化学物质释放人工改变电离层

考虑中性气体在电离层高度的扩散过程和相应的电离层离子化学过程,研究了利用主动化学物质释放来改变电离层的方法,理论计算了H₂O和SF₆两种气体释放后电离层随时间的响应过程.结果表明,在电离层高度上气体的扩散过程非常迅速,电离层F区的电子密度有很大程度的减少,而扩散慢且化学反应快的气体对电离层的影响更大,就更加有利于电离层洞的形成.     

武昌地区急始型磁暴期间电离层电子总含量的变化

利用１９８０年４月至１９９０年１２月共１３６次急始型磁暴资料统计研究了武昌地区ＴＥＣ的变化。结果表明，ＴＥＣ的暴时变化出现正相，相对变化值ΔＴＥＣ的暴时变化形态与中高纬地区一些台站所观测到的结果差别较大；如果磁暴急始出现在白天，则急始后３６小时，会出现ΔＴＥＣ的极大值，如果急始出现在夜间，则不会出现极大值，这一现象与太阳黑子数，季节无关。     

Variation in the ionospheric propagating factor M(3000)F2 at Ouagadougou,Burkina Faso

We use hourly monthly median values of propagation factor M(3000)F2 data observed at Ouagadougou Ionospheric Observatory (geographic12.4°N, 1.5°W; 5.9^o dip), Burkina Faso (West Africa) during the years Januar1987–December1988 (average F10.7 < 130 × 10⁻²² W/m²/Hz, representative of low solar flux conditions) and for January 1989–December1990 (average F10.7 ? 130 × 10⁻²² W/m²/Hz, representative of high solar epoch) for magnetically quiet conditions to describe local time, seasonal and solar cycle variations of equatorial ionospheric propagation factor M(3000)F2 in the African region. We show that that seasonal trend between solar maximum and solar minimum curves display simple patterns for all seasons and exhibits reasonable disparity with root mean square error (RMSE) of about 0.31, 0.29 and 0.26 for December solstice, June solstice and equinox, respectively. Variability Σ defined by the percentage ratio of the absolute standard deviation to the mean indicates significant dissimilarity for the two solar flux levels. Solar maximum day (10–14 LT) and night (22–02 LT) values show considerable variations than the solar minimum day and night values. We compare our observations with those of the IRI 2007 to validate the prediction capacity of the empirical model. We find that the IRI model tends to underestimate and overestimate the observed values of M(3000)F2, in particular, during June solstice season. There are large discrepancies, mainly during high solar flux equinox and December solstice between dawn and local midnight. On the other hand, IRI provides a slightly better predictions for M(3000)F2 between 0900 and 1500 LT during equinox low and high solar activity and equinox high sunspot number. Our data are of great importance in the area of short-wave telecommunication and ionospheric modeling.     

Stochastic modelling considering ionospheric scintillation effects on GNSS relative and point positioning

Global Navigation Satellite Systems (GNSS), in particular the Global Positioning System (GPS), have been widely used for high accuracy geodetic positioning. The Least Squares functional models related to the GNSS observables have been more extensively studied than the corresponding stochastic models, given that the development of the latter is significantly more complex. As a result, a simplified stochastic model is often used in GNSS positioning, which assumes that all the GNSS observables are statistically independent and of the same quality, i.e. a similar variance is assigned indiscriminately to all of the measurements. However, the definition of the stochastic model may be approached from a more detailed perspective, considering specific effects affecting each observable individually, as for example the effects of ionospheric scintillation. These effects relate to phase and amplitude fluctuations in the satellites signals that occur due to diffraction on electron density irregularities in the ionosphere and are particularly relevant at equatorial and high latitude regions, especially during periods of high solar activity. As a consequence, degraded measurement quality and poorer positioning accuracy may result.     

Prompt effects of solar wind variations on the inner magnetosphere and midlatitude ionosphere

It is well known that the solar wind can significantly affect high-latitude ionospheric dynamics. However, the effects of the solar wind on the middle- and low-latitude ionosphere are much less studied. In this paper, we report observations that large perturbations in the middle- and low-latitude ionosphere are well correlated with solar wind variations. In one event, a significant (20–30%) decrease of the midlatitude ionospheric electron density over a large latitudinal range was related to a sudden drop in the solar wind pressure and a northward turning of the interplanetary magnetic field, and the density decrease became larger at lower latitudes. In another event, periodic perturbations in the dayside equatorial ionospheric E × B drift and electrojet were closely associated with variations in the interplanetary electric field. Since the solar wind is always changing with time, it can be a very important and common source of ionospheric perturbations at middle- and low-latitudes. The relationship between solar wind variations and significant ionospheric perturbations has important applications in space weather.     

