Layer Critical Frequency Research Articles

Influence of solar activity variations on the day-to-day <i>NmE</i> variability during geomagnetically quiet conditions according to the ground-based Dourbes ionosonde data

A study of day-to-day variations in the statistical characteristics of the ionospheric E layer electron number density NmE for each month in the year under geomagnetically quiet conditions at low and middle solar activity was carried out according to the hourly ground-based Dourbes ionosonde measurements of the ionospheric E layer critical frequency during the time periods from 1957 to 2023. The NmE statistical parameters under calculations are the mathematical expectation NmEE, the most probable NmEMP, the arithmetical mean monthly median NmEMED, the standard deviations sE, sMP, sMED, and the variation coefficients CVE, CVMP, and CVMED of NmE relative to NmEE, NmEMP, and NmEMED, respectively. It was shown that the value of NmEE provides the best description of a set of observations of NmE by one parameter due to the lower day-to-day variability of NmE compared to NmEMP or NmEMED. It was proven for the first time that the transition from low to middle solar activity leads to significant changes in the day-to-day variability of NmE with the longest periods of increases and decreases in the studied variability in March and December, respectively.

Trends in the critical frequency <i>foF</i>2 at stations of the Northern and Southern hemispheres

A search for long-term trends in the F2 layer critical frequency foF2 is performed based on vertical sounding observations at three stations of the Northern Hemisphere (Juliusruh, Boulder, and Moscow) and three stations of the Southern Hemisphere (Townsville, Hobart, and Canberra). A method developed and extensively described by the authors is used. The data for two winter months in each hemisphere for five near-noon LT moments were analyzed. Three solar activity (SA) proxies (F30, Ly-α, and MgII) were used to eliminate SA effects. Negative trends are obtained for all considered situations (station, month, LT moment, SA proxy). The trends agree well with each other both if stations of the Northern and Southern hemispheres are compared individually or in aggregate.

Impact of different solar extreme ultraviolet (EUV) proxies and Ap index on hmF2 trend analysis

Abstract. Long-term trend estimation in the peak height of the F2 layer, hmF2, needs the previous filtering of much stronger natural variations such as those linked to the diurnal, seasonal, and solar activity cycles. If not filtered, they need to be included in the model used to estimate the trend. The same happens with the maximum ionospheric electron density that occurs in this layer, NmF2, which is usually analyzed through the F2 layer critical frequency, foF2. While diurnal and seasonal variations can be easily managed, filtering the effects of solar activity presents more challenges, as does the influence of geomagnetic activity. However, recent decades have shown that geomagnetic activity may not significantly impact trend assessments. On the other hand, the choice of solar activity proxies for filtering has been shown to influence trend values in foF2, potentially altering even the trend's sign. This study examines the impact of different solar activity proxies on hmF2 trend estimations using data updated to 2022, including the ascending phase of solar cycle 25, and explores the effect of including the Ap index as a filtering factor. The results obtained based on two mid-latitude stations are also comparatively analyzed to those obtained for foF2. The main findings indicate that the squared correlation coefficient, r2, between hmF2 and solar proxies, regardless of the model used or the inclusion of the Ap index, is consistently lower than in the corresponding foF2 cases. This lower r2 value in hmF2 suggests a greater amount of unexplained variance, indicating that there is significant room for improvement in these models. However, in terms of trend values, foF2 shows greater variability depending on the proxy used, whereas the inclusion or exclusion of the Ap index does not significantly affect these trends. This suggests that foF2 trends are more sensitive to the choice of solar activity proxy. In contrast, hmF2 trends, while generally negative, exhibit greater stability than foF2 trends.

