武昌地区急始型磁暴期间电离层电子总含量的变化

利用１９８０年４月至１９９０年１２月共１３６次急始型磁暴资料统计研究了武昌地区ＴＥＣ的变化。结果表明，ＴＥＣ的暴时变化出现正相，相对变化值ΔＴＥＣ的暴时变化形态与中高纬地区一些台站所观测到的结果差别较大；如果磁暴急始出现在白天，则急始后３６小时，会出现ΔＴＥＣ的极大值，如果急始出现在夜间，则不会出现极大值，这一现象与太阳黑子数，季节无关。     

Investigation of natural and artificial stimulation of the ionospheric Alfvén resonator at high latitude

A brief review is provided of recent progress in understanding the ionospheric Alfvén resonator (IAR) at high latitude. Firstly, naturally occurring resonances of the IAR as detected by pulsation magnetometers in the auroral zone at Sodankylä and in the polar cap at Barentsburg are considered. The characteristics of the IAR in the two regions are broadly similar, although the effects of solar illumination are less clear at the higher latitudes. Secondly we review recent attempts to stimulate the IAR through high-power radio frequency experiments both in the auroral zone at Tromsø with the European Incoherent SCATter (EISCAT) heater, and within the polar cap at Longyearbyen with the Space Plasma Exploration by Active Radar (SPEAR) facility. In the auroral zone at, Tromsø the stimulated IAR has been observed by ground-based magnetometers, and through electron acceleration observed on the FAST spacecraft. At SPEAR in the polar cap, the stimulated IAR has been investigated, with ground magnetometers, with the first results indicative of a positive detection.     

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.     

Using TensorFlow-based Neural Network to estimate GNSS single frequency ionospheric delay (IONONet)

In the last 20?years, and in particular in the last decade, the availability of propagation data for GNSS has increased substantially. In this sense, the ionosphere has been sounded with a large number of receivers that provide an enormous amount of ionospheric data. Moreover, the maturity of the models has also been increased in the same period of time. As an example, IGS has ionospheric maps from GNSS data back to 1998, which would allow for the correlation of these data with other quantities relevant for the user and space weather (such as Solar Flux and Kp). These large datasets would account for almost half a billion points to be analyzed. With the advent and explosion of Big Data algorithms to analyze large databases and find correlations with different kinds of data, and the availability of open source code libraries (for example, the TensorFlow libraries from Google that are used in this paper), the possibility of merging these two worlds has been widely opened. In this paper, a proof of concept for a single frequency correction algorithm based in GNSS GIM vTEC and Fully Connected Neural Networks is provided. Different Neural Network architectures have been tested, including shallow (one hidden layer) and deep (up to five hidden layers) Neural Network models. The error in training data of such models ranges from 50% to 1% depending on the architecture used. Moreover, it is shown that by adjusting a Neural Network with data from 2005 to 2009 but tested with data from 2016 to 2017, Neural Network models could be suitable for the forecast of vTEC for single frequency users. The results indicate that this kind of model can be used in combination with the Galileo Signal-in-Space (SiS) NeQuick G parameters. This combination provides a broadcast model with equivalent performances to NeQuick G and better than GPS ICA for the years 2016 and 2017, showing a 3D position Root Mean Squared (RMS) error of approximately 2?m.     

Ionospheric TEC disturbances over China during the strong geomagnetic storm in September 2017

From September 7 to 8, 2017, a G4-level strong geomagnetic storm occurred, which seriously impacted on the Earth’s ionosphere. In this work, the global ionospheric maps released by Chinese Academy of Sciences are used to investigate the ionospheric responses over China and its adjacent regions during the strong storm. The prominent TEC enhancements, which mainly associated with the neutral wind and eastward prompt penetration electric field, are observed at equatorial ionization anomaly crests during the main phase of the storm on 8 September 2017. Compared with those on 8 September, the TEC enhancements move to lower-latitude regions during the recovery phase on 9 September. A moderate storm occurred well before the start of the strong storm causes similar middle-latitude TEC enhancements on 7 September. However, the weak TEC depletion is observed at middle and low latitude on 9–10 September, which could be associated with the prevailing westward disturbance electric field or storm-time neural composition changes. In addition, the storm-time RMS and STD values of the ionospheric TEC grids over China increase significantly due to the major geomagnetic storm. The maximum of the RMS reaches 12.0 TECU, while the maximum of the STD reaches 8.3 TECU at ~04UT on 8 September.     

Doppler characteristics of HF spread Doppler clutter recorded at Alice Springs,Australia

Mean night-time peak power, Doppler shift and Doppler width of spread Doppler clutter (SDC) received by a high frequency backscatter radar located at Alice Springs, Australia from 2000 to 2018 is presented as a function of azimuth, sunspot number, time of year and frequency. The sampled region covers 90 degrees from West to North and includes the northern and southern equatorial anomalies.SDC peak power diminished across all azimuths during the winter solstice from around May to August (local winter) coinciding with the global decrease in F layer density due to the annual non-seasonal F2 anomaly but was generally constant during the equinoxes. In contrast, SDC Doppler width and inbound Doppler shift both increased during the equinoxes and exhibited azimuthal dependence related to the eastward equatorial plasma drift.SDC peak power increased with increasing sunspot number with frequency dependence during winter but not summer. Inbound Doppler shift and Doppler width increased with increasing sunspot number during equinox but not solstice with a strong dependence on azimuth and a weak dependence on frequency.     

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.     

Application of Wuhan Ionospheric Oblique Backscattering Sounding System (WIOBSS) for the investigation of midlatitude ionospheric irregularities

An upgrade of Wuhan Ionospheric Backscattering Sounding System (WIOBSS) was developed in 2015. Based on the Universal Serial Bus (USB), and a high performance FPGA, the newly designed WIOBSS has a completely digital structure, which makes it portable and flexible. Two identical WIOBSSs, which were situated at Mile (24.31°N, 103.39°E) and Puer (22.74°N, 101.05°E) respectively, were used to investigate the ionospheric irregularities. The comparisons of group distance, Doppler shift and width between Mile-Puer and Puer-Mile VHF ionospheric propagation paths indicate that the reciprocity of the irregularities is satisfied at midlatitude region. The WIOBSS is robust in the detection of ionospheric irregularities.