Total Electron Content Measurements Research Articles

Secondary Gravity Wave Propagation in Tropical Thermospheric Region: Role of Varying Kinematic Viscosity

AbstractThe current study has investigated the thunderstorm induced atmospheric gravity waves (AGWs) over Indian region based on the perturbation signatures in ionospheric total electron content (TEC) measurement. Robust traveling ionospheric disturbance (TID) signature has been identified along the east side of the thunderstorm affected area. Neutral wind was found to have a favorable impact in this aspect for a certain time duration of the day by modulating the vertical wavelength. The role of temperature was analyzed in terms of kinematic viscosity which is a crucial component, especially over tropical region, for wave dissipation and reflection along its propagation path. Ray tracing algorithm is also applied with varying kinematic viscosity and thermal diffusivity for retrieval of possible ray paths and source location of observed waves. A statistical investigation has been carried out to identify the dissipation altitude of observed waves along the ray paths. It has been found that all waves dissipated at almost a constant altitude for a specific kinematic viscosity and above this altitude vertical wavelength was found to decrease. The ray paths interacted at a common point which was located at about 125 km altitude and was very close to the region of maximum lightning activity. It can also be noted that the observed phase velocities can't be achieved by a wave below the turbopause. It indicates that the observed waves were excited from a secondary source and not directly connected to convective system. The study provides an in‐depth analysis of mesoscale system induced gravity wave propagation and dissipation over tropical region.

High-resolution 3-D imaging of electron density perturbations using ultra-dense GNSS observation networks in Japan: an example of medium-scale traveling ionospheric disturbances

For the first time using computerized ionospheric tomography (CIT) and leveraging ultra-dense slant total electron content (STEC) measurements derived from two ground-based Global Navigation Satellite System (GNSS) receiver networks in Japan, we have reconstructed the 3-D field-aligned structure of nighttime medium-scale traveling ionospheric disturbances (MSTIDs) with high spatiotemporal resolution. The CIT algorithm focuses on electron density perturbation components, allowing for the imaging of disturbances with small amplitudes and scales. Slant TECs used for CIT are setup to consist of two components: the background derived from IRI-2016 model and TEC perturbations obtained by subtracting a 30-min running average from observations. The resolution is set to 0.25º in latitude and longitude, 10 km in altitude, 30 s in time. Simulations were conducted to assess the performance of the CIT algorithm, revealing that this technique has good fidelity by accurately reconstructing more than 80% of the electron density perturbations. The focus is on the nighttime event of July 4, 2022, when data were accessible. The reconstruction results show that the MSTIDs initially form at lower altitudes and subsequently develop to exhibit large amplitudes and scales that extend to higher altitudes, characterized by a well-defined frontal structure with electrodynamic signatures. These results are consistent with theories and snippets of observational evidence regarding electromagnetic-influenced MSTIDs, hence affirming the effectiveness of the developed CIT technique in probing of the variations in the 3-D structure of ionospheric electron density. This is expected to contribute to a compressive understanding of the underlying mechanisms of ionospheric inhomogeneities.Graphical

Effect of Polar Cap Patches on the High‐Latitude Upper Thermospheric Winds

AbstractThis study focuses on the poorly known effect of polar cap patches (PCPs) on the ion‐neutral coupling in the F‐region. The PCPs were identified by total electron content measurements from the Global Navigation Satellite System (GNSS) and the ionospheric parameters from the Defense Meteorological Satellite Program spacecraft. The EISCAT incoherent scatter radars on Svalbard and at Tromsø, Norway observed that PCPs entered the nightside auroral oval from the polar cap and became plasma blobs. The ionospheric convection further transported the plasma blobs to the duskside. Simultaneously, long‐lasting strong upper thermospheric winds were detected in the duskside auroral oval by a Fabry‐Perot Interferometer (FPI) at Tromsø and in the polar cap by the Gravity Recovery and Climate Experiment satellite. Using EISCAT ion velocities and plasma parameters as well as FPI winds, the ion drag acting on neutrals and the time constant for the ion drag could be estimated. Due to the arrival of PCPs/blobs and the accompanied increase in the F‐region electron densities, the ion drag is enhanced between about 220 and 500 km altitudes. At the F peak altitudes near 300 km, the median ion drag acceleration affecting neutrals more than doubled and the associated median e‐folding time decreased from 4.4 to 2 hr. The strong neutral wind was found to be driven primarily by the ion drag force due to large‐scale ionospheric convection. Our results provide a new insight into ionosphere‐thermosphere coupling in the presence of PCPs/blobs.