Sporadic E critical frequency detection using three EIA region ionosonde stations over Southeast Asia

This paper presents the occurrence of the sporadic E layer critical frequency (foEs) measured from three ionosonde stations in the Southeast Asia equatorial ionization anomaly (EIA) regions. These three ionosonde stations include two in Thailand: Chiang Mai (18.76°N, 98.93°E, Dip 12.7°) and Chumphon (10.72°N, 99.37°E, Dip 3.0°), and one in Indonesia: Kototabang (0.2°S, 100.32°E, Dip -10.1°). The daily hourly foEs values observed during 2010 and 2015 were statistically analyzed for foEs occurrence during low and high solar activity periods. Additionally, the number of foEs occurrences was analyzed in terms of the percentage of occurrence (%foEs). The results show that the occurrences of foEs from all three stations were similar, with the monthly hourly occurrence of foEs peaking in the June solstice season (May, June, July, August). Meanwhile, foEs appeared relatively low during the September equinox (September, October) and the December solstice (November, December, January, February) seasons. Furthermore, the frequency of foEs occurrence peaks around 16-20 LT, except in 2015 at Chiang Mai and Chumphon, where peaks were observed at 10 LT and 15 LT, respectively. Additionally, comparing the three stations reveals that in 2010, the maximum number of foEs occurrences was at Chiang Mai (≈21%), followed by Kototabang (≈19%) and Chumphon (≈16%). In 2015, the highest number was observed at Kototabang (≈17%), followed by Chumphon (≈14%) and Chiang Mai (≈8%). Furthermore, the maximum frequency of foEs was highest at Chiang Mai (20-25 MHz), followed by Chumphon (15-20 MHz) and Kototabang (10-15 MHz). Additionally, foEs occurrences during low solar activity (2010) were higher than those during high solar activity (2015). It was assumed that the occurrence of foEs in the Southeast Asian sector was anti-correlated with the solar cycle and asymmetric characteristics. We hope that this analytical information will be useful for future HF and VHF communications design in the Southeast Asia region.

A Comparison of PSO-based Neural Network Predictions of F2 Ionospheric Layer Critical Frequency in Malaysia with IRI-2016

This paper discussed the prediction of the equatorial ionospheric F2 layer critical frequencies, foF2, using a backpropagation neural network (BPNN) model in conjunction with a particle swarm optimization (PSO) algorithm, named as the BPNN–PSO model, for various solar and geomagnetic activities, and compared it with the IRI-2016 model. The critical frequency data were taken from an ionosonde located at Universiti Tun Hussein Onn Malaysia in Johor, Malaysia (1.86° N, 103.80° E). The model’s outputs were analyzed using root-mean-square error (RMSE). The BPNN–PSO model outperformed the IRI-2016 model during low, medium, and high solar activity. The BPNN–PSO model had the lowest RMSE of 0.20 MHz and performed best during periods of high solar activity. This is much better than the RMSE for IRI-2016 model, which was 2.95 MHz. In addition, compared with the IRI-2016 model, the BPNN–PSO model made accurate predictions during both quiet and geomagnetic storm conditions. The BPNN–PSO model had the lowest RMSE of 0.54 MHz during an intense storm, while the IRI-2016 model had the RMSE of 2.84 MHz during this storm.

Simultaneous monitoring of the limited area ionosphere with the use of GPS and ionosonde

The importance of this study lies in its contribution to the field of ionospheric science, particularly in the monitoring and prediction of ionospheric parameters. This study focuses on comparing two techniques for spatio-temporal kriging of critical ionospheric parameters, namely the F2 layer critical frequency (foF2) and Total Electron Content (TEC), under both quiet and disturbed ionospheric conditions. The first technique, Ordinary Kriging (OK), relies solely on foF2 data, while the second technique, Kriging with External Drift (KED), incorporates the dynamic relationship between foF2 and TEC data to improve the interpolation process. This study demonstrates how KED, which utilizes dynamic secondary information, offers advantages over OK. By simultaneously monitoring the ionosphere from a single ionosonde station and collecting data from visible GPS satellites, KED enhances the accuracy of spatial structural analysis, enabling more precise estimations of ionospheric characteristics across interpolation grid nodes. The research highlights that the non-uniform distribution of ionosonde stations, especially in regions with limited foF2 data, can benefit from KED's incorporation of TEC data. Additionally, the study reveals the potential for improving TEC maps by assimilating foF2 data located at the periphery of the observation area. Furthermore, the paper discusses the determination of semivariogram structures for both foF2 and TEC data, emphasizing the spatial correlations between data points. These findings contribute to a better understanding of ionospheric behavior and the potential for enhanced ionospheric modeling.

