Ionospheric heating due to solar flares as measured by SROSS-C2 satellite

The data on thermal fluctuations of the topside ionosphere have been measured by Retarding Potential Analyser (RPA) payload aboard the SROSS-C2 satellite over the Indian region for half of the solar cycle (1995–2000). The data on solar flare has been obtained from National Geophysical Data Center (NGDC) Boulder, Colorado (USA) and other solar indices (solar radio flux and sunspot number) were download from NGDC website. The ionospheric electron and ion temperatures show a consistent enhancement during the solar flares. The enhancement in the electron temperature is 28–92% and for ion temperature it is 18–39% compared to the normal day’s average temperature. The enhancement of ionospheric temperatures due to solar flares is correlated with the variation of sunspot and solar radio flux (F10.7cm). All the events studied in the present paper fall in the category of subflare with almost same intensity. The ionospheric electron and ion temperatures enhancement have been compared with the IRI model values.     

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.     

What is the optimum solar proxy for long-term ionospheric investigations?

The problem of optimum solar proxy is important for long-term and/or climatological studies of ionospheric parameters. Here we focus on possibly different optimum solar proxies for different ionospheric parameters, as they are affected by partly different spectral ranges of solar ionizing radiation. We use yearly average values of foF2 and foE of four European stations with long (1976–2014) and high-quality data (Juliusruh, Pruhonice, Rome, Slough/Chilton), and the global total electron content (G-TEC). Four solar proxies are used: F10.7, Mg II, solar Lymna-alpha flux Fα and sunspot numbers. The most important finding is that the optimum solar proxies are different for different ionospheric parameters. The most suitable solar proxy for foF2 is found to be Mg II, whereas for foE F10.7 evidently outperforms Mg II. Fα and sunspot numbers perform slightly worse but none of four solar proxies performs poorly. F10.7 is favored for G-TEC, to some extent surprisingly, as previous results favored rather Mg II.     

EUV-TEC proxy to describe ionospheric variability using satellite-borne solar EUV measurements: First results

Primary photoionisation of major ionospheric constituents is calculated from satellite-borne solar EUV measurements. Number densities of the background atmosphere are taken from the NRLMSISE-00 climatology. From the calculated ionisation rates, a proxy termed EUV-TEC, which is based on the global total ionisation is calculated, and describes the ionospheric response to solar EUV and its variability. The proxy is compared against the global mean ionospheric total electron content (TEC) derived from GPS data. Results show that the EUV-TEC proxy provides a better overall representation of global TEC than conventional solar indices like F10.7 do. The EUV-TEC proxy may be used for scientific research, and to describe the ionospheric effects on radio communication and navigation systems.     

Validate the IRI2007 model by the COSMIC slant TEC data during the extremely solar minimum of 2008

During 2008, the solar activity is extremely low. The satellite observations show that the ionospheric height and electron density is much lower than the predictions by the international reference ionosphere (IRI) model. In this paper, we compared the slant total electron content (TEC) observed by the COSMIC satellites during 2008 with the IRI model results. It is found that the IRI model with IRI2001 and IRI2001 Cor. topside options will always overestimate the electron density in both lower and higher altitudes. But the rest two topside options (NeQuick, and TTS) tend to overestimate the electron density in the F layer and underestimate it in the topside altitudes. The switch altitude between overestimation and underestimation and the latitude-local time distribution of the model deviation depend on the topside option. The current investigation might be useful for the model improvement as well as data assimilation work based on the IRI model and the LEO TEC data.     

Effects of solar activity variations on the low latitude topside nighttime ionosphere

We have studied the topside nighttime ionosphere of the low latitude region using data obtained from DMSP F15, ROCSAT-1, KOMPSAT-1, and GUVI on the TIMED satellite for the period of 2000–2004, during which solar activity decreased from its maximum. As these satellites operated at different altitudes, we were able to discriminate altitude dependence of several key ionospheric parameters on the level of solar activity. For example, with intensifying solar activity, electron density was seen to increase more rapidly at higher altitudes than at lower altitudes, implying that the corresponding scale height also increased. The density increased without saturation at all observed altitudes when plotted against solar EUV flux instead of F10.7. The results of the present study, as compared with those of previous studies for lower altitudes, indicate that topside vertical scale height increases with altitude and that, when solar activity increases, topside vertical scale height increases more rapidly at higher altitudes than at lower altitudes. Temperature also increased more rapidly at higher altitudes than at lower altitudes as solar activity increased. In addition, the height of the F2 peak was seen to increase with increasing solar activity, along with the oxygen ion fraction measured above the F2 peak. These results confirm that the topside ionosphere rises and expands with increasing solar activity.     

