The ionospheric equivalent slab thickness (EST, also named τ) is defined as the ratio of the total electron content (TEC) to the F2-layer peak electron density (NmF2), and it is a significant parameter representative of the ionosphere. This paper presents a comprehensive statistical study of the ionospheric slab thickness at Yakutsk, located at the high latitude of East Asia, using the GPS-TEC and ionosonde NmF2 data for the years 2010–2017. The results show that the τ has different diurnal and seasonal variations in high- and low-solar-activity years, and the τ is greatest in the winter, followed by the equinox, and it is smallest in the summer in both high- and low-solar-activity years, except during the noontime of low-solar-activity years. Specifically, the τ in inter of high-solar-activity year shows an approximate single peak pattern with the peak around noon, while it displays a double-peak pattern with the pre-sunrise and sunset peaks in winter of the low-solar-activity years. Moreover, the τ in the summer and equinox have smaller diurnal variations, and there are peaks with different magnitudes during the sunrise and post-sunset periods. The mainly diurnal variation of τ in different seasons of high- and low-solar-activity years can be explained within the framework of relative variation of TEC and NmF2 during the corresponding period. By defining the disturbance index (DI), which can visually assess the relationship between instantaneous values and the median, we found that the geomagnetic storm would enhance the τ at Yakutsk. An example on 7 June 2013 is also presented to analyze the physical mechanism. It should be due to the intense particle precipitation and expanded plasma convection electric field during the storm at high-latitude Yakutsk station. The results would improve the current understanding of climatological and storm-time behavior of τ at high latitudes in East Asia.

Spread-F (SF) is one of the most important types of the ionospheric irregularities as it causes ionospheric scintillation which can severely affect the performance and reliability of communication, navigation, and radar systems. The ionosonde provides the most effective and economical way to study the ionosphere and SF. However, the manual identification of SF from an ionogram is boring and hard work. To automatically identify SF on the ionogram and extend the study of SF into the middle and low latitudes of East Asia, this paper presents a statistical analysis of SF in this region, based on the naïve Bayesian classifier. The results showed that the accuracy of automatic identification reached up to 97% on both the validation datasets and test datasets composed of Mohe, I-Cheon, Jeju, Wuhan, and Sanya ionograms, suggesting that it is a promising way to automatically identify SF on ionograms. Based on the classification results, the statistical analysis shows that SF has a complicated morphology in the middle and low latitudes of East Asia. Specifically, there is a peak of occurrence of SF in the summer in I-Cheon, Jeju, Sanya, and Wuhan; however, the Mohe station has the highest occurrence rate of SF in December. The different seasonal variations of SF might be due to the different geographic local conditions, such as the inland-coastal differences and formation mechanism differences at these latitudes. Moreover, SF occurs more easily in the post-midnight hours when compared with the pre-midnight period in these stations, which is consistent with the previous results. Furthermore, this paper extracts the frequency SF (FSF) index and range SF (RSF) index to characterize the features of SF. The results shows that the most intense FSF/RSF appeared in the height range of 220–300 km/1–7 MHz in these stations, although there are different magnitude extensions on different season in these regions. In particular, strong spread-F (SSF) reached its maximum at the equinox at Sanya, confirming the frequent SSF occurrence at the equinox at the equator and low latitudes. These results would be helpful for understanding the characteristics of SF in East Asia.

E-region field-aligned irregularities (FAIs) are a hot topic in space research, since electromagnetic signal propagation through ionospheric irregularities can undergo sporadic enhancements and fading known as ionospheric scintillation, which could severely affect communication, navigation, and radar systems. However, the range resolution of very-high-frequency (VHF) radars, which is widely used to observe E-region FAIs, is limited due to its bandwidth. As a technology that is widely used in atmosphere radars to improve the range resolution of pulsed radars by transmitting multiple frequencies, this paper employed the multifrequency radar imaging (RIM) technique in a Wuhan VHF radar. The results showed that the range resolution of E-region FAIs greatly improved when compared with the results in traditional single-frequency mode, and that finer structures of E-region FAIs can be obtained. Specifically, the imaging results in multifrequency mode show that E-region FAIs demonstrate an overall descending trend at night, and it could be related to the tides or gravity waves due to their downward phase velocities or even driven by downwind shear. In addition, typical quasi-periodic (QP) echoes with a time period of around 10 min could be clearly seen using the RIM technique, and the features of the echoes suggest that they could be modulated by gravity waves. Furthermore, the RIM technique can be used to obtain the fine structure of irregularities within a short time period, and the hierarchical structure of E-region FAIs can be easily found. Therefore, the multifrequency imaging RIM technique is suitable for observing E-region FAIs and their evolution, as well as for identifying the different layers of E-region FAIs. Combined with the RIM technique, a VHF radar provides an effective and promising way to observe the structure of E-region FAIs in more detail to study the physical mechanism behind the formation and evolution of ionospheric E-region irregularities.

In this study, the temporal and spatial distribution characteristics of ionospheric scintillation in the East Asian sector are statistically analyzed based on S4 data provided by the COSMIC-1 occultation dataset and solar–terrestrial spatial environment parameters from 2007 to 2018. The results show that scintillation activity has an obvious distribution pattern with local time: the frequency gradually increases from 17:00 in the evening, with the peak concentrated at 22:00–01:00 at night; in terms of seasonal variation, scintillation activity is highest in spring and fall, followed by summer, and lowest in winter; and, regarding annual variation, it is highly correlated with the solar activity. Further analyses show that scintillation activity is strongly correlated with geomagnetic activity. On this basis, this study constructs a two-layer LSTM deep learning model based on weighted regression to realize S4 numerical forecasting for the next 1 h in the middle- and low-latitude regions of China, using F10.7, Kp, Dst, sunspot number, solar wind vertical velocity, and historical S4 values as inputs. The model demonstrates robust predictive performance on the validation dataset containing 8760 samples, with a mean squared error of 0.00546 and an absolute error that is distributed within the interval [−0.2, 0.2] 98% of the time, indicating strong accuracy and robustness. These results suggest that the proposed model provides a high-precision tool for ionospheric scintillation warning.