Dependence of annual asymmetry in <i>NmF2</i> on local time

Based on the global empirical model of the F2 layer critical frequency median (Satellite and Digisonde Data Model of the F2 layer, SDMF2), an analysis was made of the properties of diurnal variations in the annual asymmetry in the concentration of the F2 layer maximum NmF2 at different values of the solar activity index F. The AI index, which characterizes the relative difference in NmF2 averaged over all longitudes and latitudes between January and July at a given local time, was used as a parameter of this asymmetry. It was found that the diurnal variations of the AI index are dominated by a semidiurnal mode with maxima in the daytime and at night. The daytime maximum of the AI index is almost independent of the level of solar activity. The nighttime AI maximum decreases with increasing solar activity. For low solar activity, the daytime and nighttime AI maxima almost coincide in amplitude when AI = 16—17%. The difference in the solar radio flux between January and July due to the ellipticity of the Earth’s orbit relative to the Sun makes a significant contribution to the AI index at all hours of the day. On average, it is 3—4% and can reach 5% with low solar activity at night. The difference in the AI index for low and high activity according to the IRI model (with URSI and, especially, CCIR coefficients) is overestimated relative to the SDMF2 model at almost all hours of the day, apparently due to the limited number of experimental data when obtaining the CCIR and URSI coefficients especially over the oceans

An Empirical Model of the Sporadic E Layer Intensity Based on COSMIC Radio Occultation Observations

AbstractIonospheric sporadic E layers are common phenomena occurring in the ionospheric E region altitude (∼90–120 km) with much higher electron density. The lack of a large amount of sporadic E layer intensity observation on a global scale restrains the construction of global modeling of sporadic E layer intensity. Recent studies reveal that radio occultation observation can be used for sporadic E layer intensity inversion. In this paper, a low‐mid latitude empirical model of sporadic E layer critical frequency is constructed based on Constellation Observing System for Meteorology, Ionosphere, and Climate radio occultation data during 2007–2012. Model results show good accordance with ionosonde observations over 16 stations in different latitudes. In general, the model has a good performance in simulating the climate variation features of sporadic E layer intensity with averaged deviation 0.23 MHz which indicates a slight overestimation. Besides, spatial and temporal variations simulated by the model are also analyzed and show good agreement with known sporadic E layer features. However, the empirical may be only suitable for climate research at present and potential methods to improve the model will be investigated in the latter research.

Ionospheric Variability over the Brazilian Equatorial Region during the Minima Solar Cycles 1996 and 2009: Comparison between Observational Data and the IRI Model

The behavior of the Brazilian equatorial ionosphere during the solar minimum periods, 1996 and 2009, which cover the solar cycles 22/23 and 23/24, respectively, is investigated. For this, the F2 layer critical frequency (foF2) and peak height (hmF2) registered by a Digisonde operated at São Luis (2.33° S; 44° W) are carefully analyzed. The results show that the seasonal mean values of the foF2 and the hmF2 in the equinoxes and winter during 2009 were lower than in 1996. In the summer, an anomalous response to solar variability was observed. In this case, the hmF2 in 2009 is higher than in 1996 during a specific daytime interval. Besides that, it was verified that the prereversal enhancement of the zonal electric field (PRE) during the equinoxes in 2009 occurred a few minutes earlier than in 1996. Additionally, a Fast Fourier Transform (FFT) analysis was used to investigate the impacts of solar atmospheric tides (amplitude, diurnal, semidiurnal, and terdiurnal modes) on foF2 and hmF2 parameters with respect to its seasonality. Significant differences were observed between their values during the two minima, mainly in the amplitude of hmF2, which was higher in 1996 than in 2009 for all days analyzed. Moreover, the seasonality in the diurnal and semidiurnal modes for both periods presented an annual variability, while the terdiurnal mode exhibited annual and semiannual components. The results are compared with the International Reference Ionosphere (IRI) model, and the main differences between the observation and the model results are discussed in this work.