Variations of total electron content over high latitude region during the ascending phase of 24th solar cycle

The solar cycle variation and seasonal changes significantly affects the ionization process of earth’s ionosphere and required to be monitored in real time basis for regional level refinement of existing models. In view of this, the present study has been carried out by using the ionospheric Total Electron Content (TEC) data observed with the help of Global Ionospheric Scintillation and TEC monitoring (GISTM) system installed at Indian Antarctic Research Station, “Maitri” [70°46′00″S 11°43′56″E] during the ascending phase of 24th solar cycle. The daily values of solar extreme ultraviolet (EUV) flux (0.1–50?nm wavelength), 10.7?cm radio flux F_10.7 and Sunspot number (SSN) has been taken as a proxy to represent the solar cycle variation to correlate with TEC. The linear regression results revels better correlation of TEC with EUV flux rather than F_10.7 and SSN. Also, the EUV and TEC show better agreement during summer as compared to winter and equinox period. Correlation between TEC and EUV appears significantly noticeable during ten internationally defined quiet days of each month (stable background geophysical condition) as compared to the overall days (2010–2014). Further, saturation effect has been observed on TEC values during the solar maxima year 2014. The saturation effects are more prominent during the night hours of winter and equinox season due to transportation losses manifested by the equator-ward direction of meridional wind.     

Accuracy of IRI profiles of ionospheric density and temperatures derived from comparisons to Kharkov incoherent scatter radar measurements

The incoherent scatter radar (ISR) facility in Kharkov, Ukraine (49.6°N, 36.3°E) measures vertical profiles of electron density, electron and ion temperature, and ion composition of the ionospheric plasma up to 1100 km altitude. Acquired measurements constitute an accurate ionospheric reference dataset for validation of the variety of models and alternative measurement techniques. We describe preliminary results of comparing the Kharkov ISR profiles to the international reference ionosphere (IRI), an empirical model recognized for its reliable representation of the monthly-median climatology of the density and temperature profiles during quiet-time conditions, with certain extensions to the storm times. We limited our comparison to only quiet geomagnetic conditions during the autumnal equinoxes of 2007 and 2008. Overall, we observe good qualitative agreement between model and data both in time and with altitude. Magnitude-wise, the measured and modeled electron density and plasma temperatures profiles appear different. We discovered that representation accuracy improves significantly when IRI is driven by observed-averaged values of the solar activity index rather than their predictions. This result motivated us to study IRI performance throughout protracted solar minimum of the 24th cycle. The paper summarizes our observations and recommendations for optimal use of the IRI.     

Ionospheric disturbances under low solar activity conditions

The paper is focused on ionospheric response to occasional magnetic disturbances above selected ionospheric stations located at middle latitudes of the Northern and Southern Hemisphere under extremely low solar activity conditions of 2007–2009. We analyzed changes in the F2 layer critical frequency foF2 and the F2 layer peak height hmF2 against 27-days running mean obtained for different longitudinal sectors of both hemispheres for the initial, main and recovery phases of selected magnetic disturbances. Our analysis showed that the effects on the middle latitude ionosphere of weak-to-moderate CIR-related magnetic storms, which mostly occur around solar minimum period, could be comparable with the effects of strong magnetic storms. In general, both positive and negative deviations of foF2 and hmF2 have been observed independent on season and location. However positive effects on foF2 prevailed and were more significant. Observations of stormy ionosphere also showed large departures from the climatology within storm recovery phase, which are comparable with those usually observed during the storm main phase. The IRI STORM model gave no reliable corrections of foF2 for analyzed events.     

E10.7指数在软X射线谱段的修正应用

表征EUV辐射通量的E10.7指数在越来越多的研究和应用中被用来代替传统的F10.7指数.X射线对地球D层和E层的电离起着重要作用,但由于D层观测数据的不足和E层电离源的多样性,难以被用来考虑X射线对电离层的影响.火星电离层下层的电离源几乎是单一的软X射线,这为研究X射线对电离层的作用提供了可能性.通过研究火星电离层下层的峰值电子浓度对E10.7的依赖关系,发现即便经过必要的修正,这种关系对不同的观测时段并不具备一致性.通过理论推导和数据分析,得到了一种特别用于描述太阳软X射线辐射通量的新指数,即Xs指数,用来替代E10.7指数.Xs指数在描述火星电离层下层对太阳辐射的依赖关系时,不同的观测时段有很好的一致性,表明Xs指数在表征太阳软X射线辐射强度方面比E10.7指数更加合适.      

