foF2 Values Research Articles

Solar Transients Disturbing the Mid Latitude Ionosphere during the High Solar Activity

We investigate the effect of solar transients on the mid latitude ionosphere during the high solar activity period of solar cycle 23 i.e 2003 and 2004. A mid latitude station, Guangzhou (23.1N, 113.4E) was selected to carry out the investigation. The ionospheric behaviour at the selected station is characterized by considering the critical frequency of F2 layer (foF2) obtained by using the ground based Ionosonde observations. Then we selected two types of solar transients viz. solar flares and Coronal Mass Ejections (CMEs). To quantify the effect of solar flares we have considered the X-ray flux (1-8 Å) and EUV flux (26-34nm). Similarly to quantify the effect of CMEs, we have considered the geomagnetic storms, because during high solar activity the geomagnetic storms are caused by CMEs. From our analysis we conclude that during the geomagnetic storms the value of foF2 decreases as compared to quiet days thereby showing a negative effect. On the contrary we found that during solar flares there is sudden and intense increase in foF2. We also performed a correlation analysis to access the magnitude of association between changes in flux values and peak values of Dst during flares and storms with the corresponding changes and peak values of foF2. We found that a strong correlation exists between the enhancements/decrements in foF2 and enhancements in flux values and Dst. We conclude, while geomagnetic activity suppresses ionospheric activity the flares enhance the same.

Long-term changes in the relation between foF2 and hmF2

The change in the dependence of the F2-layer critical frequency on its height hmF2 is considered based on two sources of initial data used earlier by the authors. It is found that the slope k of the foF2 dependence on hmF2 systematically decreases from the earlier (“etalon”) period, 1958–1980, to the later periods of 1988–2010, 1998–2010, and 1998–2014. Since the foF2 value depends on the atomic oxygen concentration in the F region much more strongly than hmF2, the found decrease in k confirms the concept of a decrease in the atomic oxygen concentration in the thermosphere with time previously formulated by the authors.

FoF2 vs solar indices for the Rome station: Looking for the best general relation which is able to describe the anomalous minimum between cycles 23 and 24

Analyses of the dependence of the F2layer critical frequency, foF2, on five widely used solar activity indices (F10.7, Lym-α, MgII, R and EUV0.1–50)are carried out considering noon values manually validated at the ionospheric station of Rome (41.8°N, 12.5°E, Italy) between January 1976 and December 2013, a period of time covering the last three solar cycles and including the prolonged and anomalous minimum of solar cycle 23/24 (years 2008–2009). After applying a 1-year running mean to both foF2 and solar activity indices time series, a second order polynomial fitting proves to perform better than a linear one, and this is specifically due to the very low solar activity of the last solar minimum and to the remaining saturation effect characterizing the high solar activity. A comparison between observed and synthetic foF2 values, the latter calculated by using the analytical relations found for every index, and some considerations made on the R parameter introduced by Solomon et al. (2013), suggest that MgII is the best index to describe the dependence of foF2 on the solar activity. Three main reasons justify this result: (1) the good sensibility of MgII to the variations of foF2 for low solar activity; (2) the reduced saturation effect characterizing MgII at high solar activity; (3) the poor influence of the hysteresis effect characterizing MgII at medium solar activity. On the other hand, the F10.7 index, widely used as input parameter for numerous ionospheric models, does not represent properly the last minimum; specifically, it is not able to describe the variations of foF2 under a solar activity level of F10.7=82·10–22 [JHz–1s–1m–2].

Ionosphere dynamics in the auroral zone during the magnetic storm of March 17–18, 2015

A comprehensive study of the ionospheric processes encountered during the superstorm which started on March 17th 2015 has been carried out using magnetometer, ionosonde, riometer, ionospheric tomography and an all-sky camera installed in the observatory of Sodankylä, Finland. The storm manifested a number of interesting features. From 12:00 on March 17 there was a significant decrease of critical frequencies foF2 and intensive sporadic Es layers were observed. During the disturbance, there was a lack of variation of the X-component of the magnetic field at times, but the absorption level measured by the riometer was high. A comparison of the electron density distributions for the quiet and disturbed days as shown in the tomography data were very different. Where results were available at the same times, the tomographic foF2 values coincided with the “real” foF2 values from the ionosonde. Where the ionosonde data was missing due to absorption, the tomographic foF2 values were used instead. The keograms from the all-sky camera showed that during disturbed days the aurorae manifested themselves as bright discrete forms. It was shown that the peaks of absorption due to particle precipitation seen by the riometer coincided in time with the brightenings of aurorae seen on the keograms.

