We present the ionospheric disturbance responses over low-latitude regions by using total electron content from Geostationary Earth Orbit (GEO) satellites of the BeiDou Navigation Satellite System (BDS), ionosonde data and Swarm satellite data, during the geomagnetic storm in August 2018. The results show that a prominent total electron content (TEC) enhancement over low-latitude regions is observed during the main phase of the storm. There is a persistent TEC increase lasting for about 1–2 days and a moderately positive disturbance response during the recovery phase on 27–28 August, which distinguishes from the general performance of ionospheric TEC in the previous storms. We also find that this phenomenon is a unique local-area disturbance of the ionosphere during the recovery phase of the storm. The enhanced $f_o{F}_2$ and $h_m{F}_2$ of the ionospheric F2 layer is observed by SANYA and LEARMONTH ionosonde stations during the recovery phase. The electron density from Swarm satellites shows a strong equatorial ionization anomaly (EIA) crest over the low-latitude area during the main phase of storm, which is simultaneous with the uplift of the ionospheric F2 layer from the SANYA ionosonde. Meanwhile, the thermosphere O/N₂ ratio shows a local increase on 27–28 August over low-latitude regions. From the above results, this study suggests that the uplift of F layer height and the enhanced O/N₂ ratio are possibly main factors causing the local-area positive disturbance responses during the recovery phase of the storm in August 2018.

Under the background of clean and low-carbon energy transformation, renewable distributed generation is connected to the distribution system on a large scale. This study proposes a probabilistic assessment method of hosting capacity considering wind–photovoltaic–load temporal characteristics in distribution networks. First, based on time series of wind, photovoltaic, and load demands, a discretization–aggregation technique is introduced to generate and filter extreme combinations. The method can effectively reduce the scenarios that need to be evaluated. Then a holomorphic embedding method considering generation and load scaling directions is proposed. The holomorphic function of voltage about an embedding variable is established, and it is analytically expanded in the form of series. The hosting capacity restrained by the voltage violation problem is calculated quickly and accurately. Finally, the proposed stochastic framework is implemented to evaluate hosting capacity involving renewable energy types, penetration levels, and locations. The hosting capacity of single energy and hybrid wind–solar renewable energy systems is evaluated from the perspective of probability analysis. The results verify the outstanding performance of the hybrid wind–solar energy system in improving the hosting capacity.

Computerized ionospheric tomography is a highly ill-posed inverse problem, and regularization tends to stabilize the problem to provide a unique solution. When a regularization method is used, the choice of an optimal parameter is a key issue. In this article, we propose an adaptive regularization method for 3-D ionospheric tomography based on the U-curve. The proposed approach uses a U-curve method to determine the optimal regularization parameter from Global Navigation Satellite Systems (GNSS) observation data. Comparative case studies are investigated based on GNSS simulated observations and real measurements. The simulation results indicate that the proposed method is superior to the adaptive regularization method based on the L-curve. In addition, we further validate the tomographic results with actual ionosonde station data. The results demonstrate the reliability and superiority of the proposed method compared to traditional methods.

The ionospheric mapping function (MF) is used to achieve mutual conversion between the vertical total electron content (VTEC) and slant total electron content (STEC) and is vital to the application of ionospheric products. Currently, the typically used MFs consider only the effect of the ionospheric thin-layer height and signal elevation angle, whereas the effects of ionospheric spatiotemporal changes and the azimuth angle, which severely restrict the accuracy of the MF, are not considered. In this study, an ionospheric MF model with the modified Julian day, local time, elevation angle, and azimuth angle of the ionospheric pierce point as inputs is proposed. The MF model, which is named long short-term memory (LSTM)-MF, is constructed using data from the United States provided by MIT/Haystack Observatory from September 1, 2021 to April 30, 2022, and ionospheric grid products named Model VTEC are established based on the LSTM-MF model. On the test set, the root mean square errors (RMSE) of the STEC projected using the LSTM-MF model in elevation angle ranges of 20°-40°, 40°-70°, and 70°-90° are 48.66%, 33.79%, and 11.36% higher than that of the single-layer mapping function (SLMF) model, respectively. On December 5, 2021, the STEC obtained by projecting the Model VTEC product using the LSTM-MF model is 43.8% higher in accuracy than that obtained by projecting MIT VTEC products using SLMF model at low elevation angles of 20°-50°. The LSTM-MF model proposed herein and the established VTEC product improved the STEC accuracy obtained from low-elevation-angle conversion.

The determination of ionospheric total electron content (TEC) is crucial for various applications in space weather. However, due to the uneven distribution of stations, complex data processing and reconstruction algorithms are usually required to obtain a seamless global TEC map. To reduce the difficulty of this process, we show the possibility of reconstructing a high-resolution global TEC map based on the image inpainting method Aggregated Contextual-Transformation Generative Adversarial Nets (AOT-GAN). First, the AOT-GAN model is used to learn the data fitting process and TEC spatial distribution characteristics in the UQRG, and then the data completion performance and generalization ability of the model are verified under different data-missing conditions and geomagnetic activity levels. The verification results show that the model has relatively reliable completion results under different conditions. The average RMSE between the filled results and UQRG is mainly concentrated in 2~3 TECU, and the average SSIM index is mainly concentrated in 0.95~0.97. Even during the geomagnetic storm periods and the land data missing rate exceeds 30%, more than 92% of the biases are still within ±5 TECU. In addition, the model can also achieve considerable results when completing CODG, with more than 63% of the biases within ±1 TECU and more than 92% of the biases within ±5 TECU. Finally, the Massachusetts Institute of Technology (MIT)-TEC map is filled using the trained model. When part of MIT-TEC is removed, the biases between the completed result and the original MIT-TEC are relatively small. For the ocean area, the completed MIT-TEC map has the lowest RMSE and the STD level is similar to the ESAG product. The completed MIT-TEC maps not only maintain the global structure of TEC but also have rich details.

Medium-scale traveling ionospheric disturbances (MSTIDs) to the June 22 and 23, 2015 geomagnetic storm over Japan are investigated by using the Global Navigation Satellite System Earth Observation Network of Japan (GEONET) in this letter. We have detected two groups of MSTIDs on June 22 and 23 and a negative ionospheric disturbance response on June 22 observed by the high-resolution detrended total electron content (TEC) maps from GPS observations. The negative ionospheric response (IR) performs a large-scale ionosphere depletion covering a wide range of areas (~125°E to ~140°E and ~25°N to ~40°N) simultaneously, which starts at 1900 universal time (UT) [04:00 local time (LT)] with a period of ~30 min on June 22. Compared with typical MSTIDs, the nighttime and the daytime MSTIDs in this letter both have a southwestward propagated direction and a propagated velocity of ~87.8 and ~157.8 m/s, respectively. The physical sources of the IRs over Japan during this geomagnetic storm are possibly attributed to the prompt penetration electric field (PPEF) and lower atmospheric gravity waves (AGW) referring to the previous studies. We believe that these findings can contribute to the complement of ionospheric research on MSTIDs over Japan.