IRI Model Research Articles

A comparison of neural network-based predictions of foF2 with the IRI-2012 model at conjugate points in Southeast Asia

This paper presents the development of Neural Network (NN) model for the prediction of the F2 layer critical frequency (foF2) at three ionosonde stations near the magnetic equator of Southeast Asia. Two of these stations including Chiang Mai (18.76°N, 98.93°E, dip angle 12.7°N) and Kototabang (0.2°S, 100.3°E, dip angle 10.1°S) are at the conjugate points while Chumphon (10.72°N, 99.37°E, dip angle 3.0°N) station is near the equator. To produce the model, the feed forward network with backpropagation algorithm is applied. The NN is trained with the daily hourly values of foF2 during 2004–2012, except 2009, and the selected input parameters, which affect the foF2 variability, include day number (DN), hour number (HR), solar zenith angle (C), geographic latitude (θ), magnetic inclination (I), magnetic declination (D) and angle of meridian (M) relative to the sub-solar point, the 7-day mean of F10.7 (F10.7_7), the 81-day mean of SSN (SSN_81) and the 2-day mean of Ap (Ap_2). The foF2 data of 2009 and 2013 are then used for testing the NN model during the foF2 interpolation and extrapolation, respectively. To examine the performance of the proposed NN, the root mean square error (RMSE) of the observed foF2, the proposed NN model and the IRI-2012 (CCIR and URSI options) model are compared. In general, the results show the same trends in foF2 variation between the models (NN and IRI-2012) and the observations in that they are higher during the day and lower at night. Besides, the results demonstrate that the proposed NN model can predict the foF2 values more closely during daytime than during nighttime as supported by the lower RMSE values during daytime (0.5≤RMSE≤1.0 for Chumphon and Kototabang, 0.7≤RMSE≤1.2 at Chiang Mai) and with the highest levels during nighttime (0.8≤RMSE≤1.5 for Chumphon and Kototabang, 1.2≤RMSE≤2.0 at Chiang Mai). Furthermore, the NN model predicts the foF2 values more accurately than the IRI model at the three sites on average, as clearly seen on the yearly RMSE averages. The RMSE values of NN model are lower than those of both CCIR and URSI options, and in terms of the yearly percentage improvements, the NN model gives improvement of around 10–15% in 2009 and 10% in 2013 for Chiang Mai, 20–25% in 2009 and 5–10% in 2013 for Chumphon, and around 18–25% in 2009 and 20–30% in 2013 at Kototabang. Although the NN model predicts the foF2 values closely to the observed data and produces more accurate prediction than the IRI models, in some cases, the IRI model performs better than the NN model. Hence, there is still room for further improvement of the proposed NN model.

Study of ionospheric topside variations based on NeQuick topside formulation and comparisons with the IRI-2012 model at equatorial latitude station, Chumphon, Thailand

It is well-known that the equatorial anomaly at equatorial and low latitudes is caused by the fountain effect, therefore, the modeling of topside electron density profiles (EDPs) and the knowledge of electron density distribution in the region are particular challenging. Chumphon station, Thailand, is located within this region. However, at this station, since only an FMCW ionosonde system is installed, the topside EDP cannot be automatically obtained. Therefore, in this work, the topside EDPs are derived using the NeQuick topside formulation of the NeQuick 2 model (namely, NeQuick-derived topside EDPs) and then compared with those of three options of the IRI-2012 model including NeQuick, IRI01-corr, and IRI2001 options. The results show that, at Chumphon station, the NeQuick-derived topside EDPs are generally closer to the topside EDPs of IRI01-corr option in winter season and the topside EDPs of NeQuick option in equinox and summer seasons. When analyzing the topside TEC values obtained from each profile and the IGS TEC, it is found that the topside TEC values integrated from NeQuick-derived topside EDPs and predicted by both IRI01-corr and IRI-2001 options of the IRI-2012 model are sometimes higher than the IGS TEC values observed at Chumphon. In addition, we study the diurnal variations of the scale height computed from NeQuick topside formulation (Hsc), hmF2 and foF2 parameters. The correlation of Hsc with the parameters hmF2 and the bottomside thickness parameter of NeQuick model (B2bot). The computed Hsc values during daytime are lower than those during nighttime and they show non-linear correlations with hmF2 and B2bot. The main cause of these discrepancies are possibly due to the B2bot expressions used to compute the Hsc.

