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Journal articles on the topic 'Ionospheric modeling'
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1
Wang, Yafeng, Hu Wang, Yamin Dang, Hongyang Ma, Changhui Xu, Qiang Yang, Yingying Ren, and Shushan Fang. "BDS and Galileo: Global Ionosphere Modeling and the Comparison to GPS and GLONASS." Remote Sensing 14, no. 21 (October 31, 2022): 5479. http://dx.doi.org/10.3390/rs14215479.
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The ionospheric delay is one of the important error sources in the Global Navigation Satellite System (GNSS) data processing. With the rapid construction and development of GNSS, the abundant satellite resources have brought new opportunities for ionospheric monitoring. To further investigate the performances and abilities of Galileo and BDS in ionosphere modeling, we study the ionosphere modeling based on the 15th order spherical harmonic function, and 364 stations around the world are selected for global ionospheric modeling of GPS, GLONASS, Galileo and BDS systems under ionospheric quiet and active conditions, respectively. The results show that the average biases of the ionospheric models built by GPS, GLONASS and Galileo are relatively small, which are within 2 Total Electron Content Unit (TECU) as compared to the Center for Orbit Determination in Europe (CODE) global ionospheric map (GIM), while the average biases of the models built by BDS are between 6 and 8 TECU during the ionospheric quiet and active days, respectively. In addition, in order to analyze the modeling performances before and after using BDS geostationary earth orbit (GEO) satellites, BDS is divided into two groups, in which one group contains medium earth orbit (MEO), inclined geosynchronous orbit (IGSO) and GEO satellites; and the other group contains only MEO and IGSO satellites. The results show that the influence of GEO satellites on ionospheric modeling is less than 1 TECU. Due to the distribution of the stations, the 0-value region in the ionospheric model is mainly distributed in the mid and high-latitude regions of the southern hemisphere. Since the ionospheric parameters are lumped with the Differential Code Bias (DCB), we also estimate the DCB parameters and analyze their performances. The DCB estimated in ionosphere modeling shows strong stability, with the average biases of GPS, GLONASS, Galileo and BDS under 0.25 ns, 0.25 ns, 0.2 ns and 0.42 ns, respectively. We also estimate other DCB types of the four GNSS systems. The results show that the DCB is stable and shows consistency with Chinese Academy of Sciences (CAS) DCB products.
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Ким, Антон, Anton Kim, Елена Романова, Elena Romanova, Галина Котович, Galina Kotovich, Сергей Пономарчук, and Sergey Ponomarchuk. "Modeling z-shaped disturbance along the Pedersen ray of oblique sounding ionogram using adaptation of IRI to experimental data." Solar-Terrestrial Physics 2, no. 4 (February 2, 2017): 55–69. http://dx.doi.org/10.12737/24273.
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We present the results of numerical modeling of a traveling ionospheric disturbance that causes z-shaped bends at the Pedersen ray of oblique incidence ionograms. The results of trajectory synthesis of oblique incidence ionograms are given for the ionosphere, taking into account the traveling ionospheric disturbance. In the work, we use the International Reference Ionosphere, adapted to experimental data, and the Global Model of the Ionosphere and Plasmasphere.
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Su, Ke, and Shuanggen Jin. "Three Dual-Frequency Precise Point Positioning Models for the Ionospheric Modeling and Satellite Pseudorange Observable-Specific Signal Bias Estimation." Remote Sensing 13, no. 24 (December 15, 2021): 5093. http://dx.doi.org/10.3390/rs13245093.
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Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) enables the estimation the ionospheric vertical total electron content (VTEC) as well as the by-product of the satellite Pseudorange observable-specific signal bias (OSB). The single-frequency PPP models, with the ionosphere-float and ionosphere-free approaches in ionospheric studies, have recently been discussed by the authors. However, the multi-frequency observations can improve the performances of the ionospheric research compared with the single-frequency approaches. This paper presents three dual-frequency PPP approaches using the BeiDou Navigation Satellite System (BDS) B1I/B3I observations to investigate ionospheric activities. Datasets collected from the globally distributed stations are used to evaluate the performance of the ionospheric modeling with the ionospheric single- and multi-layer mapping functions (MFs), respectively. The characteristics of the estimated ionospheric VTEC and BDS satellite pseudorange OSB are both analyzed. The results indicated that the three dual-frequency PPP models could all be applied to the ionospheric studies, among which the dual-frequency ionosphere-float PPP model exhibits the best performance. The three dual-frequency PPP models all possess the capacity for ionospheric applications in the GNSS community.
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Håkansson, Martin. "Nadir-Dependent GNSS Code Biases and Their Effect on 2D and 3D Ionosphere Modeling." Remote Sensing 12, no. 6 (March 19, 2020): 995. http://dx.doi.org/10.3390/rs12060995.
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Recent publications have shown that group delay variations are present in the code observables of the BeiDou system, as well as to a lesser degree in the code observables of the global positioning system (GPS). These variations could potentially affect precise point positioning, integer ambiguity resolution by the Hatch–Melbourne–Wübbena linear combination, and total electron content estimation for ionosphere modeling from global navigation satellite system (GNSS) observations. The latter is an important characteristic of the ionosphere and a prerequisite in some applications of precise positioning. By analyzing the residuals from total electron content estimation, the existence of group delay variations was confirmed by a method independent of the methods previously used. It also provides knowledge of the effects of group delay variations on ionosphere modeling. These biases were confirmed both for two-dimensional ionosphere modeling by the thin shell model, as well as for three-dimensional ionosphere modeling using tomographic inversion. BeiDou group delay variations were prominent and consistent in the residuals for both the two-dimensional and three-dimensional case of ionosphere modeling, while GPS group delay variations were smaller and could not be confirmed due to the accuracy limitations of the ionospheric models. Group delay variations were, to a larger extent, absorbed by the ionospheric model when three-dimensional ionospheric tomography was performed in comparison with two-dimensional modeling.
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Jee, Geonhwa. "Fundamentals of Numerical Modeling of the Mid-latitude Ionosphere." Journal of Astronomy and Space Sciences 40, no. 1 (March 2023): 11–18. http://dx.doi.org/10.5140/jass.2023.40.1.11.
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The ionosphere is one of the key components of the near-Earth’s space environment and has a practical consequence to the human society as a nearest region of the space environment to the Earth. Therefore, it becomes essential to specify and forecast the state of the ionosphere using both the observations and numerical models. In particular, numerical modeling of the ionosphere is a prerequisite not only for better understanding of the physical processes occurring within the ionosphere but also for the specification and forecast of the space weather. There are several approaches for modeling the ionosphere, including data-based empirical modeling, physics-based theoretical modeling and data assimilation modeling. In this review, these three types of the ionospheric model are briefly introduced with recently available models. And among those approaches, fundamental aspects of the physics-based ionospheric model will be described using the basic equations governing the mid-latitude ionosphere. Then a numerical solution of the equations will be discussed with required boundary conditions.
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Романова, Елена, Elena Romanova, Галина Котович, Galina Kotovich, Сергей Пономарчук, Sergey Ponomarchuk, Антон Ким, and Anton Kim. "Modeling z-shaped disturbance along the Pedersen ray of oblique sounding ionogram using adaptation of IRI to experimental data." Solnechno-Zemnaya Fizika 2, no. 4 (December 20, 2016): 43–53. http://dx.doi.org/10.12737/21815.
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We present the results of numerical modeling of a traveling ionospheric disturbance that causes z-shaped bends at the Pedersen ray of oblique incidence ionograms. The results of trajectory synthesis of oblique incidence ionograms are given for the ionosphere, taking into account the traveling ionospheric disturbance. In the work, we use the International Reference Ionosphere, adapted to experimental data, and the Model of Ionosphere and Plasmasphere.
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Onohara, A. N., I. S. Batista, and H. Takahashi. "The ultra-fast Kelvin waves in the equatorial ionosphere: observations and modeling." Annales Geophysicae 31, no. 2 (February 7, 2013): 209–15. http://dx.doi.org/10.5194/angeo-31-209-2013.
