Rate Of TEC Index Research Articles

Storm‐Time Subauroral Ionospheric Plasma Density Irregularities and the Substorm Current Wedge

AbstractWe report on the development of plasma density irregularities in the subauroral ionosphere over the North American sector during the 17 March 2015 Saint Patrick's Day geomagnetic storm. Data from network of ground‐based observation instruments including the National Oceanic and Atmospheric Administration Continuously Operating Reference Station global navigation satellite system receivers and Time History of Events and Macroscale Interactions during Substorms (THEMIS) all‐sky imagers, as well as in situ measurements from the Defense Meteorological Satellite Program (DMSP) and the Van Allen Radiation Belt Storm Probes (RBSP) spacecrafts, were examined to characterize the spatial and temporal development of subauroral irregularities. The auroral electrojet (AE) index was used as primary indicator of substorm occurrences, aided by some cross‐referencing with the SYM‐H index and SYM‐H time derivative. Special attention was given to substorms that happened at the beginning of this geomagnetic storm. Analysis of Global Positioning System (GPS) rate‐of‐total electron content index (ROTI) data along an east‐west cut line near the US‐Canada border indicates that subauroral ionospheric irregularities may start to form as early as a few minutes after a substantial increase in the AE index. Contemporaneous DMSP and RBSP observations confirmed the presence of subauroral polarization streams wave structures when the aforementioned enhancement in AE index and GPS ROTI occurred. An equatorward expansion of bright auroral arc and subsequent auroral breakups were also seen in the THEMIS all‐sky imager observation data. The relatively short time scales for irregularities to develop suggest possible roles played by the penetration of magnetotail plasma flow bursts into the plasmasphere and the substorm current wedge development in their formation in the subauroral ionosphere.

Occurrence of Nighttime Irregularities and Their Scale Evolution in the Ionosphere Due To the Solar Eclipse Over East Asia on 21 June 2020

AbstractSolar eclipse is a daytime phenomenon that significantly disturbs the ionosphere, but whether the eclipse induces ionospheric irregularities in the nighttime remains unknown. In this study, we analyzed the dense total electron content (TEC) observations from the ground‐based Global Navigation Satellite System receivers over East and South Asia to examine the development of the irregularities in the nighttime on the day of the 21 June 2020 annular solar eclipse. The rate of TEC index (period <5 min) indicates the occurrence of the irregularities that evolve from the large or coarse structures with a period ranging from hours to dozens of minutes in the nighttime due to the eclipse. We take advantage of the data‐adaptive analysis method, Hilbert‐Huang transform, to derive the instantaneous amplitude and frequency of the TEC time series, which exposes the temporal and spatial evolutions of the irregularities from larger structures continuously.

Study of Ionosphere Irregularities over the Iberian Peninsula during Two Moderate Geomagnetic Storms Using GNSS and Ionosonde Observations

Studies on the irregularities of the ionosphere during disturbed geomagnetic conditions are fundamental to understanding the complex dynamics taking place in the upper atmosphere. In this work, different data sources are used to study the ionosphere effects of two moderate geomagnetic storms, 26–27 February 2014 and 17–18 September 2021, over the Iberian Peninsula. Data are obtained from digital ionosondes in Spain, Italy and Greece; the Global Navigation Satellite System (GNSS) derived Total Electron Content (TEC) and Rate Of TEC Index (ROTI) from several receiver stations in Spain, Portugal and Morocco; and the UPC Quarter-of-an-hour time resolution Rapid GIM (UQRG), vertical TEC global ionosphere maps (GIMs), produced at 15 min intervals by the Universitat Politecnica de Catalunya (UPC, Spain). This analysis showed that, during the two moderate storms, spread-F and high values of ROTI, indicating the presence of irregularities, are found in a very localized area (Southern Iberian Peninsula and northwest Africa) and local times (night-time). However, no irregularities are found eastwards and northwards of the location indicated. We propose some possible explanations for these observations for both the storms, one of them related to the position of the Equatorial Ionosphere Anomaly (EIA) and the other one attributed to the Perkins’ instabilities.