Statistical Analysis and Modeling of the Local Ionospheric Critical Frequency: A Mid-latitude Single-Station Model for Use in Forecasting

The hourly values of the F-layer critical frequency from the ionospheric sounder in Dourbes (50.1°N, 4.6°E) during the time interval from 1957 to 2010, comprising five solar cycles, were analyzed for the effects of the solar activity. The hourly time series were reduced to hourly monthly medians which in turn were used for fitting a single station foF2 monthly median model. Two functional approaches have been investigated: a statistical approach and a spectral approach. The solar flux F10.7 is used to model the dependence of foF2 on the solar activity and is incorporated into both models by a polynomial expression. The statistical model employs polynomial functions to fit the F-layer critical frequency while the spectral model is based on spectral decomposition of the measured data and offers a better physical interpretation of the fitting parameters. The daytime and nighttime foF2 values calculated by both approaches are compared during high and low solar activity. In general, the statistical model has a slightly lower uncertainty at the expense of the larger number of fitting parameters. However, the spectral approach is superior for modeling the periodic effects and performs better when comparing the results for high and low solar activity. Comparison with the International Reference Ionosphere (IRI 2012) shows that both local models are better at describing the local values of the F-layer critical frequency.

Ionospheric response under the influence of the solar eclipse occurred on 20 March 2015: Importance of autoscaled data and their assimilation for obtaining a reliable modeling of the ionosphere

This paper wants to highlight how the availability of measurements autoscaled at some reference ionospheric stations, and their assimilation by ionospheric models, was of crucial importance in determining, during the solar eclipse conditions occurred on 20 March 2015, a reliable representation of the ionosphere. Even though the solar eclipse falls in the recovery phase of the St. Patrick geomagnetic storm started on 17 March 2015, its influence on the ionospheric plasma seems undeniable. The reference ionospheric stations considered here are those of Rome (41°.8’ N, 12°.5’ E), and Gibilmanna (37°.9’ N, 14°.0’ E), Italy. Specifically, in a time interval including that of the eclipse, the electron density profiles autoscaled by the Automatic Real-Time Ionogram Scaler with True-height (ARTIST) system at San Vito (40°.6′ N, 17°.8′ E), Italy, which are here considered as the truth profiles, were compared with both the electron density profiles calculated by the IRI-SIRMUP-Profiles (ISP) model, after assimilating data recorded at Rome and Gibilmanna, and the electron density profiles provided by the IRI-CCIR model. The ISP and IRI-CCIR performances were then evaluated in terms of the root mean square errors made on the whole electron density profiles. The three-dimensional (3-D) electron density mappings of the ionosphere provided by ISP and IRI-CCIR models were also considered as the ionospheric environment by the ray tracing software tool IONORT to calculate quasi-vertical synthesized ionograms over the short radio link San Vito – Brindisi (40°.4′ N, 17°.6′ E), Italy. The corresponding synthesized values of foF2 and fxF2, obtained by IONORT-ISP and IONORT-(IRI-CCIR) procedures, were compared with those autoscaled by ARTIST from the vertical ionograms recorded at the truth site of San Vito. Some examples of IONORT-ISP and IONORT-(IRI-CCIR) synthesized ionograms are shown and discussed. Finally, comparisons in terms of foF2 deduced by long-term prediction and nowcasting maps are also shown. The results achieved in this work demonstrate how the assimilation of autoscaled data into the ionospheric models turned out to be valuable in providing a better representation of the ionospheric electron density under very unusual conditions.

