Improving Lightning and Precipitation Prediction of Severe Convection Using Lightning Data Assimilation with NCAR WRF-RTFDDA

In this study, a new lightning data assimilation (DA) scheme based on the Weather Research and Forecasting – Real-Time Four-Dimensional Data assimilation (WRF-RTFDDA) system was developed. The lightning DA system retrieved graupel mixing ratio (q_g) using total lightning rate. To retrieve q_g on model grid-box, column-integrated graupel mass was first calculated using an observation-based linear formula between graupel mass and total lightning rate. Then the graupel mass was distributed vertically according to the empirical q_g vertical profiles constructed from model simulations. Finally, a horizontal spread method was devised by considering the existence of q_g in the adjacent areas of lightning-recorded grids. The retrieved 3D graupel fields are assimilated into RTFDDA with the hydrometeor and latent heat nudging (HLHN) scheme that accounts for the latent heat release associated with the formation of graupel while nudging the mixing ratio of the graupel into the WRF model. The time-dependent observation weighting function of RTFDDA was modified for assimilating lightning data properly. Two severe convection cases occurred in the central plain of the United State and five severe convection events occurred in Shenzhen of China were studied to evaluate the lightning DA scheme for short-term (0 – 6 h) forecasts of severe convective storms. The model results demonstrated that the lightning DA was effective in improving the short-term lightning and precipitation forecasts and better simulated the graupel field, updrafts, cold pool and frontal position than those without lightning DA. The improvements were most significant for the first two hours, which presents desired benefit for the applications that are highly impacted by lightning and convective storms, including electric power-grid operation, aviation, urban life and economic safety of super-cities, etc.