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.     

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.     

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.     

On the performance of IRI-2016 to predict the North-South asymmetry of the equatorial ionization anomaly around 73°E longitude

The ionospheric total electron content (TEC) in both northern and southern Equatorial anomaly regions are examined by using the Global Positioning System (GPS) based TEC measurements around 73°E Longitude in the Asian sector. The TEC contour charts obtained at SURAT (21.16°N; 72.78°E; 12.9°N Geomagnetic Lat.) and DGAR (7.27°S; 72.37°E; 15.3°S Geomagnetic Lat.) over 73°E longitude during a very low solar activity phase (2009) and a moderate solar activity (2012) phase are used in this study. The results show the existence of hemispheric asymmetry and the effects of solar activity on the EIA crest in occurrence time, location and strength. The results are also compared with the TEC derived by IRI-2016 Model and it is found that the North-South asymmetry at the EIA region is clearly depicted by IRI-2016 with some discrepancies (up to 20% in the northern hemisphere at SURAT and up to 40% in the southern hemisphere at DGAR station for June Solstice and up to 10% both for SURAT and DGAR for December Solstice). This discrepancy in the IRI-2016 model is found larger during the year 2012 than that during the solar minimum year 2009 at both the hemispheres. Further, an asymmetry index, (A_i) is determined to illustrate the North-South asymmetry observed in TEC at EIA crest. The seasonal, annual and solar flux dependence of this index are investigated during both solstices and compared with the TEC derived by IRI.     

The longitudinal and hemispherical variation of the IRI’s foF2 estimates at ±40° dip angle around 95°E and 130°E sector under fluctuating solar flux conditions

The deviation of the IRI estimates of the monthly mean foF2 in the low mid latitude of 95°E–130°E longitude sector is investigated using simultaneous ground measurements at four stations during 2010–2014. The stations form two conjugate pairs of the same geo-magnetic latitude at two fixed longitudes enabling direct longitudinal and hemispheric comparison. The temporal, spatial, seasonal and solar activity variations of the deviations are discussed with reference to the longitudinal density variation in the transition region between low and midlatitudes. Cases of underestimation/overestimation as well as good estimate are noted. Underestimation (overestimation) in the daytime and overestimation (underestimation) in the nighttime of 95°E (130°E) are common. The longitudinal difference in the measurements suggests negative (positive) foF2 gradient from west to east in daytime (nighttime). In contrast, the IRI predicts flatter or increasing longitudinal profiles from 95°E to 130°E. The local time and longitudinal variation of the IRI deviations can be attributed to the combined role of the longitudinal EIA structure as well as midlatitude zonal wind-magnetic declination effect. The station/season independent deviations relate the role of solar activity representation in the IRI. These deviations may be attributed to the weak IRI response to rapid solar flux fluctuations.     

Proposal of new models of the bottom-side B0 and B1 parameters for IRI

The time series of hourly electron density profiles N(h) obtained from 27 ionosonde stations distributed world-wide have been used to obtain N(h) average profiles on a monthly basis and to extract the expected bottom-side parameters that define the IRI profile under quiet conditions. The time series embrace the time interval from 1998 to 2006, which practically contains the entire solar cycle 23. The Spherical Harmonic Analysis (SHA) has been used as an analytical technique for modeling globally the B0 and B1 parameters as general functions on a spherical surface. Due to the irregular longitudinal distribution of the stations over the globe, it has been assumed that the ionosphere remains approximately constant in form for a given day under quiet conditions for a particular coordinate system. Since the Earth rotates under a Sun-fixed system, the time differences have been considered to be equivalent to longitude differences. The time dependence has been represented by a two-degree Fourier expansion to model the annual and semiannual variations and the year-by-year analyses of the B0 and B1 have furnished nine sets of spherical harmonic coefficients for each parameter. The spatial–temporal yearly coefficients have been further expressed as linear functions of Rz12 to model the solar cycle dependence. The resultant analytical model provides a tool to predict B0 and B1 at any location distributed among the used range of latitudes (70°N–50°S) and at any time that improves the fit to the observed data with respect to IRI prediction.     

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.     

The variability and IRI2007-predictability of hmF2 over South Africa

This paper presents an investigation into the variability and predictability of the maximum height of the ionospheric F2 layer, hmF2 over the South African region. Data from three South African stations, namely Madimbo (22.4°S, 26.5°E, dip angle: −61.47°), Grahamstown (33.3°S, 26.5°E, dip angle: −64.08°) and Louisvale (28.5°S, 21.2°E, dip angle: −65.44°) were used in this study. The results indicate that hmF2 shows a larger variability around midnight than during the daytime for all seasons. Monthly median hmF2 values were used in all cases and were compared with predictions from the IRI-2007 model, using the URSI (Union Radio-Scientifique Internationale) coefficient option. The analysis covers the diurnal and seasonal hourly hmF2 values for the selected months and time sectors e.g. January, July, April and October for 2003 and 2005. The time ranges between (03h00–23h00 UT; LT = UT + 2h) representing the local sunrise, midday, sunset and midnight hours. The time covers sunrise, midday, sunrise, and midnight hours (03–06h00 UT, 07–11h00 UT, sunrise 16–18h00 UT and 22–23h00 UT; LT = UT + 2h). The dependence of the results on solar activity levels was also investigated. The IRI-2007 predictions follow fairly well the diurnal and seasonal variation patterns of the observed hmF2 values at all the stations. However, the IRI-2007 model overestimates and underestimates the hmF2 value during different months for all the solar activity periods.     

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.     

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.