Equatorial Plasma Bubbles Identification with Single Frequency GNSS Receiver Data

Ionosphere is the highest contributor of positional error in Global Navigation Satellite System (GNSS) owing to the trans-ionospheric signal delay, distortion and possible outage. Equatorial and Low latitudinal ionosphere experiences frequent perturbations in plasma density most of which is due to the presence of Equatorial Plasma Bubbles (EPBs). In order to improve positional and navigational precision of GNSS signals, EPBs must be identified and corrected. EPBs begin to manifest post-sunset and continue to thrive past midnight. This paper proposes a Rate of TEC Index (ROTI) based EPB identifier using single frequency GNSS receiver data. GNSS data has been collected from the archives of Scripps Orbit and Permanent Array Center (SOPAC). The raw data has been downloaded from the global continuous network station, IISC, located at Bangalore (13.0219°N, 77.5671°E) in Receiver Independent Exchange (RINEX) format. Analysis of EPB occurrence has been carried out for six consecutive years in the second half of the 24th solar cycle (2014-2019). The results show a clear surge in the number of EPBs identified in the course of equinoxes.

A Retrospective of Global Navigation Satellite System Ionospheric Irregularities Monitoring Networks in Brazil

The use of Global Navigation Satellite System (GNSS) for air and terrestrial navigation and for many applications is increasing in the last decades. However, the Earth’s ionosphere causes GNSS signal delay due to the total electron content (TEC) and scintillation in the signal phase and amplitude. This scintillation can give rise to deleterious effects in the GNSS positioning. So, it is important to assess the effects of the ionosphere over the GNSS signal. To achieve this goal, it is necessary to have a large spatial and temporal coverage of data from many different sounders, being the GNSS receivers of great importance due to their global coverage and availability. In this work, we present a retrospective of the scintillation monitoring networks in Brazil and their characteristics. As the RBMC network managed by the IBGE provides TEC and as rate of TEC index (ROTI) is well correlated with ionospheric irregularities, we present also the RBMC network description. These RBMC GNSS receivers provide data in regions with scarcity of scintillation monitors. The description of the Ionospheric Scintillation Monitoring Receivers (ISMR) Query Tool, that is a web software that has been supporting research on the ISMR data, is also presented.

Auroral Oval Boundary Dynamics on the Nature of Geomagnetic Storm

During emergency events, we could significantly depend on the stable operation of radio communication, navigation, and radars. The ionosphere, especially its auroral regions, significantly influences radio systems, which is why scientists and engineers create systems to monitor these regions. Using data from the global GNSS network, we analyzed the 10 strongest magnetic storms of solar cycle 24: five coronal mass ejection-driven (CME-driven) and five high-speed stream-driven (HSS-driven) storms. The analysis was based on the calculation of the standard deviation of the total electron content (TEC) derivative (rate of TEC index, ROTI). Under all the storms, the ROTI featured similar dynamics: the average ROTI reaches the highest values during the main phase, and the higher the intensity is, the more intense and equatorward the average ROTI registered. The highest cross-correlations are observed with a lag of 1 h, between the IMF z-component Bz and the magnetic latitude where the highest ROTI values appear. The auroral electrojet (SME index) shows the highest impact on the ROTI dynamics. An increase in the space weather indices (in absolute value) is accompanied by a decrease in the latitude where the maximal ROTI occurs. We found that the peculiarities of a storm affect the ROTI dynamics: all the CME-driven storms feature a high cross-correlation (>0.75) between the IMF z-component Bz and the magnetic latitude where the highest ROTI appears, while the HSS-driven storms feature a lower cross-correlation (<0.75) between them. The difference in duration of similar (by maximal values of geomagnetic indices) HSS- and CME-driven storms could produce differences in the highest ROTI values. Correlations show that compared to HSS-driven storms, CME-driven ones more directly impact the ROTI values and locations of regions with a high ROTI.