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Abstract. The main purpose of this study is to investigate the vertical coupling between the mesosphere and lower thermosphere (MLT) region and the ionosphere through ultra-fast Kelvin (UFK) waves in the equatorial atmosphere. The effect of UFK waves on the ionospheric parameters was estimated using an ionospheric model which calculates electrostatic potential in the E-region and solves coupled electrodynamics of the equatorial ionosphere in the E- and F-regions. The UFK wave was observed in the South American equatorial region during February–March 2005. The MLT wind data obtained by meteor radar at São João do Cariri (7.5° S, 37.5° W) and ionospheric F-layer bottom height (h'F) observed by ionosonde at Fortaleza (3.9° S; 38.4° W) were used in order to calculate the wave characteristics and amplitude of oscillation. The simulation results showed that the combined electrodynamical effect of tides and UFK waves in the MLT region could explain the oscillations observed in the ionospheric parameters.
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DABBAKUTI, J. R. K. Kumar, D. Venkata RATNAM, and Surendra SUNDA. "MODELLING OF IONOSPHERIC TIME DELAYS BASED ON ADJUSTED SPHERICAL HARMONIC ANALYSIS." Aviation 20, no. 1 (April 11, 2016): 1–7. http://dx.doi.org/10.3846/16487788.2016.1162197.
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The ionosphere is the region of the upper atmosphere and the study of the upper atmosphere has a significant role in monitoring, modeling and forecasting for satellite based navigation services. As India lies in a low latitude region, a more careful approach has to be taken to characterize the ionosphere due to the irregularities and equatorial anomaly conditions. In order to study the ionospheric temporal variations, a regional ionospheric model based on the Adjusted Spherical Harmonic Analysis (ASHA) is implemented. The results indicate that the ASHA model is one of the contenders for estimating ionospheric delays well for GNSS augmentation systems.
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Danzer, J., S. B. Healy, and I. D. Culverwell. "A simulation study with a new residual ionospheric error model for GPS radio occultation climatologies." Atmospheric Measurement Techniques 8, no. 8 (August 21, 2015): 3395–404. http://dx.doi.org/10.5194/amt-8-3395-2015.
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Abstract. In this study, a new model was explored which corrects for higher order ionospheric residuals in Global Positioning System (GPS) radio occultation (RO) data. Recently, the theoretical basis of this new "residual ionospheric error model" has been outlined (Healy and Culverwell, 2015). The method was tested in simulations with a one-dimensional model ionosphere. The proposed new model for computing the residual ionospheric error is the product of two factors, one of which expresses its variation from profile to profile and from time to time in terms of measurable quantities (the L1 and L2 bending angles), while the other describes the weak variation with altitude. A simple integral expression for the residual error (Vorob’ev and Krasil’nikova, 1994) has been shown to be in excellent numerical agreement with the exact value, for a simple Chapman layer ionosphere. In this case, the "altitudinal" element of the residual error varies (decreases) by no more than about 25 % between ~10 and ~100 km for physically reasonable Chapman layer parameters. For other simple model ionospheres the integral can be evaluated exactly, and results are in reasonable agreement with those of an equivalent Chapman layer. In this follow-up study the overall objective was to explore the validity of the new residual ionospheric error model for more detailed simulations, based on modeling through a complex three-dimensional ionosphere. The simulation study was set up, simulating day and night GPS RO profiles for the period of a solar cycle with and without an ionosphere. The residual ionospheric error was studied, the new error model was tested, and temporal and spatial variations of the model were investigated. The model performed well in the simulation study, capturing the temporal variability of the ionospheric residual. Although it was not possible, due to high noise of the simulated bending-angle profiles at mid- to high latitudes, to perform a thorough latitudinal investigation of the performance of the model, first positive and encouraging results were found at low latitudes. Furthermore, first application tests of the model on the data showed a reduction in temperature level of the ionospheric residual at 40 km from about −2.2 to −0.2 K.
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Wang, Jin, Guanwen Huang, Peiyuan Zhou, Yuanxi Yang, Qin Zhang, and Yang Gao. "Advantages of Uncombined Precise Point Positioning with Fixed Ambiguity Resolution for Slant Total Electron Content (STEC) and Differential Code Bias (DCB) Estimation." Remote Sensing 12, no. 2 (January 17, 2020): 304. http://dx.doi.org/10.3390/rs12020304.
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The determination of slant total electron content (STEC) between satellites and receivers is the first step for establishing an ionospheric model. However, the leveling errors, caused by the smoothed ambiguity solutions in the carrier-to-code leveling (CCL) method, degrade the performance of ionosphere modeling and differential code bias (DCB) estimation. To reduce the leveling errors, an uncombined and undifferenced precise point positioning (PPP) method with ambiguity resolution (AR) was used to directly extract the STEC. Firstly, the ionospheric observables were estimated with CCL, PPP float-ambiguity solutions, and PPP fixed-ambiguity solutions, respectively, to analyze the short-term temporal variation of receiver DCB in zero or short baselines. Then, the global ionospheric map (GIM) was modeled using three types of ionospheric observables based on the single-layer model (SLM) assumption. Compared with the CCL method, the slight variations of receiver DCBs can be obviously distinguished using high precise ionospheric observables, with a 58.4% and 71.2% improvement of the standard deviation (STD) for PPP float-ambiguity and fixed-ambiguity solutions, respectively. For ionosphere modeling, the 24.7% and 27.9% improvements for posteriori residuals were achieved for PPP float-ambiguity and fixed-ambiguity solutions, compared to the CCL method. The corresponding improvement for residuals of the vertical total electron contents (VTECs) compared with the Center for Orbit Determination in Europe (CODE) final GIM products in global accuracy was 9.2% and 13.7% for PPP float-ambiguity and fixed-ambiguity solutions, respectively. The results show that the PPP fixed-ambiguity solution is the best one for the GIM product modeling and satellite DCBs estimation.
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Le, H., L. Liu, X. Yue, and W. Wan. "The ionospheric responses to the 11 August 1999 solar eclipse: observations and modeling." Annales Geophysicae 26, no. 1 (February 4, 2008): 107–16. http://dx.doi.org/10.5194/angeo-26-107-2008.
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Abstract. A total eclipse occurred on 11 August 1999 with its path of totality passing over central Europe in the latitude range 40°–50° N. The ionospheric responses to this eclipse were measured by a wide ionosonde network. On the basis of the measurements of foE, foF1, and foF2 at sixteen ionosonde stations in Europe, we statistically analyze the variations of these parameters with a function of eclipse magnitude. To model the eclipse effects more accurately, a revised eclipse factor, FR, is constructed to describe the variations of solar radiation during the solar eclipse. Then we simulate the effect of this eclipse on the ionosphere with a mid- and low-latitude ionosphere theoretical model by using the revised eclipse factor during this eclipse. Simulations are highly consistent with the observations for the response in the E-region and F1-region. Both of them show that the maximum response of the mid-latitude ionosphere to the eclipse is found in the F1-region. Except the obvious ionospheric response at low altitudes below 500 km, calculations show that there is also a small response at high altitudes up to about 2000 km. In addition, calculations show that when the eclipse takes place in the Northern Hemisphere, a small ionospheric disturbance also appeared in the conjugate hemisphere.
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Bi, Cheng, Peng Ren, Ting Yin, Zheng Xiang, and Yang Zhang. "Modeling and Forecasting Ionospheric foF2 Variation in the Low Latitude Region during Low and High Solar Activity Years." Remote Sensing 14, no. 21 (October 28, 2022): 5418. http://dx.doi.org/10.3390/rs14215418.
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Prediction of ionospheric parameters, such as ionospheric F2 layer critical frequency (foF2) at low latitude regions is of significant interest in understanding ionospheric variation effects on high-frequency communication and global navigation satellite system. Currently, deep learning algorithms have made a striking accomplishment in capturing ionospheric variability. In this paper, we use the state-of-the-art hybrid neural network combined with a quantile mechanism to predict foF2 parameter variations under low and high solar activity years (solar cycle-24) and space weather events. The hybrid neural network is composed of a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), in which CNN and BiLSTM networks extracted spatial and temporal features of ionospheric variation, respectively. The proposed method was trained and tested on 5 years (2009–2014) of ionospheric foF2 observation data from Advanced Digital Ionosonde located in Brisbane, Australia (27°53′S, 152°92′E). It is evident from the results that the proposed model performs better than International Reference Ionosphere 2016 (IRI-2016), long short-term memory (LSTM), and BiLSTM ionospheric prediction models. The proposed model extensively captured the variation in ionospheric foF2 feature, and better predicted it under two significant space weather events (29 September 2011 and 22 July 2012).