Analysis of ionospheric TEC response to solar and geomagnetic activities at different solar activity stages

Studying the relationship of total electron content (TEC) to solar or geomagnetic activities at different solar activity stages can provide a reference for ionospheric modeling and prediction. On the basis of solar activity indices, geomagnetic activity parameters, and ionospheric TEC data at different solar activity stages, this study analyzes the overall variation relationships of solar and geomagnetic activities with ionospheric TEC, the characteristics of the quasi-27-day periodic oscillations of the three variables at different stages, and the delayed TEC response of solar activity by conducting correlation analysis, Butterworth band-pass filtering, Fourier transform, and time lag analysis. The following results are obtained. (1) TEC exhibits a significant linear relationship with solar activity at different solar activity stages. The correlation coefficients |R| are arranged as follows: |R|_EUV > |R|_F10.7 > |R|sunspot number. No significant linear relationship exists between TEC and geomagnetic activity parameters (|R| < 0.35). (2) TEC, solar activity indices, and geomagnetic activity parameters have a period of 10.5 years. The maximum amplitudes of the Fourier spectrum for TEC and solar activity indices are nearly 27 days and those of geomagnetic activity parameters are nearly 27 and 13.5 days. (3) The deviations of the quasi-27-day significant periodic oscillation of TEC and solar activity indices are consistent. (4) No evident relationship exists between the quasi-27-day periodic oscillation of TEC and geomagnetic activity parameters. (5) The delay time of TEC for the 10.7 cm solar radio flux and extreme ultraviolet is always consistent, whereas that for sunspot number varies at each stage.     

Variation of foF2 with solar activity

Ionospheric hourly monthly-median values of the F2-layer critical frequency, foF2, from six European stations are correlated with the corresponding 12-month running mean values of each of the six solar indices, the Zurich sunspot number R, the solar radio noise flux at 10.7 cm F, the ionospheric index of solar activity IF2, the index IG, the Australian T index and the Russian RS ionospheric index, using various models. The statistical analysis shows that there is no difference in the degree of correlation in using one index over another. Their statistical behaviour is virtually identical. Furthermore, it is shown that there is a slight degree of favourability for a quadratic relation between foF2 and any index of solar activity.     

Comparison of GPS-TEC measurements with NeQuick2 and IRI model predictions in the low latitude East African region during varying solar activity period (1998 and 2008–2015)

This paper examines the performances of NeQuick2, the latest available IRI-2016, IRI-2012 and IRI-2007 models in describing the monthly and seasonal mean total electron content (TEC) over the East African region. This is to gain insight into the success of the various model types and versions at characterizing the ionosphere within the equatorial ionization anomaly. TEC derived from five Global Positioning System (GPS) receivers installed at Addis Ababa (ADD, 5.33°N, 111.99°E Geog.), Asab (ASAB, 8.67°N, 116.44°E Geog.), Ambo (ABOO, 5.43°N, 111.05°E Geog.), Nairobi (RCMN, ?4.48°N, 108.46°E Geog.) and Nazret (NAZR, 4.78°N, 112.43°E Geog.), are compared with the corresponding values computed using those models during varying solar activity period (1998 and 2008–2015). We found that different models describe the equatorial and anomaly region ionosphere best depending on solar cycle, season and geomagnetic activity levels. Our results show that IRI-2016 is the best model (compared to others in terms of discrepancy range) in estimating the monthly mean GPS-TEC at NAZR, ADD and RCMN stations except at ADD during 2008 and 2012. It is also found that IRI-2012 is the best model in estimating the monthly mean TEC at ABOO station in 2014. IRI show better agreement with observations during June solstice for all the years studied at ADD except in 2012 where NeQuick2 better performs. At NAZR, NeQuick2 better performs in estimating seasonal mean GPS-TEC during 2011, while IRI models are best during 2008–2009. Both NeQuick2 and IRI models underestimate measured TEC for all the seasons at ADD in 2010 but overestimate at NAZR in 2009 and RCMN in 2008. The periodic variations of experimental and modeled TEC have been compared with solar and geomagnetic indices at ABOO and ASAB in 2014 and results indicate that the F10.7 and sunspot number as indices of solar activity seriously affects the TEC variations with periods of 16–32?days followed by the geomagnetic activity on shorter timescales (roughly periods of less than 16?days). In this case, NeQuick2 derived TEC shows better agreement with a long term period variations of GPS-TEC, while IRI-2016 and IRI-2007 show better agreement with observations during short term periodic variations. This indicates that the dependence of NeQuick2 derived TEC on F10.7 is seasonal. Hence, we suggest that representation of geomagnetic activity indices is required for better performance over the low latitude region.     

