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 observed TEC values with IRI-2007 TEC and IRI-2007 TEC with optional foF2 measurements predictions at an equatorial region,Chumphon, Thailand

In this research, as part of working towards improving the IRI over equatorial region, the total electron content (TEC) derived from GPS measurements and IRI-2007 TEC predictions at Chumphon station (10.72°N, 99.37°E), Thailand, during 2004–2006 is analyzed. The seasonal variation of the IRI-2007 TEC predictions is compared with the TEC from the IRI-2007 TEC model with the option of the actual F2 plasma frequency (foF2) measurements as well as the TEC from the GPS and International GNSS service (IGS). The Chumphon station is located at the equatorial region and the low latitude of 3.22°N. For a declining phase of the solar cycle (2004–2006), the study shows that the IRI-2007 TEC underestimates the IRI-2007 TEC with the foF2 observation at the nighttime by about 5 TECU. The maximum differences are about 15 TECU during daytime and 5 TECU during nighttime. The overestimation is more evident at daytime than at nighttime. When compared in terms of the root-mean square error (RMSE), we find that the highest RMSE between GPS TEC and IRI 2007 TEC is 14.840 TECU at 1230 LT in 2004 and the lowest average between them is 1.318 TECU at 0630 LT in 2006. The noon bite-out phenomena are clearly seen in the IRI-2007 TEC with and without optional foF2 measurements, but not on the GPS TEC and IGS TEC. The IRI TEC with optional foF2 measurements gives the lowest RMSE values between IRI TEC predicted and TEC measurement. However, the TEC measurements (GPS TEC and IGS TEC) are more correct to use at Chumphon station.     

Study the behavior of the ionospheric frequencies at Karachi during three consecutive solar minima of cycle 21, 22 & 23 and their comparison with IRI-2016

The behavior of critical frequencies of ionospheric E and F2 layers (foE & foF2) along with minimum ionospheric frequency (fmin) is studied for solar minima of cycle 21 (1986), 22 (1996) and 23 (2008) over Karachi (24.95$°$N, 67.13$°$E), Pakistan. The station is located at the crest of equatorial ionization anomaly region. Beside seasonal differences, pronounced change in the values of frequencies is noted from one solar minimum to another solar minimum. A strong and direct correlation of foF2 with Smoothed Sunspot Number (SSN) and F10.7?cm solar flux is observed. In the minimum of cycle 23, reduction in foF2 is noted due to reduction of solar EUV as compared to other minima. Also disappearance of semi-annual variations in foF2 is noted in cycle 23 minimum. Unexpectedly higher values of foE and fmin are observed in minimum of cycle 23 as compared to other minima. It is difficult to explain this unusual behavior of fmin and foE along with disappearance of semi-annual variation in foF2. It is possible that during very low solar activity, thermospheric conditions are changed which in turn altered the ionosphere. Further investigation of atmosphere-ionosphere coupling is required to understand this complex behavior. On comparison of observed values with IRI-2016, higher deviations are observed in foE before noon hours while in case of foF2, large deviations are noted during daytime. The absence of foF2 semi-annual variation in cycle 23 is not reproduced by IRI-2016. It is suggested that IRI-2016 need some modification for extremely low solar activity condition.     

Ionospheric variation at Thailand equatorial latitude station: Comparison between observations and IRI-2001 model predictions

In this paper, the F2-layer critical frequency (foF2) and peak height (hmF2) measured by the FM/CW ionosonde at Thailand equatorial latitude station, namely Chumphon (10.72°N, 99.37°E, dip 3.22) are presented. The measurement data during low solar activity from January 2004 to December 2006 are analyzed based on the diurnal, seasonal variation. The results are then compared with IRI-2001 model predictions. Our study shows that: (1) In general, both the URSI and CCIR options of the IRI model give foF2 close to the measured ones, but the CCIR option produces a smaller range of deviation than the URSI option. The agreement during daytime is generally better than during nighttime. Overestimation mostly occurs in 2004 and 2006, while underestimation is during pre-sunrise hours in June solstice in 2005. The peak foF2 around sunset is higher during March equinox and September equinox than the other seasons, with longer duration of maximum levels in March equinox than September equinox. Large coefficients of variability foF2 occur during pre-sunrise hours. Meanwhile, the best agreement between the observed foF2 and the IRI model is obtained in June solstice. (2) In general, The IRI (CCIR) model predicts the observed hmF2 well during daytime in June solstice from 2004–2006, but it overestimates during March equinox, September equinox and December solstice. For nighttime, the model overestimates hmF2 values for all seasons especially during March equinox and September equinox. However, the model underestimates hmF2 values during September equinox and for some cases during June solstice and December solstice at pre-sunrise. The agreement between the IRI model and the hmF2(M3000_OBS) is worst around noontime, post-sunset and pre-sunrise hours. All comparative studies give feedback for new improvements of CCIR and URSI IRI models.     