Doppler characteristics of HF spread Doppler clutter recorded at Alice Springs,Australia

Mean night-time peak power, Doppler shift and Doppler width of spread Doppler clutter (SDC) received by a high frequency backscatter radar located at Alice Springs, Australia from 2000 to 2018 is presented as a function of azimuth, sunspot number, time of year and frequency. The sampled region covers 90 degrees from West to North and includes the northern and southern equatorial anomalies.SDC peak power diminished across all azimuths during the winter solstice from around May to August (local winter) coinciding with the global decrease in F layer density due to the annual non-seasonal F2 anomaly but was generally constant during the equinoxes. In contrast, SDC Doppler width and inbound Doppler shift both increased during the equinoxes and exhibited azimuthal dependence related to the eastward equatorial plasma drift.SDC peak power increased with increasing sunspot number with frequency dependence during winter but not summer. Inbound Doppler shift and Doppler width increased with increasing sunspot number during equinox but not solstice with a strong dependence on azimuth and a weak dependence on frequency.     

Using the radial basis function neural network to predict ionospheric critical frequency of F2 layer over Wuhan

Neural networks (NNs) have been applied to ionospheric predictions recently. This paper uses radial basis function neural network (RBF-NN) to forecast hourly values of the ionospheric F₂ layer critical frequency(f_oF₂), over Wuhan (30.5N, 114.3E), China. The false nearest neighbor method is used to determine the embedding dimension, and the principal component analysis (PCA) is used to reduce noise and dimension. The whole study is based on a sample of about 26,000 observations of f_oF₂ with 1-h time resolution, derived during the period from January 1981 to December 1983. The performance of RBF-NN is estimated by calculating the normalized root-mean-squared (NRMSE) error, and its results show that short-term predictions of f_oF₂ are improved.     

Tomographic reconstruction of the ionospheric electron density as a function of space and time

Electron density distribution is the major determining parameter of the ionosphere. Computerized Ionospheric Tomography (CIT) is a method to reconstruct ionospheric electron density image by computing Total Electron Content (TEC) values from the recorded Global Positioning Satellite System (GPS) signals. Due to the multi-scale variability of the ionosphere and inherent biases and errors in the computation of TEC, CIT constitutes an underdetermined ill-posed inverse problem. In this study, a novel Singular Value Decomposition (SVD) based CIT reconstruction technique is proposed for the imaging of electron density in both space (latitude, longitude, altitude) and time. The underlying model is obtained from International Reference Ionosphere (IRI) and the necessary measurements are obtained from earth based and satellite based GPS recordings. Based on the IRI-2007 model, a basis is formed by SVD for the required location and the time of interest. Selecting the first few basis vectors corresponding to the most significant singular values, the 3-D CIT is formulated as a weighted least squares estimation problem of the basis coefficients. By providing significant regularization to the tomographic inversion problem with limited projections, the proposed technique provides robust and reliable 3-D reconstructions of ionospheric electron density.     

Ionospheric electron density over Resolute Bay according to E-CHAIM model and RISR radar measurements

In this study, predictions of the E-CHAIM ionospheric model are compared with measurements by the incoherent scatter radars RISR at Resolute Bay, Canada, in the northern polar cap. Reasonable coverage was available for all seasons except winter for which no conclusions were drawn. It is shown that ratios of the model-to measured electron densities are close to unity in the central part of the F layer, around its peak. This is particularly evident for summer daytime. Distributions of the ratios are wider for other seasons indicating larger number of cases when the model underestimates or overestimates. E-CHAIM underestimates the electron density at ionospheric topside and bottomside by ～ 10–20 %. At the bottomside, the underestimations are strongest in summer and equinoctial nighttime. At the topside, the underestimations are strongest in autumn nighttime. Model overestimations are noticeable in the middle part of the F layer during dawn hours in autumn. Overall, the model tends to not predict highest-observed peak electron densities and the largest-observed heights of the peak.