Ionospheric Critical Frequency Research Articles

Weak ionization of the global ionosphere in solar cycle 24

Abstract. Following prolonged and extremely quiet solar activity from 2008 to 2009, the 24th solar cycle started slowly. It has been almost 5 years since then. The measurement of ionospheric critical frequency (foF2) shows the fact that solar activity has been significantly lower in the first half of cycle 24, compared to the average levels of cycles 19 to 23; the data of global average total electron content (TEC) confirm that the global ionosphere around the cycle 24 peak is much more weakly ionized, in contrast to cycle 23. The weak ionization has been more notable since the year 2012, when both the ionosphere and solar activity were expected to be approaching their maximum level. The undersupply of solar extreme ultraviolet (EUV) irradiance somewhat continues after the 2008–2009 minimum, and is considered to be the main cause of the weak ionization. It further implies that the thermosphere and ionosphere in the first solar cycle of this millennium would probably differ from what we have learned from the previous cycles of the space age.

Emissions of ionospheric Alfvén resonator and ionospheric conditions

We analyze continuous magnetic observations of ionospheric Alfvén resonator (IAR) emissions at mid-latitude observatory Mondy. The measurements were by a LEMI-30 search-coil magnetometer covering the period from March 2010 to May 2011. The results are compared with data from simultaneous ionospheric sounding data and International Reference Ionosphere (IRI-2012) model parameters. The large amount of observational data allowed us to inspect the daily and seasonal variations in some morphological characteristics of the emissions as well as their relationship to ionospheric conditions. The main factor affecting the duration of the emission is how long the lower ionosphere stays in Earth's shadow. We demonstrate a close inverse correlation between the diurnal and seasonal IAR frequency variations, on the one hand, and changes in the ionospheric critical frequency, f0F2, on the other. Additionally, the expected emission frequency scale calculated with the IRI-2012 model is in good agreement with the values measured from the emission spectrograms.

Unusual Enhancement of Ionospheric F2 Layer Critical Frequency Before the 23 August 2011 Virginia (USA) Earthquake

Unusual Enhancement of Ionospheric F2 Layer Critical Frequency Before the 23 August 2011 Virginia (USA) Earthquake

Long-term changes in thermospheric composition inferred from a spectral analysis of ionospheric F-region data

Abstract. A study of ionospheric data recorded at Slough/Chilton, UK, from 1935 to 2012, has revealed long-term changes in the relative strength of the annual and semi-annual variability in the ionospheric F2 layer critical frequencies. Comparing these results with data from the southern hemisphere station at Stanley in the Falkland Islands between 1945 and 2012 reveals a trend that appears to be anti-correlated with that at Chilton. The behaviour of foF2 is a function of thermospheric composition and so we argue that the observed long-term changes are driven by composition change. The ionospheric trends share some of their larger features with the trend in the variability of the aa geomagnetic index. Changes to the semi-annual/annual ratio in the Slough/Chilton and Stanley data may therefore be attributable to the variability in geomagnetic activity which controls the average latitudinal extent of the auroral ovals and subsequent thermospheric circulation patterns. Changes in ionospheric composition or thermospheric wind patterns are known to influence the height of the F2 layer at a given location. Long-term changes to the height of the F2 layer have been used to infer an ionospheric response to greenhouse warming. We suggest that our observations may influence such measurements and since the results appear to be dependent on geomagnetic longitude, this could explain why the long-term drifts observed in F2 layer height differ between locations.

Geomagnetic Disturbances and Its Impact on Ionospheric Critical Frequency (foF2) at High, Mid and Low Latitude Region

A geomagnetic storm is a major disturbance of Earth's magnetosphere that occurs when there is a very efficient exchange of energy from the solar wind into the space environment surrounding Earth. During solar and geomagnetic activities, critical frequency of F2 layer (foF2) varies in a great extent. In this Study, our main aim is to examine the effect of solar and geomagnetic activities on the critical frequency (foF2) during January 2014 to April 2014 respectively. One magnetic intense storm occurred on 19 February with (Dst -112) and other moderate storm occurred on 12 April 2014 with (Dst -80). In our study, we have analyzed these effects on critical frequency of F2 layer for ionospheric monitoring. We have used ionospheric data at Low, mid and high latitude station. The absorption and ionization of the ionospheric medium depends on solar activity. The value of foF2 increased from their normal value at all the three latitudes. This is due to geomagnetic storms that occurred around the same time. A very interesting feature that can be seen in the figures is that the increase of foF2 at Low latitude is much more intense as compare to high and mid latitude. Comparison among all the latitudes shows that the values of foF2 at high latitude are quite less as compared to low and mid latitude. We have found that the effect of solar and geomagnetic storm disturbances is strongest at the low latitude and weakest at the high latitude during the geomagnetic storm time.