A procedure for the reliability improvement of the oblique ionograms automatic scaling algorithm

AbstractA procedure made by the combined use of the Oblique Ionogram Automatic Scaling Algorithm (OIASA) and Autoscala program is presented. Using Martyn's equivalent path theorem, 384 oblique soundings from a high‐quality data set have been converted into vertical ionograms and analyzed by Autoscala program. The ionograms pertain to the radio link between Curtin W.A. (CUR) and Alice Springs N.T. (MTE), Australia, geographical coordinates (17.60°S; 123.82°E) and (23.52°S; 133.68°E), respectively. The critical frequency foF2 values extracted from the converted vertical ionograms by Autoscala were then compared with the foF2 values derived from the maximum usable frequencies (MUFs) provided by OIASA. A quality factor Q for the MUF values autoscaled by OIASA has been identified. Q represents the difference between the foF2 value scaled by Autoscala from the converted vertical ionogram and the foF2 value obtained applying the secant law to the MUF provided by OIASA. Using the receiver operating characteristic curve, an appropriate threshold level Qt was chosen for Q to improve the performance of OIASA.

Anomalous behavior of ionospheric parameters above the Kamchatka peninsula before and during seismic activity

In the present work, searching for new methods of earthquake prediction, variations of ionospheric plasma parameters and ionospheric turbulence before and during seismic activity are studied applying complex radiophysical methods and a theoretical probabilistic approach. The analysis of radiophysical observations of some seismic events of February–March (28.02.–02.03.) 2013 shows, that K-layer formation (appearance of a corpuscular layer due to precipitation of particles from the radiation belts), Es- and F-spread effects as well as an increase of the critical foF2-frequency occurred about one day before earthquakes with a magnitude M ≥ 6.5. F2-spread was even observed at low geomagnetic activity. One seismic shock was preceded by an abnormal increase in the value of the critical frequency foF2, and about 2 h after the shock, foF2 was again well below the median value although a geomagnetic storm happened. Therefore, it may be concluded that, in future, variations of ionospheric plasma parameters and turbulence may be used as additional tool to determine the magnitude of preparing strong earthquakes. The propabilistic method which is applied in the present work is already described in (Bogdanov et al., J. Volcanology and Seismology, 4(6), 412–422, 2010). It allowed to detect a growth of seismic activity in the Kamchatka region in 2013.

Predicting ionospheric critical frequency of the F2 layer over Lycksele using the neural network improved by error compensation technology

In this contribution, according to the critical frequency of the F2 layer (foF2) from the ionosonde station and the International Reference Ionosphere 2012 (IRI2012) model [the International Radio Consultative Committee (CCIR) coefficient], a single station model (called the Fusion model) for predicting the hourly value of foF2 over Lycksele (64.69°N, 18.80°E) is developed by the back-propagation neural network (BPNN) technology compensated for the model-deviation of the IRI2012 model. The input parameters of this BPNN-based foF2 prediction model include day number (day of the year), universal time, solar zenith angle, solar cycle information, geomagnetic activity (a 3-day running mean of the 3-h planetary magnetic index Ap and Kp) and the foF2 values from the IRI2012 model; the output parameter is the model-deviation. The data sets employed in this model are obtained from the National Geophysical Data Centre and National Aeronautics and Space Administration (NASA), about 215 614 sets, which are derived during the period from January 1958 to December 1984 (1960s data is missing). The data sets from 1971 to 1984 are selected for validation instead of for training use. Prediction values from the Fusion model, the General BPNN and IRI2012 models are each compared with the observed data. The results indicate that the proposed model is superior to the other models for hourly value of foF2 prediction over Lycksele. According to the statistical analysis of average root mean square error, the proposed model offers an improvement of 19.11% over the IRI2012 model.

Region of permanent generation of large-scale irregularities in the daytime winter ionosphere of the Southern Hemisphere

With the use of data from topside sounding on board the Interkosmos-19 (IK-19) satellite, the region of permanent generation of large-scale irregularities in the daytime winter ionosphere of the Southern Hemisphere is differentiated. This region is characterized by low values of foF2 and hmF2 and occupies a rather large latitudinal band, from the equatorial anomaly ridge to ~70° S within the longitudinal range from 180° to 360°. Irregularities with a dimension of hundreds kilometers are regularly observed in the period from 0700–0800 to 1800–1900 LT, i.e., mainly in the daytime. In the IK-19 ionograms, they normally appear in the form of an extra trace with a critical frequency higher than that of the main trace reflected from the ionosphere with lower density. The electron density in the irregularity maximum sometimes exceeds the density of the background ionosphere by nearly a factor of 3. A model of the ionosphere with allowance for its irregular structure was created, and it was shown on the basis of trajectory calculations how the IK-19 ionograms related to these irregularities are formed. A possible mechanism of the generation of large-scale irregularities of the ionospheric plasma is discussed.

