An Integrated Thermodynamic and Microphysical Framework for Thunderstorm and Lightning Prediction Using the WRF Model

Abstract Bangladesh is located within the highly lightning-prone region (30N-30S belt) and experiences significant casualties and property loss, particularly during the pre-monsoon and monsoon season due to lightning activity. Traditional thunderstorm and lightning forecasting methods are mostly rely on thermodynamic instability indices. These indices have limitations in forecasting the intensity, duration, and spatial distribution of the lightning. Recent advances in high-resolution Numerical Weather Prediction (NWP) have facilitated the development of microphysics and cloud electrification-based techniques, such as the Lightning Potential Index (LPI) and Lightning Flash Density (LFD). They improve lightning forecasts with greater spatial accuracy but have a very shorter lead time. This study investigates four severe thunderstorm events occurring between May and July 2023 over Bangladesh using Weather Research and Forecasting (WRF) model with electrification scheme (WRF-Elec). Here, we investigate an integrated approach of thermodynamic and microphysical framework to improve lightning forecasting in both temporal and spatial dimensions. We find that microphysical fields like maximum reflectivity, LPI, and LFD capture the lightning activity with 2-6 hours lead time and spatial accuracy of 1.5$\times$1.5 deg boundary. On the other hand, the conventional thermodynamic fields predict convective activity 10-12 hours lead time but provide the information of little to no spatial boundary. In the integrated approach combining microphysical and thermodynamic fields we find the lightning prediction with a significantly larger lead time while maintaining spatial accuracy for lightning activity. These findings indicate that the integrated microphysical–thermodynamic framework could be adopted more broadly to enhance short-term lightning prediction in different regions and operational forecasting settings.