Modeling and Forecasting Ionospheric foF2 Variation in the Low Latitude Region during Low and High Solar Activity Years

Prediction of ionospheric parameters, such as ionospheric F2 layer critical frequency (foF2) at low latitude regions is of significant interest in understanding ionospheric variation effects on high-frequency communication and global navigation satellite system. Currently, deep learning algorithms have made a striking accomplishment in capturing ionospheric variability. In this paper, we use the state-of-the-art hybrid neural network combined with a quantile mechanism to predict foF2 parameter variations under low and high solar activity years (solar cycle-24) and space weather events. The hybrid neural network is composed of a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), in which CNN and BiLSTM networks extracted spatial and temporal features of ionospheric variation, respectively. The proposed method was trained and tested on 5 years (2009–2014) of ionospheric foF2 observation data from Advanced Digital Ionosonde located in Brisbane, Australia (27°53′S, 152°92′E). It is evident from the results that the proposed model performs better than International Reference Ionosphere 2016 (IRI-2016), long short-term memory (LSTM), and BiLSTM ionospheric prediction models. The proposed model extensively captured the variation in ionospheric foF2 feature, and better predicted it under two significant space weather events (29 September 2011 and 22 July 2012).

Performance Evaluation of Modified IRI2016 and Its Application to the 24 hr Ahead Forecast foF2 Mapping Over China

AbstractIn this paper, we have modified the International Reference Ionosphere model 2016 (IRI2016) with the Global Navigation Satellite System total electron content data observation in China by adjusting the ionospheric index (IG12) for given location and time. The capability of the modified IRI2016 to reproduce the F2 layer critical frequency foF2 is validated for high/low solar activity conditions and disturbed geomagnetic conditions for the time period 2014–2017 over low‐latitude ionosonde station located at Sanya in China. The analysis shows that the modified IRI2016 better reproduced the variability of the observed foF2 versus time and seasons. Also, the modified IRI2016 foF2 prediction exhibits lower root mean square error and higher correlation coefficients (R) over different solar activity periods, and significantly reduces the average percentage deviations (△foF2(%)) under enhanced geomagnetic activity periods. Subsequently, the 24 hr ahead forecast foF2 map over China constructed by the combination of the modified IRI2016 and the eXtreme Gradient Boosting algorithm is presented for the first time. The promising performance of the modified IRI2016 indicates that this combination method may be an effective way to predict the ionospheric parameters, though further validations are needed in the future work.

A regional ionospheric assimilation study with GPS and COSMIC measurements using a 3D-var algorithm (IDA4D)

The Ionospheric Data Assimilation Four-Dimension (IDA4D) is, developed by Bust et al. (2007) , a continuous time and three-dimension variational (3D-Var) algorithm that can optimally estimate the ionosphere from a model and measured data. In this study, we utilized three different data types into IDA4D for a regional ionosphere estimation: slant total electron contents (STEC) obtained from a Global Positioning System (GPS) network, NmF2 (peak electron density of the F2 layer) and STEC from Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) satellite. These multiple type data were assimilated into a background model, the International Reference Ionosphere (IRI – 2016). To evaluate the effect of each data type, the assimilation was performed on the following data combinations (cases): (1) GPS-STEC’s only; (2) GPS-STEC’s and NmF2′s from COSMIC; (3) GPS-STEC’s and COSMIC-STEC’s; and (4) all three data types. For each case computed foF2′s (F2 layer critical frequency) from IDA4D were compared with measured values from five ionosondes (I-Cheon, Jeju, Okinawa, Kokubunji, and Wakkanai) in the region of Korea and vicinities for the test periods of March, June, September and December in 2015. The comparison shows that computed foF2′s for all cases have higher correlation coefficients (CC) and less root mean square errors (RMSE) from measured values than IRI estimated values. In Cases 2, 3 and 4, IDA4D performance progressively improved in areas where GPS measurements were not covered but COSMIC STEC and NmF2 data were available. Furthermore, the IDA4D assimilation yields better results for electron density profiles and TEC values in comparison with observed values than the IRI model does. Thus, our study suggests that the IDA4D model with multiple data types can provide a reliable estimation of the regional ionosphere over the Korean Peninsula and vicinities.