Evaluation of a global model of ionospheric slab thickness for foF2 estimation during geomagnetic storm

<p class="p0">This study aims to evaluate the performance of the global model of ionospheric slab thickness (GMIST) in terms of F2 layer critical frequency (foF2) estimation during geomagnetic disturbed conditions. Hourly values of foF2 as obtained from ionosonde stations located at equatorial, low- and mid-latitude regions are compared with the corresponding GMIST and IRI-STORM modeled values. For this purpose, the correlation coefficient, daily mean, root mean square error and improvement percentage are calculated at different regions and geomagnetic disturbance levels. The results show that GMIST is more accurate than IRI-STORM model in terms of foF2 estimation at low- and mid-latitude regions, while at equatorial areas GMIST is less accurate during geomagnetically disturbed and quiet conditions.</p>

On the inclusion of data from solar cycle 19 to estimate F2 layer characteristic long term trends

<p>The effect of including solar cycle 19 (1954-1964) in ionospheric trend estimation is assessed using experimental foF2 values. The dominant influence on the F2 layer is solar EUV radiation. In fact, around 90% of inter-annual variance of ionospheric parameters, such as foF2, is explained by solar EUV proxies such as the sunspot number, Rz, and solar radio flux at 10.7 cm, F10.7. This makes necessary to filter out solar activity effects prior to long term trends estimation, which is reduced at most to the remaining 10% variance. In general solar activity is filtered assessing the residuals of a linear regression between foF2 and Rz, or between foF2 and F10.7. Solar cycle 19 is a strong cycle during which Rz and F10.7 exceeded the values beyond which the ionosphere does not respond linearly to a further increase in EUV radiation. This effect, called saturation, implies a break down of the linearity between foF2 and EUV, and results in persistent negative residuals during this period. Since solar cycle 19 is at the beginning of the time series, trends result to be positive, or less negative, than trends without considering this period. In this case the filtering process is generating a “spurious” trend in the filtered data series which may lead to erroneous conclusions. hmF2 that do not present a saturation effect is also analyzed.</p><div> </div>

Comparative Preliminary Ionospheric Forecasting In Romania With Data From The European Ionosonde Service Versus Data Extracted From The International Reference Ionosphere Model

Abstract Radiocommunications in the HF band depend on the ionospheric parameters of radiowaves reflexion, though the quality of a radio link depends on: the time of day; season; solar cycle; geographical position. Taking into account the ionosphere characteristics over Romania, a forecasting is made over four cities in our country in order to provide the values of the critical frequency foF2 of the F2 ionospheric layer over a 24 hours cycle. A comparative analysis of this parameter is applied by using the International Reference Ionosphere model and interpolated experimental data collected from the European Ionosonde Service. Results show that the f0F2 values are slightly underestimated in all four locations in the model versus measurements, sustaining the necessity of own measurements in order to prepare quality data links in Romania if HF band is to be used for emergency data communications.

Ionospheric response to annular and partial solar eclipse of 29 April 2014 in Antarctica and Australian Regions

An annular and partial solar eclipse was observed on 29 April 2014 over Australian and Antarctic regions. In this study we have analyzed the ionospheric response of this solar eclipse event. We have done a comprehensive study to find out the changes that occurred in various ionospheric parameters during the solar eclipse event over Australia and Antarctic region. We selected four Australian stations Brisbane (27.5◦S, 152.9◦E), Canberra (35.3◦S, 149.1◦E), Hobart (42.9◦S, 147.3◦E) and Perth (31.955◦S, 115.859◦E) as well as one Antarctic station Mawson (70.6455◦S, 131.2573◦E). We have studied the changes in the E and F ionospheric layers using the ground based observations at these stations. From our analysis we found that there occurred a decrease in the critical frequencies of sporadic E (foEs) and F (foF2) layers during the time eclipse was in progress at all the four Australian stations while as at Antarctic the value of foF2 recorded an enhancement. At the same time an increase in the corresponding heights of these layers (h′Es , h′F2) was also observed. This is the e-book version of the article, published in Russian Journal of Earth Sciences (doi:10.2205/2015ES000548). It is generated from the original source file using LaTeX’s epub.cls class.

