Ionosphere over Ukrainian Antarctic Akademik Vernadsky station under minima of solar and magnetic activities, and daily insolation: case study for June 2019

et al. 2022

UAJ

The paper presents the results of ionospheric observations performed over the Ukrainian Antarctic Akademik Vernadsky station and Millstone Hill (USA). Ionospheric parameters such as peak electron density and height (hmF2 and NmF2) in October 2021 are shown and discussed. The results of the comparative analysis between observations and predictions of the International Reference Ionosphere 2016 (IRI-2016) model are presented. The main objectives of this work are an investigation of the ionosphere response to space weather effects in the Northern and Southern hemispheres in the American longitudinal sectorusing ionosondes located at the Vernadsky station and near the magnetically conjugate region – Millstone Hill, and a comparison of observations with the model. The F2-layer peak height was calculated from ionograms obtained by ionosonde using subsequent electron density profile inversion. Diurnal variations of hmF2 and NmF2 were calculated using a set of sub-models of the IRI-2016 model for comparison with experimental results. A strong negative response of the ionosphere to the moderate geomagnetic storm on October 12, 2021 was revealed over the Vernadsky station and Millstone Hill. During October 21–31, 2021, the gradual night-to-night increase in NmF2 (by a factor of ~2) was observed over the Vernadsky station. It was found that the IRI hmF2 sub-models (SHU-2015 and AMTB-2013) provide a relatively good agreement with the observed variations of hmF2 in the daytime and nighttime for almost the entire investigated period over both the Vernadsky station and Millstone Hill. The largest deviations for both IRI hmF2 sub-models occurred during the nighttime of geomagnetically disturbed periods. The IRI NmF2 submodels (URSI and CCIR) generally agree with the observations. However, observations and model predictions differ somewhat in the geomagnetically disturbed periods. According to the results of the standard deviation calculations, it cannot be concluded that any of the IRI-2016 sub-models is better than the others. The hypotheses on the possible reasons for the differences in the modeled and observed variations of hmF2 and NmF2 are proposed and discussed in the frame of well-known ionospheric storms’ mechanisms. The results obtained in this paper demonstrate the peculiarities of the ionosphere in different hemispheres of the American longitude sector under geomagnetically quiet and disturbed conditions and provide one more validation of the modern empirical international reference models of the ionosphere.

Observation of the ionosphere by ionosondes in the Southern and Northern hemispheres during geospace events in October 2021

Reznychenko

et al. 2022

UAJ

An artificial neural network for analysis of ionograms obtained by ionosonde at the Ukrainian Antarctic Akademik Vernadsky station

Shulha

et al. 2020

UAJ

The article presents the developed artificial neural network for F2 ionosphere layer traces scaling on ionograms obtained using the IPS-42 ionosonde installed at the Ukrainian Antarctic Akademik Vernadsky station. The parameters of the IPS-42 ionosonde and the features of the data obtained with it, in particular the format of the output files, are presented. The advantages of using an artificial neural network for identification of traces on ionograms are demonstrated. Usually, an automatic scaling of the ionograms requires a lot of machine time however implementation of an artificial neural network speeds up computations significantly allowing to process incoming ionograms even in the real time mode. The choice of architecture of an artificial neural network is substantiated. The U-Net architecture was chosen. The method of creating and training the neural network is described. The artificial neural network development process included choosing the number of layers, types of activation functions, optimization method and input layer size. Software developed was written in Python programming language with use of the Keras library. Examples of data used for training of the artificial neural network are shown. The results of testing an artificial neural network are presented. The data obtained with the artificial neural network are compared with the results of manual processing of ionograms. Data for training the artificial neural network were obtained in March, 2017 using the IPS-42 ionosonde installed at the Ukrainian Antarctic Akademik Vernadsky station; data for testing were obtained in 2017 and 2020. The developed artificial neural network has minor flaws but they are easily eliminated by retraining the network on a more representative dataset (obtained in various years and seasons). The general results of testing indicate good prospects in further developing this artificial neural network and software for working with it.

Investigation of the ionosphere over Antarctica under quiet space weather conditions: results of vertical sounding of the ionosphere September 14–24, 2020

Shulha

et al. 2020

PhAG

We present observational results of variations in the ionospheric parameters hmF2 and NmF2 over the Ukrainian Antarctic station “Akademik Vernadsky” for magnetically quiet conditions. The results of comparative analysis of observational data and the International Reference Ionosphere-2016 model predictions are presented. The main objective of this study is to investigate the temporal variations of two key ionospheric parameters – the F2 layer peak height and electron density – during very quiet space weather conditions using data of vertical sounding of the ionosphere obtained over the Ukrainian Antarctic station “Akademik Vernadsky” and comparison the observation results with model values. Methods: The temporal variations of the F2 layer peak height and electron density were calculated from ionograms obtained with ionosonde installed at the Ukrainian Antarctic station “Akademik Vernadsky” with subsequent electron density profile inversion. Diurnal variations of hmF2 and NmF2 were calculated using a set of sub-models of the IRI-2016 model for comparison with results of observational studies. Results: We found that for the Antarctic region option of IRI-2016 model for the F2 layer peak height SHU-2015 provides a better fit for hmF2 through the investigated period compare to the AMTB-2013 model predictions. Electron density models (URSI, CCIR) generally well reproduce the observed variations of NmF2 during periods of absence non-standard manifestations of space weather, which are possible for quiet conditions too. Hypotheses regarding the possible reasons for experimental and model differences in variations of NmF2 are discussed. The analysis of effect of geomagnetic storm on September 24, 2020 on NmF2 variations was carried out. Conclusions: The obtained results demonstrate peculiarities of the state of the ionosphere-plasmasphere system over Antarctica under very quiet space weather conditions and provide evaluation of predictive capabilities of modern international reference ionosphere models. New knowledge about the features of electron density variations in the ionosphere for magnetically quiet conditions over the Antarctic region has practical value for specialists which are engaged in the study of the near-Earth space environment, in particular, at high latitudes, and also work on correction of global ionospheric models. Keywords: electron density, F2 layer peak height, ionosonde, quiet space weather, models of the ionosphere, downward plasma flux