The effect of the geomagnetic activity to the hourly variations of ionospheric foF2 values at low latitudes

In this study, the relationship between the hourly changes of the ionospheric critic frequency values of F2 layers in low latitudes and geomagnetic activity is examined by using statistical methods. The ionospheric critical frequency data has been taken from the Manila (121.1° E, 14.7° N) ionosonde station. In order to investigate the effect of sun activity on ionospheric critical frequency, the data of 1981 when the sun was active and of 1985 when the sun was less active has been used. According to the Granger causality test results, on 5 % significance level, a causality relationship from disturbance storm time (Dst) index values to ionospheric critical frequency values direction has been observed. However, a causality relationship from ionospheric critical frequency values to Dst values has not been observed. From the results of cause-and-effect analysis, it is evaluated that the effect of a shockwave occurring in geomagnetic activity on ionospheric critical frequency continues along 72 h, that is, geomagnetic activity has a long-term effect on ionospheric critical frequency. The response of ionospheric critical frequency to geomagnetic activity substantially depends on seasons. This response is more observed especially in equinox period when the sun is active and in winter months. The increase in geomagnetic activity causes ionospheric critical frequency to decrease in night hours and increase in day hours. The same relationship has not been observed exactly, though observed very little in winter months, for 1985 when the sun was less active.

Predicting foF2 in the China region using the neural networks improved by the genetic algorithm

A regional model for the ionospheric critical frequency of the F2 layer (foF2) over China is developed by neural networks (NNs) trained by the genetic algorithm (GA). In order to avoid the ‘local minimum’ phenomena in most NN applications, GA is utilized here to optimize the initial weights of NNs. The input parameters used in this GA-NN based foF2 prediction model include Beijing time (BJT, GMT+8), day number (day of the year), seasonal information, solar cycle information, magnetic activity, magnetic declination, magnetic dip angle, angle of meridian relative to sub-solar point, solar zenith angle, and geographic coordinates. The foF2 datasets employed in this model are obtained from nine ionosonde stations located in China for the time span of 1990–2004 that covers one entire sunspot cycle. The datasets for 1996 and 2000 are selected for validation instead of for training use. Prediction results of GA-NN model, unimproved NN model, and International Reference Ionosphere 2007 (IRI2007) model (from International Radio Consultative Committee (CCIR) coefficient) are compared with the observation data for the year of 1996 and 2000 respectively. The results indicate that GA-NN model is superior to the unimproved NN model and the IRI2007 model for foF2 prediction. According to the statistical analysis of average RMSE, the GA-NN method offers an improvement of 4.89% over NN method and an improvement of 27.79% over IRI2007 model. The improvement of accuracy for one single station forecasting is validated with the data from the Wuhan ionosonde station both at 00:00 (BJT) and 12:00 (BJT) in 1996 (solar minimum) and 2000 (solar maximum).

Large ionospheric disturbances during a minor geomagnetic storm on June 23, 2000

<p>We investigate the variations in the ionosphere during a small geomagnetic storm on June 23, 2000, using the total electron content of the Jet Propulsion Laboratory global positioning system, and the ionospheric critical frequency. Large and long-lasting reductions in the daytime electron density were observed at mid-latitudes in the northern hemisphere by ionosondes. These reductions reached 30% to 40% compared to the 27-day median value. At the same time, a transformation from similar large positive storm effects to negative storm effects was observed in the northern hemisphere by the global positioning system receivers. The geomagnetic disturbance was very weak from June 23-25, 2000, as the SYM-H index was >−40 nT and ASY-H was <90 nT. Of note, during this case there were neither long-lasting southward IMF Bz nor strong positive IMF By components, where a large positive IMF By might be the main reason for ionospheric storms during minor geomagnetic disturbances [Goncharenko et al. 2006]. We confirm a 13-h enhanced energy input from the disturbed solar wind by calculation of the Borovsky, Akasofu and Newell coupling functions, the global auroral precipitation, and the Joule heating. We suggest this enhanced energy input as the main cause of these intense ionospheric storms, although the maximum of the energy input was not large. In addition, we propose that the Newell coupling function might be more suitable for reflecting the energy transfer from the disturbed solar wind to the magnetosphere under weak geomagnetic activity.</p>