The Prediction of Day‐to‐Day Occurrence of Low Latitude Ionospheric Strong Scintillation Using Gradient Boosting Algorithm

AbstractIonospheric scintillations caused by equatorial plasma bubbles (EPBs) can seriously affect various high technology systems based on Global Navigation Satellite System (GNSS) signals at equatorial and low latitudes. A reliable prediction of ionospheric scintillation occurrence is critical to relieve the effect. Using the long‐term ground‐based GNSS receiver and ionosonde data collected in the Brazilian longitude sector during 2012–2020, an ionospheric strong scintillation prediction model based on the gradient boosting algorithms extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and CatBoost is created and tested. It is for the first time that the XGBoost, LightGBM, and CatBoost are utilized to predict the day‐to‐day occurrence of regional ionospheric scintillation during post‐sunset hours. The relative importance of different parameters affecting EPB/scintillation occurrence for building the prediction model is examined. A comparison of daily scintillation occurrence from the modeled and observed results during 2014 (solar maximum) and 2020 (solar minimum) shows that the gradient boosting algorithms are effective for predicting strong scintillations over low latitude, with a prediction accuracy of ∼85%. The results suggest that the trained model with input of total electron content, equatorial F layer peak height and critical frequency before sunset could be well employed to predict the occurrence/nonoccurrence of intense scintillations over low latitude after sunset on a daily basis.

FoF2 Seasonal Prediction With IRI-2016 Over Quiet Activity at Dakar Station

This study deals with comparison between Dakar station ionospheric F2 layer critical frequency (foF2) data and both subroutines (CCIR and URSI) of IRI-2016 model predictions. Dakar station is located near the crest of the African Equatorial Ionization Anomaly (EIA) region. Comparisons are made for very quiet activity during the four seasons (spring, summer, autumn and winter) over both solar cycles 21 and 22. The quietest days per season are determined by taking the five days with the lowest aa. The relative standard deviation of modeled foF2 values is used to assess the quality of IRI model prediction. Model predictions are suitable with observed data by day than by night. The accuracy is better during spring season and poor during winter season. During all seasons, both model subroutines don’t express the signature of the observed vertical drift E×B. But they express an intense counter electrojet at the place of mean intensity or high electrojet.

Joint Ionosonde Studies of F2 Layer Critical Frequency Variations in the Ionosphere Over Kharkiv and Tromsø During Fall Equinox in Quiet and Disturbed Conditions

According to the results of joint ionosonde studies of variations in the ionospheric F2 layer critical frequency over Kharkiv and Tromsø during low solar activity for fall equinox on September 22 – 24, 2020, the features of foF2 variations in middle and low latitudes were investigated for magnetically quiet and magnetically disturbed conditions. On the magnetically quiet day of September 22, 2020, the foF2 values over Kharkiv were found to exceed the foF2 values over Tromsø for the entire time interval of joint observations 02:45 - 16:45 UT. Both over Tromsø and over Kharkiv, a rapid increase in foF2 to its local maximum value was observed after the sunrise. Quasi-periodic variations in foF2 were revealed at high latitudes, which had lower amplitude compared to variations in foF2 over Kharkiv. Over both measuring sites, a pre-sunset local maximum in foF2 was observed. During magnetically disturbed conditions over Tromsø and Kharkiv, quasi-periodic fluctuations in foF2 were observed after the sunrise. Oscillations over Tromsø had lower amplitude than over Kharkiv, and were almost completely suppressed after the onset of a strong magnetic disturbance at high latitudes on September 23, 2020. The foF2 values over Tromsø exceeded its values over Kharkiv in a time interval of 10:45 – 12:15 UT. Comparison of the time variation of foF2 over Tromso on a magnetically quiet day, September 22, 2020, and on a magnetically disturbed day, September 23, 2020, showed that the foF2 value for September 23, 2020 from 10:15 to 15:00 UT exceeded the foF2 values for the same period on September 22, 2020. Comparison of the temporal variations in foF2 over Kharkiv on a magnetically quiet day, September 22, 2020, and on a magnetically disturbed day, September 24, 2020, showed that the foF2 value for September 24, 2020 exceeded its value for September 22, 2020 from 03:00 to 04:45 UT and from 07:00 to 13:00 UT. Magnetic disturbances were found to cause a rapid increase in foF2 values both over Kharkiv and Tromsø, which exceeded foF2 values under magnetically quiet conditions, and also led to a significant increase in the relative amplitudes of traveling ionospheric disturbances over Kharkiv.