Mapping high spatial resolution ionospheric total electron content by integrating Time Series InSAR with International Reference Ionosphere model

Total electron content (TEC) is a key parameter for characterizing the ionosphere. Conventional TEC measurement methods have low spatial resolution, hindering accurate representation of ionospheric spatial characteristics. Synthetic Aperture Radar (SAR) and Interferometric SAR (InSAR) have shown their potential for high-spatial-resolution TEC estimation. However, SAR-based absolute TEC estimation typically relies on full-polarimetric SAR images, while the InSAR-based method can only extract differential TEC. This study proposes a novel TEC mapping method integrating Time Series InSAR (TS-InSAR) with the International Reference Ionospheric (IRI) model and does not leverage full-polarimetric SAR data. The Advanced Land Observing Satellite-1 (ALOS-1) SAR images covering the Chile and Greenland regions were collected to test the proposed method. The TECs derived from the IRI model and International GNSS Service (IGS) and the electron density observed by the Incoherent Scattering Radar (ISR) site of SONDRESTROM were acquired to evaluate the performance and validate the accuracy of the proposed method, respectively. The results show that the proposed method can achieve TEC mapping with resolutions of tens of meters, much higher than the tens or hundreds of kilometers of the IRI and IGS TECs. The spatial features of our method-derived TECs show overall good consistency with those of the IRI and IGS TECs, but the described spatial information is more detailed. Also, compared to the original IRI model, the improvement rates of root-mean-square errors (RMSEs) between the estimated electron density and ISR observations exceeded 21.67% after the update using the TEC obtained from the proposed method. These experiments demonstrate the proposed method’s feasibility and reliability for ionospheric TEC mapping.

Measurement and Comparison of Total Electron Content for Assessment of Ionospheric Models during April 7, 2000 Geomagnetic Storms

Measurement and Comparison of Total Electron Content for Assessment of Ionospheric Models during April 7, 2000 Geomagnetic Storms

Detection of Traveling Ionospheric Disturbances Triggered by 2022 Tonga Volcanic Eruptions Through CubeSats Coherent GNSS‐Reflectometry Measurement

AbstractWe present two case studies of traveling ionospheric disturbances (TIDs) triggered by the 2022 Tonga volcanic eruption observed by low‐cost CubeSat‐based global navigation satellite system reflectometry (GNSS‐R) measurements. The GNSS‐R data used in this work are from Spire Global CubeSats. Our analysis shows that coherent GNSS signals reflected over the ocean can be used to derive precise ionospheric total electron content (TEC) measurements. The first case shows clear TID structures with a TEC disturbance magnitude of ∼1 TEC unit (TECu) and horizontal wavelength of ∼330 km over Northwest Australia on the day of Tonga volcanic eruption. The second case shows the TIDs with ∼0.05 TECu disturbance magnitude and horizontal wavelength of ∼240 km over East Russia the day after the eruption. The second case is likely a TIDs propagated outward from Tonga for the second time after it traversed around the Earth. The GNSS‐R observed TID may be associated with the incident or reflection signal ray path. In this paper, the appropriate ray path was identified using simultaneous observations from ground receiver networks in the areas of both ray paths.