Regional optimization of the IRI-2012 output (TEC, foF2) by using derived GPS-TEC

Accurate measurement and determination of the state of the ionosphere has become a key point as ground-based communication systems become more space dependent. However, due to limited infrastructure, a number of global models have been developed with extensive interpolation techniques to comprehensively describe ionospheric dynamics. As a result, most global models do not perform adequately in regions with a paucity of ionospheric measurements. In this paper, the most recent International Reference Ionosphere (IRI-2012) model output, Total Electron Content (TEC) and F2 layer critical frequency (foF2), are optimized (over a range of 120 ° E–150 ° E and 20 ° N–50 ° N in longitude and latitude, respectively). To obtain the optimal solution, we adjust two input parameters, the 12-month running mean sun spot number (R12) and the ionospheric index (IG12), in relation to the derived Global Positioning System (GPS) vertical TEC (VTEC). The results are compared to the measured TEC and foF2 from GPS receivers and ionosondes, respectively. The analysis shows that the modified IRI-2012 model is more accurate at estimating both the TEC and the foF2 values than the original model during days of geomagnetic quiet and disturbance.

Spatial features of Weddell Sea and Yakutsk Anomalies in foF2 diurnal variations during high solar activity periods: Interkosmos-19 satellite and ground-based ionosonde observations, IRI reproduction and GSM TIP model simulation

We studied the main morphology of the formation of summer ionospheric anomalies which includes the Weddell Sea Anomaly (WSA) and the Yakutsk Anomaly (YA) in terms of positive night-to-day foF2 differences. For this purpose, we have for the first time used topside sounding (Interkosmos-19 satellite) and ground-based (ionosonde) data as well as results from an empirical model (International Reference Ionosphere – IRI) and from a first-principles model (Global Self-consistent Model of the Thermosphere, Ionosphere and Protonosphere – GSM TIP). The main spatial morphological characteristics of the WSA and YA are similar which points to a common cause for their occurrence. Our preliminary GSM TIP model results showed that the foF2 values at nighttime are greater than at daytime due to: (1) the horizontal plasma transport due to electromagnetic drift; (2) the vertical component of plasma transport along the geomagnetic field lines via meridional neutral wind; (3) the distribution of the neutral composition of the thermosphere.

GNSS derived TEC data ingestion into IRI 2012

Experimental vertical total electron content (VTEC) data given by Global Ionospheric Maps (GIM) has been ingested into the IRI version 2012, aiming to obtain grids of effective input parameter values that allow to minimize the difference between the experimental and modeled vertical TEC.Making use of the experience gained with the technique of model adaptation applied to NeQuick (Nava et al., 2005), it has been found possible to compute IRI world grids of effective ionosphere index parameters (IG). The IG grids thus obtained can be interpolated in space and time to calculate with IRI the 3D electron density at any location and also the TEC along any ground-to-satellite ray-path for a given epoch. In this study, the ingestion technique is presented and a posteriori validation, along with an assessment of the capability of the ‘ingested’ IRI to reproduce the ionosphere day-to-day foF2 variability during disturbed and quiet periods. The foF2 values retrieved are compared with data from about 20 worldwide ionosondes for selected periods of high (year 2000) and moderate to low solar activity (year 2006). It was found that the use of the ingestion scheme enhances the performance of the model when compared with its standard use based on solar activity drivers (R12 and F10.7), especially for high solar activity. As an example, the mean and standard deviation of the differences between experimental and reconstructed F2-peak values for April of year 2000 is 0.09 and 1.28MHz for ingested IRI, compared to −0.81 and 1.27MHz (IRI with R12 input) and −0.02 and 1.46MHz (IRI with F10.7 input).

