Computerized ionospheric tomography with the IRI model

Computerized ionospheric tomography (CIT) is a method to estimate ionospheric electron density distribution by using the global positioning system (GPS) signals recorded by the GPS receivers. Ionospheric electron density is a function of latitude, longitude, height and time. A general approach in CIT is to represent the ionosphere as a linear combination of basis functions. In this study, the model of the ionosphere is obtained from the IRI in latitude and height only. The goal is to determine the best representing basis function from the set of Squeezed Legendre polynomials, truncated Legendre polynomials, Haar Wavelets and singular value decomposition (SVD). The reconstruction algorithms used in this study can be listed as total least squares (TLS), regularized least squares, algebraic reconstruction technique (ART) and a hybrid algorithm where the reconstruction from the TLS algorithm is used as the initial estimate for the ART. The error performance of the reconstruction algorithms are compared with respect to the electron density generated by the IRI-2001 model. In the investigated scenario, the measurements are obtained from the IRI-2001 as the line integral of the electron density profiles, imitating the total electron content estimated from GPS measurements. It has been observed that the minimum error between the reconstructed and model ionospheres depends on both the reconstruction algorithm and the basis functions where the best results have been obtained for the basis functions from the model itself through SVD.     

A 2-d ionospheric model for low latitude area – Hong Kong

The ionosphere is an important part of the atmosphere and it is the largest error source of GNSS positioning for single-frequency users. So establishing a precise ionosphere model is one of the critical steps for satellite navigation and also for ionospheric research.     

Ionospheric response to solar and magnetospheric protons during January 15–22, 2005: EAGLE whole atmosphere model results

We present an analysis of the ionosphere and thermosphere response to Solar Proton Events (SPE) and magnetospheric proton precipitation in January 2005, which was carried out using the model of the entire atmosphere EAGLE. The ionization rates for the considered period were acquired from the AIMOS (Atmospheric Ionization Module Osnabrück) dataset. For numerical experiments, we applied only the proton-induced ionization rates of that period, while all the other model input parameters, including the electron precipitations, corresponded to the quiet conditions. In January 2005, two major solar proton events with different energy spectra and proton fluxes occurred on January 17 and January 20. Since two geomagnetic storms and several sub-storms took place during the considered period, not only solar protons but also less energetic magnetospheric protons contributed to the calculated ionization rates. Despite the relative transparency of the thermosphere for high-energy protons, an ionospheric response to the SPE and proton precipitation from the magnetotail was obtained in numerical experiments. In the ionospheric E layer, the maximum increase in the electron concentration is localized at high latitudes, and at heights of the ionospheric F2 layer, the positive perturbations were formed in the near-equatorial region. An analysis of the model-derived results showed that changes in the ionospheric F2 layer were caused by a change in the neutral composition of the thermosphere. We found that in the recovery phase after both solar proton events and the enhancement of magnetospheric proton precipitations associated with geomagnetic disturbances, the TEC and electron density in the F region and in topside ionosphere/plasmasphere increase at low- and mid-latitudes due to an enhancement of atomic oxygen concentration. Our results demonstrate an important role of magnetospheric protons in the formation of negative F-region ionospheric storms. According to our results, the topside ionosphere/plasmasphere and bottom-side ionosphere can react to solar and magnetospheric protons both with the same sign of disturbances or in different way. The same statement is true for TEC and foF2 disturbances. Different disturbances of foF2 and TEC at high and low latitudes can be explained by topside electron temperature disturbances.     

A MARS-based method for estimating regional 2-D ionospheric VTEC and receiver differential code bias

The geometry-free linear combination of dual-frequency GNSS reference station ground observations are currently used to build the Vertical Total Electron Content (VTEC) model of the ionosphere. As it is known, besides ionospheric delays, there are differential code bias (DCB) of satellite (SDCB) and receiver (RDCB) in the geometry-free observation equation. The SDCB can be obtained using the International GNSS Service (IGS) analysis centers, but the RDCB for regional and local network receivers are not provided. Therefore, estimating the RDCB and VTEC model accurately and simultaneously is a critical factor investigated by researchers. This study uses Multivariate Adaptive Regression Splines (MARS) to estimate the VTEC approximate model and then substitutes this model in the observation equation to form the normal equation. The least squares method is used to solve the RDCB and VTEC model together. The research findings show that this method has good modeling effectiveness and the estimated RDCB has good reliability. The estimated VTEC model applied to GPS single-frequency precise point positioning has better positioning accuracy in comparison to the IGS global ionosphere map (GIM).     

Comparative study of foF2 measurements with IRI-2007 model predictions during extended solar minimum

The unusually deep and extended solar minimum of cycle 23/24 made it very difficult to predict the solar indices 1 or 2 years into the future. Most of the predictions were proven wrong by the actual observed indices. IRI gets its solar, magnetic, and ionospheric indices from an indices file that is updated twice a year. In recent years, due to the unusual solar minimum, predictions had to be corrected downward with every new indices update. In this paper we analyse how much the uncertainties in the predictability of solar activity indices affect the IRI outcome and how the IRI values calculated with predicted and observed indices compared to the actual measurements. Monthly median values of F2 layer critical frequency (foF2) derived from the ionosonde measurements at the mid-latitude ionospheric station Juliusruh were compared with the International Reference Ionosphere (IRI-2007) model predictions. The analysis found that IRI provides reliable results that compare well with actual measurements, when the definite (observed and adjusted) indices of solar activity are used, while IRI values based on earlier predictions of these indices noticeably overestimated the measurements during the solar minimum. One of the principal objectives of this paper is to direct attention of IRI users to update their solar activity indices files regularly. Use of an older index file can lead to serious IRI overestimations of F-region electron density during the recent extended solar minimum.     

武汉地区电离层电子浓度总含量的统计经验模式研究

由武汉电离层观象台一个太阳黑子周期(1980-1990年)的实测电离层电子浓度总含量(TEC)资料,统计分析得出了武汉地区的一个 TEC经验模式.模式很好地再现了武汉地区的TEC观测值.其预测误差在太阳活动高年稍大,低年较小;在春秋两季稍大,冬夏两季较小;在当地时间白天和傍晚稍大,夜间和早晨较小.此外,与国际参考电离层模式IRI的计算结果比较,本模式预测的TEC值更接近于实际观测结果.同时,本文也初步探讨了TEC的半年变化特征和冬季异常现象.