possible causes of the pre-storm response events. By analyzing the geomagnetic indices during the events with long-time delay, we infer that this kind of events may not be caused by magnetic storms, and they might belong to ionospheric Q-disturbances.     

TEC differences for the mid-latitude ionosphere in both sides of the longitudes with zero declination

Based on measurements of ground-based GPS station network, differences of the mid-latitude ionospheric TEC in the east and west sides of North America, South America and Oceania have been analyzed in this paper. Results show that for nearly all seasons from 2001 to 2010 and in both sides of the longitudes with zero declination, there exist systematic differences for the mid-latitude ionospheric TEC in the regions mentioned above and the features of these differences markedly depend upon the local time but less depend upon seasons and the level of solar activity. Theory analysis shows that the longitude variations of both declination and zonal thermospheric winds are one of important factors to cause differences of the mid-latitude ionospheric TEC in both sides of the longitudes with zero declination.     

L-band nighttime scintillations at the northern edge of the EIA along 95°E during the ascending half of the solar cycle 24

The characteristics of nighttime ionospheric scintillations measured at the L-band frequency of 1.575 GHz over Dibrugarh (27.5°N, 95°E, MLAT ～ 17°N, 43° dip) during the ascending half of the solar cycle 24 from 2010 to 2014 have been investigated and the results are presented in this paper. The measurement location is within or outside the zone of influence of the equatorial ionization anomaly depending on solar and geomagnetic activity. Maximum scintillation is observed in the equinoxes irrespective of solar activity with clear asymmetry between March and September. The occurrence frequency in the solstices shifts from minimum in the June solstice in low solar activity to a minimum in the December solstice in high solar activity years. A significant positive correlation of occurrence of scintillations in the June solstice with solar activity has been observed. However, earlier reports from the Indian zone (～75°E) indicate negative or no correlation of scintillation in June solstice with solar activity. Scintillations activity/occurrence in solstices indicates a clear positive correlation with Es recorded simultaneously by a collocated Ionosonde. In equinoxes, maximum scintillations occur in the pre-midnight hours while in solstices the occurrence frequency peaks just after sunset. The incidence of strong scintillations (S₄ ≥ 0.4) increases with increase in solar activity. Strong (S₄ ≥ 0.4) ionospheric scintillations accompanied by TEC depletions in the pre-midnight period is attributed to equatorial irregularities whereas the dusk period scintillations are related to the sporadic-E activity. Present results thus indicate that the current location at the northern edge of the EIA behaves as low as well as mid-latitude location.     

电离层周日变化对解算GPS硬件延迟稳定性的影响

针对电离层周日变化特征分析了其可能对SCORE方法估算的硬件延迟稳定性的影响. 利用BJFS以及XIAM台站的GPS观测数据, 解算了位于太阳活动高年(2001年)和太阳活动低年(2009年)的卫星硬件延迟并分析了估算的硬件延迟的稳定性. 研究发现, 电离层周日变化对估算的硬件延迟稳定性具有一定影响, 但是利用不同台站所得到的卫星硬件延迟稳定性在昼夜不同时间上的解算结果存在一定差异. 电离层周日变化对利用 BJFS台站数据解算的硬件延迟稳定性日夜差异较为明显, 在太阳活动高年利用XIAM 台站数据解算的硬件延迟日夜稳定性差异不很明显, 由于XIAM台站处于电离层赤道异常峰附近, 夜间电离层变化很大, 因此对比中纬度地区, 电离层周日变化对赤道异常峰附近地区硬件延迟稳定性解算结果的影响相对较小, 但在太阳活动低年, 其影响仍较为显著.