Determination of the ionospheric foF2 using a stand-alone GPS receiver

The critical frequency of ionospheric F2 layer (foF2) is a measure of the highest frequency of radio signal that may be reflected back by the F2 layer, and it is associated with ionospheric peak electron density in the F2 layer. Accurate long-term foF2 variations are usually derived from ionosonde observations. In this paper, we propose a new method to observe foF2 using a stand-alone global positioning system (GPS) receiver. The proposed method relies on the mathematical equation that relates foF2 to GPS observations. The equation is then implemented in the Kalman filter algorithm to estimate foF2 at every epoch of the observation (30-s rate). Unlike existing methods, the proposed method does not require any additional information from ionosonde observations and does not require any network of GPS receivers. It only requires as inputs the ionospheric scale height and the modeled plasmaspheric electron content, which practically can be derived from any existing ionospheric/plasmaspheric model. We applied the proposed method to estimate long-term variations of foF2 at three GPS stations located at the northern hemisphere (NICO, Cyprus), the southern hemisphere (STR1, Australia) and the south pole (SYOG, Antarctic). To assess the performance of the proposed method, we then compared the results against those derived by ionosonde observations and the International Reference Ionosphere (IRI) 2012 model. We found that, during the period of high solar activity (2011–2012), the values of absolute mean bias between foF2 derived by the proposed method and ionosonde observations are in the range of 0.2–0.5 MHz, while those during the period of low solar activity (2009–2010) are in the range of 0.05–0.15 MHz. Furthermore, the root-mean-square-error (RMSE) values during high and low solar activities are in the range of 0.8–0.9 MHz and of 0.6–0.7 MHz, respectively. We also noticed that the values of absolute mean bias and RMSE between foF2 derived by the proposed method and the IRI-2012 model are slightly larger than those between the proposed method and ionosonde observations. These results demonstrate that the proposed method can estimate foF2 with a comparable accuracy. Since the proposed method can estimate foF2 at every epoch of the observation, it therefore has promising applications for investigating various scales (from small to large) of foF2 irregularities.

Analysis of ionospheric TEC from GNSS observables over the Turkish region and predictability of IRI and SPIM models

The present study investigates the ionospheric Total Electron Content (TEC) variations in the lower mid-latitude Turkish region from the Turkish Permanent GNSS Network (TPGN) and International GNSS Services (IGS) observations during the period from January 2015 to December 2015. The corresponding TEC predicted by the International Reference Ionosphere (IRI 2012) and Standard Plasmasphere-Ionosphere Model (SPIM), and interpolated from Global Ionosphere Maps (GIMs) are evaluated to realize their reliability over the region. We studied the diurnal and monthly behavior of TEC and the relative TEC deviations along with the upper and lower quartiles to represent its spatio-temporal variability. The diurnal variation of GNSS-derived TEC indicates its maximum peak value around 10.00 UT which decreases gradually to attain minimum value after midnight. The monthly maximum value of TEC is observed in March followed by May and August, and the lowest value is seen during September. Studies show that the monthly relative deviation of TEC variability lies in the range of −1 to 4 units for all stations with the maximum difference between positive and negative variability remaining around 5. The studies also cover seasonal variation, grand-mean of ionospheric TEC and TEC intensity from the TPGN. The seasonal ionospheric VTEC pattern over all stations depicts slight increment in VTEC distribution during March equinox compared to September equinox. The December solstice perceived relatively higher VTEC than June solstice. The overall of VTEC values enhanced at all stations towards end of the year 2015 compare to mid of year due the high solar activity. The maximum grand-mean of VTEC is registered in March equinox while the lowest value is seen in September irrespective of all stations. The measured grand-mean intensity variations of VTEC values are in ascending phase during March, May, August and November months, but in descending phase during February, April, June and September months. The latitudinal study shows daytime TEC slowly decreasing with latitudes with a latitudinal gradient range of 0.1–0.2 TECU/degree. Additionally, the TEC analysis during the strong geomagnetic storm period (07–11 September 2015; SYM-H −120 nT) infers relatively better predictability of the SPIM model compared to the IRI 2012 model. The outputs of this study would complement towards a complete understanding of the lower mid-latitude ionospheric dynamics and its effects on radio propagations, particularly over the Turkish region.

