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.     

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.     

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.     

Identification of seismic activity sources on the subsatellite track by ionospheric plasma disturbances detected with the Sich-2 onboard probes

Using a cylindrical Langmuir probe and the authors’ proprietary two-channel pressure transducer, ionospheric plasma parameter distributions along the orbit of the Sich-2 satellite (Ukraine, 2011–2012) were measured. This paper is concerned with identifying the space–time location of ionospheric plasma disturbance sources, including the epicenters of actual earthquakes (before or during the satellite flyover) and incipient earthquakes on the subsatellite track, from the measured distributions of the electron density and temperature and the neutral particle temperature along the satellite orbit. To do this, the measured ionospheric plasma parameter distributions are connected to the coordinates on the subsatellite track.It is shown that local disturbances in the electron density and temperature and neutral particle temperature distributions in the satellite orbit in the ionosphere may serve as indicators of seismic activity on the subsatellite track. The epicenters of incipient earthquakes may be set off from other plasma parameter disturbance sources associated with seismic activity using information provided by special monitoring and survey centers that monitor the current seismic situation.     

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.     

A comparative study of ionospheric IRIEup and ISP assimilative models during some intense and severe geomagnetic storms

Three-dimensional (3-D) electron density matrices, computed in the Mediterranean area by the IRI climatological model and IRIEup and ISP nowcasting models, during some intense and severe geomagnetic-ionospheric storms, were ingested by the ray tracing software tool IONORT, to synthesize quasi-vertical ionograms. IRIEup model was run in different operational modes: (1) assimilating validated autoscaled electron density profiles only from a limited area which, in our case, is the Mediterranean sector (IRIEup_re(V) mode); (2) assimilating electron density profiles from a larger region including several stations spread across Europe: (a) without taking care of validating the autoscaled data in the assimilation process (IRIEup(NV)); (b) validating carefully the autoscaled electron density profiles before their assimilation (IRIEup(V)).The comparative analysis was carried out comparing IRI, IRIEup_re(V), ISP, IRIEup(NV), and IRIEup(V) foF2 synthesized values, with corresponding foF2 measurements autoscaled by ARTIST, and then validated, at the truth sites of Roquetes (40.80°N, 0.50°E, Spain), San Vito (40.60°N, 17.80°E, Italy), Athens (38.00°N, 23.50°E, Greece), and Nicosia, (35.03°N, 33.16°E, Cyprus). The outcomes demonstrate that: (1) IRIEup_re(V), performs better than ISP in the western Mediterranean (around Roquetes); (2) ISP performs slightly better than IRIEup_re(V) in the central part of Mediterranean (around Athens and San Vito); (3) ISP performance is better than the IRIEup_re(V) one in the eastern Mediterranean (around Nicosia); (4) IRIEup(NV) performance is worse than the IRIEup(V) one; (5) in the central Mediterranean area, IRIEup(V) performance is better than the IRIEup_re(V) one, and it is practically the same for the western and eastern sectors.Concerning the overall performance, nowcasting models proved to be considerably more reliable than the climatological IRI model to represent the ionosphere behaviour during geomagnetic-ionospheric storm conditions; ISP and IRIEup(V) provided the best performance, but neither of them has clearly prevailed over the other one.     

Characterization of ionospheric amplitude scintillations using wavelet entropy detrended GNSS data

The extensive monitoring networks of Global Navigation Satellite System (GNSS) ionospheric scintillation have been established to continuously log observation data. Further, the amplitude scintillation index and the phase scintillation index, which are derived from scintillation observations, are anticipated to accommodate the accuracy requirement of both the user level and the monitoring station level. However, raw scintillation observations essentially measure superposed waveform impairments of GNSS signals propagating through ionosphere and troposphere. It implies that fluctuations of raw scintillation observations are caused by multiple factors from the entire radio propagation environment. Hence, it is crucial to characterize ionospheric scintillations from GNSS observation data. And the characterization is implemented through extracting fluctuations of raw observations merely induced by ionospheric scintillations. Designed to address this problem by means of Fourier filtering detrending, the present work investigates the influence of varying detrending cutoff frequencies on wavelet statistical energy and wavelet entropy distributions of scintillation data. It consequently derives criteria on the optimum detrending cutoff frequency for three types of raw amplitude scintillation data, which are classified by their wavelet energy distributions. Results of the present work verify that detrending with specific optimum cutoff frequencies rather than the fixed and universally applicable one renders the validity and credibility of characterizing ionospheric scintillations as the part of GNSS observation fluctuations purely induced by ionosphere electron density irregularities whose scale sizes are comparable with or smaller than the Fresnel scale.