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Fuller-Rowell, T. J., M. C. Codrescu, and P. Wilkinson. "Quantitative modeling of the ionospheric response to geomagnetic activity." Annales Geophysicae 18, no. 7 (July 31, 2000): 766–81. http://dx.doi.org/10.1007/s00585-000-0766-7.
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Abstract. A physical model of the coupled thermosphere and ionosphere has been used to determine the accuracy of model predictions of the ionospheric response to geomagnetic activity, and assess our understanding of the physical processes. The physical model is driven by empirical descriptions of the high-latitude electric field and auroral precipitation, as measures of the strength of the magnetospheric sources of energy and momentum to the upper atmosphere. Both sources are keyed to the time-dependent TIROS/NOAA auroral power index. The output of the model is the departure of the ionospheric F region from the normal climatological mean. A 50-day interval towards the end of 1997 has been simulated with the model for two cases. The first simulation uses only the electric fields and auroral forcing from the empirical models, and the second has an additional source of random electric field variability. In both cases, output from the physical model is compared with F-region data from ionosonde stations. Quantitative model/data comparisons have been performed to move beyond the conventional "visual" scientific assessment, in order to determine the value of the predictions for operational use. For this study, the ionosphere at two ionosonde stations has been studied in depth, one each from the northern and southern mid-latitudes. The model clearly captures the seasonal dependence in the ionospheric response to geomagnetic activity at mid-latitude, reproducing the tendency for decreased ion density in the summer hemisphere and increased densities in winter. In contrast to the "visual" success of the model, the detailed quantitative comparisons, which are necessary for space weather applications, are less impressive. The accuracy, or value, of the model has been quantified by evaluating the daily standard deviation, the root-mean-square error, and the correlation coefficient between the data and model predictions. The modeled quiet-time variability, or standard deviation, and the increases during geomagnetic activity, agree well with the data in winter, but is low in summer. The RMS error of the physical model is about the same as the IRI empirical model during quiet times. During the storm events the RMS error of the model improves on IRI, but there are occasionally false-alarms. Using unsmoothed data over the full interval, the correlation coefficients between the model and data are low, between 0.3 and 0.4. Isolating the storm intervals increases the correlation to between 0.43 and 0.56, and by smoothing the data the values increases up to 0.65. The study illustrates the substantial difference between scientific success and a demonstration of value for space weather applications.Key words: Ionosphere (ionospheric disturbances; mid-latitude ionosphere; modeling and forecasting)
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Zhang, Mingze. "Establishment of European Regional Ionosphere Model Based on Spherical Harmonic Functions." Journal of World Architecture 5, no. 6 (November 29, 2021): 5–9. http://dx.doi.org/10.26689/jwa.v5i6.2676.
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In order to study the temporal and spatial variation characteristics of the regional ionosphere and the modeling accuracy, the experiment is based on the spherical harmonic function model, using the GPS, Glonass, and Galileo dual-frequency observation data from the 305th-334th day of the European CORS network in 2019 to establish a global ionospheric model. By analyzing and evaluating the accuracy of the global ionospheric puncture points, VTEC, and comparing code products, the test results showed that the GPS system has the most dense puncture electricity distribution, the Glonass system is the second, and the Galileo system is the weakest. The values of ionospheric VTEC calculated by GPS, Glonass and Galileo are slightly different, but in terms of trends, they are the same as those of ESA, JPL and UPC. GPS data has the highest accuracy in global ionospheric modeling. GPS, Glonass and Galileo have the same trend, but Glonass data is unstable and fluctuates greatly.
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Elsayed, Ahmed, Ahmed Sedeek, Mohamed Doma, and Mostafa Rabah. "Vertical ionospheric delay estimation for single-receiver operation." Journal of Applied Geodesy 13, no. 2 (April 26, 2019): 81–91. http://dx.doi.org/10.1515/jag-2018-0041.
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Abstract An apparent delay is occurred in GPS signal due to both refraction and diffraction caused by the atmosphere. The second region of the atmosphere is the ionosphere. The ionosphere is significantly related to GPS and the refraction it causes in GPS signal is considered one of the main source of errors which must be eliminated to determine accurate positions. GPS receiver networks have been used for monitoring the ionosphere for a long time. The ionospheric delay is the most predominant of all the error sources. This delay is a function of the total electron content (TEC). Because of the dispersive nature of the ionosphere, one can estimate the ionospheric delay using the dual frequency GPS. In the current research our primary goal is applying Precise Point Positioning (PPP) observation for accurate ionosphere error modeling, by estimating Ionosphere delay using carrier phase observations from dual frequency GPS receiver. The proposed algorithm was written using MATLAB and was named VIDE program. The proposed Algorithm depends on the geometry-free carrier-phase observations after detecting cycle slip to estimates the ionospheric delay using a spherical ionospheric shell model, in which the vertical delays are described by means of a zenith delay at the station position and latitudinal and longitudinal gradients. Geometry-free carrier-phase observations were applied to avoid unwanted effects of pseudorange measurements, such as code multipath. The ionospheric estimation in this algorithm is performed by means of sequential least-squares adjustment. Finally, an adaptable user interface MATLAB software are capable of estimating ionosphere delay, ambiguity term and ionosphere gradient accurately.
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MacDougall, J. W., D. A. Andre, G. J. Sofko, C. S. Huang, and A. V. Koustov. "Travelling ionospheric disturbance properties deduced from Super Dual Auroral Radar measurements." Annales Geophysicae 18, no. 12 (December 31, 2000): 1550–59. http://dx.doi.org/10.1007/s00585-001-1550-z.
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Abstract. Based on modeling of the perturbations in power and elevation angle produced by travelling ionospheric disturbances (TIDs), and observed by the Super Dual Auroral Radar Network, procedures for determining the TID properties are suggested. These procedures are shown to produce reasonable agreement with those properties of the TIDs that can be measured from simultaneous ionosonde measurements. The modeling shows that measurements of angle-of-elevation perturbations by SuperDARN allows for better determination of the TID properties than using only the perturbations of power as is commonly done.Key words: Ionosphere (auroral ionosphere; ionosphere-atmosphere interactions)
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Xu, Xin, Ling Huang, Shun Wang, Yicai Ji, Xiaojun Liu, and Guangyou Fang. "VLF/LF Lightning Location Based on LWPC and IRI Models: A Quantitative Study." Remote Sensing 14, no. 22 (November 16, 2022): 5784. http://dx.doi.org/10.3390/rs14225784.
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The group velocity of lightning electromagnetic signals plays an important role in lightning location systems using the time difference of arrival (TDOA) method. Accurate estimation of group velocity is difficult due to the space- and time-varying properties of the Earth’s ionospheric waveguide. Besides, the analytical solution of the group velocity is difficult to obtain from the classic mode theory, especially when higher-order modes, anisotropic geomagnetic background, diffuse ionosphere profile, and propagation path segmentation are all taken into consideration. To overcome these challenges, a novel numerical method is proposed in this paper to estimate the group velocity of the lightning signal during ionospheric quiet periods. The well-known Long Wavelength Propagation Capability (LWPC) code is used to model the propagation of VLF/LF radio waves. Since LWPC uses a simplified ionospheric model which is unable to describe the subtle variations of ionospheric parameters over time and space, the IRI-2016 model is incorporated into the numerical modeling process to provide more accurate ionosphere parameters. Experimental results of a VLF/LF lightning location network are demonstrated and analyzed to show the effectiveness of our method. The proposed method is also applicable when there is a sudden ionospheric disturbance as long as the parameters of the ionosphere are obtained in real time by remote sensing methods.
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Н.В., Фетисова,, and Мандрикова, О.В. "Modeling and analysis of ionospheric parameters based on generalized multicomponent model." Вестник КРАУНЦ. Физико-математические науки, no. 4 (December 22, 2022): 89–106. http://dx.doi.org/10.26117/2079-6641-2022-41-4-89-106.
