Effect of Ionospheric Variability on the Electron Energy Spectrum estimated from Incoherent Scatter Radar Measurements

The first part of this paper reviews methods using effective solar indices to update a background ionospheric model focusing on those employing the Kriging method to perform the spatial interpolation. Then, it proposes a method to update the International Reference Ionosphere (IRI) model through the assimilation of data collected by a European ionosonde network. The method, called International Reference Ionosphere UPdate (IRI UP), that can potentially operate in real time, is mathematically described and validated for the period 9–25 March 2015 (a time window including the well-known St. Patrick storm occurred on 17 March), using IRI and IRI Real Time Assimilative Model (IRTAM) models as the reference. It relies on foF2 and M(3000)F2 ionospheric characteristics, recorded routinely by a network of 12 European ionosonde stations, which are used to calculate for each station effective values of IRI indices $$IG_{12}$$ and $$R_{12}$$ (identified as $$IG_{{12{\text{eff}}}}$$ and $$R_{{12{\text{eff}}}}$$ ); then, starting from this discrete dataset of values, two-dimensional (2D) maps of $$IG_{{12{\text{eff}}}}$$ and $$R_{{12{\text{eff}}}}$$ are generated through the universal Kriging method. Five variogram models are proposed and tested statistically to select the best performer for each effective index. Then, computed maps of $$IG_{{12{\text{eff}}}}$$ and $$R_{{12{\text{eff}}}}$$ are used in the IRI model to synthesize updated values of foF2 and hmF2. To evaluate the ability of the proposed method to reproduce rapid local changes that are common under disturbed conditions, quality metrics are calculated for two test stations whose measurements were not assimilated in IRI UP, Fairford (51.7°N, 1.5°W) and San Vito (40.6°N, 17.8°E), for IRI, IRI UP, and IRTAM models. The proposed method turns out to be very effective under highly disturbed conditions, with significant improvements of the foF2 representation and noticeable improvements of the hmF2 one. Important improvements have been verified also for quiet and moderately disturbed conditions. A visual analysis of foF2 and hmF2 maps highlights the ability of the IRI UP method to catch small-scale changes occurring under disturbed conditions which are not seen by IRI.

The focus of this thesis is on the development, implementation, and validation of a three-dimensional regional assimilative model of the ionospheric electron density. Empirical climatological models, like the International Reference Ionosphere (IRI) model (Bilitza et al. 2017), cannot predict the whole ionospheric variability, specifically under disturbed magnetic conditions. The model presented in this work has the purpose to improve the IRI description by implementing a data assimilation procedure, based on ionospheric measurements collected by several ground-based or satellite-based instruments. The first phase of the development of the model, called IRI UPdate (IRI UP), is devoted to update the IRI model by ingesting effective indices (IG12eff and R12eff) calculated after assimilating F2 layer characteristics values, measured by a network of ionosondes or derived by vertical total electron content values measured by a network of Global Navigational Satellite Systems receivers. The ingestion of effective indices in the IRI model allows to significantly improve the F2 layer peak density and height description. Being the F2 layer peak an anchor point for the whole IRI’s vertical electron density profile, such procedure allows to update the whole profile. The second phase of the development of the model is devoted to improve the modeling of the topside part of the ionospheric vertical electron density profile by making use of the IRI UP method and in-situ measurements collected by Swarm satellites. Finally, a procedure called IonoPy, embedding the two aforementioned steps, assimilates the whole bottomside electron density profile measured by an ionosonde, thus further improving the ionospheric plasma description in the bottomside ionosphere. All the procedures described in this thesis have been tested and validated by comparing them with other similar models or with independent datasets, for both quiet and disturbed conditions.