ROTI Keograms based on CMONOC to characterize the ionospheric irregularities in 2014

Ionospheric irregularities have been studied since ~ 70 years ago. With the development of Global Navigation Satellite system (GNSS), networks of GNSS receivers have been used to obtain the characteristics of the irregularities, including the drift velocity, the structure, and the evolution. In this paper, keograms based on the Crustal Movement Observation Network of China (CMONOC) were used to characterize the irregularities over the area from longitude 85 to 125 °E and latitude 11 to 35 °N in 2014. Keograms were obtained for the rate of TEC index (ROTI) for every 0.5 degree longitude and 30 min universal time pixel. The results showed that the occurrence rate of irregularities in 2014 was high in the equinox months and December, and lowest in June. In equinox months the irregularities often appeared after sunset. In March the irregularities usually had long lifetime of ~ 5–7 h and ~ 5 degrees apparent longitudinal width. The long lifetime usually was accompanied by obvious eastward drift of ~ 100 m/s and large vertical ROTI (vROTI). In September the irregularities had weaker ROTI and shorter lifetime than those in March. The irregularities in the 2 equinox months should be related to the equatorial plasma bubbles (EPBs). In June, they appeared ~ 2–3 h later than those in equinoxes and drifted westward. The summer irregularities had weakest ROTI and their latitude was ~ 30 °N, much higher than those in equinoxes. In December, the irregularities were discrete patches with a longitudinal width of ~ 2 degrees and short lifetime of ~ 2 h. Unlike the equatorial irregularities in equinox months which are part of equatorial plasma bubbles, the solstice irregularities mainly appear to be a local phenomenon.Graphical

Comparative Study of Predominantly Daytime and Nighttime Lightning Occurrences and Their Impact on Ionospheric Disturbances

Space weather events adversely impact the operations of Global Navigation Satellite Systems (GNSS). Understanding space weather mechanisms, interactions in the atmosphere, and the extent of their impact are useful in developing prediction and mitigation models. In this study, the hourly lightning occurrence and its impact on ionospheric disturbances, quantified using the Rate of Total electron content Index (ROTI), were assessed. The linear correlation between diurnal lightning activity and ROTI in the coastal region of southern China where lightning predominates in the daytime was initially negative contrary to a positive correlation in southern Africa where lighting predominates in the evening. After appreciating and applying the physical processes of gravity waves, electromagnetic waves and the Trimpi effect arising from lightning activity, and the time delay impact they have on the ionosphere, the negative correlation was overturned to a positive one using cross-correlation. GNSS has demonstrated its capability of revealing the impact lightning has on the ionosphere at various times of the day.

ROTI‐Based Stochastic Model to Improve GNSS Precise Point Positioning Under Severe Geomagnetic Storm Activity

AbstractFor global navigation satellite system (GNSS), ionospheric disturbances caused by the geomagnetic storm can reduce the accuracy and reliability of precision point positioning (PPP). At present, common stochastic models in GNSS PPP, such as the elevation angle stochastic (EAS) model or carrier‐to‐noise power‐density ratio () based SIGMA‐ model, do not properly consider storm effects on GNSS measurements. To mitigate severe storm effects on GNSS PPP, this study further implements the rate of total electron content index (ROTI) parameter into the EAS model referred to as the EAS‐ROTI model. This model contains two operations. The first one is to adjust variance of GNSS measurements using ROTI observations on EAS model. The second one is to determine the ratio of the priori variance factor between pseudorange and carrier phase measurements during severe storm conditions. The performance of EAS‐ROTI model is verified by using a large number of international GNSS service stations datasets on 17 March and 23 June in 2015. Experimental results indicate that on a global scale, the EAS‐ROTI model improves the PPP accuracy in 3D direction by approximately 12.9%–14.7% compared with the EAS model, and by about 24.8%–45.9% compared with the SIGMA‐ model.