Variations of B0 and B1 with the solar quiet Sq-current system and comparison with IRI-2012 model at Ilorin

The ionospheric thickness (B0) and shape (B1) are bottomside profile parameters introduced by the International Reference Ionosphere (IRI) model. We have validated these parameters with the latest version of the IRI-2012 model and compared them with the solar quiet of geomagnetic H-component (SqH). The B0, B1 and SqH are calculated from the measurements obtained from digisonde DPS-4 sounder and the Magnetic Data Acquisition System (MAGDAS) magnetometer, respectively at Ilorin (geo latitude 8.50°N, geo longitude 4.68°E, and Magnetic dip 4.1°S) an equatorial station in the African sector. The study was for the year 2010, a year of low solar activity (with 27-day averaged solar index, F10.7=80sfu). The results show that B0 for the entire months was higher during the daytime than during the night time. On the other hand, the magnitude of B1during the daytime period is lower than nighttime values and exhibit oscillatory pattern. By comparing the experimental observations of the profile parameters with the IRI-2012 model prediction, we found that B0 was fairly represented by the IRI model options during the nighttime period while discrepancies exist between the model estimates and the experimental values during the morning till midday. A close agreement exists between the observed B1 values and IRI model options. We observed a positive and significant correlation coefficient between B0 and SqH indicating a plausible relationship between these parameters while a weak and negative correlation coefficient between B1 and SqH was observed. We concluded that the difference in the relationship of SqH and the profile parameters B0 and B1 observed can be attributed to their sensitivity to the electric field which is responsible for the E×B drift which in turn modulate the height of the F2.

Prediction and Measurement of High Frequency Radio Frequencies in Peninsular Malaysia and Comparisons with the International Reference Ionosphere Model

Prediction of High Frequency (HF) radio frequency is important in the planning and operation of HF radio system because of the highly variable ionospheric region. Therefore, there is a requirement to find reliable and accurate HF operating frequencies in the Malaysian environment. The main aim of this study was to observe and analyze the HF prediction and measurement in Peninsular Malaysia which was then compared to the IRI Model prediction. This study was carried out in the equatorial region and in the middle of solar cycle 24 which was in July and August of 2014. The HF prediction process involved two maximum usable frequency (MUF) models, and the predicted result, i.e., operating working frequency (OWF) was based on hourly monthly median values. The results show that the IRI Model overestimated MUF prediction at about 36% for July 2014 and 38% for August 2014. This indicates that the IRI Model is an inappropriate model to be used for prediction of HF operating frequency in the Malaysian region. Meanwhile, the OWF measurements were around the OWF prediction, and this indicates that the OWF measurements are in the range of the OWF prediction. Accordingly, the lower decile MUF, i.e., OWF is the right range for HF operating frequency.

Performance evaluation of ionospheric time delay forecasting models using GPS observations at a low-latitude station