Global Navigation Satellite System (GNSS) is one of the valuable techniques used in researching ionospheric total electron content (TEC). GNSS observations above ground-based stations can be used to obtain high-precision ionospheric TEC with the so-called inverse technique. Subsequently, regional and/or global ionospheric TEC models could be established with some modeling techniques. Ionospheric TEC modeling with GNSS has become a great significance for improving the accuracy of GNSS navigation and positioning, as well as analyzing the ionospheric spatial structure, which is a great motivation to the development of ionospheric TEC modeling. There is no doubt that it is easier to get a satisfactory ionospheric TEC modeling result if the used stations are evenly distributed. However, stations are usually unevenly distributed because of some practical factors. For instance, there are few stations in ocean and Antarctic region. Due to lack of GNSS observations in ocean and Antarctic regions, ionosphere pierce points (IPPs) in these regions are also unevenly distributed or even blank. Consequently, the accuracy of ionospheric modeling is less satisfactory and some negative TEC values without physical meaning even occurred. In order to improve the accuracy of global ionospheric modeling, this work tries to solve this problem by using virtual TEC observations from empirical ionospheric models as constraints in global ionospheric TEC modeling. The spherical harmonic function was employed as the modeling technique, three empirical ionospheric models, Klobuchar, International Reference Ionosphere (IRI) and NeQuick, are used to calculate virtual TEC observations in four regions with no IPP, and GNSS observations above 279 global stations are used to calculate the ionospheric TEC values. Through experimental analysis, this work compares the accuracy improvement in global ionospheric modeling by using additional empirical constraints, and studies performance of the three used empirical ionospheric models in different IPP-blank regions. The results show that additional virtual TEC observations could effectively improve the accuracy of global ionospheric TEC modeling, especially for regions with very few IPPs. The contribution of TEC constraints from empirical models to global ionospheric modeling in different epochs is different. Taking the results in UT11 as an example, three empirical ionospheric models can improve the accuracy of global ionospheric modeling from 11.43 TECU to 3.28, 3.42 and 4.15 TECU, respectively. Generally, improvement performances of the three used empirical ionospheric models in mid-high latitude region and Antarctic are comparably, while Klobuchar model is relatively advantaged in mid-latitude region and IRI model outperforms the others in equator region.

Abstract. Incoherent scatter radar measurements are an important source for studies of ionospheric plasma parameters. In this paper the EISCAT Svalbard radar (ESR) long-term database is used to evaluate the International Reference Ionosphere (IRI) model. The ESR started operations in 1996, and the accumulated database up to 2012 thus covers 16 years, giving an overview of the ionosphere in the polar cap and cusp during more than one solar cycle. Data from ESR can be used to obtain information about primary plasma parameters: electron density, electron and ion temperature, and line-of-sight plasma velocity from an altitude of about 50 and up to 1600 km. Monthly averages of electron density and temperature and ion temperature and composition are also provided by the IRI model from an altitude of 50 to 2000 km. We have compared electron density data obtained from the ESR with the predicted electron density from the IRI-2016 model. Our results show that the IRI model in general fits the ESR data well around the F2 peak height. However, the model seems to underestimate the electron density at lower altitudes, particularly during winter months. During solar minimum the model is also less accurate at higher altitudes. The purpose of this study is to validate the IRI model at polar latitudes.

Empirical STORM-E model: I. Theoretical and observational basis

In this study, an improved ionospheric model is presented by applying self‐specified F2 layer parameters and an adaptive topside model into the International Reference Ionosphere (IRI) model. Three F2 layer parameters, the critical frequency (foF2), peak height (hmF2), and the scale height (Hsc) obtained from Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations, are modeled by spherical harmonics expansion. The empirical orthogonal functions are used to construct the associated parameters in the adaptive topside model. The improved model is validated by incoherent scatter radar (ISR) data of Millstone station and the Global Ionospheric Maps. Results show that the NmF2 and hmF2 of improved model have better agreement with ISR measurements. The vertical total electron content deviation compared with Global Ionospheric Map is discussed in different seasons and levels of solar activity. With radio occultation‐based parameters, the accuracy of original IRI model is improved by 1 total electron content unit globally on average.

Mid latitude ionospheric TEC modeling and the IRI model validation during the recent high solar activity (2013–2015)