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В работе представлены результаты моделирования и анализа параметров ионосферы в периоды магнитных бурь 2017-2021 гг. Использовались данные кри- тической частоты F2-слоя ионосферы (foF2 ) (по данным ионозонда ст. <Паратунка>, п-ов Камчатка, ИКИР ДВО РАН). Моделирование выполнялось на основе разработанной авторами обобщенной многокомпонентной модели параметров ионосферы (ОМКМ). Представленная в работе ОМКМ позволяет детально изучать динамику параметров ионосферы в возмущенные периоды. Идентификация модели основана на совместном применении вейвлет преобразования и авторегрессионных моделей (АРПСС модели). ОМКМ описывает три класса аномалий, характеризующих сильные (класс 3), умеренные (класс 2) и слабые (класс 1) ионосферные возмущения. Исследование динамики параметров ионосферы проводилось в зависимости от силы геомагнитного возмущения (рассматривались события слабой, умеренной и высокой интенсивности). В процессе моделирования обнаружены ионосферные аномалии разной интенсивности и продолжительности. Накануне умеренных и сильных магнитных бурь отмечен факт высокой частоты эффекта предповышения в ионосфере, имеющий важную прикладную значимость. The results of modeling and analysis of ionospheric parameters during magnetic storms in 2017-2021 are presented. We used the critical frequency variations of the ionospheric F2 layer (foF2 ) (according to the ionosonde data from Paratunka site, Kamchatka peninsula, IKIR FEB RAS). The modeling was based on a generalized multicomponent model of ionospheric parameters (GMCM) developed by the authors. GMCM allows us to study in detail the dynamics of ionospheric parameters during disturbed periods. The GMCM identification is based on the combination of wavelet transform and autoregressive models (ARIMA models). The model describes three classes of anomalies characterizing strong (class 3), moderate (class 2) and weak (class 1) ionospheric disturbances. The ionospheric parameter dynamics was studied with respect to the strength of a geomagnetic disturbance (weak, moderate and strong intensity events were considered). On the basis of the modeling, we detected ionospheric anomalies of various intensity and duration. On the eve of moderate and strong magnetic storms, the fact of a high frequency of the pre-increase effect in the ionosphere was noted. It has an important applied significance.
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Waters, C. L., T. K. Yeoman, M. D. Sciffer, P. Ponomarenko, and D. M. Wright. "Modulation of radio frequency signals by ULF waves." Annales Geophysicae 25, no. 5 (June 4, 2007): 1113–24. http://dx.doi.org/10.5194/angeo-25-1113-2007.
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Abstract. The ionospheric plasma is continually perturbed by ultra-low frequency (ULF; 1–100 mHz) plasma waves that are incident from the magnetosphere. In this paper we present a combined experimental and modeling study of the variation in radio frequency of signals propagating in the ionosphere due to the interaction of ULF wave energy with the ionospheric plasma. Modeling the interaction shows that the magnitude of the ULF wave electric field, e, and the geomagnetic field, B0, giving an e×B0 drift, is the dominant mechanism for changing the radio frequency. We also show how data from high frequency (HF) Doppler sounders can be combined with HF radar data to provide details of the spatial structure of ULF wave energy in the ionosphere. Due to spatial averaging effects, the spatial structure of ULF waves measured in the ionosphere may be quite different to that obtained using ground based magnetometer arrays. The ULF wave spatial structure is shown to be a critical parameter that determines how ULF wave effects alter the frequency of HF signals propagating through the ionosphere.
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Tsunomura, S. "Numerical analysis of global ionospheric current system including the effect of equatorial enhancement." Annales Geophysicae 17, no. 5 (May 31, 1999): 692–706. http://dx.doi.org/10.1007/s00585-999-0692-2.
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Abstract. A modeling method is proposed to derive a two-dimensional ionospheric layer conductivity, which is appropriate to obtain a realistic solution of the polar-originating ionospheric current system including equatorial enhancement. The model can be obtained by modifying the conventional, thin shell conductivity model. It is shown that the modification for one of the non-diagonal terms (Σθφ) in the conductivity tensor near the equatorial region is very important; the term influences the profile of the ionospheric electric field around the equator drastically. The proposed model can reproduce well the results representing the observed electric and magnetic field signatures of geomagnetic sudden commencement. The new model is applied to two factors concerning polar-originating ionospheric current systems. First, the latitudinal profile of the DP2 amplitude in the daytime is examined, changing the canceling rate for the dawn-to-dusk electric field by the region 2 field-aligned current. It is shown that the equatorial enhancement would not appear when the ratio of the total amount of the region 2 field-aligned current to that of region 1 exceeds 0.5. Second, the north-south asymmetry of the magnetic fields in the summer solstice condition of the ionospheric conductivity is examined by calculating the global ionospheric current system covering both hemispheres simultaneously. It is shown that the positive relationship between the magnitudes of high latitude magnetic fields and the conductivity is clearly seen if a voltage generator is given as the source, while the relationship is vague or even reversed for a current generator. The new model, based on the International Reference Ionosphere (IRI) model, can be applied to further investigations in the quantitative analysis of the magnetosphere-ionosphere coupling problems.Key words. Ionosphere (electric fields and currents; equatorial ionosphere; ionosphere-magnetosphere interactions)
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Farah, Ashraf. "Nequick2 Model Behaviour for Global Ionospheric Delay Mitigation During Solar Cycle-24." Artificial Satellites 53, no. 4 (December 1, 2018): 127–39. http://dx.doi.org/10.2478/arsa-2018-0010.
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Abstract The ionospheric delay is the major current source of potential range delay for single-frequency GNSS users. Different ionospheric delay mitigation methods have been developed to mitigate the ionospheric delay effects for single-frequency users. The NeQuick is a quick-run ionospheric electron density model particularly designed for trans-ionospheric propagation applications developed at the Aeronomy and Radio propagation Laboratory of the Abdus Salam International Centre for Theoretical Physics (ICTP), Italy. NeQuick2 is the latest version of the NeQuick ionosphere electron density model. NeQuick model been used by the European Space Agency (ESA) European Geostationary Navigation Overlay Service (EGNOS) project for assessment analysis and has been adopted for single-frequency positioning applications in the frame work of the European satellite navigation system (Galileo). NeQuick2 model adopted modifications related to the modeling of the F1 layer peak electron density, height and thickness parameter. Also, a new formulation of the shape parameter k has been adopted. This paper presents a global study for the behavior of the modified NeQuick2 model. The zenith ionospheric range delay correction by the model has been assessed using the highly accurate IGS-Global Ionospheric Maps (IGS-GIMs) for two different-latitude stations (Aswan, Egypt) (low-latitude) (24.1o N) and (Helsinki, Finland) (high-latitude) (60.2o N). The study was carried out during current solar cycle-24 over three different months that each of them reflects a different state of solar activity. It can be concluded that NeQuick2 model globally presents overestimation for ionospheric delay for quiet and medium ionospheric activity states respectively, while the model presents underestimation for high activity state of the ionosphere layer.
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Palmroth, M., P. Janhunen, T. I. Pulkkinen, and H. E. J. Koskinen. "Ionospheric energy input as a function of solar wind parameters: global MHD simulation results." Annales Geophysicae 22, no. 2 (January 1, 2004): 549–66. http://dx.doi.org/10.5194/angeo-22-549-2004.
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Abstract. We examine the global energetics of the solar wind magnetosphere-ionosphere system by using the global MHD simulation code GUMICS-4. We show simulation results for a major magnetospheric storm (6 April 2000) and a moderate substorm (15 August 2001). The ionospheric dissipation is investigated by determining the Joule heating and precipitation powers in the simulation during the two events. The ionospheric dissipation is concentrated largely on the dayside cusp region during the main phase of the storm period, whereas the nightside oval dominates the ionospheric dissipation during the substorm event. The temporal variations of the precipitation power during the two events are shown to correlate well with the commonly used AE-based proxy of the precipitation power. The temporal variation of the Joule heating power during the substorm event is well-correlated with a commonly used AE-based empirical proxy, whereas during the storm period the simulated Joule heating is different from the empirical proxy. Finally, we derive a power law formula, which gives the total ionospheric dissipation from the solar wind density, velocity and magnetic field z-component and which agrees with the simulation result with more than 80% correlation. Key words. Ionosphere (modeling and forecasting) – Magnetospheric physics (magnetosphere-ionosphere interactions; storms and substorms)
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Пилипенко, Вячеслав, Vyacheslav Pilipenko, Ольга Козырева, Olga Kozyreva, Евгений Федоров, Eugeny Fedorov, Михаил Успенский, Mikhail Uspensky, Кирсти Кауристи, and Kirsti Kauristie. "Latitudinal amplitude-phase structure of MHD waves: STARE radar and image magnetometer observations and modeling." Solar-Terrestrial Physics 2, no. 3 (October 27, 2016): 56–73. http://dx.doi.org/10.12737/22285.