Testing the Equality of Mean Functions of Ionospheric Critical Frequency Curves

SummaryThe paper develops a significance test for evaluating the equality of the mean functions in two samples of spatially indexed functional data. The problem is motivated by an important question in space physics research which is related to the hypothesis of ionospheric global cooling (as opposed to the conjectured global warming of near surface atmosphere). The critical electron frequency of the ionosphere's F2 region, foF2, can be used to test conjectures about the trends in the ionosphere empirically. We apply the proposed test to the foF2-records over eastern and western Europe to verify whether there is a conjectured difference between first-order behaviour of these records over regions with different magnetic inclinations. It is found that the difference between the means is statistically significant for night-time records. The implications of this result are discussed. Finite sample performance of the test proposed is validated via numerical simulations.

Method of Detection Abnormal Features in Ionosphere Critical Frequency Data on the Basis of Wavelet Transformation and Neural Networks Combination

The research is focused on the development of automatic detection method of abnormal features, that occur in recorded time series of ionosphere critical frequency fOF2 during periods of high solar or seismic activity. The method is based on joint application of wavelet-transformation and neural networks. On the basis of wavelet transformation algorithms for the detection of features and estimation of their parameters were developed. Detection and analysis of characteristic components of time series are performed on the basis of joint application of wavelet transformation and neural networks. Method's approbation is performed on fOF2 data obtained at the observatory “Paratunka” (Paratunka settlement, Kamchatskiy Kray).

On the small-scale fluctuations in the peak electron density of Martian ionosphere observed by MEX/MARSIS

We reported the small-scale fluctuations in the peak electron density of dayside Martian ionosphere observed by MEX/MARSIS. MARSIS is an ionospheric sounder that can measure the vertical electron density profile of the topside ionosphere. In the experiment the ionospheric critical frequency can be determined within the accuracy of 5kHz, corresponding to a typical accuracy in electron density of 0.02%. As a space-borne remote sensing instrument, MARSIS can observe the ionosphere with a time resolution of 8s, enabling one to study the horizontal variation of the ionosphere. Besides the normal variations of the peak electron density with respect to the solar zenith angles, small fluctuations in peak electron density is detected within single orbit of observation. The appearance of these fluctuations is relatively smooth and wavy, distinct from measurement errors which are random and noisy. The fluctuations do not exhibit a prevailing wavelength either in space or in time. The peak-to-valley amplitude of the fluctuation can reach 200kHz in frequency, corresponding to a 10% variation in peak electron density. Over 38,000 peak values of electron density profiles were recorded, organized along each orbit. A mean variation of ∼6% in the peak electron density is found. Fourier analysis of the data was performed with respect to the horizontal distance the spacecraft passes in one orbit. Resulting spectra generally follow a −5/3 power law in a double logarithm plot, suggesting a turbulence-dominated nature. Perturbations propagating from upper ionosphere and fluctuations in the neutral density are discussed as potential causes for this observation. This observation reveals a sensitive proxy to monitor the dynamics of neutral Martian atmosphere at ∼130km altitude.

Inter-hemispheric imaging of the ionosphere with the upgraded IRI-Plas model during the space weather storms

International Reference Ionosphere extended to the plasmasphere (IRI-Plas) is upgraded analytically for assimilative mode of operation using GPS-derived Total Electron Content (TEC) for reconstruction of instantaneous ionospheric critical frequency and topside scale height at magnetic conjugate hemisphere. The performance of IRI-Plas code is examined with TECgps retrieved from Global Ionospheric Maps compared with the F2-layer critical frequency at eight ionosonde locations in East Asia region on both hemispheres during the space weather storms at solar maximum (2000) and solar minimum (2006). Missing ionosonde data are completed by cloning of critical frequency. Decomposition of TECgps in electron density profile with IRI-Plas code reveals the opposite relative changes of critical frequency and the topside scale height depending on solar activity. The ionospheric weather W index is computed for the desired locations in conjugate hemispheres and consistent results are obtained indicating the departure of instantaneous values of ionospheric parameters from their respective median varying from quiet state to intense storm.