<p>Increasing the quality of ionosphere modeling is crucial and remains a challenge for many geodetic applications such as GNSS Precise Point Positioning (PPP) and navigation. Ionosphere models are the main tool to provide an estimation of Total Electron Content (TEC) to be corrected from GNSS career phase and pseudorange measurements. Skills of these models are however limited due to the simplifications in model equations and the imperfect knowledge of model parameters. In this study, an ionosphere reconstruction approach is presented, where global estimations of geodetic-based TEC measurements are combined with an ionospheric background model. This is achieved here through a novel simultaneous Calibration and Data Assimilation (C/DA) technique that works based on the sequential Ensemble Kalman Filter (EnKF). The C/DA method ingests the actual ionospheric measurements (derived from global GNSS measurements) into the IRI (International Reference Ionosphere) model. It also calibrates those parameters that control the F2 layer’s characteristics such as selected important CCIR (Comité Consultatif International des Radiocommunicationsand) URSI (International Union of Radio Science) coefficients.  The calibrated parameters derived from the C/DA are then replaced in the IRI to simulate TEC values in locations, where less GNSS ground-station infrastructure exists, as well as to enhance the prediction of TEC when the observations are not available or their usage is cautious due to low quality. Our numerical assessments indicate the advantage of the C/DA to improve the IRI’s performance. Values of the TEC-Root Mean Square of Error (RMSE) are found to be decreased by up to 30% globally, compared to the original IRI simulations. The importance of the new TEC estimations is demonstrated for PPP applications, whose results show improvements in navigation applications.</p><p><strong>Keywords: </strong>Ionosphere, Calibration and Data Assimilation (C/DA), IRI, Total Electron Content (TEC), Precise Point Positioning (PPP), GNSS</p>

The 630‐nm nighttime airglow is radiated by O(1D) atoms, which are produced by the dissociative recombination of O2+ ions. The typical approach used to calculate the red line emission rate at night is based on the assumption that O2+ is mainly produced by the reaction of O+ with molecular oxygen. In the case that the O2+ density is much smaller than the O+ density, [O+] = ne in the F2 region. Good agreement between measured nighttime integrated emission rates and the emission rates calculated by this typical approach, using both electron densities measured by incoherent scatter radars and given by the International Reference Ionosphere (IRI) model, has been shown. However, the O2+ densities given by the IRI model are much higher than the densities produced by the reaction of O+ with O2, and these densities do not correspond to the condition [O+] = ne. In this case, the typical approach cannot be applied and molecular ions must be included in the emission rate calculations. The integrated emission rates calculated including the molecular ion density given by the IRI model have been found to be much higher than the measured 630.0‐nm emission rates. This discrepancy takes place at latitudes below about ±30° in the western longitude sector, mainly for the period from March to November, and the disagreement is higher than 1 order of magnitude at the equator. In addition, we model the F2 region green line O(1S) emission at 557.7 nm resulting from the dissociative recombination of O2+. Using measurements of this volume emission rate made by the Wind Imaging Interferometer (WINDII) satellite, we are able to show that IRI overestimates the O2+ density (and ion fraction) on the bottomside of the F2 region. A revision of the ion composition in the IRI model on the bottomside seems to be needed on the basis of these results. Airglow measurements may be useful in constraining such a revision. A revision could utilize the formulae for the relationship between the molecular ion densities and neutral densities derived here, using the Mass Spectrometer Incoherent Scatter (MSIS) neutral densities and the IRI electron density. These calculations are based on the assumption that O2+ and NO+ are only produced through ion‐molecular reactions. Such a revision would correct the magnitude and altitudinal dependence of the molecular ion fraction in the IRI model.

[1] This work presents the results of a local empirical model that describes the behavior of the ionospheric F2 region peak. The model was developed using nearly 25 years of incoherent scatter radar (ISR) measurements made at the Arecibo Observatory (AO) between 1985 and 2009. The model describes the variability of the F2 peak frequency (foF2) and F2 peak height (hmF2) as a function of local time, season, and solar activity for quiet-to-moderate geomagnetic activity conditions (Kp < 4+). Our results show that the solar activity control of hmF2 and foF2 over Arecibo can be better described by a new proxy of the solar flux (F107P), which is presented here. The variation of hmF2 parameter with F107P is virtually linear, and only a small saturation of the foF2 parameter is observed at the highest levels of solar flux. The winter anomaly and asymmetries in the variation of the modeled parameters between equinoxes were detected during the analyses and have been taken into account by the AO model. Comparisons of ISR data with international reference ionosphere (IRI) model predictions indicate that both CCIR and URSI modes overestimate foF2 during the daytime and underestimate it at night. As expected, this underestimation is not observed in the AO model. Our analyses also show that the hmF2 parameter predicted by the IRI modes shows a saturation point, which causes hmF2 to be underestimated at high solar activity. The underestimation increases with higher levels of solar activity. Finally, we also found that IRI predictions of the seasonal variability of foF2 and hmF2 over Arecibo can be improved by using a small correction that varies with solar activity and local time.