Ionospheric delay is one of the major atmospheric effects on the performance of satellite-based radio navigation systems. It limits the accuracy and availability of Global Positioning System (GPS) measurements, related to critical societal and safety applications. The temporal and spatial gradients of ionospheric total electron content (TEC) are driven by several unknown priori geophysical conditions and solar-terrestrial phenomena. Thereby, the prediction of ionospheric delay is challenging especially over Indian sub-continent. Therefore, an appropriate short/long-term ionospheric delay forecasting model is necessary. Hence, the intent of this paper is to forecast ionospheric delays by considering day to day, monthly and seasonal ionospheric TEC variations. GPS-TEC data (January 2013–December 2013) is extracted from a multi frequency GPS receiver established at K L University, Vaddeswaram, Guntur station (geographic: 16.37°N, 80.37°E; geomagnetic: 7.44°N, 153.75°E), India. An evaluation, in terms of forecasting capabilities, of three ionospheric time delay models – an Auto Regressive Moving Average (ARMA) model, Auto Regressive Integrated Moving Average (ARIMA) model, and a Holt-Winter's model is presented. The performances of these models are evaluated through error measurement analysis during both geomagnetic quiet and disturbed days. It is found that, ARMA model is effectively forecasting the ionospheric delay with an accuracy of 82–94%, which is 10% more superior to ARIMA and Holt-Winter’s models. Moreover, the modeled VTEC derived from International Reference Ionosphere, IRI (IRI-2012) model and new global TEC model, Neustrelitz TEC Model (NTCM-GL) have compared with forecasted VTEC values of ARMA, ARIMA and Holt-Winter’s models during geomagnetic quiet days. The forecast results are indicating that ARMA model would be useful to set up an early warning system for ionospheric disturbances at low latitude regions.

Comparison of midlatitude ionospheric F region peak parameters and topside Ne profiles from IRI2012 model prediction with ground-based ionosonde and Alouette II observations

The ionospheric F2 peak parameters recorded by a ground-based ionosonde at the midlatitude station Alma-Ata [43.25N, 76.92E] were compared with those obtained using the latest version of the IRI model (http://omniweb.gsfc.nasa.gov/vitmo/iri2012_vitmo.html) for quiet geomagnetic conditions of winter (January), equinoxes (March and September), and summer (July) months of 2008–2010.It was found that for the Alma-Ata (Kazakhstan) location, the IRI2012 model describes well the morphology of seasonal and diurnal variations of the ionospheric critical frequency (foF2) and peak density height (hmF2) monthly medians. The model errors in the median foF2 prediction (percentage deviations between the median foF2 values and their model predictions) were found to vary approximately in the range from about −20% to 34% and showed a stable overestimation in the median foF2 values for daytime in January and July and underestimation for day- and nighttime hours in the equinoctial months. The comparison between the ionosonde hmF2 and IRI results clearly showed that the IRI overestimates the nighttime hmF2 values for March and September months, and the difference is up to 30km. The daytime Alma-Ata hmF2 data were found to be close to the IRI predictions (deviations are approximately ±10–15km) in winter and equinoctial months, except in July when the observed hmF2 values were much more (from approximately 50–200km).The comparison between the Alouette foF2 data and IRI predictions showed mixed results. In particular, the Alouette foF2 data showed a tendency to be overestimated for daytime in winter months similar to the ionosonde data; however, the overestimated foF2 values for nighttime in the autumn equinox were in disagreement with the ionosonde observations. There were large deviations between the observed hmF2 values and their model predictions. The largest deviations were found during winter and summer (up to −90km).The comparison of the Alouette II electron density profiles with those predicted by the adapted IRI2012 model in the altitude range hmF2 of the satellite position showed a great difference in the shape of the Alouette-, NeQuick-, IRI02-coorr, and IRI2001-derived Ne profiles, with overestimated Ne values at some altitudes and underestimated Ne values at others.The results obtained in the study showed that the observation–model differences were significant especially for the real observed (not median) data. For practical application, it is clearly important for the IRI2012 model to be adapted to the observed F2-layer peak parameters. However, the model does not offer a simple solution to predict the shape of the vertical electron density profile in the topside ionosphere, because of the problem with the topside shape parameters.

