A Dual-Domain Wavelet-Based Spatiotemporal Attention Network for 24-h Global Ionospheric TEC Prediction

To address the challenges associated with the complex spatiotemporal variations of global ionospheric total electron content (TEC), this study proposes a Dual-domain Filtered-label Wavelet-based Spatiotemporal Attention Network (DFL-WT-STANet) for global TEC forecasting. The proposed framework integrates wavelet-based multi-scale feature extraction, ConvLSTM-based spatiotemporal modeling, and decoupled temporal and spatial Transformer branches to capture local and global dependencies in TEC variations. A dual-domain optimization strategy is further introduced to jointly constrain prediction errors in the time and frequency domains, enhancing the representation of temporal variations and disturbance-related characteristics. Kp, Dst, F10.7, and SSN are incorporated as auxiliary solar and geomagnetic activity features. The global TEC data from 2003 to 2024 were used for experimental evaluation, with 2015, 2019, and 2024 selected as representative test years under different solar activity conditions. DFL-WT-STANet achieves RMSE values of 2.96 and 4.81 TECU in the high-solar-activity years of 2015 and 2024, respectively, while the RMSE decreases to 1.15 TECU in the low-solar-activity year of 2019. Compared with the CODE 1-day-ahead prediction product (C1PG), DFL-WT-STANet reduces the RMSE by 26.75%, 22.06%, and 25.29% in 2015, 2019, and 2024, respectively. During a severe geomagnetic storm with a minimum Dst of −406 nT, the proposed model further reduces the storm-day RMSE and MAE by 8.93% and 11.32%, respectively, compared with WT-STANet. Monthly and latitude-dependent evaluations further show that the forecasting advantage is consistently maintained across different months and a broad range of latitude regions. These results demonstrate that DFL-WT-STANet provides accurate and robust global TEC forecasting under different solar and geomagnetic activity conditions, with particular advantages during pronounced ionospheric disturbances.