We found the signatures of the multiple prompt penetration electric fields (PPEF) and the disturbance dynamo (DD) electric field having impacts on the East Asian sector ionosphere along the meridional chain thoroughly from the equator, low-mid to high latitudes during the space weather event of 03-05 November 2021. The observation is made on GPS-TEC, digisonde, and magnetometer stations. In the main phase of the storm, intense modulations of VTEC (vertical total electron content) and foF2 (critical frequency) are observed as coherently fluctuating with IEF (interplanetary electric field) and IMF Bz reorientations. It is diagnosed that the oscillations in the DP2 (disturbance polar current 2) current system directly penetrate meridianally from high to equatorial latitudes, leading to the significant changes in ionospheric electrodynamics that governs the density fluctuations. The wavelet spectra of VTEC, foF2, h’F (virtual height), H-components and IEF give a result of common and dominant periodicity occurring at ~1hr. This result suggests that the wavelike oscillations of VTEC and foF2 and H component are associated with PP electric fields.

This study presents ultra-low frequency (ULF) Pc5 discrete spectrum simultaneously observed in the magnetosphere and high- to low-latitude ionospheres near noon hours (~10-14 MLT) during the recovery phase of geomagnetic storm on November 4, 2021. During the recovery phase, magnetospheric toroidal mode oscillations (GOES-16 Bn) appeared according to solar wind dynamic pressure enhancements after GOES Bp and Be (poloidal mode) oscillations precede during high solar wind speeds. When Bn oscillates, the ionospheric line-of-sight (LOS) velocity and echo power oscillate at the same discrete frequencies of 1.7 and 2.2 mHz (9.7 and 7.5 min), observed by Super Dual Auroral Radar Network (SuperDARN) at Saskatoon (eastward LOS). The period of negative LOS velocity (away from the radar) for 7.5 min or 9.7 min corresponds to echo power increase. This signifies that both the ionospheric density and poleward convection velocity increase are driven by the periodic forcing of the convection electric field and energetic electron precipitation. The same frequency pulsations have also been observed in the geomagnetic field (H-component) and Global Positioning System (GPS) total electron content (TEC) from high- to low-latitude ionosphere. The oscillation frequency of the H-component is consistently preserved at 1.7 mHz (9.7 min) down to low latitudes. The Pc5 oscillations at high to low latitudes can be attributed to toroidal mode Alfven waves and the compressional mode propagating across magnetic field lines as well as the fast magnetosonic waveguide mode at work by the solar wind dynamic pressure enhancements at high solar wind speeds.

Using advanced meteor radar network observations along with ERA5 data, we report observational evidence of polar to tropical mesospheric teleconnections during the 2018 major sudden stratosphere warming (SSW) event in the northern hemisphere. A peak SSW on February 14, 2018, characterized by a ~ 45 K rise in polar stratosphere temperature and a zonal wind reversal of ~ (–25) m/s at 60°N and 10 hPa, is observed. In the tropical lower mesosphere, a maximum zonal wind reversal (–24 m/s) compared with that identified in the extra-tropical regions was observed. Moreover, a time delay in the wind reversal between the tropical/polar stations and the mid-latitudes was detected. The wind reversal in the mesosphere is due to the propagation of dominant intra-seasonal oscillations (ISOs) of 30–60-days and the presence and superposition of 8-day period planetary waves (PWs). The ISOs phase propagation is observed from the high- to low-latitudes (60°N to 20°N) in contrast to 8-day PWs phase propagation, indicating the change in the meridional propagation of winds during SSW. However, the superposition of dominant ISOs and weak 8-day PWs could be responsible for the delay of the wind reversal in the tropical mesosphere. Therefore, this study has strong implications for understanding the reversed (polar to tropical) mesospheric meridional circulation during SSW.