NeQuick2 and IRI2012 models applied to mid and high latitudes, and the Antarctic ionosphere

AbstractWithin the framework of the AUSPICIO (AUtomatic Scaling of Polar Ionograms and Co-operative Ionospheric Observations) project, a limited sample of ionograms recorded mostly in 2001 and 2009, and to a lesser extent in 2006–07 and 2012–15, at the ionospheric observatories of Hobart and Macquarie Island (mid-latitude), Comandante Ferraz and Livingstone Island (high latitude), and Casey, Mawson, Davis and Scott Base (inside the Antarctic Polar Circle (APC)) were considered to study the capability of the NeQuick2 and IRI2012 models for predicting the behaviour of the ionosphere at mid- and high latitudes and over the Antarctic area. The applicability of NeQuick2 and IRI2012 was evaluated as i) climatological models taking as input the F10.7 solar activity index and ii) assimilative models ingesting the foF2 and hmF2 measurements obtained from the electron density profiles provided by the Adaptive Ionospheric Profiler (AIP). The statistical analysis results reveal that the best description of the ionosphere’s electron density is achieved when the AIP measurements are ingested into the NeQuick2 and IRI2012 models. Moreover, NeQuick2 performance is far better than IRI2012 performance outside the APC. Conversely, the IRI2012 model performs better than the NeQuick2 model inside the APC.

On Connectivity of Wireless Sensor Networks with Directional Antennas.

In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.

Global ionospheric electron density estimation based on multisource TEC data assimilation

We developed a parameterized ionospheric electron density model based on the IRI-2012 model by spherical harmonic expansions in the horizontal and empirical orthogonal functions in the vertical. Then, after assimilating the monthly multisource total electron content (TEC) data from ground-based GPS, LEO radio occultation (RO), and the oceanic altimeter during magnetically quiet time into the model, we reanalyzed the monthly global ionospheric electron density TEC and other key parameters such as foF2 and NmF2. Both the reanalyzed and IRI-2012 model results were compared to the TEC measurements, the monthly median foF2 in a middle-latitude ionosonde station, and the global TEC map from CODE. The comparisons showed that both the reanalyzed and IRI results are consistent with those observations and the reanalyzed results perform better than the IRI model. Furthermore, the reanalyzed results are also consistent with the retrieved maps of HmF2, NmF2, and TEC from COSMIC RO observations. In summary, our method can reanalyze the global TEC and electron density using multisource TEC data assimilated into our model and improve the performance of IRI model.

Plasma and Fields Evaluation at the Chinese Seismo-Electromagnetic Satellite for Electric Field Detector Measurements

Model predictions are presented to evaluate the electrodynamic parameters as expected at the orbit of the China Seismic-Electromagnetic Satellite (CSES). The main objective of this paper is that of improving the accuracy of the electric field detectors (EFDs), which are installed on CSES and will measure the field vector in a wideband from dc up to 3.5 MHz. The electric field components are derived from the probe floating potential readings, thus an accurate characterization of the space environment is needed to model the currents collected from the ionosphere and establish the EFD probe response. The plasma environment and the magnetic field along the orbit are determined using the standard IRI and IGRF models. Simulations are used to determine the bias currents, which have to be applied to the probes to minimize the contact impedance between the EFDs and the ionospheric plasma. Correction voltages required to remove the $\vec {v}\times \vec {B}$ electric field from the EFD measurements are also estimated.

Adapting a climatology model to improve estimation of ionosphere parameters and subsequent validation with radio occultation and ionosonde data

AbstractThis paper reports on the adaptation and modification of a climatological model, the International Reference Ionosphere (IRI 2012 model) with the use of total electron content (TEC) data derived from the Global Navigation Satellite System (GNSS), and most importantly its subsequent validation with both radio occultation from Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) and ionosonde data. By adjusting the solar activity indices used within the standard IRI 2012 model with the aim of minimizing error differences between IRI TEC and GNSS TEC, the adjusted indices are used as drivers of the IRI 2012 model on a regional scale and results for electron density (Ne) profiles, maximum height of the F2 layer (hmF2), TEC, and critical frequency of the F2 layer (foF2) generated. Validation was done by direct comparison with ionosonde and COSMIC‐derived data parameters. By averaging results over low, equatorial, and midlatitude regions, the modified IRI 2012 gave an improvement of about 18% in estimating TEC during the storm period of 9 March 2012. An important result observed during our candidate period of study is that COSMIC data provides maximum electron density of the F2 layer (NmF2) and hmF2 closer to ionosonde data even during the disturbed period and is hence a suitable data set that can be incorporated into the climatological IRI model to improve its performance. The Ne profiles from the modified IRI 2012 model accurately approximates ionosonde Ne profiles especially below 300 km altitude but underestimates the ionosonde NmF2 and hence foF2 in midlatitude regions. In most cases both standard and modified IRI 2012 models match COSMIC data for topside electron density representation, making the COSMIC data set a valuable resource for the improvement of ionospheric climatological models.

