Monthly mean foF2 model for an African low-latitude station and comparison with IRI

We have employed the hourly values of the ionospheric F-region critical frequency (foF2) obtained from Ouagadougou ionosonde, Burkina Faso (geographic coordinates 12° N, 1.8° W) during the interval of 1985–1995 (solar cycle 22) and solar radio flux of 10 cm wavelength (F10.7) to develop a local model (LM) for the African low-latitude station. The model was developed from regression analysis method, using the two-segmented regression analysis. We validated LM with foF2 data from Korhogo observatory, Cote d’Ivorie (geographical coordinates 9.3° N, 5.4° W). LM as well as the International Reference Ionosphere (IRI) agrees well with observations. LM gave some improvement on the IRI-predicted foF2 values at the sunrise (06 LT) at all solar flux levels and in all seasons except June solstice. The performance of the models at the representing the salient features of the equatorial foF2 was presented. Considering daytime and nighttime performances, LM and IRI are comparable in low solar activity (LSA), LM performed better than IRI in moderate solar activity (MSA), while IRI performed better than LM in high solar activity (HSA). CCIR has a root mean square error (r.m.s.e), which is only 0.10 MHz lower than that of LM while LM has r.m.s.e, which is about 0.05 MHz lower than that of URSI. In general, our result shows that performance of IRI, especially the CCIR option of the IRI, is quite comparable with the LM. The improved performance of IRI is a reflection of the numerous contributions of ionospheric physicists in the African region, larger volume of data for the IRI and the diversity of data sources, as well as the successes of the IRI task force activities.     

Correlation of IRTAM and FPMU data confirming the application of IRTAM to support ISS Program safety

A “Real-Time” plasma hazard assessment process was developed to support International Space Station (ISS) Program real-time decision-making providing solar array constraint relief information for Extravehicular Activities (EVAs) planning and operations. This process incorporates real-time ionospheric conditions, ISS solar arrays’ orientation, ISS flight attitude, and where the EVA will be performed on the ISS. This assessment requires real-time data that is presently provided by the Floating Potential Measurement Unit (FPMU) which measures the ISS floating potential (FP), along with ionospheric electron number density (Ne) and electron temperature (Te), in order to determine the present ISS environment. Once the present environment conditions are correlated with International Reference Ionosphere (IRI) values, IRI is used to forecast what the environment could become in the event of a severe geomagnetic storm. If the FPMU should fail, the Space Environments team needs another source of data which is utilized to support a short-term forecast for EVAs. The IRI Real-Time Assimilative Mapping (IRTAM) model is an ionospheric model that uses real-time measurements from a large network of digisondes to produce foF2 and hmF2 global maps in 15?min cadence. The Boeing Space Environments team has used the IRI coefficients produced in IRTAM to calculate the Ne along the ISS orbital track. The results of the IRTAM model have been compared to FPMU measurements and show excellent agreement. IRTAM has been identified as the FPMU back-up system that will be used to support the ISS Program if the FPMU should fail.     

Equatorial predictions from a new neural network based global foF2 model

A new neural network (NN) based global empirical model for the foF2 parameter, which represents the peak ionospheric electron density, has been developed using extended temporal and spatial geophysical relevant inputs. It has been proposed that this new model be considered as a suitable replacement for the International Union of Radio Science (URSI) and International Radio Consultative Committee (CCIR) model options currently used within the International Reference Ionosphere (IRI) model for the purpose of F2 peak electron density predictions. The most recent version of the model has incorporated data from 135 global ionospheric stations including a number of equatorial stations.     