A new global version of M(3000)F2 prediction model based on artificial neural networks

A new version of global empirical model for the ionospheric propagation factor, M(3000)F2 prediction is presented. Artificial neural network (ANN) technique was employed by considering the relevant geophysical input parameters which are known to influence the M(3000)F2 parameter. This new version is an update to the previous neural network based M(3000)F2 global model developed by Oyeyemi et al. (2007), and aims to address the inadequacy of the International Reference Ionosphere (IRI) M(3000)F2 model (the International Radio Consultative Committee (CCIR) M(3000)F2 model). The M(3000)F2 has been found to be relatively inaccurate in representing the diurnal structure of the low latitude region and the equatorial ionosphere. In particular, the existing hmF2 IRI model is unable to reproduce the sharp post-sunset drop in M(3000)F2 values, which correspond to a sharp post-sunset peak in the peak height of the F2 layer, hmF2. Data from 80 ionospheric stations globally, including a good number of stations in the low latitude region were considered for this work. M(3000)F2 hourly values from 1987 to 2008, spanning all periods of low and high solar activity were used for model development and verification process. The ability of the new model to predict the M(3000)F2 parameter especially in the low latitude and equatorial regions, which is known to be problematic for the existing IRI model is demonstrated.     

Modeling M(3000)F2 based on extreme learning machine

This paper presents an novel extreme learning machine (ELM)-based prediction model for the ionospheric propagation factor M(3000)F2 at Darwin station (12.4°S, 131.5°E; −44.5°dip) in Australia. The proposed ELM model is trained with hourly daily values of M(3000)F2 from the period 1998–2014 except 2001 and 2009. The hourly daily values of 2001 (high solar activity) and 2009 (low solar activity) are used for validating the prediction accuracy. The proposed ELM for modeling M(3000)F2 can achieve faster training process and similar testing accuracy compared with backward propagation neural network (BPNN). In addition, the performance of the ELM is verified by comparing the predicted values of M(3000)F2 with observed values and the international reference ionosphere (IRI −2016) model predicted values. Based on the error differences (the root mean square error (RMSE) and the M(3000)F2 percentage improvement values M(3000)F2_IMP(%)), the result demonstrates the effectiveness of the ELM model compared with the IRI-2016 model at hourly, daily, monthly, and yearly in high (2001) and low (2009) solar activity years. The ELM also shows good agreement with observations compared with the IRI during disturbed magnetic activity.     

基于因果卷积与LSTM网络的电离层总电子含量预报

电离层总电子含量（TEC）不仅是分析电离层形态的关键参数之一,同时为导航及定位等空间应用系统消除电离层附加时延提供重要支撑。由于电离层TEC的时空变化特征,本文融合因果卷积和长短时记忆网络,以太阳活动指数F_10.7、地磁活动指数Dst和电离层TEC历史数据作为特征输入,构建深度学习模型,实现提前24 h预报电离层TEC。进一步利用2005－2013年连续9年的CODE TEC数据,全面评估了模型在北京站（40°N,115°E）、武汉站（30.53°N,114.36°E）和海口站（20.02°N,110.38°E）的预报性能。结果显示不同太阳活动条件下三个站的TEC值与真实测量值的相关系数都大于0.87,均方根误差大都集中在0～1 TECU以内,且模型预报精度与纬度、太阳、地磁活动程度、季节变化相关。与仅由长短时记忆网络构成的预报模型相比,本实验模型均方根误差降低了15%,为电离层TEC预报模型的实际应用提供了参考。      

利用F_(10.7)短期预报电离层F_0F_2

通过对电离层历史数据和太阳射电流量F10.7的回归分析,提出了一种单站电离层f0F2的短期预报方法,以F10.7的流动平均值fc为输入,以未米3天的f0F2为输出,分别利用中国地区8个台站的数据进行检验,分析不同太阳活动水平、季节以及地方时预报误差的分布特征.结果表明,该方法能有效地预测未来1～3天的f0F2.该方法还可应用于其他电离层参量的短期预报.     

利用神经网络预报电离层f0F2

由中国武汉电离层台站和澳大利亚Hobart台站的电离层F2层临界频率(f0F2)的资料,利用三层前向反馈神经网络(BP网络),提出一种提前24h预测f0F2的方法,该方法以前5天观测的f0F2数据拟合的5个系数以及太阳活动参数作为输入,以当天24 h的f0F2作为输出对网络进行训练,训练好的网络可以实现对f0F2提前24 h的预报.预测结果显示,利用神经网络预测的f0F2与实际观测结果变化趋势较一致,并且比IRI的计算结果更加准确.误差分析表明,在南半球Hobart(-42.9°,147.3°)台站比中国武汉站(30.4°,114.3°)的结果要好,在低年比高年要好,在冬夏季节比春秋季节稍好.本文说明利用神经网络对电离层参量进行预报是一种切实可行的方法.     

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.