Comparative study of COSMIC/FORMOSAT-3, Irkutsk incoherent scatter radar, Irkutsk Digisonde and IRI model electron density vertical profiles

The long-duration continuous Irkutsk incoherent scatter radar observations allowed us to collect 337 electron density vertical profiles obtained almost simultaneously with the radar and the COSMIC in the radar vicinity. The COSMIC electron density profiles were compared with those from the radar, Digisonde, and the IRI model. The comparison included 4 seasons and 2 solar activity levels (low and moderate). The number of simultaneous cases was ∼10 times more than in the previous incoherent scatter radar comparisons. In the case of the bottomside characteristics (peak density and bottomside electron content), the deviations between the COSMIC and the ground-based facilities data may be interpreted as the COSMIC measurement errors without significant systematic biases and with root-mean-square values that are ∼1.4–1.6 times smaller those that from the IRI model prediction. In the case of the topside characteristics (topside electron content and ionospheric electron content), the IRI model overestimates the COSMIC data by 0.6–0.8tecu on average, and the COSMIC overestimates the Irkutsk incoherent scatter radar data by 1.0–1.1tecu on average. The percentage differences between the radar and COSMIC in the topside electron content can reach 80%. In terms of the root-mean-square deviation, the COSMIC and the radar agree better than each of them agrees with the IRI model.

Solar cycle variation of ionospheric parameters over the low latitude station Hainan, China, during 2002–2012 and its comparison with IRI-2012 model

The low latitude ionospheric data observed by digisonde at Hainan station (19.5°N, 109.1°E) in a whole solar activity cycle period from 2002 to 2012 within Ap<20 have been analyzed to explore the diurnal, seasonal, annual variations and solar activity dependences of the ionospheric peak parameters (foF2, hmF2, and Chapman scale height Hm), as well as some quantitative comparison with IRI-2012 modeling predictions. The results show that the winter anomaly in the daytime foF2 appears at different levels of solar activity. The semiannual anomaly in the daytime and nighttime foF2 with two maxima in equinox seasons is present. The foF2 have a close correlation with a solar activity factor F107P=(F107+F107A)/2 and the correlation coefficients (r) in their diurnal variation are around 0.7. The slope of foF2 varying with F107P in daytime is usually smaller than in nighttime. The afternoon and evening hmF2 show good correlation with F107P (their r values exceed 0.6), but hmF2 at other time are low or poor related to F107P. The prominent character of hmF2 in equinox and summer seasons is its strong increase at sunset in high solar activity period, which may be due to pre-reversal enhancement (PRE) of local electric field. We also note that hmF2 values around midnight slightly decrease with increasing F107P index in equinox seasons. The diurnal variation of Hm usually has two peaks around noontime and pre-sunrise. The daytime Hm has an annual variation with maximum in summer and minimum in winter. Moreover, the dependence of the daytime Hm on solar activity is not strong due to meridional wind and other factors. The above results over Hainan are considerably different from those reported over Millstone Hill, which is attributed to their different geomagnetic locations. The quantitative results compared between IRI-2012 model predictions and observations show that the predicted foF2 values are basically underestimated and the magnitude of their deviations obviously increases with increasing solar activity. The predicted hmF2 obtained with measured M(3000)F2 inputs in low and moderate solar activity agree well with the observed ones. However, their deviations in high solar activity are significantly magnified.