Performance of IRI 2016 model in predicting total electron content (TEC) compared with GPS-TEC over East Africa during 2019–2021

This study evaluated the applicability of IRI-2016 model in predicting GPS TEC using the monthly means of the five (5) quiet days for equinoxes and solstices months. GPS-derived TEC data were obtained from the IGS network of ground based dual frequency GPS receivers from three stations [(KYN3 0.53° S, 38.53° E; Geom. Lat. 3.91.63° S), (MBAR 0.60° S, 30.74° E; Geom. Lat. 2.76° S) and HOID 1.45° S, 31.34° E; Geom. Lat. 3.71° S]. All the three options for topside Ne of IRI-2016 model and ABT-2009 for bottomside thickness have been used to compute the IRI TEC. The results were compared with the GPS TEC measurements. Correlation Coefficients between the two sets of data, the Root-Mean Square Errors of the IRI-TEC from the GPS-TEC, and the percentage RMSE of the IRI-TEC from the GPS-TEC have been computed. In general, the IRI-2016 model underestimated GPS-TEC during the nighttime, whereas the model overestimated GPS-TEC values during the daytime. At most of the stations and during all seasons where data were available, correlation coefficient was above 0.9, which is quite strong. The variation of O/N2 ratio may potentially be the cause of the IRI TEC deviation from the GPS TEC. This variation arises from lower thermosphere plasma drift that moves upward.

GNSS Differential Code Bias Determination Using Rao‐Blackwellized Particle Filtering

AbstractThe Assimilative Canadian High Arctic Ionospheric Model (A‐CHAIM) is a near‐real‐time data assimilation model of the high latitude ionosphere, incorporating measurements from many instruments, including slant Total Electron Content measurements from ground‐based Global Navigation Satellite System (GNSS) receivers. These measurements have receiver‐specific Differential Code Biases (DCB) which must be resolved to produce an absolute measurement, which are resolved simultaneously with the ionospheric state using Rao‐Blackwellized particle filtering. These DCBs are compared to published values and to DCBs determined using eight different Global Ionospheric Maps (GIM), which show small but consistent systematic differences. The potential cause of these systematic biases is investigated using multiple experimental A‐CHAIM test runs, including the effect of plasmaspheric electron content. By running tests using the GIM‐derived DCBs, it is shown that using A‐CHAIM DCBs produces the lowest overall error, and that using GIM DCBs causes an overestimation of the topside electron density which can exceed 100% when compared to in situ measurements from DMSP.

Space Domain Awareness Observations Using the Buckland Park VHF Radar

There is increasing interest in space domain awareness worldwide, motivating investigation of the use of non-traditional sensors for space surveillance. One such class of sensor is VHF wind profiling radars, which have a low cost relative to other radars typically applied to this task. These radars are ubiquitous throughout the world and may potentially offer complementary space surveillance capabilities to the Space Surveillance Network. This paper updates an initial investigation on the use of Buckland Park VHF wind profiling radars for observing resident space objects in low Earth orbit to further investigate the space surveillance capabilities of the sensor class. The radar was operated during the Australian Defence “SpaceFest” 2019 activity, incorporating new beam scheduling and signal processing functionality that extend upon the capabilities described in the initial investigation. The beam scheduling capability used two-line element propagations to determine the appropriate beam direction to use to observe transiting satellites. The signal processing capabilities used a technique based on the Keystone transform to correct for range migration, allowing the development of new signal processing modes that allow the coherent integration time to be increased to improve the SNR of the observed targets, thereby increasing the detection rate. The results reveal that 5874 objects were detected over 10 days, with 2202 unique objects detected, representing a three-fold increase in detection rate over previous single-beam direction observations. The maximum detection height was 2975.4 km, indicating a capability to detect objects in medium Earth orbit. A minimum detectable RCS at 1000 km of −10.97 dBm2 (0.09 m2) was observed. The effects of Faraday rotation resulting from the use of linearly polarised antennae are demonstrated. The radar’s utility for providing total electron content (TEC) measurements is investigated using a high-range resolution mode and high-precision ephemeris data. The short-term Fourier transform is applied to demonstrate the radar’s ability to investigate satellite rotation characteristics and monitor ionospheric plasma waves and instabilities.