Comparison of observed ionospheric vertical TEC over the sea in Indian region with IRI-2016 model

The vertical ionospheric TEC values obtained from GAGAN grid based ionospheric delay correction values over the sea in the Indian equatorial region have been compared with the corresponding values derived from the International Reference Ionosphere model, IRI-2016. The objective of this work is to study the deviation of the vertical TEC derived from the IRI model from ground truths over the sea for different conditions. This will serve the basic intention of assessing the candidature of the IRI model as an alternative ionospheric correction model in navigation receivers in terms of accuracy. We have chosen different solar activity periods, seasons, geomagnetic conditions, locations etc. for our comparison and analysis. The TEC values by the IRI-2016 were compared with the actual measured values for the given conditions and errors were obtained. The measured vertical TEC values at the ionospheric grid points were derived from the GAGAN broadcast ionospheric delay data and used as reference. The IRI model with standard internal functions was used in estimating the TEC at the same ionospheric grid points. The errors in the model derived values are statistically analysed. Broadly, the results show that, for the Indian sector over the sea, the IRI model performs better on quiet days in off equatorial regions, particularly in the northern region. The overall performance degrades for other conditions with the model generally underestimating the true TEC values and most severely in the equatorial region. The performance is worst in this region for the disturbed days of the equinoctial period. The comparison study is also done with the TEC data measured directly by dual frequency GPS receivers. The results were found to be in general agreement with those obtained by comparing the model with GAGAN broadcast data as reference. This study will be useful in considering the IRI-2016 model for real time estimates of TEC as an alternative to the current parametric model in a satellite navigation receiver in absence of other options.     

A 12 year comparison of MIDAS and IRI 2007 ionospheric Total Electron Content

Data assimilation in conventional meteorological applications uses measurements in conjunction with a physical model. In the case of the ionised region of the upper atmosphere, the ionosphere, assimilation techniques are much less mature. The empirical model known as the International Reference Ionosphere (IRI) could be used to augment data-sparse regions in an ionospheric now-cast and forecast system. In doing so, it is important that it does not introduce systematic biases to the result. Here, the IRI model is compared to ionospheric observations from the Global Positioning System satellites over Europe and North America. Global Positioning System data are processed into hour-to-hour monthly averages of vertical Total Electron Content using a tomographic technique. A period of twelve years, from January 1998 to December 2009, is analysed in order to capture variations over the whole solar cycle. The study shows that the IRI model underestimates Total Electron Content in the daytime at solar maximum by up to 37% compared to the monthly average of GPS tomographic images, with the greatest differences occurring at the equinox. IRI shows good agreement at other times. Errors in TEC are likely due to peak height and density inaccuracies. IRI is therefore a suitable model for specification of monthly averages of Total Electron Content and can be used to initialise a data assimilation process at times away from solar maximum. It may be necessary to correct for systematic deviations from IRI at solar maximum, and to incorporate error estimation into a data assimilation scheme.     

A regional model for the prediction of M(3000)F2 over East Asia

Research on empirical or physical models of ionospheric parameters is one of the important topics in the field of space weather and communication support services. To improve the accuracy of predicting the monthly median ionospheric propagating factor at 3000 km of the F2 layer (identified as M(3000)F2) for high frequency radio wave propagation, a model based on modified orthogonal temporal–spatial functions is proposed. The proposed model has three new characteristics: (1) The solar activity parameters of sunspot number and the 10.7-cm solar radio flux are together introduced into temporal reconstruction. (2) Both the geomagnetic dip and its modified value are chosen as features of the geographical spatial variation for spatial reconstruction. (3) A series of harmonic functions are used to represent the M(3000)F2, which reflects seasonal and solar cycle variations. The proposed model is established by combining nonlinear regression for three characteristics with harmonic analysis by using vertical sounding data over East Asia. Statistical results reveal that M(3000)F2 calculated by the proposed model is consistent with the trend of the monthly median observations. The proposed model is better than the International Reference Ionosphere (IRI) model by comparison between predictions and observations of six station, which illustrates that the proposed model outperforms the IRI model over East Asia. The proposed method can be further expanded for potentially providing more accurate predictions for other ionospheric parameters on the global scale.     

TEC variability near northern EIA crest and comparison with IRI model

Monthly median values of hourly total electron content (TEC) is obtained with GPS at a station near northern anomaly crest, Rajkot (geog. 22.29°N, 70.74°E; geomag. 14.21°N, 144.9°E) to study the variability of low latitude ionospheric behavior during low solar activity period (April 2005 to March 2006). The TEC exhibit characteristic features like day-to-day variability, semiannual anomaly and noon bite out. The observed TEC is compared with latest International Reference Ionosphere (IRI) – 2007 model using options of topside electron density, NeQuick, IRI01-corr and IRI-2001 by using both URSI and CCIR coefficients. A good agreement of observed and predicted TEC is found during the daytime with underestimation at other times. The predicted TEC by NeQuick and IRI01-corr is closer to the observed TEC during the daytime whereas during nighttime and morning hours, IRI-2001 shows lesser discrepancy in all seasons by both URSI and CCIR coefficients.     