Testing the improvement of performance of the IRI model in the estimation of TEC over the mid-latitude American regions

The ionospheric delay is of paramount importance to radio communication, satellite navigation and positioning. It is necessary to predict high-accuracy ionospheric peak parameters for single frequency receivers. In this study, the state-of-the-art artificial neural network (ANN) technique optimized by the genetic algorithm is used to develop global ionospheric models for predicting foF2 and hmF2. The models are based on long-term multiple measurements including ionospheric peak frequency model (GIPFM) and global ionospheric peak height model (GIPHM). Predictions of the GIPFM and GIPHM are compared with the International Reference Ionosphere (IRI) model in 2009 and 2013 respectively. This comparison shows that the root-mean-square errors (RMSEs) of GIPFM are 0.82 MHz and 0.71 MHz in 2013 and 2009, respectively. This result is about 20%–35% lower than that of IRI. Additionally, the corresponding hmF2 median errors of GIPHM are 20% to 30% smaller than that of IRI. Furthermore, the ANN models present a good capability to capture the global or regional ionospheric spatial-temporal characteristics, e.g., the equatorial ionization anomaly and Weddell Sea anomaly. The study shows that the ANN-based model has a better agreement to reference value than the IRI model, not only along the Greenwich meridian, but also on a global scale. The approach proposed in this study has the potential to be a new three-dimensional electron density model combined with the inclusion of the upcoming Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) data.

The International Reference Ionosphere (IRI) imports global effective ionospheric IG12 index based on ionosonde measurements of the critical frequency foF2 as a proxy of solar activity. Similarly, the global electron content (GEC), smoothed by the sliding 12-months window (GEC12), is used as a solar proxy in the ionospheric and plasmaspheric model IRI-Plas. GEC has been calculated from global ionospheric maps of total electron content (TEC) since 1998 whereas its productions for the preceding years and predictions for the future are made with the empirical model of the linear dependence of GEC on solar activity. At present there is a need to re-evaluate solar and ionospheric indices in the ionospheric models due to the recent revision of sunspot number (SSN2) time series, which has been conducted since July 1, 2015 [Clette et al., 2014]. Implementation of SSN2 instead of the former SSN1 series with the ionospheric model could increase model prediction errors. A formula is proposed to transform the smoothed SSN212 series to the proxy of the former basic SSN112=R12 index, which is used by the IRI and IRI-Plas models for long-term ionospheric predictions. Regression relationships are established between GEC12, the sunspot number R12, and the proxy solar index of 10.7 cm microwave radio flux, F10.712. Comparison of calculations by the IRI-Plas and IRI models with observations and predictions for Moscow during solar cycles 23 and 24 has shown the advantage of implementation of GEC12 index with the IRI-Plas model.

The international reference ionosphere (IRI) is the internationally recognized and recommended standard for the specification of plasma parameters in Earth’s ionosphere. It describes monthly averages of electron density, electron temperature, ion temperature, ion composition, and several additional parameters in the altitude range from 60 to 1,500 km. A joint working group of the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) is in charge of developing and improving the IRI model. As requested by COSPAR and URSI, IRI is an empirical model being based on most of the available and reliable data sources for the ionospheric plasma. The paper describes the latest version of the model and reviews efforts towards future improvements, including the development of new global models for the F2 peak density and height, and a new approach to describe the electron density in the topside and plasmasphere. Our emphasis will be on the electron density because it is the IRI parameter most relevant to geodetic techniques and studies. Annual IRI meetings are the main venue for the discussion of IRI activities, future improvements, and additions to the model. A new special IRI task force activity is focusing on the development of a real-time IRI (RT-IRI) by combining data assimilation techniques with the IRI model. A first RT-IRI task force meeting was held in 2009 in Colorado Springs. We will review the outcome of this meeting and the plans for the future. The IRI homepage is at http://www.IRI.gsfc.nasa.gov.

Diurnal variations of the ionospheric electron density height profiles over Irkutsk: Comparison of the incoherent scatter radar measurements, GSM TIP simulations and IRI predictions