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We have developed a numerical model that yields a steady-state distribution of field components of MHD wave in an inhomogeneous plasma box simulating the realistic magnetosphere. The problem of adequate boundary condition at the ionosphere–magnetosphere interface for coupled MHD mode is considered. To justify the model’s assumptions, we have derived the explicit inequality showing when the ionospheric inductive Hall effect can be neglected upon the consideration of Alfven wave reflection from the ionospheric boundaries. The model predicts a feature of the ULF spatial amplitude/phase distribution that has not been noticed by the field line resonance theory: the existence of a region with opposite phase delays on the source side of the resonance. This theoretical prediction is supported by the amplitude-phase latitudinal structures of Pc5 waves observed by STARE radar and IMAGE magnetometers. A gradual decrease in azimuthal wave number m at smaller L-shells was observed at longitudinally separated radar beams.
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Kulyamin, Dmitry V., Pavel A. Ostanin, and Valentin P. Dymnikov. "INM-IM: INM RAS Earth ionosphere F region dynamical model." Russian Journal of Numerical Analysis and Mathematical Modelling 37, no. 6 (December 1, 2022): 349–62. http://dx.doi.org/10.1515/rnam-2022-0028.
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Abstract A new INM RAS global dynamical model of Earth’s ionosphere F region (100–500 km), which takes into account plasma-chemical processes, ambipolar diffusion, and advective ion transport due to electromagnetic drifts and neutral wind is presented. The model includes parameterizations of polar electric fields induced by magnetospheric convection and simplified equatorial drifts considerations. The focus of the paper is directed on the description of specific methods developed and utilized in the ionospheric model. Key processes responsible for the formation of global ionospheric features are outlined and their representation in the model is evaluated. The main global ionospheric characteristic features, such as seasonal and diurnal cycles, the equatorial ionization anomaly (EIA), polar ionization caps and the main trough have been adequately reproduced based on this model.
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Yuan, Liangliang, Shuanggen Jin, and Mainul Hoque. "Estimation of GPS Differential Code Biases Based on Independent Reference Station and Recursive Filter." Remote Sensing 12, no. 6 (March 16, 2020): 951. http://dx.doi.org/10.3390/rs12060951.
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The differential code bias (DCB) of the Global Navigation Satellite Systems (GNSS) receiver should be precisely corrected when conducting ionospheric remote sensing and precise point positioning. The DCBs can usually be estimated by the ground GNSS network based on the parameterization of the global ionosphere together with the global ionospheric map (GIM). In order to reduce the spatial-temporal complexities, various algorithms based on GIM and local ionospheric modeling are conducted, but rely on station selection. In this paper, we present a recursive method to estimate the DCBs of Global Positioning System (GPS) satellites based on a recursive filter and independent reference station selection procedure. The satellite and receiver DCBs are estimated once per local day and aligned with the DCB product provided by the Center for Orbit Determination in Europe (CODE). From the statistical analysis with CODE DCB products, the results show that the accuracy of GPS satellite DCB estimates obtained by the recursive method can reach about 0.10 ns under solar quiet condition. The influence of stations with bad performances on DCB estimation can be reduced through the independent iterative reference selection. The accuracy of local ionospheric modeling based on recursive filter is less than 2 Total Electron Content Unit (TECU) in the monthly median sense. The performance of the recursive method is also evaluated under different solar conditions and the results show that the local ionospheric modeling is sensitive to solar conditions. Moreover, the recursive method has the potential to be implemented in the near real-time DCB estimation and GNSS data quality check.
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Li, Wei, Keke Wang, and Kaitian Yuan. "Performance and Consistency of Final Global Ionospheric Maps from Different IGS Analysis Centers." Remote Sensing 15, no. 4 (February 12, 2023): 1010. http://dx.doi.org/10.3390/rs15041010.
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Ionospheric delay is one of the most problematic errors in satellite-based positioning data processing. The Global Ionospheric Map (GIM), which is publicly available daily in various analysis centers, is thus vitally important for positioning users. There are variations in the accuracy and consistency of GIMs issued by Ionosphere Associate Analysis Centers (IAACs) due to the differences in ionospheric modeling methods and selected tracking stations. In this study on the International GNSS Service’s (IGS) final GIM, the ionospheric total electron content (TEC) (from 243 global navigation satellite system (GNSS) monitoring stations around the world) and the ionospheric TEC (from the Jason-3 altimeter satellite) are selected as reference. By using these three references, we evaluate the performance and consistency of final GIM products from seven IGS IAACs, including the Chinese Academy of Sciences (CAS), the Center for Orbit Determination in Europe (CODE), Natural Resources Canada (EMR), the European Space Agency (ESA), the Jet Propulsion Laboratory (JPL), Universitat Politècnica de Catalunya (UPC), and Wuhan University (WHU) in the mid-solar activity year (2022) and the low-solar activity year (2020). Firstly, the comparison with the IGS final GIM shows that the consistency of each GIMs is basically the same, with the mean value ranging from −0.3 TECu (total electron content unit) to 1.4 TECu. Secondly, the validation with Jason-3 altimeter satellite shows that the accuracy of several GIMs is almost the same, except for the JPL with the worst accuracy and an overall mean deviation (BIAS) between 2 and 6 TECu. Thirdly, the comparison with VTEC extracted from GNSS monitor stations shows that the CAS has the best accuracy in different latitude bands with a root mean square (RMS) of about 2.2–4.7 TECu. In addition, it is found that the accuracy in areas with more stations for ionospheric modelling is better than those with less stations in different latitude bands; meanwhile, the accuracy is closely related to the modeling methods of different GIMs.
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Zamogilnyi, Dmitrii. "PREDICTION OF THE TOTAL ELECTRONIC CONTENT OF THE IONOSPHERE BASED ON MACHINE LEARNING ALGORITHMS." H&ES Research 14, no. 4 (2022): 39–46. http://dx.doi.org/10.36724/2409-5419-2022-14-4-39-46.
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Introduction. The paper presents and describes the technology of applying the machine learning algorithm in predicting the vertical total electron content of the ionosphere. The ionospheric error is one of the most significant sources of pseudorange measurement errors from GNSS signals. Increasing every year requirements for the accuracy of positioning and navigation by GNSS signals leads to the need to develop new methods to reduce the impact of various measurement errors, including the ionospheric error. At present, ionospheric models of various types are used for ionospheric correction of measurements. The currently widely used ionospheric models do not allow a significant increase in the accuracy of positioning based on GNSS signals. At the moment, the creation of a new effective method for modeling and forecasting the ionosphere that meets modern requirements for positioning accuracy is an important and urgent task. The purpose of this work is to create a methodology for modeling and predicting the total electron content of the ionosphere using machine learning algorithms. Machine learning is currently a fairly common and popular method for solving problems of classification, recognition and prediction. The method has been used for many years in medicine, robotics, industry, finance and many other branches of modern science and economics. To achieve this goal, it is necessary to solve a number of tasks. First of all, you need to select and collect data for training the model, then you need to select a machine learning method and hyperparameters for the selected method. Next, it is necessary to perform TEC prediction based on the trained model and evaluate the accuracy of the results obtained. comparison of the obtained results with the accuracy of other existing models It is shown that machine learning does a good job of predicting full electronic content. The resulting trained model makes it possible to obtain a forecast with an accuracy comparable to the accuracy of the Klobuchar, NeQuick models, and in some cases much more accurate.
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Pulkkinen, A., and M. Engels. "The role of 3-D geomagnetic induction in the determination of the ionospheric currents from the ground geomagnetic data." Annales Geophysicae 23, no. 3 (March 30, 2005): 909–17. http://dx.doi.org/10.5194/angeo-23-909-2005.