The Mechanism for GNSS‐Based Kinematic Positioning Degradation at High‐Latitudes Under the March 2015 Great Storm

AbstractIn this study, we focus on the kinematic precise point positioning (PPP) solutions at high‐latitudes during the March 2015 great geomagnetic storm. We aim to discover the mechanism behind the positioning degradation from the perspective of the impacts of the storm‐induced ionospheric disturbance on the global navigation satellite system (GNSS) data processing. We observed that the phase scintillation dominated the amplitude scintillation at high‐latitudes and the variation pattern of the rate of total electron content index (ROTI) was consistent with that of the phase scintillation during the storm. The kinematic PPP errors at high‐latitudes were almost three times larger than those at the middle‐ and low‐latitude, which were accompanied by large ROTI variations. From the perspective of GNSS data processing, the large positioning errors were also found to be related to the large number of satellites experiencing cycle slips (CSs). Based on the lock time from the ionospheric scintillation monitoring receiver, we found that a large amount of the CSs was falsely detected under the conventional threshold of the CS detector. By increasing such threshold, the kinematic positioning accuracy at high‐latitudes can be improved to obtain similar magnitude as at middle‐ and low‐latitude. The improved positioning accuracy may suggest that the ionospheric disturbance induced by the geomagnetic storm at high‐latitudes has minor effects on triggering the CSs. Therefore, precise positioning can be achieved at high‐latitudes under geomagnetic storms, given that the CS problem is well addressed.

Findings of the unusual plasma bubble occurrences at dawn during the recovery phase of a moderate geomagnetic storm over the Brazilian sector

In this work, we observe for the first time the unusual pre-sunrise Equatorial Plasma Bubbles (EPBs) during a moderate geomagnetic storm recovery phase caused by the High-Speed Solar Wind Stream (HSS) on February 17, 2015, over the Brazilian sector. Therefore, this study aims to explain the generation mechanism of this uncommon event, which started at 08:00 UT on February 18, 2015. We used Multiple Global Navigation Satellite Systems (Multi-GNSS, GPS, and GLONASS) data to produce two-dimensional maps of the Rate Of TEC index (ROTI) that show EPB features elongated in magnetic meridians. Also, Digisonde data from São Luís (2.53° S, 44.30° W, dip angle: 8.57°), Boa Vista (12.81° N, 60.67° W, dip angle: 33.71°), and Campo Grande (20.44° S, 54.64° W, dip angle: 25.98°), and magnetometer data at São Luís and Eusébio (3.89° S, 38.45° W, dip angle: 17.96°). Our analysis shows that the unusual pre-sunrise plasma bubbles lasted longer after sunrise, around 1 h. Finally, we showed that these EPBs are likely driven by a disturbance wind dynamo effect, which helps to understand the role of the external factors in EPBs development.

Ionospheric irregularities during disturbed geomagnetic conditions over Argentinian EIA region

Ionospheric irregularities can severely degrade radio communication and navigation systems. Geomagnetic storms may affect the generation of these irregularities in a way that is not yet fully understood. To improve the forecasting of this phenomenon, we need to study the ionosphere in different regions of the world, and in particular in the equatorial ionization anomaly (EIA) where irregularities are usually more intense. This study analyses the effect of geomagnetic storms on ionospheric irregularities. We examined the occurrence of irregularities at the southern crest of the EIA in Argentina (Tucumán, 26.9°S, 294.6°E, dip latitude 15.5°S) during three intense and one moderate geomagnetic storm of different solar sources, between 2015 and 2018. We used data from an ionosonde, a Global Positioning System receiver and magnetometers. Ionogram spread-F, the F-layer bottom side (h'F), the critical frequency of the F2-layer (foF2), the rate of TEC index and the S4 scintillation index were analysed. The data show irregularities were present as range spread-F and moderate TEC fluctuations in one storm: 27 May 2017 (a coronal mass ejection CME-driven storm occurred on local winter), and were absent in the other events. We suggest that eastward disturbance dynamo electric field and over-shielding prompt penetration electric fields may create favourable conditions for developing these irregularities, whereas westward storm time electric fields might inhibit the growth of irregularities during the other storms considered. During co-rotating interaction region CIR-driven storms, the westward disturbance dynamo electric field may be associated with the non-occurrence of irregularities.

