AbstractThis work evaluates the performance of the assimilation of total lightning data within a three-dimensional variational (3DVAR) framework for the analysis and short-term forecast of the 24 May 2011 tornado outbreak using the Weather Research and Forecasting (WRF) Model at convection-allowing scales. Between the lifted condensation level and a fixed upper height, pseudo-observations for water vapor mass first are created based on either the flash extent densities derived from Oklahoma Lightning Mapping Array data or the lightning source densities derived from the Earth Networks pulse data, and then assimilated by the 3DVAR system. Assimilation of radar data with 3DVAR and a cloud analysis algorithm (RAD) also are performed as a baseline for comparison and in tandem with lightning to evaluate the added value of this lightning data assimilation (LDA) method.Given a scenario wherein the control experiment without radar or lightning data assimilation fails to accurately initiate and forecast the observed storms, the LDA and RAD yield comparable short-term forecast improvements. The RAD alone produces storms of similar strength to the observations during the first 30 min of forecast more rapidly than the LDA alone; however, the LDA is able to better depict individual supercellular features at 1-h forecast. When both the lightning and radar data are assimilated, the 30-min forecast showed noteworthy improvements over RAD in terms of the model’s ability to better resolve individual supercell structures and still maintained a 1-h forecast similar to that from the LDA. The results chiefly illustrate the potential value of assimilating total lightning data along with radar data.