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Abstract. The geomagnetic field variations measured at the surface of the Earth are composed of both internal and external parts. The external field arises from the sources in the magnetosphere and ionosphere, whereas the internal field is generated by the currents induced within the Earth. The internal part may in some situations comprise a notable part of the measured total field and thus a blind usage of geomagnetic field recordings potentially produces significant errors to estimated ionospheric currents. In this paper the role of geomagnetic induction in auroral ionospheric studies is investigated by modeling the induction using simultaneously the realistic ionospheric source and a realistic three-dimensional Earth conductivity structure. The modeling results imply that the effects of the lateral ground conductivity anomalies on ionospheric equivalent current patterns are, though clearly detected, less severe than anticipated for fields varying with periods from 5 to 120min. However, the amplification of the determined currents caused by induction is significant, leading to an overestimation of up to 30% of the main current flow intensities, with the overestimation increasing sharply when moving away from the region of the main flow. In addition to the 3-D modeling, a simple method is introduced to help estimate the internal contribution to the measured variations of the IL index (local variant of the AL index). A test with the 26 June 1998 substorm event indicates that the method can help to extract the internal contribution from the IL index.
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Yang, Xuguang, Aijun Liu, Changjun Yu, and Linwei Wang. "Ionospheric Clutter Model for HF Sky-Wave Path Propagation with an FMCW Source." International Journal of Antennas and Propagation 2019 (May 8, 2019): 1–10. http://dx.doi.org/10.1155/2019/1782942.
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A theoretical model of the sky-wave path propagation with frequency modulated continuous wave (FMCW) source for high frequency (HF) radar is proposed in this paper. Based on the modeling of pulsed source, the expression of the received electric field with an FMCW source is derived for the reflection case from the ionospheric irregularities. Subsequently, the ionospheric reflection coefficient with different phase power spectrums for vertical and oblique backscattering propagation paths is incorporated into the ionospheric clutter model. Simulation results show that the peak power of FMCW in average is lower than that of pulsed waveform. Furthermore, different incident angles and magnetic field in mid-latitude can also influence the power density of the backscattering ionospheric clutter. Finally, the data analysis results from the high frequency surface wave radar (HFSWR) and Ionosonde collected in Yellow Sea preliminarily verify the inversion of the variance of the electron density fluctuation and the vertical drift velocity of the irregularities within ionosphere.
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ELIASSON, BENGT. "FULL-SCALE SIMULATIONS OF IONOSPHERIC LANGMUIR TURBULENCE." Modern Physics Letters B 27, no. 08 (March 13, 2013): 1330005. http://dx.doi.org/10.1142/s0217984913300056.
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This brief review is devoted to full-scale numerical modeling of the nonlinear interactions between electromagnetic (EM) waves and the ionosphere, giving rise to ionospheric Langmuir turbulence. A numerical challenge in the full-scale modeling is that it involves very different length- and time-scales. While the EM waves have wavelengths of the order 100 meters, the ionospheric Langmuir turbulence involving electrostatic waves and nonlinear structures can have wavelengths below one meter. A full-scale numerical scheme must resolve these different length- and time-scales, as well as the ionospheric profile extending vertically hundreds of kilometers. To overcome severe limitations on the timestep and computational load, a non-uniform nested grid method has been devised, in which the EM wave is represented in space on a relatively coarse grid with a spacing of a few meters, while the electrostatic wave turbulence is locally resolved on a much denser grid in space at the critical layer where the turbulence occurs. Interpolation and averaging schemes are used to communicate values of the EM fields and current sources between the coarse and dense grids. In this manner, the computational load can be drastically decreased, making it possible to perform full-scale simulations that cover the different time- and space-scales. We discuss the simulation methods and how they are used to study turbulence, stimulated EM emissions, particle acceleration and heating, and the formation of artificial ionospheric plasma layers by ionospheric Langmuir turbulence.
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Merkin, V. G., J. G. Lyon, B. J. Anderson, H. Korth, C. C. Goodrich, and K. Papadopoulos. "A global MHD simulation of an event with a quasi-steady northward IMF component." Annales Geophysicae 25, no. 6 (June 29, 2007): 1345–58. http://dx.doi.org/10.5194/angeo-25-1345-2007.
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Abstract. We show results of the Lyon-Fedder-Mobarry (LFM) global MHD simulations of an event previously examined using Iridium spacecraft observations as well as DMSP and IMAGE FUV data. The event is chosen for the steady northward IMF sustained over a three-hour period during 16 July 2000. The Iridium observations showed very weak or absent Region 2 currents in the ionosphere, which makes the event favorable for global MHD modeling. Here we are interested in examining the model's performace during weak magnetospheric forcing, in particular, its ability to reproduce gross signatures of the ionospheric currents and convection pattern and energy deposition in the ionosphere both due to the Poynting flux and particle precipitation. We compare the ionospheric field-aligned current and electric potential patterns with those recovered from Iridium and DMSP observations, respectively. In addition, DMSP magnetometer data are used for comparisons of ionospheric magnetic perturbations. The electromagnetic energy flux is compared with Iridium-inferred values, while IMAGE FUV observations are utilized to verify the simulated particle energy flux.
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Schunk, Robert W., Ludger Scherliess, and Jan J. Sojka. "Ionospheric Specification and Forecast Modeling." Journal of Spacecraft and Rockets 39, no. 2 (March 2002): 314–24. http://dx.doi.org/10.2514/2.3815.
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Kumar, Mohi, and Ernie Tretkoff. "Research Spotlight: Modeling ionospheric variations." Eos, Transactions American Geophysical Union 91, no. 44 (2010): 416. http://dx.doi.org/10.1029/eo091i044p00416-04.
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Liu, Zhizhao, Susan Skone, Yang Gao, and Attila Komjathy. "Ionospheric modeling using GPS data." GPS Solutions 9, no. 1 (February 10, 2005): 63–66. http://dx.doi.org/10.1007/s10291-004-0129-z.
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Schunk, Robert W., and Jan J. Sojka. "Ionospheric climate and weather modeling." Eos, Transactions American Geophysical Union 69, no. 11 (1988): 153. http://dx.doi.org/10.1029/88eo00100.
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Richmond, A. D. "Modeling equatorial ionospheric electric fields." Journal of Atmospheric and Terrestrial Physics 57, no. 10 (August 1995): 1103–15. http://dx.doi.org/10.1016/0021-9169(94)00126-9.
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Mandrikova, Oksana, Nadezhda Fetisova, Yuryi Polozov, and Vladimir Geppener. "Analysis of the ionospheric parameter dynamics on the basis of a generalized multicomponent model." E3S Web of Conferences 62 (2018): 02003. http://dx.doi.org/10.1051/e3sconf/20186202003.
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In the present paper, we have carried out an analysis of the ionospheric critical frequency data of the F2 layer during strong magnetic storms in 2017-2018. The ionospheric data of Paratunka (IKIR FEB RAS, Kamchatka, 53.0 N, 158.7 E), Wakkanai (Japan, 45.16 N, 141.75 E), and Moscow stations (Russia, 55.49 N, 37.29 E) were used. The study was carried out using a generalized multicomponent model (GMCM) developed by the authors. GMCM allows studying the dynamics of the ionospheric parameters in detail and estimating their characteristics. Using the modeling, we detected and studied anomalous changes in the ionosphere preceding and accompanying the periods of magnetic storms in the analyzed areas. The study results were compared with the traditional median method and showed the perspectiveness of GMCM. The research is supported by a grant from the Russian Science Foundation (project No. 14-11-00194).
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Lin, Xu, Hongyue Wang, Qingqing Zhang, Chaolong Yao, Changxin Chen, Lin Cheng, and Zhaoxiong Li. "A Spatiotemporal Network Model for Global Ionospheric TEC Forecasting." Remote Sensing 14, no. 7 (April 2, 2022): 1717. http://dx.doi.org/10.3390/rs14071717.