Spatial and Temporal Distributions of Ionospheric Irregularities Derived from Regional and Global ROTI Maps

Major advancements in the monitoring of both the occurrence and impacts of space weather can be made by evaluating the occurrence and distribution of ionospheric disturbances. Previous studies have shown that the fluctuations in total electron content (TEC) values estimated from Global Navigation Satellite System (GNSS) observations clearly exhibit the intensity levels of ionospheric irregularities, which vary continuously in both time and space. The duration and intensity of perturbations depend on the geographic location. They are also dependent on the physical activities of the Sun, the Earth’s magnetic activities, as well as the process of transferring energy from the Sun to the Earth. The aim of this study is to establish ionospheric irregularity maps using ROTI (rate of TEC index) values derived from conventional dual-frequency GNSS measurements (30-s interval). The research areas are located in Southeast Asia (15°S–25°N latitude and 95°E–115°E longitude), which is heavily affected by ionospheric scintillations, as well as in other regions around the globe. The regional ROTI map of Southeast Asia clearly indicates that ionospheric disturbances in this region are dominantly concentrated around the two equatorial ionization anomaly (EIA) crests, occurring mainly during the evening hours. Meanwhile, the global ROTI maps reveal the spatial and temporal distributions of ionospheric scintillations. Within the equatorial region, South America is the most vulnerable area (22.6% of total irregularities), followed by West Africa (8.2%), Southeast Asia (4.7%), East Africa (4.1%), the Pacific (3.8%), and South Asia (2.3%). The generated maps show that the scintillation occurrence is low in the mid-latitude areas during the last solar cycle. In the polar regions, ionospheric irregularities occur at any time of the day. To compare ionospheric disturbances between regions, the Earth is divided into ten sectors and their irregularity coefficients are calculated accordingly. The quantification of the degrees of disturbance reveals that about 58 times more ionospheric irregularities are observed in South America than in the southern mid-latitudes (least affected region). The irregularity coefficients in order from largest to smallest are as follows: South America, 3.49; the Arctic, 1.94; West Africa, 1.77; Southeast Asia, 1.27; South Asia, 1.24; the Antarctic, 1.10; East Africa, 0.89; the Pacific, 0.32; northern mid-latitudes, 0.15; southern mid-latitudes, 0.06.

A ROTI-Aided Equatorial Plasma Bubbles Detection Method

In this study, we present a Rate of Total Electron Content Index (ROTI)-aided equatorial plasma bubbles (EPBs) detection method based on a Global Navigation Satellite System (GNSS) ionospheric Total Electron Content (TEC). This technique seeks the EPBs occurrence time according to the ROTI values and then extracts the detrended ionospheric TEC series, which include EPBs signals using a low-order, partial polynomial fitting strategy. The EPBs over the Hong Kong area during the year of 2014 were detected using this technique. The results show that the temporal distribution and occurrence of EPBs over the Hong Kong area are consistent with that of previous reports, and most of the TEC depletion error is smaller than 1.5 TECU (average is 0.63 TECU), suggesting that the detection method is feasible and highly accurate. Furthermore, this technique can extract the TEC depletion series more effectively, especially for those with a long duration, compared to previous method.

Machine Learning Prediction of Storm‐Time High‐Latitude Ionospheric Irregularities From GNSS‐Derived ROTI Maps

AbstractThis study presents an image‐based convolutional long short‐term memory (convLSTM) machine learning algorithm to predict storm‐time ionospheric irregularities. Unlike existing methods that are either focused on irregularities at individual locations or treat the irregularity prediction as a classification problem, the convLSTM‐based architecture forecasts an entire regions' ionospheric irregularity occurrence and intensity values. We implemented the convLSTM‐based model with a custom‐designed loss function (convLSTM‐Lc) that includes a dynamic penalty on the difference between the truth and the predicted rate of total electron content index (ROTI) maps. The convLSTM‐Lc is trained with real ROTI data collected during January 1–August 7, 2015 from ∼550 global navigation satellite system receivers located in (45°–90°N, 0°–180°W). Test results show that the convLSTM‐Lc algorithm can forecast irregularity structures more accurately than a convLSTM model that implements conventional loss functions. The model also outperforms the convLSTM‐L1, convLSTM‐L2, and persistence models according to statistical classification metrics with a lead time of up to 60 min.

