Global ionospheric total electron content (TEC) maps are widely utilized in research regarding ionospheric physics and the associated space weather impacts, so there is a great interest in the community in short‐term ionosphere TEC forecasting. In this study, the long short‐term memory (LSTM) neural network (NN) is applied to forecast the 256 spherical harmonic (SH) coefficients that are traditionally used to construct global ionospheric maps (GIM). Multiple input data, including historical time series of the SH coefficients, solar extreme ultraviolet (EUV) flux, disturbance storm time (Dst) index, and hour of the day, are used in the developed LSTM NN model. Different combinations of the above parameters have been used in constructing the LSTM NN model, and it is found that the model using all four parameters performs the best. Then the best performing LSTM model is used to forecast the SH coefficients, and the global hourly TEC maps are reproduced using the 256 predicted SH coefficients. A comprehensive evaluation is carried out with respect to the CODE GIM TEC. Results show that the first/second hour TEC root mean square error (RMSE) is 1.27/2.20 TECU during storm time and 0.86/1.51 TECU during quiet time, so the developed model performs well during both quiet and storm times. Moreover, typical ionospheric structures, such as equatorial ionization anomaly (EIA) and storm‐enhanced density (SED), are well reproduced in the predicted TEC maps during storm time. The developed model also shows competitive performance in predicting global TEC when compared to the persistence model and two empirical models (IRI‐2016 and NeQuick‐2).

This paper applies the convolutional long short‐term memory (convLSTM)‐based machine learning models to forecast global ionospheric total electron content (TEC) maps with up to 24 hr of lead time at a 1‐hr interval. Four convLSTM‐based models were investigated, and the one that implements the L1 loss function and the residual prediction strategy demonstrates the best performance. The convLSTM models are trained and evaluated using Center for Orbit Determination in Europe (CODE) global TEC maps over a period of nearly seven years from 19 October 2014 to 21 July 2021. Results show that the best convLSTM model outperforms the 1‐day predicted global TEC products released by CODE analysis center (c1pg) and persistence models under various levels of solar and geomagnetic activities, except for a lead time beyond 8 hr during the storm time where the c1pg has slightly better performance. The convLSTM forecasting performance degrades as the lead time increases.

This paper studies the ionosphere's response to the annular solar eclipse on 26 December 2019, utilizing the following ground‐based and space‐borne measurements: Global Navigation Satellite System (GNSS) total electron content (TEC) data, spectral radiance data from the Sentinel‐5P satellite, in situ electron density and/or temperature measurements from DMSP and Swarm satellites, and local magnetometer data. Analysis concentrated on ionospheric effects over low‐latitude regions with respect to obscuration, local time, latitude, and altitude. The main results are as follows: (1) a local TEC reduction of ∼4–6 TECU (30–50%) was identified along the annular eclipse path, with larger depletion and longer recovery periods in the morning eclipse compared to midday. (2) The equatorial electrojet current was significantly weakened when the eclipse trajectory crossed the magnetic equator in the morning (India) sector, which contributed to large and prolonged TEC depletion therein. (3) At midday, equatorial ionization anomaly exhibited enhancements of 20–40% as well as poleward shifting of 3–4°, likely triggered by modified neutral wind and electrodynamics patterns. (4) The behavior of equatorial ionospheric electron density showed considerable altitudinal differences in the topside, exhibiting ∼30% reduction around 500 km and ∼30% enhancement with 300–500 K Te reduction around 850 km, before the arrival of maximum eclipse. This may have been caused by the enhanced eastward electric field and equatorward neutral wind, and other possible factors are also discussed.