The Hunt for Perpendicular Magnetic Field Measurements in Plasma

The one consistent technique for remotely estimating the magnetic field in plasma has been Faraday rotation. It is only sensitive to the portion of the vector parallel to the propagation path. We show how to remotely detect the portion of the vector that is perpendicular using a modified measurement. Isolating this electromagnetic propagation wave mode to measure the magnetic field enables us to (i) study more about the magnetic field vector in plasma, (ii) reduce error in total electron content measurements, and (iii) discover new magnetic field information from archived data sets. The Appleton–Hartree equation is used to verify a new approach to calculating the phase change to an electromagnetic wave propagating through a plasma at frequencies larger than the gyrofrequency, the cyclotron frequency, and the upper hybrid frequency. Focusing on the perpendicular propagation modes, the simplified equation for the integrated path effect from a perpendicular magnetic field is calculated. The direction of the perpendicular component is unknown, because the magnetic field is squared. Isolating the magnetic term in the equation with dual frequency waves is shown. We also show how to eliminate the magnetic field contribution to total electron content measurements with a similar approach. In combination with Faraday rotation, the degeneracy of the magnetic field vector direction is reduced to a cone configuration.

Performance of the double-thin-shell approach for studying nighttime medium-scale traveling ionospheric disturbances using two dense GNSS observation networks in Japan

Electrodynamic coupling between the ionospheric E and F regions is widely recognized as the underlying mechanism for generating medium-scale traveling ionospheric disturbances (MSTIDs) during nighttime at midlatitudes. Recently, the double-thin-shell approach has proven to be a useful tool for studying the E–F coupling. By using total electron content (TEC) measurements, this approach enables the simultaneous reconstruction of electron density perturbations in both the E and F regions with broad and continuous coverage. However, the current reconstruction performance is limited when using only GPS-TEC measurements from GEONET, a dense network of ground-based Global Navigation Satellite System (GNSS) receivers over Japan. The expansion of available data sources and the integration of multi-GNSS observation data are considered important to enhance the double-thin-shell model. Fortunately, SoftBank Corp., a Japanese telecommunications provider, has recently developed a dense independent GNSS observation network to improve positioning services. In this paper, we analyze the potential of the improved double-thin-shell approach and emphasize the importance of incorporating multi-GNSS observation data from both GEONET and SoftBank networks. The solvability analysis, simulation, and observation results collectively indicate a substantial improvement in the spatiotemporal resolution. Specifically, the longitudinal and latitudinal resolution is improved from 0.15° to 0.1° in the E region, and from 0.5° to 0.3° in the F region. The temporal resolution is also improved from 2 to 1 min. In addition, significant improvements have been achieved in the reconstruction performance, particularly for the E region under complex background conditions. Based on these assessments, we conclude that the incorporation of GEONET and SoftBank GNSS observation data holds significant potential for improving the double-thin-shell model and advancing our understanding of MSTIDs.Graphical abstract

The capability of Artificial Neural Networks as a Model for Predicting Total Electron Content (TEC): A Review

The results of investigations from a complete analysis of ANN application on Total Electron Content (TEC) prediction are presented in this paper. TEC is important in defining the ionosphere and has many everyday applications, for example, satellite navigation, time delay and range error corrections for single frequency Global Positioning System (GPS) satellite signal receivers. The total electron content (TEC) in the ionosphere has been measured using GPS. GPS are not installed in every point on the earth to make global TEC measurements possible. As a result, it is crucial to have certain models that can aid to get data from places where there is not any in order to comprehend the global behavior of TEC. Neural Network (NN) models have been shown to accurately anticipate data patterns, including TEC. The capacity of neural networks to represent both linear and nonlinear relationships directly from the data being modeled is what makes them so powerful. The survey from literature reveals that, Levenberg-Marquardt algorithm is preferred and used mostly because of its speed and efficiency during learning process, and that ANN showed a good prediction of TEC compared to the IRI model. As a result, NNs are suitable for forecasting GPS TEC values at various locations if the model's input parameters are well specified.