In our previous study (Moon et al., 2020), we developed a Long Short Term Memory (LSTM) deep-learning model for geomagnetic quiet days to perform effective long-term predictions for the regional ionosphere. However, their model could not predict geomagnetic storm days effectively at all. This study developed an LSTM model suitable for geomagnetic storms using the new training data set and re-designing input parameters and hyper-parameters. We collected 131 days of geomagnetic storm cases from 1 January 2009 to 31 December 2019, and obtained the IMF Bz, Dst, Kp, and AE indices related to the geomagnetic storm corresponding to each storm date. These indices and F2 parameters of Jeju ionosonde (33.43˚N, 126.30˚E) were used as input parameters for the LSTM model. To test and verify the predictive performance and the usability of the LSTM model for geomagnetic storms developed in this manner, we created and diagnosed the 0.5, 1, 2, 3, 6, 12, and 24-hour predictive LSTM models. According to the results of this study, the LSTM storm model for 24-hour developed in this study achieved a predictive performance during the geomagnetic storms about 32% (10%), 34% (17%), and 37% (5%) better in RMSE of foF2 (hmF2) than the LSTM quiet model (Moon et al., 2020), SAMI2, and IRI-2016 models. We propose that the short-term predictions of less than 3 hours are sufficiently competitive compared to other traditional ionospheric models. Thus, this study suggests that our model can be used for short-term prediction and monitoring of the regional mid-latitude ionosphere.

We analyzed OH airglow images observed from an all-sky camera at King Sejong Station, Antarctica for the period of 2012–2016. Using M-transform method, 2D-power spectra of short period waves (< 1 hr) were obtained from 107 image sequences. The power spectral densities evidently show that the mesospheric wave activity is the strongest during winter. We also constructed climatological wind blocking diagrams using horizontal winds obtained from MERRA-2 for the altitudes of = 10–64 km, and from KSS meteor radar data for = 80–90 km. The wind blocking diagrams are negatively matched with the dominant propagating directions of the observed slow speed waves (< 30 m/s), providing the graphical evidence of wind filtering effects. However, there are significant eastward waves in winter and strong south-eastward waves in spring that are not blocked by the stratospheric winds. We speculate that these waves may be generated from the upper stratosphere or mesosphere.

This paper presents a study on the possibility of predicting the regional ionosphere at mid-latitude by assimilating the predicted ionospheric parameters from a neural network (NN) model into the SAMI2 model. The NN model was constructed from the dataset of Jeju ionosonde (33.43˚N, 126.30˚E) for the period of 1 Jan 2011 to 31 Dec 2015 by using the long-short term memory (LSTM) algorithm. The NN model provides 24-hour prediction of the peak density (NmF2) and peak height (hmF2) of the F2 layer over Jeju. The predicted NmF2 and hmF2 were used to compute two ionospheric drivers (total ion density and effective neutral meridional wind), which were assimilated into the SAMI2 model. The SAMI2-LSTM model estimates the ionospheric conditions over the mid-latitude region around Jeju on the same geomagnetic meridional plane. We evaluate the performance of the SAMI2-LSTM by comparing predicted NmF2 and hmF2 values with measured values during the geomagnetic quiet and storm periods. The root mean square error values of NmF2 (hmF2) from Jeju ionosonde measurements are lower by 31%, 22%, and 29% (35%, 24%, and 17%) than those of the SAMI2, TIEGCM, and IRI-2016 models during the geomagnetic quiet periods. However, during the geomagnetic storm periods, the performance of SAMI2-LSTM, like all other models, is significantly worse than during the quiet periods. We discuss the advantage and possible improving strategy on the predictability of the regional mid-latitude ionosphere by utilizing data-assimilated physics models and deep-learning techniques together.

Broad plasma depletions (BPDs) are bubble-like plasma depletions in the equatorial F region whose longitudinal widths (> 4 degree) are greater than those of regular bubbles. Their occurrence in satellite observations is understood in terms of the uplift of the ionosphere; BPDs are observed when satellites pass through the bottomside of bubbles. However, a merger of bubbles is also suggested as the cause of BPDs. We investigate the origin of BPDs by examining the occurrence climatology of BPDs and its association with vertical plasma motion. Our preliminary results derived from the C/NOFS observations in 2008–2012 show that BPDs occur more frequently during lower solar activity, during higher magnetic activity, and at lower altitudes. BPDs during solar maximum and minimum periods show different behavior. BPDs during solar maximum period occur frequently at premidnight and during the equinoxes and December solstices (for highly geomagnetically disturbed periods). On the contrary, BPDs during the solar minimum period occur predominantly at postmidnight and during the June solstices. The occurrence rates of postmidnight BPDs are positively correlated with AE index and are inversely correlated with 10.7 cm solar radio flux. Low solar activity creates favorable conditions for generating BPDs by thinning the F region. At the solar minimum, the density of the F region’s bottomside changes significantly even with slight altitude shifts, which can be recognized as BPDs. When a geomagnetic disturbance occurs, the eastward electric field can be enhanced at the equatorial F region, and the entire F layer can move upward.