GPS scintillation and TEC depletion near the northern crest of equatorial anomaly over South China

This study presents a statistical analysis of GPS L-band scintillation with data observed from July 2008 to March 2012 at the northern crest of equatorial anomaly stations in Guangzhou and Shenzhen of South China. The variations of the scintillation with local time, season, solar activity and duration of scintillation patches were investigated. The relationship between the scintillation and TEC depletion was also reported. Our results revealed that GPS scintillation occurred from 19:30 LT (pre-midnight) to 03:00 LT (post-midnight). During quiet solar activity years, the scintillation was only observed in pre-midnight hours of equinox months and patches durations were mostly less than 60 min. During high solar activity years, more scintillation occurred in the pre-midnight hours of equinox and winter months; and GPS scintillation started to occur in the post-midnight hours of summer and winter. The duration of scintillation patches extended to 180 min in high solar activity years. Solar activity had a larger effect to strong scintillations (S₄ > 0.6) than to weak scintillations (0.6 ? S₄ > 0.2). Strong scintillations were accompanied by TEC depletion especially in equinox months. We also discussed the relationship between TEC depletion and plasma bubble.     

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.     

Variability of the ionospheric electron density at fixed heights and validation of IRI-2007 profile’s prediction at Ilorin

A study on the variability of the equatorial ionospheric electron density was carried out at fixed heights below the F2 peak using one month data for each of high and low solar activity periods. The data used for this study were obtained from ionograms recorded at Ilorin, Nigeria, and the study covers height range from 100 km to the peak of the F2 layer for the daytime hours and height range from 200 km to the peak of the F2 layer for the nighttime hours. The results showed that the deviation of the electron density variation from simple Chapman variation begins from an altitude of about 200 km for the two months investigated. Daytime minimum variability of between 2.7% and 9.0% was observed at the height range of about 160 and 200 km during low solar activity (January 2006) and between 3.7% and 7.8% at the height range of 210 and 260 km during high solar activity (January 2002). The nighttime maximum variability was observed at the height range of 210 and 240 km at low solar activity and at the height range of 200 and 240 km at high solar activity. A validation of IRI-2007 model electron density profile’s prediction was also carried out. The results showed that B0 option gives a better prediction around the noontime.     

Neural network prediction of the topside electron content over the Euro-African sector derived from Swarm-A measurements

This study presents the first prediction results of a neural network model for the vertical total electron content of the topside ionosphere based on Swarm-A measurements. The model was trained on 5 years of Swarm-A data over the Euro-African sector spanning the period 1 January 2014 to 31 December 2018. The Swarm-A data was combined with solar and geomagnetic indices to train the NN model. The Swarm-A data of 1 January to 30 September 2019 was used to test the performance of the neural network. The data was divided into two main categories: most quiet and most disturbed days of each month. Each category was subdivided into two sub-categories according to the Swarm-A trajectory i.e. whether it was ascending or descending in order to accommodate the change in local time when the satellite traverses the poles. Four pairs of neural network models were implemented, the first of each pair having one hidden layer, and the second of each pair having two hidden layers, for the following cases: 1) quiet day-ascending, 2) quiet day-descending, 3) disturbed day-ascending, and 4) disturbed day-descending. The topside vertical total electron content predicted by the neural network models compared well with the measurements by Swarm-A. The model that performed best was the one hidden layer model in the case of quiet days for descending trajectories, with RMSE = 1.20 TECU, R = 0.76. The worst performance occurred during the disturbed descending trajectories where the one hidden layer model had the worst RMSE = 2.12 TECU, (R = 0.54), and the two hidden layer model had the worst correlation coefficient R = 0.47 (RMSE = 1.57).In all cases, the neural network models performed better than the IRI2016 model in predicting the topside total electron content. The NN models presented here is the first such attempt at comparing NN models for the topside VTEC based on Swarm-A measurements.     

