Numerical Simulations of a Convective Outbreak with Lightning Data Siimilation Using GSI

The dynamical and microphysical processes associated with a convective outbreak over the Washington, D.C. region during 18 and 19 May 2017 are studied. High-resolution mesoscale numerical simulations were performed with an advanced research version of the Weather Research and Forecasting (WRF ARW) model. Conventional observations and available lightning data were assimilated into the WRF model using the Gridpoint Statistical Interpolation (GSI) system to examine the impact of data assimilation on the numerical simulations of the convective outbreak during this period. It is found that by assimilating conventional observation and lightning data, the timing and placement of convection are greatly improved. Further analysis is being done to investigate the influence of data assimilation on the representation of low- and middle-level moisture, the wind, and temperature profiles, as well as thermodynamic indices such as convective available potential energy (CAPE), lapse rates and lifted indices in the WRF model. The dynamic and thermodynamic processes that control the convective initiation, evolution, and dissipation will be diagnosed.