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.     

Ionospheric variability at taiwan low latitude station: Comparison between observations and IRI-2001 model

This paper presents the observed ionospheric F-region critical frequency, foF2, and peak height, hmF2, at northern crest of equatorial ionization anomaly (EIA) area station, namely Chung-Li (24.9°N, 121.1°E, dip 35°), and to be compared with International Reference Ionosphere model (IRI-2001) predictions for the period from 1994 to 1999, corresponding to half of the 23rd solar cycle. The diurnal and seasonal variation of foF2 and hmF2 are analyzed for different solar phases, respectively. The result shows the largest discrepancies were observed during nighttime for foF2 and hmF2, respectively. The value of foF2 both CCIR and URSI selected in the IRI model produced a good agreement during the daytime and underestimated during the noon time for high solar activities. The underestimation at noon time is mainly caused by the fountain effect from equator. Further, the peak height hmF2 shows a larger variability around the midnight than daytime in the equinox and winter seasons and reserved in summer, respectively. The study shows that the monthly median values of observed hmF2 is somewhat lower than those predicated by the IRI model, at night time in all the seasons except the period of 04:00–06:00 LT and reverse at daytime in summer. In general the IRI model predictions with respect to the observed in hmF2 is much better than foF2. The percentage deviation of the observed foF2 (hmF2) values with respect to the IRI model varies from 5% to 80% (0–25%) during nighttime and 2–17% (0–20%) at daytime, respectively. In general, the model generates good results, although some improvements are still necessary to implement in order to obtain better simulations for ionospheric low-latitudes region.     

TEC derived from some GPS stations in Nigeria and comparison with the IRI and NeQuick models

Total electron content (TEC) measured simultaneously using Global Positioning System (GPS) ionospheric monitors installed at some locations in Nigeria during the year 2011 (Rz = 55.7) was used to study the diurnal, seasonal, and annual TEC variations. The TEC exhibits daytime maximum, seasonal variation and semiannual variations. Measured TEC were compared with those predicted by the improved versions of the International Reference Ionosphere (IRI) and NeQuick models. The models followed the diurnal and seasonal variation patterns of the observed values of TEC. However, IRI model produced better estimates of TEC than NeQuick at all locations.     

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.     

Performance evaluation of IRI-2007 at equatorial latitudes and its Matlab version for GNSS applications

International Reference Ionosphere (IRI) model is the widely used empirical model for ionospheric predictions, especially TEC which is an important parameter for radio navigation and communication. The Fortran based IRI-2007 does not support real-time interactive visualization and debugging. Therefore, the source code is converted into Matlab and is validated for the purposes of this study. This facilitates easy representation of results and for near real-time implementation of IRI in the applications including spacecraft launching, now casting, pseudolite based navigation systems etc. In addition, the vertical delay results over the equatorial region derived from IRI and GPS data of three IGS stations namely Libreville (Garbon, Africa), Brasilia (Brazil, South America) and Hyderabad (India, Asia) are compared. As the IRI model does not account for plasmasphere TEC, the vertical delays are underestimated compared to vertical delays of GPS signals. Therefore, the model should be modified accordingly for precise TEC estimation.     