Validation of the STORM model in IRI-2001 at a high latitude station

The International Reference Ionosphere IRI-2001 model contains geomagnetic activity dependence based on an empirical storm time ionospheric correction (STORM model). An extensive validation of the STORM model for the middle latitude region has been performed. In this paper the ability of the STORM model to predict foF2 values at high latitudes is analyzed. For this, ionosonde data obtained at Base Gral. San Martin (68.1°S, 293°E) are compared with those obtained by the IRI-2001 model with or without storm correction during four geomagnetic storms that occurred in 2000 (Rz₁₂ = 117) and 2001 (Rz₁₂ = 111). The results show that predicted values with the STORM model follow the behaviour of foF2 experimental data better than without the STORM model. The relative deviation between measured and predicted foF2 reaches values of up to 24% and 43% with and without the STORM model in IRI-2001, during the main phase of the storms. In order to explain increases of electron density that occurred prior to the storm onset and also decreases of electron density observed during the first part of the recovery of the storm, possible physical mechanisms are discussed.     

Validation of B0 and B1 in the IRI 2001 model at low solar activity for Ilorin an equatorial station

A new set of data obtained at low solar activity from Ilorin, Nigeria (geog. latitude 8.5°N, geog longitude, 4.6°E, dip 4.1°S) is used to validate the IRI 2001 model at low solar activity. The results show in general a good agreement between model and observed B0 at night but an over estimation during daytime. The overestimation is greatest during the morning period (0600LT–1000LT). The model prediction for B1 is fairly good at night and during the day. A dependence of B0 on solar zenith angle χ is observed during the daytime. A formulation of the form B0 = A[cos(χ)ⁿ] is therefore proposed. Values of the constants n and A were determined for the period of low solar activity for this station.     

A new algorithm on increasing the sensitivity of microwave radiometer based on nonlinear prediction

Currently, microwave radiometer, which has been one of the most important remote sensors in the land, ocean or atmosphere remote sensing, has played a vital role in space exploration such as the lunar exploration in China. As a passive remote sensor, microwave radiometer receives the noise resembling signals that are generated by microwave radiation while mixed with the systemic noise of the receiver. Therefore, it is the significant subject that how to improve the sensitivity of microwave radiometer that people devotes to study. And on the system noise reduction lies the key. So far, except through choosing low noise element to the receiver, there is no effective alternative to remove the influence of the systemic noise on output uncertainty of microwave radiometer. However, for the purpose of providing or inspiring solution to this problem, this paper inquires into the application of nonlinear predictive method in predication the systemic noise of microwave radiometer. As the substance of the method, neural network shows its function on reducing the systemic noise effectively by estimating and predicating it. Because neural network can improve the estimated precision when estimating the systemic noise, after the noise passes through filter, certain random characters are lost while determinacy are presented to some extent. In fact, the more narrow filter band is, the smaller predictive error will be. The results are of assistance in understanding the intrinsic quality of the systemic noise and offer a new way for improving property of microwave radiometer.     

Performance of the IRI-2007 model for equatorial topside ion density in the African sector for low and extremely low solar activity

The recent availability of new data sets during the recent extreme solar minimum provides an opportunity for testing the performance of the International Reference Ionosphere in historically undersampled regions. This study presents averages and variability of topside ionospheric densities over Africa as a function of season, local time, altitude, and magnetic dip latitude as measured by the Communication/Navigation Outage Forecast System (C/NOFS) satellite. The results are compared to the three topside model options available in IRI-2007. Overall, the NeQuick model is found to have the best performance, though during the deepest part of the solar minimum all three options significantly overestimate density.     

Variability of the behavior of the bottomside (B0, B1) parameters obtained from the ground-based ionograms at China’s low latitude station