Comparison of GPS-derived TEC with IRI-2012 and IRI-2007 TEC predictions at Surat, a location around the EIA crest in the Indian sector, during the ascending phase of solar cycle 24

This paper presents a comparison of GPS-derived TEC with IRI-2012 and IRI-2007 TEC Predictions at Surat (21.16°N Geographic latitude, 72.78°E Geographic longitude, 12.90°N Geomagnetic latitude) a location around the Equatorial Ionisation Anomaly (EIA) crest in the Indian sector, during the Ascending Phase of Solar Cycle 24, for a period of three years (January 2010–December 2012). In this comparison, plasmaspheric electron content (PEC) contribution to the GPS-TEC has been removed. It is observed that percentage PEC contribution to the GPS-TEC varies from about ∼15% (at the noon local time) to about ∼30% (at the morning local time). From the monthly comparison of GPS-TEC with IRI-TEC, it is observed that, TEC predicted by both the models overestimates in June-2012 and underestimates TEC in November-2011, December-2011 and March-2011. For all other months IRI estimates the TEC well. From the seasonal comparison, it is observed that the peak time appears ∼1-h later than the actual peak time in Winter 2010, Summer 2011, and Equinox 2010 and 2012 (the result suggest that it may be due to discrepancies/disagreement of both the versions of the IRI model in estimating the peak density as well as the thickness and shape parameters of the electron density profiles). For the Summer season, the IRI-TEC estimates the TEC well for all the years. Further, the seasonal variation of the GPS-TEC for all the three years matches well with IRI-2012 model compared to IRI-2007 model. Also, the mean annual TEC is predicted well by both the versions of the IRI model.

Variability of ionospheric parameters during solar minimum and maximum activity and assessment of IRI model

The ionospheric parameters (electron and ion plasma temperatures (Te and Ti) and total ion density, Ni) as obtained by the Indian SROSS-C2 satellite (altitude ∼500km) have been investigated during low (year 1995, F10.7∼77 sfu) and high (year 2000, F10.7∼177 sfu) solar activity periods. The region under study spans over 5°S-30°N geomag. latitude and 60–100°E geog. longitude over the Indian sector. The observations are compared with the modelled values using IRI-2007 and IRI-2012 versions to assess model predictability. We found that minimum plasma temperatures (Te and Ti) in nighttime gets twice hotter whereas maximum temperatures in early morning gets reduced by half (cooler) when the solar flux gets doubled indicating a direct relation of Te and Ti with solar flux, F10.7 in nighttime but inverse in the morning hours. The ion density (Ni) exhibits solar activity dependence throughout the day and increases by one order when solar activity gets doubled. The modelled Te and Ti are found in agreement to the observed values for high solar activity over both the regions. Whereas the discrepancy exists during low solar activity period over both the regions with over-/under-estimated values in nighttime/morning and noontime respectively. The latest IRI-2012 model improves the nighttime Te and Ti whereas the modelled Ni is found in complete agreement to the observations.

A new expression for computing the bottomside thickness parameter and comparisons with the NeQuick and IRI-2012 models during declining phase of solar cycle 23 at equatorial latitude station, Chumphon, Thailand