Ground and Space-based response of the ionosphere during the geomagnetic storm of 02–06 November 2021 over the low-latitudes across different longitudes

The strong geomagnetic storm of class G3 that occurred on 03 November 2021 (Dst min = −118 nT, Kp = 8) was the first of this class recorded during the ascending phase of solar cycle 25. In this study, we examined the response of the ionosphere during the geomagnetic storm period from 02–06 November 2021 using the Total Electron Content (TEC) observations from a chain of Global Navigation Satellite System (GNSS) receiver stations in five longitudinal sectors i.e, Asian, East-African, West-African, South-American, and Pacific-west sectors, in the low-latitudes and space-based Swarm satellite electron density, Ne and TEC measurements. The Rate of Change of TEC Index (ROTI) was derived from the ground and space based TEC measurements to examine the occurrence of ionospheric irregularities. The Rate of change of electron density index (RODI) was also derived from Swarm Ne measurements to identify the occurrence of ionospheric irregularities at Swarm altitudes. A positive ionospheric storm effect was observed in all the longitudinal sectors considered in this study. A clear hemispherical asymmetry, with higher VTEC in the northern hemisphere was observed. The determining factors for ionospheric responses to this storm are; local time of the storm’s onset, local time of storm’s minimum SYM-H, and changes in thermospheric O/N2 ratio. These geomagnetic storm effects were discussed in terms of the Prompt Penetration Electric Field (PPEF) storm induced wind lifting effect and Disturbance Dynamo Electric Field (DDEF). The geomagnetic storm inhibited the occurrence of ionospheric irregularities in all the sectors, during the main phase, except for three IGS receiver stations in South American sector. Overall, a longitudinal dependence of the enhancement/inhibition of ionospheric irregularities was observed. The generation of post-sunset irregularities was attributed to the local time occurrence of maximum ring current, PPEF and DDEF.

IONOSPHERIC TEMPORAL-SPATIAL CORRELATION ANALYSIS USING GNSS NETWORKS OVER CHINA

Abstract. The Global Navigation Satellite System (GNSS) is well recognized as a valuable tool for studying ionospheric variation, providing a means to measure variations in the Total Electron Content (TEC) of the ionosphere. In this manuscript, we focus specifically on the use of GNSS networks to study ionospheric diurnal variation over China, highlighting some of the key findings and challenges in this area. We begin by describing the basic principles of GNSS-based TEC measurements. We then analyze ionospheric diurnal variation using about 320 GNSS stations in China, including the Southern, Middle, and Northern areas. We also discuss some of the challenges associated with GNSS-based TEC measurement and analysis, such as the effects of receiver and satellite biases and understanding of spatial–temporal TEC variation. Finally, we highlight the sunset enhancement and scintillation of GNSS-based ionospheric diurnal variation research. Overall, this abstract provides a valuable overview of the use of GNSS networks for studying ionospheric diurnal variation and its potential applications for improving space weather forecasting and mitigating the effects of ionospheric disturbances on GNSS-based navigation systems.

Co-seismic ionospheric disturbances due to 2004 Sumatra-Andaman earthquake

The Coseismic Ionospheric Disturbances (CID) due to the 26th December 2004 earthquake of Mw 9.2, which occurred in the Sumatra-Andaman subduction zone, are analyzed using cGPS-aided Total Electron Content (TEC) measurements. For the CID analysis, data from nearby seven Sumatran GPS Array (SuGAr) and two International GNSS Stations (IGS) located to the south of the epicenter, at a distance of 500–1000km (near-field) and two IGS stations located to the north-west of the epicenter at a distance of 2000km (far-field) are considered. The CIDs with a propagation velocity of 595–694m/s arrived within 2–10min after the earthquake, depending upon the distance of a station from the epicentre. Variations in the CIDs can be prominently seen at the nearest cGPS Station SAMP immediately after the earthquake. NTUS, being the farthest station shows some small variations. The delay in the occurrence of variations at GPS sites can also be associated with rupture propagation. Because all the stations used in our analysis are located south of the epicenter and rupture of the earthquake propagated in the north, the trend of rupture propagation could not be analyzed clearly.