In this paper, data of (B0, B1) parameters deduced from the electron density profiles that are inverted from the ionograms recorded at Hainan (19.4°N, 109.0°E), China during a three year period from March 2002 to February 2005 are used to study the diurnal and seasonal variation of (B0, B1) parameters at low latitude. The observational results are compared with the IRI2001 model predictions. Variability study of (B0, B1) in terms of percentage ratio of the inter-quartiles to the median values and correlative analysis between (B0, B1) parameters and other ionospheric characteristics such as hmF2 and M(3000)F2 are also made. Our present study showed that: (1) for daytime hours, the IRI2001 model results with new table option (B0_Tab) is in a better agreement with the observational results (B0_Obs) than the IRI2001 model results with Gulyaeva option (B0_Gul) for summer season, whereas B0_Gul is in a better agreement with B0_Obs than B0_Tab for winter season. For nighttime, in general, B0_Gul is in a better agreement with B0_Obs than B0_Tab. For other occasions, both B0_Tab and B0_Gul showed some systematic deviations from the observational ones. Moreover, the deviations of B0_Tab and B0_Gul from B0_Obs showed opposite trends; (2) the monthly upper (lower) quartiles of (B0, B1) parameter showed a good linear relationship with the monthly median values, this makes it possible to do the regression analysis between the monthly upper (lower) quartiles and the monthly median values, which can give a measure of the variability of these parameters. In terms of the percentage ratio of the inter-quartiles to the median values, the variability of B0 showed a diurnal variation ranging between 22% and 36% with maximum value occurring at pre-sunrise hours, whereas the variability of B1 showed a diurnal variation ranging between 15% and 30% with higher value by daytime than at night; (3) B0 shows high linear correlative relationships with hmF2 and M(3000)F2 for most of the local time period of a day except for a few hours around midnight, whereas B1 showed high linear correlations with B0, hmF2 for daytime hours, but not for nighttime hours. This suggests that it maybe is possible to obtain the synthetic database of (B0, B1) parameter or to construct the model of (B0, B1) using database of hmF2 or M(3000)F2 which is much easier to obtain from experimental measurements.     

Towards a GPS-based TEC prediction model for Southern Africa with feed forward networks

In this paper, first results from a national Global Positioning System (GPS) based total electron content (TEC) prediction model over South Africa are presented. Data for 10 GPS receiver stations distributed through out the country were used to train a feed forward neural network (NN) over an interval of at most five years. In the NN training, validating and testing processes, five factors which are well known to influence TEC variability namely diurnal variation, seasonal variation, magnetic activity, solar activity and the geographic position of the GPS receivers were included in the NN model. The database consisted of 1-min data and therefore the NN model developed can be used to forecast TEC values 1 min in advance. Results from the NN national model (NM) were compared with hourly TEC values generated by the earlier developed NN single station models (SSMs) at Sutherland (32.38°S, 20.81°E) and Springbok (29.67°S, 17.88°E), to predict TEC variations over the Cape Town (33.95°S, 18.47°E) and Upington (28.41°S, 21.26°E) stations, respectively, during equinoxes and solstices. This revealed that, on average, the NM led to an improvement in TEC prediction accuracy compared to the SSMs for the considered testing periods.     

Klobuchar电离层模型误差分析及预测

电离层延迟误差是全球导航卫星系统(global navigation satellite system,GNSS)中的重要误差源之一.目前在电离层延迟改正模型中,应用最广泛的是Klobuchar参数模型,但是该模型的改正率仅能达到60％左右,无法满足日益增长的精度需求.将国际GNSS监测评估系统(internation...     

Comparison between African equatorial station ground-based inferred vertical E × B drift,Jicamarca direct measured drift,and IRI model

The Incoherent Scatter Radar measurement over Jicamarca, together with the IRI model-2007 measurements were compared with ground-based digisonde inferred E × B drift over Ilorin in the African region during year of solar minima (F10.7 = 81). Seasonally, Ilorin pre-reversal enhancement (PRE) had peak drift velocities of 7.2, 3.7 and 7.9 m/s for March equinox, September equinox and December solstice respectively, while Jicamarca drifts indicated 13.0, 10.5 and 5.2 m/s; as well as the IRI model with 14.3, 8.4 and 0.7 m/s in similar order. PRE value was insignificant during June solstice. The PRE magnitude of the IRI-model during the equinoxes is twice the value obtained at Ilorin. The daytime E × B drift peaked over Ilorin 1–2 h earlier than both the modeled and Jicamarca observations. This could be due to the difference in sunset time at the conjugate points corresponding to the altitude of the observation. During the evening time PRE, the respective correlation coefficients (R) for Vz–F10.7 relation over Jicamarca, Ilorin and the modeled observations are −0.5559, 0.4796 and −0.4979. Similarly, the Vz–Ap relation exhibit excellent anti-correlation coefficient (R = −0.8637) for the IRI-model, −0.4827 over Jicamarca and 0.3479 for Ilorin. Annual mean drift velocities over Jicamarca, Ilorin and IRI model measurements respectively are 10, 5.6 and 10 m/s for the peak PRE observation; 15, 16 and 21 m/s for the daytime pre-sunrise peak values; and −21, −9 and −16 m/s for the nighttime downward reversals. The root-mean square (RMS) deviation between IRI-model and the Ilorin drift between 2000 and 0500 h is 4.37, 2.03, 3.71 and 2.42 m/s for March equinox, June solstice, September equinox and December solstice respectively. For Jicamarca–Ilorin drift relation, RMS deviation is 5.48, 2.30, 3.47 and 1.27 m/s in the same order respectively. Annual hmF2 inferred drift over Ilorin during daytime is higher by a factor of ≈2 and 3 at Jicamarca and IRI model measurements respectively; and by a factor of ≈5 for both during the night-time period. The limitations in using hmF2 to infer drifts are discussed.     