Modeling Center‐of‐Mass of the Ionosphere From the Slab‐Thickness

AbstractThe present study explores the center‐of‐mass (Hc) of the ionosphere as the effective ionospheric varying shell height (VSH). We presents global ionospheric maps GIM‐Hc produced with IRI‐Plas model by assimilating the instant GIM‐TEC maps provided by JPL from 1994 to present which allows obtaining global maps of the F2 layer critical frequency, GIM‐foF2 (or NmF2) and peak height, GIM‐hmF2. Ratio TEC/NmF2 represents the slab‐thickness model of the ionosphere, GIM‐τ, fitted to foF2, hmF2 peak at each cell of a map. The slab‐thickness τ is for the first time tied to hmF2 peak height with its components τbot below hmF2 and topside τtop. Equations for evaluating Hc with IRI‐Plas and NeQuick models are derived from Ne(h) profile complemented with the total electron content—height profile TEC(h) from the bottom boundary of the ionosphere (65–80 km over the Earth) to varying altitude h up to 20,200 km (GPS orbit). The position of Hc depends on the altitude range selected at the ionosphere and plasmasphere. We determine Hc from Ne(h) and TEC(h) profile within the borders of τ from the bottom side (hmF2 − τbot) to topside (hmF2 + τtop). Regression linear model of Hc variation with hmF2 is derived which allows estimate of Hc from the F2 layer peak height hmF2. Statistical characteristics of GIM‐Hc maps can serve for validation and updating the effective shell height with Hc parameter varying over the globe for improved vertical TEC evaluation from the slant TEC observations.

An Evaluation of Spire Radio Occultation Data in Assimilative Ionospheric Model GPSII and Validation by Ionosonde Measurements

AbstractThis paper presents a comprehensive analysis of results obtained using NWRA’s assimilative ionospheric model GPSII when it is driven by Spire Global, Inc.’s global navigation satellite system ‐ radio occultation (GNSS‐RO) measurements. Results of the assimilative model are validated using the database of Digisonde and Dynasonde ionograms. A week’s worth of dual‐frequency phase data was collected from Spire’s constellation of low‐Earth orbiting micro‐satellites carrying GNSS receivers and assimilated into GPSII. A validation study of GNSS‐RO measurements was performed in four geographical regions. GPSII operation with the data was evaluated and the results were validated against independent ionospheric measurements. Ground‐based ionosondes were employed in diagnosing the accuracy of the derived models; we studied the differences between the F2 peak parameters (the F2 layer critical frequency, , and the peak height of the F2 layer, ) derived from ionograms and those computed with GPSII. For the 1,491 validation events used in this study, the magnitude of the deviation of the GPSII‐predicted at an ionosonde location from the corresponding ionosonde‐observed value was found on average to be 0.608 MHz (with a median of 0.461 MHz) and the magnitude of the deviation of the GPSII‐predicted at an ionosonde location from the corresponding ionosonde‐observed value was found to be on average 22.9 km (with a median value of 18.0 km). Median GPSII validation errors for are a factor of four smaller than corresponding errors for IRI, while GPSII errors are a factors of two smaller than those for IRI. The analysis showed that Spire’s TEC data was both compatible for ingestion into GPSII and that the assimilation of the data improved the comparison to ground‐based ionosondes.

A Bidirectional Long Short-Term Memory-Based Ionospheric foF2 and hmF2 Models for a Single Station in the Low Latitude Region

Equatorial electrojet (EEJ) and the subsequent development of equatorial ionization anomaly (EIA) are responsible for the highly complex and nonlinear variability nature of the ionosphere. Prediction of ionospheric parameters like Ionospheric F2 layer Critical frequency (foF2) and peak height (hmF2) feature at low latitude regions is of significant interest in understanding the ionospheric weather effects on communication and navigation systems. The role of artificial intelligence-based machine learning algorithms is successful in the prediction of ionospheric variability. In this letter, a deep learning model based on Bidirectional long short-term memory (Bi-LSTM) technique is implemented for predicting foF2 and hmF2 parameters. The Bi-LSTM method was trained and tested on one-year (2015) ionospheric foF2 and hmF2 data from Canadian Advanced Digital Ionosonde (CADI) located at Hyderabad, India (17.47 °N, 78.57 °E). Bi-LSTM model captures time sequence processing features using past and present foF2 and hmF2 data samples. It is evident from the results that the Bi-LSTM model performs better than long short-term memory (LSTM), neural networks (NNs), and International Reference Ionosphere (IRI) 2016 models in predicting foF2 and hmF2 values. The performance of the Bi-LSTM model tested and found to better predict ionospheric foF2 and hmF2 features for two significant geomagnetic storms occurred in the year 2015 (March and June).