Modified solar flux index for upper atmospheric applications

[1] The F10.7 solar flux index was modified in order to better describe short-term variations in solar extreme ultraviolet (EUV) irradiance for application in ionosphere and thermosphere studies. Several parameters were computed from the F10.7 time series with the assistance of an artificial neural network (ANN) technique, and the daily F10.7 index value was converted to a new solar flux index, MEI10.7. The ANN consists of an input layer that includes an experimental solar input and the day of the year to take seasonal factors into account, one hidden layer, and a target layer of ionospheric total electron content (TEC). The ANN training and validation data set covered one solar cycle from 1997 to 2008. The parameter set that yielded the smallest root-mean-square errors (RMSEs) between the observed and ANN-predicted TECs was adopted for modifying the solar flux index. The MEI10.7 index was evaluated via the same ANN technique. MEI10.7 yielded a smaller RMSE than the magnesium index (Mg II core-to-wing ratio) and a similar RMSE to the EUV index based on the integrated 26–34 nm emission measured by the Solar and Heliospheric Observatory. An advantage of MEI10.7 is long-term availability since the 1940s, unlike satellite measurements. A long-term trend analysis of the ionospheric critical frequency (foF2) at Kokubunji, Japan, conducted for the period from 1957 to 2010 examined the difference between the ANN-modeled and measured foF2 values. The linear regression error when foF2 was modeled by MEI10.7 was appreciably smaller than when it was modeled by F10.7.

Performance of IRI‐based ionospheric critical frequency calculations with reference to forecasting

Ionospheric critical frequency (foF2) is an important ionospheric parameter in telecommunication. Ionospheric processes are highly nonlinear and time varying. Thus, mathematical modeling based on physical principles is extremely difficult if not impossible. The authors forecast foF2 values by using neural networks and, in parallel, they calculate foF2 values based on the IRI model. The foF2 values were forecast 1 h in advance by using the Middle East Technical University Neural Network model (METU‐NN) and the work was reported previously. Since then, the METU‐NN has been improved. In this paper, 1 h in advance forecast foF2 values and the calculated foF2 values have been compared with the observed values considering the Slough (51.5°N, 0.6°W), Uppsala (59.8°N, 17.6°E), and Rome (41.8°N, 12.5°E) station foF2 data. The authors have considered the models alternative to each other. The performance results of the models are promising. The METU‐NN foF2 forecast errors are smaller than the calculated foF2 errors. The models may be used in parallel employing the METU‐NN as the primary source for the foF2 forecasting.

Time variations of the ionosphere at the northern tropical crest of ionization at Phu Thuy, Vietnam

Abstract. This study is the first which gives the climatology of the ionosphere at the northern tropical crest of ionization in the Asian sector. We use the data from Phu Thuy station, in Vietnam, through three solar cycles (20, 21 and 22), showing the complete morphology of ionosphere parameters by analyzing long term variation, solar cycle variation and geomagnetic activity effects, seasonal evolution and diurnal development. Ionospheric critical frequencies, foF2, foF1 and foE, evolve according to the 11-year sunspot cycle. Seasonal variations show that foF2 exhibits a semiannual pattern with maxima at equinox, and winter and equinoctial anomalies depending on the phases of the sunspot solar cycle. ΔfoF2 exhibits a semiannual variation during the minimum phase of the sunspot solar cycle 20 and the increasing and decreasing phases of solar cycle 20, 21 and 22. ΔfoF1 exhibits an annual variation during the maximum phase of solar cycles 20, 21 and 22. Δh'F2 shows a regular seasonal variation for the different solar cycles while Δh'F1 exhibits a large magnitude dispersion from one sunspot cycle to another. The long term variations consist in an increase of 1.0 MHz for foF2 and of 0.36 MHz for foF1. foE increases 0.53 MHz from solar cycle 20 to solar cycle 21 and then decreases −0.23 MHz during the decreasing phase of cycle 21. The diurnal variation of the critical frequency foF2 shows minima at 05:00 LT and maxima around 14:00 LT. foF1 and foE have a maximum around noon. The diurnal variation of h'F2 exhibits a maximum around noon. The main features of h'F1 are a minimum near noon and the maximum near midnight. Other minima and maxima occur in the morning, at about 04:00 or 05:00 LT and in the afternoon, at about 18:00 or 19:00 LT but they are markedly smaller. Only during the maximum phase of all sunspot solar cycles the maximum near 19:00 LT is more pronounced.

Rise and fall of electron temperatures: Ohmic heating of ionospheric electrons from underdense HF radio wave pumping

Here we present electron temperature variations observed with incoherent scatter radar during a European Incoherent Scatter Scientific Association Heating experiment with high‐frequency (HF) radio wave transmission at frequencies above the peak ionospheric critical frequency. The electron temperature increased from 2000 K up to 2800 K during the HF transmission periods. During the experiment both pump frequency and polarization were altered between pump pulses. The observed temperature variation is compared with numerical solutions to the electron energy equation with ohmic heating modeling the effect of the radio wave heating of the plasma. Agreement between observations and model is found to be good.

