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

摘要

In this study, a lightning data assimilation (LDA) scheme was developed and implemented in the National Center for Atmospheric Research Weather Research and Forecasting-Real-Time Four-Dimensional Data Assimilation system. In this LDA method, graupel mixing ratio (q_g) is retrieved from observed total lightning. To retrieve q_g on model grid boxes, column-integrated graupel mass is first calculated using an observation-based linear formula between graupel mass and total lightning rate. Then the graupel mass is distributed vertically according to the empirical q_g vertical profiles constructed from model simulations. Finally, a horizontal spread method is utilized to consider the existence of graupel in the adjacent regions of the lightning initiation locations. Based on the retrieved q_g fields, latent heat is adjusted to account for the latent heat releases associated with the formation of the retrieved graupel and to promote convection at the observed lightning locations, which is conceptually similar to the method developed by Fierro et al. Three severe convection cases were studied to evaluate the LDA scheme for short-term (0-6 h) lightning and precipitation forecasts. The simulation results demonstrated that the LDA was effective in improving the short-term lightning and precipitation forecasts by improving the model simulation of the q_g fields, updrafts, cold pool, and front locations. The improvements were most notable in the first 2 h, indicating a highly desired benefit of the LDA in lightning and convective precipitation nowcasting (0-2 h) applications.