This paper proposes a new expression for computing the bottomside thickness parameter at equatorial latitude station, Chumphon (10.72°N, 99.37°E), Thailand. Its diurnal variations from 2004 to 2006 at this location are then studied. The proposed expression is derived based on two experimental data sources: FMCW ionosonde and dual-frequency GPS system, and some expressions of the NeQuick 2 model. Hence, after both the bottomside thickness parameter computed by the proposed equation, B2bot_Pro, and the bottomside shape parameter (namely, B1_Pro in this work) are computed, the bottomside electron density and the height where the bottomside electron density drops down to be 24% of the NmF2 (namely, h0.24) can be computed and shown in this work using the analytical functions of the IRI model. Moreover, the diurnal variations of the B2bot_Pro are compared with those computed from the NeQuick model, B2bot_NeQ, and the predicted B0 of the IRI-2012 model with ABT-2009 and Bil-2000 options (namely, “B0_ABT” and “B0_Bil”, respectively). The averaged, minimum, and maximum values of percentage deviations among these bottomside thickness parameters are also computed and shown in this work. Our results show that the diurnal variations of B2bot_Pro at Chumphon station have the following patterns: they start to increase during nighttime to the first peaks during pre-sunrise hours, and then decrease abruptly to their minimum values during sunrise hours. Afterward, they increase again to reach the second peaks around local noontime and fall gradually to their starting times during 20–04 LT. The diurnal variations of B2bot_Pro follow generally the same trends as those of the B2bot_NeQ and the B0_ABT, except pre-sunrise hours. The pre-sunrise peaks and sunrise collapses in both the B2bot_NeQ and the B0_ABT can be found occasionally. On the other hand, the diurnal variations in B2bot_Pro differ from those in B0_Bil due to the flattened variation in B0_Bil and the pre-sunrise peaks as well as sunrise collapses in B0_Bil disappear. The pre-sunrise peaks of the B2bot_Pro at the Chumphon station are higher than those of the B2bot_NeQ, the B0_ABT, and the observed B0 at other regions. Furthermore, the percentage deviations between the B2bot_Pro and the B0_ABT (PD_B2B0ABT) are mostly lower than 30% for all seasons of the studied years, opposite to the other percentage deviations studied in this work. The proposed B2bot_Pro parameters in this work follow a similar trend to the B2bot_NeQ and the B0_ABT, but it is not conclusive that the proposed values are equivalent to them.

A comparison of TEC predicted by IRI-2012 with that measured at three different stations in low latitude Indian region for the years (2010–2012)

The present study reports the comparison of GPS measured Total Electron Content (TEC) with that predicted by the latest IRI-2012 model at three different stations located within the Equatorial Ionization Anomaly region (EIA) in the Indian sector. The data used for the study are retrieved from three different stations, namely, Surat (geographic latitude 21.16°N, geographic longitude 72.78°E; geomagnetic latitude 12.90°N), Hyderabad (geographic latitude 17.25°N, geographic longitude 78.30°E; geomagnetic latitude 8.65°N) and Bangalore (geographic latitude 13.02°N, geographic longitude 77.57°E; geomagnetic latitude 4.58°N). The period of comparison is three years for rising solar activity from 2010 to 2012. Here it is to note that both Hyderabad and Bangalore are IGS station with the station code (HYDE and IISC respectively). The results for the comparison of seasonal variation shows a good agreement between the measured and modeled TEC for all seasons with deviation of (±15 TECU) for all three years at Surat and Bangalore and with a deviation of (±25 TECU) at Hyderabad. Both topside options NeQuick and IRI01-Corr derived nearly equal TEC at all three stations. It is observed that the GPS TEC data shows the EIA crest at (23.5°N) where as the IRI TEC predicts the EIA crest at (19.7°N) on an average for all the years 2010–2012.

The effect of QBO on foE

In the present work, the relationship with QBO of difference (ΔfoE=foEmea−foEIRI) between critical frequency (foE) values of ionospheric E-region, measured at Darwin and Casos Island stations and calculated by IRI-2012 ionospheric model, is statistically investigated. A multiple regression model is used as statistical tool. The “Dummy” variables (“DummyWest” and “DummyEast” represent westerly QBO values and easterly QBO values, respectively) are added to model in order to see the effect of westerly and easterly QBO. In the result of calculations, it is observed that the changes in ΔfoE about 50–52% can be explained by QBO at both stations. The relationship between QBO and ΔfoE is negative at both stations. The change of 1ms−1 in whole set of QBO leads to a decrease of 0.008MHz at Casos Island station and 0.017MHz at Darwin station in ΔfoE. Directions of QBO have an effect on ΔfoE at the Darwin station, but they’ve not any effect on ΔfoE at Casos Island station. It is thought that the difference values in the foE are due to not to be included in the IRI-model of all parameters affecting the critical frequency value. Thus, QBO which is not included to IRI-model can have an effect on foE and more accurate results can be obtained by IRI model if the QBO is included in this model calculations.