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In the Global Navigation Satellite System, ionospheric delay is a significant source of error. The magnitude of the ionosphere total electron content (TEC) directly impacts the magnitude of the ionospheric delay. Correcting the ionospheric delay and improving the accuracy of satellite navigation positioning can both benefit from the accurate modeling and forecasting of ionospheric TEC. The majority of current ionospheric TEC forecasting research only considers the temporal or spatial dimensions, ignoring the ionospheric TEC’s spatial and temporal autocorrelation. Therefore, we constructed a spatiotemporal network model with two modules: (i) global spatiotemporal characteristics extraction via forwarding spatiotemporal characteristics transfer and (ii) regional spatiotemporal characteristics correction via reverse spatiotemporal characteristics transfer. This model can realize the complementarity of TEC global spatiotemporal characteristics and regional spatiotemporal characteristics. It also ensures that the global spatiotemporal characteristics of the global ionospheric TEC are transferred to each other in both temporal and spatial domains at the same time. The spatiotemporal network model thus achieves a spatiotemporal prediction of global ionospheric TEC. The Huber loss function is also used to suppress the gross error and noise in the ionospheric TEC data to improve the forecasting accuracy of global ionospheric TEC. We compare the results of the spatiotemporal network model with the Center for Orbit Determination in Europe (CODE), the convolutional Long Short-Term Memory (convLSTM) model and the Predictive Recurrent Neural Network (PredRNN) model for one-day forecasts of global ionospheric TEC under different conditions of time and solar activity, respectively. With internal data validation, the average root mean square error (RMSE) of our proposed algorithm increased by 21.19, 15.75, and 9.67%, respectively, during the maximum solar activity period. During the minimum solar activity period, the RMSE improved by 38.69, 38.02, and 13.54%, respectively. This algorithm can effectively be applied to ionospheric delay error correction and can improve the accuracy of satellite navigation and positioning.
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Wang, Qisheng, Shuanggen Jin, and Xianfeng Ye. "A Novel Method to Estimate Multi-GNSS Differential Code Bias without Using Ionospheric Function Model and Global Ionosphere Map." Remote Sensing 14, no. 9 (April 21, 2022): 2002. http://dx.doi.org/10.3390/rs14092002.
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Global navigation satellite system (GNSS) differential code bias (DCB) is one of main errors in ionospheric modeling and applications. Accurate estimation of multiple types of GNSS DCBs is important for GNSS positioning, navigation, and timing, as well as ionospheric modeling. In this study, a novel method of multi-GNSS DCB estimation is proposed without using an ionospheric function model and global ionosphere map (GIM), namely independent GNSS DCB estimation (IGDE). Firstly, ionospheric observations are extracted based on the geometry-free combination of dual-frequency multi-GNSS code observations. Secondly, the VTEC of the station represented by the weighted mean VTEC value of the ionospheric pierce points (IPPs) at each epoch is estimated as a parameter together with the combined receiver and satellite DCBs (RSDCBs). Last, the estimated RSDCBs are used as new observations, whose weight is calculated from estimated covariances, and thus the satellite and receiver DCBs of multi-GNSS are estimated. Nineteen types of multi-GNSS satellite DCBs are estimated based on 200-day observations from more than 300 multi-GNSS experiment (MGEX) stations, and the performance of the proposed method is evaluated by comparing with MGEX products. The results show that the mean RMS value is 0.12, 0.23, 0.21, 0.13, and 0.11 ns for GPS, GLONASS, BDS, Galileo, and QZSS DCBs, respectively, with respect to MGEX products, and the stability of estimated GPS, GLONASS, BDS, Galileo, and QZSS DCBs is 0.07, 0.06, 0.13, 0.11, and 0.11 ns, respectively. The proposed method shows good performance of multi-GNSS DCB estimation in low-solar-activity periods.
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Tang, Jun, Shimeng Zhang, Dengpan Yang, and Xuequn Wu. "Assimilating GNSS TEC with an LETKF over Yunnan, China." Remote Sensing 15, no. 14 (July 14, 2023): 3547. http://dx.doi.org/10.3390/rs15143547.
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A robust ionospheric model is indispensable for providing the atmospheric delay corrections for global navigation satellite system (GNSS) navigation and positioning and forecasting the space environment. The accuracy of ionospheric models is limited due to the simplified model structures. Complicated spatiotemporal variations in total electron content (TEC) biases between GNSS and international reference ionosphere (IRI) suggest a robust strategy to optimally combine GNSS and IRI TEC for high-precision modeling. In this paper, we propose a novel ionospheric data assimilation method, which is a local ensemble transform Kalman filter (LETKF), to construct an ionospheric model over Yunnan in southwestern China. We used the LETKF method to assimilate the ionospheric TEC extracted from GNSS observations in Yunnan into the IRI-2016 model. The experimental results indicate that the ionospheric data assimilation has a more pronounced improvement effect on the IRI empirical model during periods of geomagnetic quiet than during periods of geomagnetic disturbance. On quiet magnetic days, the skill score (SKS) of the assimilation is 0.60 and the root mean square error (RMSE) values before and after assimilation are 5.08 TECU and 2.02 TECU, respectively. The correlation coefficient after assimilation increases from 0.94 to 0.99. On magnetic storm days, the SKS of the assimilation is 0.42 and the RMSE values before and after assimilation are 5.99 TECU and 3.46 TECU, respectively. The correlation coefficient after assimilation increases from 0.98 to 0.99. The results suggest that the LETKF algorithm can be considered an effective method for ionospheric data assimilation.
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Srećković, Vladimir A., Desanka M. Šulić, Ljubinko Ignjatović, and Veljko Vujčić. "Low Ionosphere under Influence of Strong Solar Radiation: Diagnostics and Modeling." Applied Sciences 11, no. 16 (August 4, 2021): 7194. http://dx.doi.org/10.3390/app11167194.
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Solar flares (SFs) and intense radiation can generate additional ionization in the Earth’s atmosphere and affect its structure. These types of solar radiation and activity create sudden ionospheric disturbances (SIDs), affect electronic equipment on the ground along with signals from space, and potentially induce various natural disasters. Focus of this work is on the study of SIDs induced by X-ray SFs using very low frequency (VLF) radio signals in order to predict the impact of SFs on Earth and analyze ionosphere plasmas and its parameters. All data are recorded by VLF BEL stations and the model computation is used to obtain the daytime atmosphere parameters induced by this extreme radiation. The obtained ionospheric parameters are compared with results of other authors. For the first time we analyzed physics of the D-region—during consecutive huge SFs which continuously perturbed this layer for a few hours—in detail. We have developed an empirical model of the D-region plasma density and gave a simple approximative formula for electron density.
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Sousasantos, Jonas, Alison de Oliveira Moraes, José H. A. Sobral, Marcio T. A. H. Muella, Eurico R. de Paula, and Rafael S. Paolini. "Climatology of the scintillation onset over southern Brazil." Annales Geophysicae 36, no. 2 (April 3, 2018): 565–76. http://dx.doi.org/10.5194/angeo-36-565-2018.
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Abstract. This work presents an analysis of the climatology of the onset time of ionospheric scintillations at low latitude over the southern Brazilian territory near the peak of the equatorial ionization anomaly (EIA). Data from L1 frequency GPS receiver located in Cachoeira Paulista (22.4∘ S, 45.0∘ W; dip latitude 16.9∘ S), from September 1998 to November 2014, covering a period between solar cycles 23 and 24, were used in the present analysis of the scintillation onset time. The results show that the start time of the ionospheric scintillation follows a pattern, starting about 40 min earlier, in the months of November and December, when compared to January and February. The analyses presented here show that such temporal behavior seems to be associated with the ionospheric prereversal vertical drift (PRVD) magnitude and time. The influence of solar activity in the percentage of GPS links affected is also addressed together with the respective ionospheric prereversal vertical drift behavior. Based on this climatological study a set of empirical equations is proposed to be used for a GNSS alert about the scintillation prediction. The identification of this kind of pattern may support GNSS applications for aviation and oil extraction maritime stations positioning. Keywords. Ionosphere (ionospheric irregularities; modeling and forecasting) – radio science (space and satellite communication)
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Zhang, D. H., Z. Xiao, Y. Q. Hao, A. J. Ridley, and M. Moldwin. "Modeling ionospheric <I>fo</I>F2 by using empirical orthogonal function analysis." Annales Geophysicae 29, no. 8 (August 31, 2011): 1501–15. http://dx.doi.org/10.5194/angeo-29-1501-2011.
