Enhanced Thunderstorm Forecasting over the South China Sea Through VLF Lightning Data Assimilation

To advance marine thunderstorm forecasting and enhance the operational utility of lightning data, this study developed a novel very low-frequency (VLF) lightning data assimilation scheme for the South China Sea region. The three-dimensional graupel mixing ratio field was successfully inverted from VLF lightning detection data through the application of an empirical formula linking lightning frequency to graupel mass, a database of graupel mixing ratio profiles, and a distance-weighted diffusion scheme. This reconstructed field was then subjected to horizontal diffusion and assimilated into the Weather Research and Forecasting (WRF) model using the Grid Nudging module within the WRF–Four-Dimensional Data Assimilation (WRF-FDDA) system. A quantitative evaluation of 37 nocturnal marine convective cases was conducted using Fengyun-4A(FY-4A) satellite observations. The results demonstrate that the proposed assimilation method significantly enhances short-term (0–6 h) forecast performance. Specifically, the Fractions Skill Score (FSS) derived from the Advanced Geosynchronous Radiation Imager (AGRI) data increased rapidly during the early forecast stage, exceeding a value of 0.9. Meanwhile, the Lightning Mapping Imager Event (LMIE) product evaluation showed a high probability of detection (POD) of 85% for lightning forecasts, with a false alarm ratio (FAR) of only 9%. These findings indicate that the assimilation approach improves the accuracy of capturing the spatial structure and evolution of convective systems. Although the degree of improvement diminished with longer lead times, the results confirm the value of VLF lightning data in initializing convective-scale processes and underscore its practical value in marine nowcasting applications.