The spatial and temporal structure of twin peaks and midday bite out in foF2 (with associated height changes) in the Australian and South Pacific low midlatitude ionosphere

AbstractMorning and afternoon peaks in daytime critical frequency foF2 defining a midday bite out were found to occur regularly across northern Australia during April 2008. This behavior was sufficiently repetitive to appear in the monthly median values of foF2. The twin peak and bite out phenomenon was observable across the entire longitudinal range of ionosondes which were accessible for this study, from Niue in mid‐Pacific to Learmonth on the western side of Australia. The high geographic density of ionosondes operating in Australia enabled the limited latitudinal range of occurrence to be established, the phenomenon ceasing to be present in the southern half of Australia or at equatorial latitudes. While strongest in 2008, the foF2 bite out and associated variation in hmF2, the peak height of the ionosphere, continued to be seen in monthly April medians from sunspot minimum (2007–2008) to the current low sunspot maximum (2011–2013) while diminishing in magnitude. This phenomenon was also present around the September equinox, though not of such magnitude or consistency as during the April equinox. The morning and afternoon peaks in foF2 occurred during periods of falling virtual and true height and were associated with the maximum compression of the ionosphere at this time as measured by the subpeak equivalent parabolic layer thickness ym. Meridional winds in the F2 layer are suggested as a driver of the twin peak enhancements in foF2, which may possibly be related to a simultaneous occurrence of strong tidal influences as seen to be present in descending sporadic E.

TaiWan Ionospheric Model (TWIM) prediction based on time series autoregressive analysis

AbstractAs described in a previous paper, a three‐dimensional ionospheric electron density (Ne) model has been constructed from vertical Ne profiles retrieved from the FormoSat3/Constellation Observing System for Meteorology, Ionosphere, and Climate GPS radio occultation measurements and worldwide ionosonde foF2 and foE data and named the TaiWan Ionospheric Model (TWIM). The TWIM exhibits vertically fitted α‐Chapman‐type layers with distinct F2, F1, E, and D layers, and surface spherical harmonic approaches for the fitted layer parameters including peak density, peak density height, and scale height. To improve the TWIM into a real‐time model, we have developed a time series autoregressive model to forecast short‐term TWIM coefficients. The time series of TWIM coefficients are considered as realizations of stationary stochastic processes within a processing window of 30 days. These autocorrelation coefficients are used to derive the autoregressive parameters and then forecast the TWIM coefficients, based on the least squares method and Lagrange multiplier technique. The forecast root‐mean‐square relative TWIM coefficient errors are generally <30% for 1 day predictions. The forecast TWIM values of foE and foF2 values are also compared and evaluated using worldwide ionosonde data.

Effect of solar cycle 23 in foF2 trend estimation

The effect of including solar cycle 23 in foF2 trend estimation is assessed using experimental values for Slough (51.5°N, 359.4°E) and Kokobunji (35.7°N, 139.5°E), and values obtained from two models: (1) the Sheffield University Plasmasphere-Ionosphere model, SUPIM, and (2) the International Reference Ionosphere, IRI. The dominant influence on the F2 layer is solar extreme ultraviolet (EUV) radiation, evinced by the almost 90% variance of its parameters explained by solar EUV proxies such as the solar activity indices Rz and F10.7. This makes necessary to filter out solar activity effects prior to long-term trend estimation. Solar cycle 23 seems to have had an EUV emission different from that deduced from traditional solar EUV proxies. During maximum and descending phase of the cycle, Rz and F10.7 seem to underestimate EUV solar radiation, while during minimum, they overestimate EUV levels. Including this solar cycle in trend estimations then, and using traditional filtering techniques, may induce some spurious results. In the present work, filtering is done in the usual way considering the residuals of the linear regression between foF2 and F10.7, for both experimental and modeled values. foF2 trends become less negative as we include years after 2000, since foF2 systematically exceeds the values predicted by a linear fit between foF2 and F10.7. Trends become more negative again when solar cycle 23 minimum is included, since for this period, foF2 is systematically lower than values predicted by the linear fit. foF2 trends assessed with modeled foF2 values are less strong than those obtained with experimental foF2 values and more stable as solar cycle 23 is included in the trend estimation. Modeled trends may be thought of as a ‘zero level’ trend due to the assumptions made in the process of trend estimation considering also that we are not dealing with ideal conditions or infinite time series.