A new method for improving the performance of an ionospheric model developed by multi-instrument measurements based on artificial neural network

There are remarkable ionospheric discrepancies between space-borne (COSMIC) measurements and ground-based (ionosonde) observations, the discrepancies could decrease the accuracies of the ionospheric model developed by multi-source data seriously. To reduce the discrepancies between two observational systems, the peak frequency (foF2) and peak height (hmF2) derived from the COSMIC and ionosonde data are used to develop the ionospheric models by an artificial neural network (ANN) method, respectively. The averaged root-mean-square errors (RMSEs) of COSPF (COSMIC peak frequency model), COSPH (COSMIC peak height model), IONOPF (Ionosonde peak frequency model) and IONOPH (Ionosonde peak height model) are 0.58 MHz, 19.59 km, 0.92 MHz and 23.40 km, respectively. The results indicate that the discrepancies between these models are dependent on universal time, geographic latitude and seasons. The peak frequencies measured by COSMIC are generally larger than ionosonde’s observations in the nighttime or middle-latitudes with the amplitude of lower than 25%, while the averaged peak height derived from COSMIC is smaller than ionosonde’s data in the polar regions. The differences between ANN-based maps and references show that the discrepancies between two ionospheric detecting techniques are proportional to the intensity of solar radiation. Besides, a new method based on the ANN technique is proposed to reduce the discrepancies for improving ionospheric models developed by multiple measurements, the results indicate that the RMSEs of ANN models optimized by the method are 14–25% lower than the models without the application of the method. Furthermore, the ionospheric model built by the multiple measurements with the application of the method is more powerful in capturing the ionospheric dynamic physics features, such as equatorial ionization, Weddell Sea, mid-latitude summer nighttime and winter anomalies. In conclusion, the new method is significant in improving the accuracy and physical characteristics of an ionospheric model based on multi-source observations.     

Ionospheric climate index as a driving parameter for the NeQuick model

Ionospheric delay is one of the significant error sources for global navigation satellite system (GNSS) positioning. GNSSs broadcast the coefficients of the ionospheric model to correct ionospheric delay for single-frequency users. A modified three-dimensional model (NeQuick G) based on the NeQuick climatological model is adopted for Galileo users. The NeQuick G model uses the effective ionization level (Az) instead of the sunspot number as the driving parameter. In this study, we introduce the ionospheric climate index (ICI) as a new driving parameter for the NeQuick model. In comparison, the ICI-driven NeQuick model has a better performance than the Az-driven NeQuick G model at both low and high latitudes. In addition, only one GNSS station at low latitudes is required to calculate the ICI, which would save maintenance costs and improve the efficiency of updating the broadcast coefficients. This model has potential application value for future upgrades of Galileo’s ionospheric broadcast model.     

Global comparison of the model results of GSM TIP with IRI for summer conditions

This paper presents the results of the numerical calculations thermosphere/ionosphere parameters which were executed with using of the Global Self-consistent Model of the Thermosphere, Ionosphere and Protonosphere (GSM TIP)and comparison of these results with empirically-based model IRI-2001. Model GSM TIP was developed in West Department of IZMIRAN and solves self-consistently the time-dependent, 3-D coupled equations of the momentum, energy and continuity for neutral particles (O₂, N₂, O), ions (O⁺, H⁺), molecular ions (M⁺) and electrons and largescale eletric field of the dynamo and magnetospheric origin in the range of height from 80 km to 15 Earth’s radii. The empirically derived IRI model describes the E and F regions of the ionosphere in terms of location, time, solar activity and season. Its output provides a global specification not only of N_e but also on the ion and electron temperatures and the ion composition. These two models represent a unique set of capabilities that reflect major differences in along with a substantial approaches of the first-principles model and global database model for the mapping ionosphere parameters. We focus on global distribution of the N_e, T_i, T_e and TEC for the one moment UT and fixed altitudes: 110 km, h_mF2, 300 km and 1000 km. The calculations were executed with using of GSM TIP and IRI models for August 1999, moderate solar activity and quiet geomagnetic conditions. Results present as the global differences between the IRI and GSM TIP models predictions. The discrepancies between model results are discussed.