Comparison of standard TEC models with a Neural Network based TEC model using multistation GPS TEC around the northern crest of Equatorial Ionization Anomaly in the Indian longitude sector during the low and moderate solar activity levels of the 24th solar cycle

The highest Total Electron Content (TEC) values in the world normally occur at Equatorial Ionization Anomaly (EIA) region resulting in largest ionospheric range delay values observed for any potential Space Based Augmentation System (SBAS). Reliable forecasting of TEC is crucial for satellite based navigation systems. The day to day variability of the location of the anomaly peak and its intensity is very large. This imposes severe limitations on the applicability of commonly used ionospheric models to the low latitude regions. It is necessary to generate a mathematical ionospheric forecasting and mapping model for TEC based on physical ionospheric influencing parameters. A model, IRPE-TEC, has been developed based on real time low latitude total electron content data using GPS measurements from a number of stations situated around the northern crest of the EIA during 2007 through 2011 to predict the vertical TEC values during the low and moderate solar activity levels of the 24th solar cycle. This model is compared with standard ionospheric models like International Reference Ionosphere (IRI) and Parameterized Ionospheric Model (PIM) to establish its applicability in the equatorial region for accurate predictions.     

A prediction model of short-term ionospheric foF2 based on AdaBoost

In this paper, the AdaBoost-BP algorithm is used to construct a new model to predict the critical frequency of the ionospheric F2-layer (foF2) one hour ahead. Different indices were used to characterize ionospheric diurnal and seasonal variations and their dependence on solar and geomagnetic activity. These indices, together with the current observed foF2 value, were input into the prediction model and the foF2 value at one hour ahead was output. We analyzed twenty-two years’ foF2 data from nine ionosonde stations in the East-Asian sector in this work. The first eleven years’ data were used as a training dataset and the second eleven years’ data were used as a testing dataset. The results show that the performance of AdaBoost-BP is better than those of BP Neural Network (BPNN), Support Vector Regression (SVR) and the IRI model. For example, the AdaBoost-BP prediction absolute error of foF2 at Irkutsk station (a middle latitude station) is 0.32 MHz, which is better than 0.34 MHz from BPNN, 0.35 MHz from SVR and also significantly outperforms the IRI model whose absolute error is 0.64 MHz. Meanwhile, AdaBoost-BP prediction absolute error at Taipei station from the low latitude is 0.78 MHz, which is better than 0.81 MHz from BPNN, 0.81 MHz from SVR and 1.37 MHz from the IRI model. Finally, the variety characteristics of the AdaBoost-BP prediction error along with seasonal variation, solar activity and latitude variation were also discussed in the paper.     

卡尔曼滤波和自相关分析方法短期预报电离层f0F2的比较

电离层参数f₀F₂的预报是电离层研究的一个重要方向.本文选取2011年北京、长春、青岛和苏州四个常规观测站的f₀F₂数据,分别采用卡尔曼滤波、自相关分析法和国际参考电离层模型（IRI）对f₀F₂实施短期预报（提前1h预报）,并通过与实际观测数据的对比,对三种方法预报f₀F₂的性能进行了比较.研究结果表明,在磁平静时期,采用卡尔曼滤波方法进行f₀F₂预报的均方误差为0.532MHz,相对误差8.11%,比国际电离层参考模型的均方误差和相对误差分别降低1.47MHz和14.58%;采用自相关分析方法进行f₀F₂预报的均方根误差为0.967MHz,相对误差11.46%,比国际电离层参考模型的均方误差和相对误差分别降低1.035MHz和11.23%.比较结果说明二者对f₀F₂短期预报的精度相对于国际电离层参考模型均有大幅提升.对磁暴期间三种方法的预测性能做了进一步比较,试验结果表明卡尔曼滤波短期预报性能总体上优于自相关分析法,这为f₀F₂短期预报的方法选择提供了一定指导.      

Comparison of ionospheric F2 peak parameters foF2 and hmF2 with IRI2001 at Hainan

