https://repository.kopri.re.kr/handle/201206/15761 2026-03-05T08:33:39Z 2026-03-05T08:33:39Z Back, Junho Jee, Geonhwa Kwon, Hyuck-Jin Kim, Khan-Hyuk Lee, Changsup Ham, Young-Bae Zabotin, Nikolay https://repository.kopri.re.kr/handle/201206/16018 2025-10-29T04:46:50Z 2025-06-01T00:00:00Z

Title: Classification of Ionograms Obtained from Vertical Incidence Pulsed Ionospheric Radar (VIPIR)/Dynasonde Ionospheric Radar at Jang Bogo Station, Antarctica Authors: Back, Junho; Jee, Geonhwa; Kwon, Hyuck-Jin; Kim, Khan-Hyuk; Lee, Changsup; Ham, Young-Bae; Zabotin, Nikolay Abstract: The electron density profiles produced from the ionospheric sounding system are traditionally estimated by the inversion procedure based on the image analysis of the observed ionograms. Jang Bogo Vertical Incidence Pulsed Ionospheric Radar (VIPIR) with Dynasonde (hereafter, JVD), however, uses the three-dimensional electron density inversion approach named “NeXtYZ” to produce ionospheric density, ion velocity, and tilt of the ionization in the bottomside ionosphere based on the list of detected radio echoes with their physical parameters. Sometimes, the resulting density profiles can be erroneous, not reflecting real ionosphere, probably due to severely disturbed ionosphere in the polar region. In this study, the automatic classification procedure of the estimated electron density profiles is developed to filter out unusable data for the 5-year period from 2017 to 2021. The ionograms are classified into four categories: ‘Unavailable’, ‘Sporadic E’, ‘Needs Reprocessing’, and ‘Available’. It is found that approximately 50% of ionograms are evaluated to be reasonable with proper electron density profiles and about 35% of them tend to be affected by sporadic-E like structures, blocking the F-region ionosphere to be observed. It should be noted that the sporadic-E like structures in the polar ionosphere seems to be main obstacles for the ionospheric sounding observation of the F-region ionosphere. Only less than 10% of ionograms are classified as a reprocessing type which needs to be reprocessed. Finally, no echoes are recognized by Dynasonde analysis for about 5% of ionograms. The reprocessing and/or unavailable types might be associated with auroral precipitations that disturbs the ionosphere in the polar region.

2025-06-01T00:00:00Z Jee, Geonhwa Shim, J. S. Song, I. -S. Kwak, Y. -s. Tsagouri, I. Goncharenko, L. Singh, D. Rastaetter, L. Yue, J. Chou, M. Bilitza, D. Codrescu, M. Fedrizzi, M. Fuller-Rowell, T. J. https://repository.kopri.re.kr/handle/201206/16022 2025-08-22T00:34:01Z 2025-01-01T00:00:00Z

Title: Assessment of Current Capabilities in Modeling the Ionospheric Climatology for Space Weather Applications: foF2 and hmF2-II Authors: Jee, Geonhwa; Shim, J. S.; Song, I. -S.; Kwak, Y. -s.; Tsagouri, I.; Goncharenko, L.; Singh, D.; Rastaetter, L.; Yue, J.; Chou, M.; Bilitza, D.; Codrescu, M.; Fedrizzi, M.; Fuller-Rowell, T. J. Abstract: We expand the assessment study of modeling capabilities in the prediction of foF2 and hmF2 for the ionospheric climatology (Tsagouri et al., 2018, ) by using updated empirical (IRI and MIT Empirical model) and physics-based models (CTIPe, WACCM-X, and TIE-GCM) as well as the additional observations in the southern hemisphere. Monthly medians of foF2 and hmF2 are considered to evaluate the model performance for the entire year of 2012. For quantitative evaluation, we employ several metrics including the correlation coefficient (R), coefficient of determination (R-2), root-mean square error (RMSE), mean error (ME), and mean relative error (MRE). The linear regression analysis shows that the empirical models perform much better than physics-based models for foF2 but to a lesser degree for hmF2. There are negligible hemispheric differences in the predictions from empirical models. All the physics-based models show relatively good correlations with the observations for foF2 in the northern hemisphere compared to the southern hemisphere, but the hemispheric differences are small for hmF2. The results of the study indicate that recent versions of empirical models tend to perform better than old versions of the models, but this is not always true for physics-based models.

2025-01-01T00:00:00Z