Evidence for the In‐Situ Generation of Plasma Depletion Structures Over the Transition Region of Geomagnetic Low‐Mid Latitude

AbstractOn a geomagnetic quiet night of October 29, 2018, we captured an observational evidence of the onset of dark band structures within the field‐of‐view of an all‐sky airglow imager operating at 630.0 nm over a geomagnetic low‐mid latitude transition region, Hanle, Leh Ladakh. Simultaneous ionosonde observations over New Delhi shows the occurrence of spread‐F in the ionograms. Additionally, virtual and peak height indicate vertical upliftment in the F layer altitude and reduction in the ionospheric peak frequency were also observed when the dark band pass through the ionosonde location. All these results confirmed that the observed depletions are indeed associated with ionospheric F region plasma irregularities. The rate of total electron content index (ROTI) indicates the absence of plasma bubble activities over the equatorial/low latitude region which confirms that the observed event is a mid‐latitude plasma depletion. Our calculations reveal that the growth time of the plasma depletion is ∼2 h if one considers only the Perkins instability mechanism. This is not consistent with the present observations as the plasma depletion developed within ∼25 min. By invoking possible Es layer instabilities and associated E‐F region coupling, we show that the growth rate increases roughly by an order of magnitude. This strongly suggests that the Cosgrove and Tsunoda mechanism may be simultaneously operational in this case. Furthermore, it is also suggested that reduced F region flux‐tube integrated conductivity in the southern part of onset region created conducive background conditions for the growth of the plasma depletion on this night.

Evaluation of Different Methods for Calculating the ROTI Index Over the Brazilian Sector

AbstractIonospheric irregularities as plasma bubbles occur in the ionosphere, and generally, they are characterized by the low plasma density regions. The Rate Of TEC Index (ROTI) was defined in terms of the Total Electron Content (TEC) variation and is used to characterize these plasma bubbles. It is essential to evaluate the ROTI behavior since the ionospheric irregularities can cause fluctuations in the radio signal, interfering in the ionospheric data analysis. Therefore, we performed in this work a comparative study of five different methods available to calculate the ROTI to evaluate the most suitable over the Brazilian region. The ROTI was calculated over three GNSS stations at different latitudes: São Luís (SALU, 2°31′S, 44°16′W; dip: −3.8°), Cachoeira Paulista (CHPI, 22°40'S, 44°59'W; dip: −36.4°), and Santa Maria (SMAR, 29°41′S, 53°48′W, dip: −37°). The results show that the most viable method for calculating ROTI in the Brazilian region is based on the Slant TEC equation as defined by Cherniak et al. (2018), https://doi.org/10.1007/s10291‐018‐0730‐1. Our results are supported by the comparison between the ROTI with TEC maps, ionograms collected at Fortaleza (FZA0M, 3°43'S, 38°32'W, dip: −15.8°), SALU, and CHPI and All‐Sky imagers collected at the São João do Cariri (SJCA, 7°23'S, 36°31'W, dip: −11°) and CHPI. Additionally, we observe Equatorial Plasma Bubbles (EPBs) in the Brazilian region using the ROTI index map.

