The key parameters of atmospheric convective stability, the K index (KI) and the Showalter index (SI), are important indicators for severe convective weather warnings. This study adopts a variational mode decomposition, bidirectional gated recurrent unit, and attention mechanism weighting combined model (VMD–BiGRU–Attention) to optimize core hyperparameters and verify model stability. Global Navigation Satellite Systemderived precipitable water vapor (PWV) and relative humidity (RH) are incorporated as key parameters representing atmospheric water vapor conditions, thereby assisting VMD decomposition in accurately separating effective signals related to severe convection. The results show that the optimal VMD decomposition parameter K for the KI is 10 (minimum root mean square error [RMSE] = 3.96), whereas the optimal K for the SI is 11 (minimum RMSE = 1.87), verifying the applicability of VMD decomposition. In the validation using extreme rainfall events (2021–2025) at three meteorological stations in Guangxi (Baise,Nanning, and Hepu), the model, with the auxiliary contributions of PWV and RH, stably and accurately predicts the KI and SI for the next three hours, effectively capturing the critical characteristics of severe convection. The predicted results are consistent with the observed precipitation, demonstrating significant practical application value.
Loading....