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Abstract. A similar-parameters interpolation method and an empirical orthogonal function analysis are used to construct empirical models for the ionospheric foF2 by using the observational data from three ground-based ionosonde stations in Japan which are Wakkanai (Geographic 45.4° N, 141.7° E), Kokubunji (Geographic 35.7° N, 140.1° E) and Yamagawa (Geographic 31.2° N, 130.6° E) during the years of 1971–1987. The impact of different drivers towards ionospheric foF2 can be well indicated by choosing appropriate proxies. It is shown that the missing data of original foF2 can be optimal refilled using similar-parameters method. The characteristics of base functions and associated coefficients of EOF model are analyzed. The diurnal variation of base functions can reflect the essential nature of ionospheric foF2 while the coefficients represent the long-term alteration tendency. The 1st order EOF coefficient A1 can reflect the feature of the components with solar cycle variation. A1 also contains an evident semi-annual variation component as well as a relatively weak annual fluctuation component. Both of which are not so obvious as the solar cycle variation. The 2nd order coefficient A2 contains mainly annual variation components. The 3rd order coefficient A3 and 4th order coefficient A4 contain both annual and semi-annual variation components. The seasonal variation, solar rotation oscillation and the small-scale irregularities are also included in the 4th order coefficient A4. The amplitude range and developing tendency of all these coefficients depend on the level of solar activity and geomagnetic activity. The reliability and validity of EOF model are verified by comparison with observational data and with International Reference Ionosphere (IRI). The agreement between observations and EOF model is quite well, indicating that the EOF model can reflect the major changes and the temporal distribution characteristics of the mid-latitude ionosphere of the Sea of Japan region. The error analysis processes imply that there are seasonal anomaly and semi-annual asymmetry phenomena which are consistent with pre-existing ionosphere theory.
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Mingaleva, G. I., V. S. Mingalev, and I. V. Mingalev. "Simulation study of the high-latitude F-layer modification by powerful HF waves with different frequencies for autumn conditions." Annales Geophysicae 21, no. 8 (August 31, 2003): 1827–38. http://dx.doi.org/10.5194/angeo-21-1827-2003.
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Abstract. The large-scale high-latitude F-region modification by high power radio waves is investigated using a numerical model of the convecting high-latitude ionosphere developed earlier. Simulations are performed for the point with geographic coordinates of the ionospheric heater near Tromsø, Scandinavia for autumn conditions. The calculations are made for distinct cases, in which high power waves have different frequencies, both for nocturnal and for day-time conditions. The results of modeling indicate that the frequency of HF waves ought to influence significantly the large-scale F-region modification by high power radio waves in the high-latitude ionosphere.Key words. Ionosphere (active experiments; modeling and forecasting; plasma temperature and density)
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Zhao, Lewen, Jan Douša, and Pavel Václavovic. "Accuracy Evaluation of Ionospheric Delay from Multi-Scale Reference Networks and Its Augmentation to PPP during Low Solar Activity." ISPRS International Journal of Geo-Information 10, no. 8 (July 30, 2021): 516. http://dx.doi.org/10.3390/ijgi10080516.
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The Precise Point Positioning (PPP) with fast integer ambiguity resolution (PPP-RTK) is feasible only if the solution is augmented with precise ionospheric parameters. The vertical ionospheric delays together with the receiver hardware biases, are estimated simultaneously based on the uncombined PPP model. The performance of the ionospheric delays was evaluated and applied in the PPP-RTK demonstration during the low solar activity period. The processing was supported by precise products provided by Deutsches GeoForschungsZentrum Potsdam (GFZ) and also by real-time products provided by the National Centre for Space Studies (CNES). Since GFZ provides only precise orbits and clocks, other products needed for ambiguity resolution, such as phase biases, were estimated at the Geodetic Observatory Pecny (GOP). When ambiguity parameters were resolved as integer values in the GPS-only solution, the initial convergence period was reduced from 30 and 20 min to 24 and 13 min when using CNES and GFZ/GOP products, respectively. The accuracy of ionospheric delays derived from the ambiguity fixed PPP, and the CODE global ionosphere map were then assessed. Comparison of ambiguity fixed ionospheric delay obtained at two collocated stations indicated the accuracy of 0.15 TECU for different scenarios with more than 60% improvement compared to the ambiguity float PPP. However, a daily periodic variation can be observed from the multi-day short-baseline ionospheric residuals. The accuracy of the interpolated ionospheric delay from global maps revealed a dependency on the location of the stations, ranging from 1 to 3 TECU. Precise ionospheric delays derived from the EUREF permanent network with an inter-station distance larger than 73 km were selected for ionospheric modeling at the user location. Results indicated that the PPP ambiguity resolution could be achieved within three minutes. After enlarging the inter-station distance to 209 km, ambiguity resolution could also be achieved within several minutes.
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Mandrikova, O. V., N. V. Fetisova, and Yu A. Polozov. "Method for Modeling of Ionospheric Parameters and Detection of Ionospheric Disturbances." Computational Mathematics and Mathematical Physics 61, no. 7 (July 2021): 1094–105. http://dx.doi.org/10.1134/s0965542521070137.
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Idenden, D. W. "The thermospheric effects of a rapid polar cap expansion." Annales Geophysicae 16, no. 10 (October 31, 1998): 1380–91. http://dx.doi.org/10.1007/s00585-998-1380-3.
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Abstract. In a previous publication we used results from a coupled thermosphere-ionosphere-plasmasphere model to illustrate a new mechanism for the formation of a large-scale patch of ionisation arising from a rapid polar cap expansion. Here we describe the thermospheric response to that polar cap expansion, and to the ionospheric structure produced. The response is dominated by the energy and momentum input at the dayside throat during the expansion phase itself. These inputs give rise to a large-scale travelling atmospheric disturbance (TAD) that propagates both antisunward across the polar cap and equatorward at speeds much greater than both the ion drifts and the neutral winds. We concentrate only on the initially poleward travelling disturbance. The disturbance is manifested in the neutral temperature and wind fields, the height of the pressure level surfaces and in the neutral density at fixed heights. The thermospheric effects caused by the ionospheric structure produced during the expansion are hard to discern due to the dominating effects of the TAD.Key words. Ionosphere (ionosphere · atmosphere interaction; modeling and forecasting; plasma convection).
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Пилипенко, Вячеслав, Vyacheslav Pilipenko, Ольга Козырева, Olga Kozyreva, Евгений Федоров, Eugeny Fedorov, Михаил Успенский, Mikhail Uspensky, Кирсти Кауристи, and Kirsti Kauristie. "Latitudinal amplitude-phase structure of MHD waves: STARE radar and image magnetometer observations and modeling." Solnechno-Zemnaya Fizika 2, no. 3 (September 17, 2016): 41–51. http://dx.doi.org/10.12737/19418.
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We have developed a numerical model that yields a steady-state distribution of field components of MHD wave in an inhomogeneous plasma box simulating the realistic magnetosphere. The problem of adequate boundary condition at the ionosphere–magnetosphere interface for coupled MHD mode is considered. To justify the model’s assumptions, we have derived the explicit inequality showing when the ionospheric inductive Hall effect can be neglected upon the consideration of Alfven wave reflection from the ionospheric boundaries. The model predicts a feature of the ULF spatial amplitude/phase distribution that has not been noticed by the field line resonance theory: the existence of a region with opposite phase delays on the source side of the resonance. This theoretical prediction is supported by the amplitude-phase latitudinal structures of Pc5 waves observed by STARE radar and IMAGE magnetometers. A gradual decrease in azimuthal wave number m at smaller L-shells was observed at longitudinally separated radar beams.
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Reinisch, Bodo, Dieter Bilitza, and Jan Lastovicka. "Progress in Observation-Based Ionospheric Modeling." Space Weather 6, no. 2 (February 2008): n/a. http://dx.doi.org/10.1029/2007sw000359.
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Schunk, R. W., L. Scherliess, and J. J. Sojka. "Recent approaches to modeling ionospheric weather." Advances in Space Research 31, no. 4 (January 2003): 819–28. http://dx.doi.org/10.1016/s0273-1177(02)00791-3.
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