Potential Impacts of Lightning Flash Observations on Numerical Weather Prediction With Explicit Lightning Processes

Abstract

Although various lightning observation platforms exist, lightning flash observations have not been fully utilized for numerical weather prediction (NWP), mainly due to complications related to modeling lightning processes. Herein, we investigated the potential impacts of lightning observations using an ensemble Kalman filter (EnKF) with an NWP model, including explicit lightning processes. The EnKF included flow-dependent error covariances between lightning flashes and the atmospheric state. Observing system simulation experiments were performed for an idealized convective case. Ensemble-based correlations with various observations indicated that lightning flashes provide valuable information below cloud tops where satellite infrared radiances cannot observe well due to the presence of anvil clouds. Moreover, a single-step data assimilation experiment showed that lightning flashes positively impact the analysis and forecast of wind, hydrometeors, and electric charge. The results revealed that lightning flashes are potentially useful for an EnKF with an NWP model including explicit lightning processes.