In this paper, we present observational evidence for the trans-polar propagation of large-scale Traveling Ionospheric Disturbances (TIDs) from their nightside source region to the dayside. On 13 February 2001, the 32 m dish of EISCAT Svalbard Radar (ESR) was directing toward the geomagnetic pole at low elevation (30°) during the interval 06:00–12:00 UT (MLT ≈ UT + 3 h), providing an excellent opportunity to monitor the ionosphere F-region over the polar cap. The TIDs were first detected by the ESR over the dayside north polar cap, propagating equatorward, and were subsequently seen by the mainland UHF radar at auroral latitudes around geomagnetic local noon. The propagation properties of the observed ionization waves suggest the presence of a moderately large-scale TIDs, propagating across the northern polar cap from the night-time auroral source during substorm conditions. Our results agree with the theoretical simulations by Balthazor and Moffett (1999) in which poleward-propagating large-scale traveling atmospheric disturbances were found to be self-consistently driven by enhancements in auroral heating.

In this paper, climatological features of the polar F2-region electron density (N_e) are investigated by means of statistical analysis using long-term observations from the European Incoherent Scatter UHF radar (called EISCAT in the following) and the EISCAT Svalbard radar (ESR) during periods of quiet to moderate geomagnetic activity. Field-aligned measurements by the EISCAT and ESR radars operating in CP-1 and CP-2 modes are used in this study, covering the years 1988–1999 for EISCAT and 1999–2003 for ESR. The data are sorted by season (equinox, summer and winter) and solar cycle phase (maximum, minimum, rising and falling). Some novel and interesting results are presented as follows: (1) The well-known winter anomaly is evident during the solar maximum at EISCAT, but it dies out at the latitude of the ESR; (2) The daytime peaks of N_e at EISCAT for all seasons during solar maximum lag about 1–2 h behind those at ESR, with altitudes about 10–30 km lower. (3) In addition to the daytime peak, it is revealed that there is another peak just before magnetic midnight at ESR around solar maximum, especially in winter and at equinox. The day-time ionization peak around magnetic noon observed by ESR can be attributed to soft particle precipitation in the cusp region, whereas the pre-midnight N_e maximum seems likely to be closely related to substorm events which frequently break out during that time sector, in particular for the winter case. (4) Semiannual variations are found at EISCAT during solar minimum and the falling phase of the solar cycle; at the rising phase, however, the EISCAT observations show no obvious seasonal variations.

Few-shot object detection (FSOD) has attracted significant research attention in remote sensing due to its potential to reduce reliance on large annotated datasets. However, two challenges remain in this area: (1) axis-aligned proposals, which can result in misalignment for arbitrarily oriented objects, and (2) object misclassification due to limited annotated data, which hinders generalization to unseen classes. To address these issues, we propose a novel method for few-shot oriented object detection in remote sensing images. Our approach employs oriented bounding boxes instead of horizontal ones to learn more effective feature representations for arbitrarily oriented aerial objects, enhancing detection accuracy. Additionally, we introduce a supervised contrastive learning module with a dynamically updated memory bank, enabling the model to leverage large batches of negative samples and to better learn discriminative features for unseen classes. Extensive experiments on DOTA, HRSC2016, and DIOR-R datasets demonstrate superior performance of our proposed method in few-shot oriented object detection. Code and pre-trained models will be made publicly available.

Total electron content (TEC) is a key parameter for characterizing ionospheric morphology and significantly impacts the Global Navigation Satellite System. The ionosphere responds dramatically to solar and geomagnetic activity, leading to substantial TEC fluctuations and disturbances. To improve TEC prediction accuracy, we propose Encoder‐Decoder (ED)‐Autoformer, a novel model combining ED structure with the Autoformer model. The model integrates time series data with TEC to enable 24‐hr forecasts of both disturbance storm time index (Dst) and TEC. Evaluated on global ionospheric maps TEC, our model achieves a improvement (0.51 TECu) in the root mean squared error (RMSE) during solar maximum and an improvement (0.14 TECu) in RMSE during solar minimum compared to the Convolutional Long‐Short‐Term Memory (ConvLSTM) method. Furthermore, ED‐Autoformer shows superior computational efficiency with faster inference speed compared to ED‐ConvLSTM. We further analyzed TEC disturbances during geomagnetic storm periods. For the geomagnetic storm on 20 September 2015, the RMSE remained below 3.50 TECu for most periods, peaking at 5.50 TECu during the main phase. These results demonstrate the robustness of the model in accurately predicting TEC disturbances during geomagnetic storm periods.

Substorms have been found to play an important role in ionospheric electrodynamics at low and equatorial latitudes. In this study, we have investigated the possible influence of substorm on the generation of equatorial spread F (ESF). Coherent backscatter radar (JULIA) and incoherent scatter radar measurements between 2000 and 2017 at the Jicamarca Radio Observatory (11.95° S, 76.87° W, ~0° dip lat) are used. In statistical analysis, 12,525 h of ESF measurements are considered and have been divided into two groups based on their local time: post-sunset (18–24 LT) and post-midnight (00–06 LT). The superposed epoch analysis shows that the substorm-caused disturbance on vertical plasma drift can last longer than 12 h, which further affects the occurrence rate of ESF during a substorm. The increase/decrease of ESF at the post-sunset/post-midnight sector with about a 1 h lag to the substorm commencement is attributed to the prompt penetration electric field (PPEF), while the disturbance dynamo electric field needs approximately 3.5 h to suppress/promote the post-sunset/post-midnight ESF after substorm. In addition, the absolute value of correlation coefficients between the AE index and the occurrence rate of ESF is the largest when a 3–3.5 h lag is considered, which implies that the effect of disturbance dynamo electric fields could be more significant than prompt penetration electric field for the generation (suppression) of post-midnight (post-sunset) ESF during a substorm.

Large-scale real-time ionospheric information is difficult to obtain promptly, plaguing the timely and accurate geolocation of high-frequency (HF) sources in unknown ionosphere environments. In this paper, we propose a novel HF skywave source geolocation method based on the time-difference-of-arrival (TDOA) with semidefinite programming (SDP), and no priori information about the ionosphere is necessary. In the simulations, the proposed method is compared with existing methods and detailed geolocation error distribution maps are given. In the experiments, HF I/Q data captured from the same source at different times on different dates are used to validate the proposed method. Simulated and experimental results show that the proposed method improves the positioning accuracy by about 40% compared with existing methods under the same conditions, and the average relative positioning error is less than 1.8%.