Tropospheric dispersive phase anomalies during heavy rain detected by L-band InSAR and their interpretation

The split-spectrum method (SSM) can largely isolate and correct for the ionospheric contribution in the L-band interferometric synthetic aperture radar (InSAR). The standard SSM is performed on the assumption of only the first-order ionospheric dispersive effect, which is proportional to the total electron content (TEC). It is also known that during extreme atmospheric events, either originated from the ionosphere or in the troposphere, other dispersive effects do exist and potentially provide new insights into the dynamics of the atmosphere, but there have been few detection reports of such signals by InSAR. We apply L-band InSAR into heavy rain cases and examine the applicability and limitation of the standard SSM. Since no events such as earthquakes to cause surface deformation took place, the non-dispersive component is apparently attributable to the large amount of water vapor associated with heavy rain, whereas there are spotty anomalies in the dispersive component that are closely correlated with the heavy rain area. The ionosonde and Global Navigation Satellite System (GNSS) rate of total electron content index (ROTI) map both show little anomalies during the heavy rain, which suggests few ionospheric disturbances. Therefore, we interpret that the spotty anomalies in the dispersive component of the standard SSM during heavy rain are originated in the troposphere. While we can consider two physical mechanisms, one is runaway electron avalanche and the other is the dispersive effect due to rain, comparison with the observations from the ground-based lightning detection network and rain gauge data, we conclude that the rain dispersive effect is spatiotemporally favorable. We further propose a formulation to examine if another dispersive phase than the first-order TEC effect is present and apply it to the heavy rain cases as well as two extreme ionospheric sporadic-E events. Our formulation successfully isolates the presence of another dispersive phase during heavy rain that is in positive correlation with the local rain rate. In comparison with other dispersive phases during Sporadic-E episodes, the dispersive heavy rain phases seem to have the same order of magnitude with the ionospheric higher order effects.

Latitudinal, Diurnal, and Seasonal Variations in the Accuracy of an RTK Positioning System and Its Relationship With Ionospheric Irregularities

AbstractThe Norwegian Mapping Authority operates a network real time kinematic (RTK) system called CPOS, a positioning service providing centimeter level accuracy aimed at commercial users, for example, in civil engineering, excavation, and surveying. CPOS is based on multiple Global Navigation Satellite Systems (multi‐GNSS) in addition to base stations to provide correction data. CPOS position accuracy is subject to disturbances arising from space weather phenomena, which can disturb and disrupt GNSS signals. Studies have shown that CPOS performance is sensitive to the presence of plasma irregularities, usually quantified by the rate of change of total electron content index (ROTI). This study investigates the performance of CPOS over a 3‐year period, and its relationship with ionospheric irregularities. In a statistical analysis, we observe that CPOS position errors have seasonal, diurnal, and latitudinal variations. The most frequent position errors occur around magnetic noon and are of moderate severity, while the largest position errors occur around night‐time, agreeing well with climatology studies on GNSS scintillations. Additionally, we investigate ionospheric irregularities as characterized by the rate of TEC index (ROTI). We find that there is a significant correlation between CPOS accuracy and ROTI, but that there are also other contributing factors.

Ionospheric Scintillation Prediction on S4 and ROTI Parameters Using Artificial Neural Network and Genetic Algorithm

Irregularities in electron density usually correlate with ionospheric plasma perturbations. These variations causing radio signal fluctuations, in response, generate ionospheric scintillations that frequently occur in low-latitude regions. In this research, the combination of an artificial neural network (ANN) with the genetic algorithm (GA) was implemented to predict ionospheric scintillations. The GA method was considered for obtaining the ANN model’s initial weights. This procedure was applied to GNSS observations at GUAM (13.58°E, 144.86°N, 201.922H) station for the daily prediction of ionospheric amplitude scintillations via predicting the signal-to-noise ratio (S4) or via prediction of the rate of TEC index (ROTI). Thirty-day modeling was carried out for three months in January, March, and July, representing different seasons of the winter solstice, equinox, and summer solstice during three different years, 2015, 2017, and 2020, with different solar activities. The models, along with ionospheric physical data, were used for the daily prediction of ionospheric scintillations for the consequent day after the modeling. The prediction results were evaluated using S4 derived from GNSS observations at GUAM station. The designed model has the ability to predict daily ionospheric scintillations with an accuracy of about 81% for the S4 and about 80% for the ROTI.