Performance evaluation for vertical TEC predictions over the East Africa and South America: IRI-2016 and IRI-2020 versions

In this paper, we evaluate and report the International Reference Ionosphere (IRI) model's vertical Total Electron Content (TEC) regional profile. Diurnal, monthly, seasonal, and storm-time characteristics of IRI estimates over the equatorial region's ionosphere are validated. We compared the vertical TEC derived from IRI-2020 and its predecessor, IRI-2016, with the GPS-TEC measurements. Results show that IRI (both versions) agrees with observed TEC during solar cycle maximum periods. Exceptionally, over Turkwel station, IRI-2020 produced double peak profiles on the March equinox, June solstice, and September equinox and overestimated with larger discrepancies. Over the other three stations, both IRI versions reproduced the seasonal averaged observed TEC with only slight time lags and discrepancies. During geomagnetically perturbed times, IRI-2020 better indicated positively enhanced GPS-TEC than IRI-2016. However, during the March 17, 2015 storm, IRI-2020 underestimated the storm-enhanced TEC over Bahir Dar station at all phases of the storm. IRI-2016 shows good performances for negative storms where lower TEC measurements are recorded.

Analysis of GPS-TEC and IRI model over equatorial and EIA stations during solar cycle 24

Total Electron Content (TEC) measurements provided by Global Positioning System (GPS) as well as the International Reference Ionosphere – 2016 model (IRI01-Corr, IRI-2001, and NeQuick) model were compared at two Indian GPS stations: equatorial station Bangalore (12.580N, 77.350 E) and equatorial ionization anomaly (EIA) station Lucknow (26.500N, 80.550 E) during the solar cycle 24 extending from 2007 to 2017. The spectral, regression and statistical analysis displays a double-hump shape with counterclockwise hysteresis within TEC. The solar flux along with the TEC showed erratic as well as sluggish trends throughout the increasing period and flat and rapid throughout the decreasing period of the solar cycle 24. The semiannual and winter anomaly is discovered to be a constant feature throughout the solar cycle. The main idea of the current study is to investigate the performance of IRI01-Corr, IRI-2001, and NeQuick TEC in contrast to GPS TEC data throughout solar cycle 24 at the Indian equatorial and EIA stations. The modeled TEC data exhibit almost complete agreement with the measurement highlighting the same trends in the solar cycle as well as semiannual and seasonal changes. However, there are clear biases between the observed and modeled TECs when local time, seasons, as well as solar activity phases are considered. The main findings of this paper are that the NeQuick model generally underestimates noon-time TEC while the IRI-2001 model overestimates the same. The error in estimating noontime TEC from the IRI model using IRI-2001 as a topside at the EIA station is higher (142 %) than that at the equatorial station (42 %).

Rapid Detection of Co‐Seismic Ionospheric Disturbances Associated With the 2015 Illapel, the 2014 Iquique and the 2011 Sanriku‐Oki Earthquakes

AbstractCo‐seismic Ionospheric disturbances (CID, or “ionoquakes”) are disturbances in the electron density or total electron content (TEC) of the ionosphere, produced by the ground motion due to earthquakes. Usually, ionoquakes are detected in the near‐epicentral region within 8–10 min after an earthquake onset time. In this work, we present a new methodology that allows to estimate the CID arrival time based on determining the CID peak time in TEC measurements with respect to the peak time of seismic waves registered by the nearest seismic station. Our methodology also allows to understand the altitude of GNSS detection that otherwise remains ambiguous. We apply the newly developed techniques to detect CID signatures associated with three large earthquakes: the 2015 Illapel, the 2014 Iquique, and the 2011 Sanriku‐Oki. We show that for these events, the CID arrive 250–430 s after the time of the seismic wave peak, or 350–700 s after the earthquake onset time. Our analysis show that the first CID are detected at the altitudes of 150–180 km (the Sanriku earthquake) and of 200–300 km (the Illapel and the Iquique earthquakes). The disturbances represent high‐frequency acoustic oscillations that propagate with a horizontal speed faster than 0.75 km/s.