Diurnal specification of the ionosphericf0F2parameter using a support vector machine

[1] This paper proposes a method for forecasting the ionospheric critical frequency, f0F2, up to 5 h ahead using the support vector machine (SVM) approach. The inputs to the SVM network are the universal time; day of the year; a 2 month running mean sunspot number (R2); a 3 day running mean of the 3 h planetary magnetic ap index, the solar zenith angle; the present value f0F2(t) and ten previously observed values f0F2(t − i), where i = 1, 2, 3, 4, 19, 20, 21, 22, 23, 24; and the six derivatives of previous 30 day running means of f0F2fmF2(t − j), where j = 19, 20, 21, 22, 23, 24. The output is the predicted f0F2 up to 5 h ahead. The network is trained using the ionospheric sounding data from seven Chinese stations, i.e., Guangzhou, Haikou, Chongqing, Beijing, Lanzhou, Changchun, and Manzhouli stations at solar maximum and minimum. In order to test the predictive ability, the SVM was verified with different data from the training data. The quality of the proposed model prediction is evaluated by comparison with corresponding predictions from the persistence reference, the autocorrelation and the neural network (NN) models. By using data from seven Chinese stations, it is shown that the performance of the SVM model is superior to that of the autocorrelation and persistence models, and that it is comparable to that of the NN model.

Forecasting the ionospheric f0F 2 parameter one hour ahead using a support vector machine technique

This paper proposes a method for forecasting the ionospheric critical frequency, f 0F 2, 1 h in advance, using the support vector machine (SVM) approach. The inputs to the SVM network are the time of day, seasonal information, 2 month running mean sunspot number ( R2), 3 day running mean of the 3 h planetary magnetic ap index, the solar zenith angle, the present value f 0F 2( t) and its first and second increments, the observation of f 0F 2 at t−23 h, the 30-day mean value at time, t, f mF 2 ( t) and the previous 30 day running mean of f 0F 2 at t−23 h f mF 2( t−23). The output is the predicted f 0F 2 1 h ahead. The network is trained to use the ionospheric sounding data at Haikou, Guangzhou, Chongqing, Lanzhou, Beijing, Changchun and Manzhouli stations at high and low solar activities. The performance of the SVM model was verified with observed data. It is shown that the predicted f 0F 2 has good agreement with the observed f 0F 2. The performance of the SVM model is superior to that of the autocorrelation and persistence models, and that it is comparable to that of the neural network model.

Ionospheric total electron content and critical frequencies over Europe at solar minimum

The paper presents results obtained by analyzing high-resolution ionospheric vertical total electron content (vTEC) data set evaluated from a chain of European ground-based Global Positioning System (GPS) stations and its equivalent slab thickness, as well as the F2-layer critical frequency foF2 and propagation factor M(3000)F2 from nearby ionosonde stations over the period 2006-2007. The study covers data within an area between 36°N and 68°N geographic latitude, and 7°W and 21°E geographic longitude during these last two years of minimum solar activity in the 23rd solar cycle. It reveals 15 extraordinary events, all of which exhibited some form of large short-lived vTEC and foF2 enhancements of the duration of small-magnitude solar-terrestrial events. The results clearly show a well-defined vTEC and foF2 storm-like disturbance patterns developed under these conditions. They prove that there are still some open questions related to the large electron density variations during weak disturbances that require additional study for both their relevance to different Global Navigation Satellite Systems (GNSS) applications and their role in the formation and evolution of the daytime ionosphere at middle latitudes.

Variability of foF2 in the African equatorial ionosphere

This paper presents the impact of diurnal, seasonal and solar activity effects on the variability of ionospheric foF2 in the African equatorial latitude. Three African ionospheric stations; Dakar (14.8°N, 17.4°W, dip: 11.4°N), Ouagadougou (12.4°N, 1.5°W, dip: 2.8°N) and Djibouti (11.5°N, 42.8°E, dip: 7.2°N) were considered for the investigation. The overall aim is to provide African inputs that will be of assistance at improving existing forecasting models. The diurnal analysis revealed that the ionospheric critical frequency (foF2) is more susceptible to variability during the night-time than the day-time, with two peaks in the range; 18–38% during post-sunset hours and 35–55% during post-midnight hours. The seasonal and solar activity analyses showed a post-sunset September Equinox maximum and June Solstice maximum of foF2 variability in all the stations for all seasons. At all the stations, foF2 variability was high for low solar activity year. Overall, we concluded that equatorial foF2 variability increases with decreasing solar activity during night-time.