Monthly median values of foF2, hmF2 and M(3000)F2 parameters, with quarter-hourly time interval resolution for the diurnal variation, obtained with DPS4 digisonde at Hainan (19.5°N, 109.1°E; Geomagnetic coordinates: 178.95°E, 8.1°N) are used to investigate the low-latitude ionospheric variations and comparisons with the International Reference Ionosphere (IRI) model predictions. The data used for the present study covers the period from February 2002 to April 2007, which is characterized by a wide range of solar activity, ranging from high solar activity (2002) to low solar activity (2007). The results show that (1) Generally, IRI predictions follow well the diurnal and seasonal variation patterns of the experimental values of foF2, especially in the summer of 2002. However, there are systematic deviation between experimental values and IRI predictions with either CCIR or URSI coefficients. Generally IRI model greatly underestimate the values of foF2 from about noon to sunrise of next day, especially in the afternoon, and slightly overestimate them from sunrise to about noon. It seems that there are bigger deviations between IRI Model predictions and the experimental observations for the moderate solar activity. (2) Generally the IRI-predicted hmF2 values using CCIR M(3000)F2 option shows a poor agreement with the experimental results, but there is a relatively good agreement in summer at low solar activity. The deviation between the IRI-predicted hmF2 using CCIR M(3000)F2 and observed hmF2 is bigger from noon to sunset and around sunrise especially at high solar activity. The occurrence time of hmF2 peak (about 1200 LT) of the IRI model predictions is earlier than that of observations (around 1500 LT). The agreement between the IRI hmF2 obtained with the measured M(3000)F2 and the observed hmF2 is very good except that IRI overestimates slightly hmF2 in the daytime in summer at high solar activity and underestimates it in the nighttime with lower values near sunrise at low solar activity.     

Diurnal and seasonal variation of F2-layer ionospheric parameters at equatorial ionization anomaly crest region and their comparison with IRI-2001

Diurnal and seasonal variations of critical frequency of ionospheric F2-region ‘foF2’ and the height of peak density ‘hmF2’ are studied using modern digital ionosonde observations of equatorial ionization anomaly (EIA) crest region, Bhopal (23.2°N, 77.6°E, dip 18.5°N), during solar minimum period 2007. Median values of these parameters are obtained at each hour using manually scaled data during different seasons and compared with the International Reference Ionosphere-2001 model predictions. The observations suggest that on seasonal basis, the highest values of foF2 are observed during equinox months, whereas highest values of hmF2 are obtained in summer and lowest values of both foF2 and hmF2 are observed during winter. The observed median and IRI predicted values of foF2 and hmF2 are analyzed with upper and lower bound of inter-quartile range (IQR) and it is find out that the observed median values are well inside the inter-quartile range during the period of 2007. Comparison of the recorded foF2 and hmF2 values with the IRI-2001 output reveals that IRI predicted values exhibit better agreement with hmF2 as compared to foF2. In general, the IRI model predictions show some agreement with the observations during the year 2007. Therefore it is still necessary to implement improvements in order to obtain better predictions for EIA regions.     

The variability and predictability of the IRI B0, B1 parameters over Grahamstown,South Africa

The International Reference Ionosphere (IRI) parameters B₀ and B₁ provide a representation of the thickness and shape, respectively, of the F2 layer of the bottomside ionosphere. These parameters can be derived from electron density profiles that are determined from vertical incidence ionograms. This paper aims to illustrate the variability of these parameters for a single mid latitude station and demonstrate the ability of the Neural Network (NN) modeling technique for developing a predictive model for these parameters. Grahamstown, South Africa (33.3°S, 26.5°E) was chosen as the mid latitude station used in this study and the B₀ and B₁ parameters for an 11 year period were determined from electron density profiles recorded at that station with a University of Massachusetts Lowell Center for Atmospheric Research (UMLCAR) Digisonde. A preliminary single station NN model was then developed using the Grahamstown data from 1996 to 2005 as a training database, and input parameters known to affect the behaviour of the F2 layer, such as day number, hour, solar and magnetic indices. An analysis of the diurnal, seasonal and solar variations of these parameters was undertaken for the years 2000, 2005 and 2006 using hourly monthly median values. Comparisons between the values derived from measured data and those predicted using the two available IRI-2001 methods (IRI tables and Gulyaeva, T. Progress in ionospheric informatics based on electron density profile analysis of ionograms. Adv. Space Res. 7(6), 39–48, 1987.) and the newly developed NN model are also shown in this paper. The preliminary NN model showed that it is feasible to use the NN technique to develop a prediction tool for the IRI thickness and shape parameters and first results from this model reveal that for the mid latitude location used in this study the NN model provides a more accurate prediction than the current IRI model options.