Optimal Estimation Inversion of Ionospheric Electron Density from GNSS-POD Limb Measurements: Part II-Validation and Comparison Using NmF2 and hmF2

A growing number of SmallSat/CubeSat constellations with high-rate (50–100 Hz) global navigation satellite system radio occultations (GNSS-RO) as well as low-rate (1 Hz) precise orbit determination (GNSS-POD) limb-viewing capabilities provide unprecedented spatial and temporal sampling rates for ionospheric studies. In the F-region electron density (Ne) retrieval process, instead of the conventional onion-peeling (OP) inversion, an optimal estimation (OE) inversion technique was recently developed using total electron content measurements acquired by GNSS-POD link. The new technique is applied to data acquired from the COSMIC-1, COSMIC-2, and Spire constellations. Although both OE and OP techniques use the Abel weighting function in Ne inversion, OE significantly differs in its performance, especially in the lower F- and E-regions. In this work, we evaluate and compare newly derived data sets using F2 peak properties with other space-based and ground-based observations. We determine the F2 peak Ne (NmF2) and its altitude (hmF2), and compare them with the OP-retrieved values. Good agreement is observed between the two techniques for both NmF2 and hmF2. In addition, we also utilize autoscaled F2 peak measurements from a number of worldwide Digisonde stations (∼30). The diurnal sensitivity and latitudinal variability of the F2 peak between the two techniques are carefully studied at these locations. Good agreement is observed between OE-retrieved NmF2 and Digisonde-measured NmF2. However, significant differences appear between OE-retrieved hmF2 and Digisonde-measured hmF2. During the daytime, Digisonde-measured hmF2 remains ∼25–45 km below the OE-retrieved hmF2, especially at mid and high latitudes. We also incorporate F-region Ne measurements from two incoherent scatter radar observations at high latitudes, located in the North American (Millstone Hill) and European (EISCAT at Tromso) sectors. The radar measurements show good agreement with OE-retrieved values. Although there are several possible sources of error in the ionogram-derived Ne profiles, our further analysis on F1 and F2 layers indicates that the low Digisonde hmF2 is caused by the autoscaled method, which tends to detect a height systematically below the F2 peak when the F1 layer is present.

On estimating the phase scintillation index using TEC provided by ISM and IGS professional GNSS receivers and machine learning

Amplitude and phase scintillation indexes (S4 and σϕ) provided by Ionospheric Scintillation Monitoring (ISM) receivers are the most used GNSS-based indicators of the signal fluctuations induced by the presence of ionospheric irregularities. These indexes are available only from ISM receivers which are not as abundant as other types of professional GNSS receivers, resulting in limited geographic distribution. This makes the scintillation indexes measurements rare and sparse compared to other types of ionospheric measurements available from GNSS receivers. Total Electron Content (TEC), on the other hand, is an ionospheric parameter available from a wide range of multi-frequency GNSS receivers. Many efforts have worked on establishing scintillation indicators based on TEC, and geodetic receivers in general, introducing various metrics, including the Rate of TEC change (ROT) and ROT Index (ROTI). However, a possible relationship between TEC and its variation, and the corresponding scintillation index that an Ionospheric Scintillation Monitor (ISM) receiver would estimate is not trivial. In principle, TEC can be retrieved from carrier phase measurements of the GNSS receiver, as σϕ. We investigate how to estimate σϕ from time series of TEC and ROT measurements from an ISM in Ny-Ålesund (Svalbard) using Machine Learning (ML). To evaluate its usability to estimate σϕ from geodetic receivers, the model is tested using TEC data provided by a quasi-co-located geodetic receiver belonging to the International GNSS Service (IGS) network. It is shown that the model performance when TEC from the IGS receiver is used gives comparable results to the model performance when TEC from the ISM receiver is utilised. The model's ability to infer the exact value of the scintillation index is bound to Mean Square Error (MSE) = 0.1 radians2 when σϕ≤0.8 radians. For σϕ>0.8 the MSE reaches 0.18 and 0.45 radians2 in operative testing using ISM and IGS measurements, respectively. However, the model’s ability to detect phase scintillation from IGS TEC measurements is comparable to expert visual inspection. Such a model has potential in alerting against phase fluctuations resulting in enhanced σϕ, especially in locations where ISM receivers are not available, but other types of dual-frequency GNSS receivers are present.