First Look at a Geomagnetic Storm With Santa Maria Digisonde Data: F Region Responses and Comparisons Over the American Sector

AbstractSanta Maria Digisonde data are used for the first time to investigate the F region behavior during a geomagnetic storm. The August 25, 2018 storm is considered complex due to the incidence of two Interplanetary Coronal Mass Ejections and a High‐Speed Solar Wind Stream (HSS). The F 2 layer critical frequency (f o F 2) and its peak height (h m F 2) collected over Santa Maria, near the center of the South American Magnetic Anomaly (SAMA), are compared with data collected from Digisondes installed in the Northern (NH) and Southern (SH) Hemispheres in the American sector. The deviation of f o F 2 (Df o F 2) and h m F 2 (Dh m F 2) are used to quantify the ionospheric storm effects. Different F region responses were observed during the main phase (August 25–26), which is attributed to the traveling ionospheric disturbances and disturbed eastward electric field during nighttime. The F region responses became highly asymmetric between the NH and SH at the early recovery phase (RP, August 26) due to a combination of physical mechanisms. The observed asymmetries are interpreted as caused by modifications in the thermospheric composition and a rapid electrodynamic mechanism. The persistent enhanced thermospheric [O]/[N2] ratio observed from August 27 to 29 combined with the increased solar wind speed induced by the HSS and IMF B z fluctuations seem to be effective in causing the positive ionospheric storm effects and the shift of the Equatorial Ionization Anomaly crest to higher than typical latitudes. Consequently, the most dramatic positive ionospheric storm during the RP occurred over Santa Maria (∼120%).

Simultaneous ionosonde investigations of the ionospheric F2 layer critical frequency and peak height at both ends of the geomagnetic tube

Based on the results of simultaneous ionosonde observations during low solar and weak magnetic activities, a coupling was found between diurnal and quasi-periodic variations in ionospheric parameters over magnetically conjugated regions, where the Ukrainian Antarctic Station (UAS) and Millstone Hill Observatory are located. A significant impact of the summer hemisphere on the nighttime variations of the F2 layer critical frequency foF2 in the magnetically conjugated region in the winter hemisphere was found. The most characteristic manifestation of this impact is the control of foF2 variations over the UAS not by the local sunset (sunrise), but by the sunset (sunrise) over Millstone Hill. It was found that the sunset over Millstone Hill leads to an increase in foF2 over the UAS, while the sunrise leads to a decrease in foF2 with a subsequent sharp increase. Both phenomena are associated with changes in the photoelectron flux from the northern hemisphere, corresponding changes in the electron temperature in the ionosphere above the UAS and the effect of these changes on the compression or rarefaction of the ionospheric plasma and changes in the plasmaspheric fluxes of H + ions. It was shown that the transition from nighttime to daytime conditions over both observation points was characterized by a significant decrease in the F2 layer peak height, and the difference in the values of this ionospheric parameter over Millstone Hill and UAS at night is due to seasonal differences in the thermospheric circulation and the difference in the behavior of the ionospheric parameters in the Northern and Southern hemispheres. Manifestations of atmospheric gravity waves, caused by the passage of local sunrise terminators, as traveling ionospheric disturbances with periods of about 90 and 75 – 120 mins over Millstone Hill and UAS, respectively, were found. These waves were most likely generated in the region located between the ionospheric F1 and F2 layers, where the sharp gradients in the electron and ion densities occur during changes in the intensity of solar radiation. It is confirmed that wave disturbances in atmospheric and ionospheric parameters can be transferred between magnetically conjugated regions by slow magnetohydrodynamic waves generated both at the heights of the ionospheric dynamo region due to the modulation of atmospheric and ionospheric parameters by atmospheric waves and the occurrence of external currents, and at the top of the plasmaspheric tube, where sharp plasma compression and heating or rarefaction and cooling occur during the passage of the solar terminator. Keywords: the ionosphere, F2 region, ionosonde measurements, geomagnetic field tube, magnetoconjugate region coupling, atmospheric gravity waves, traveling ionospheric disturbances, generation of slow magnetohydrodynamic waves