Sensitivity of Real-Data Simulations of the 3 May 1999 Oklahoma City Tornadic Supercell and Associated Tornadoes to Multimoment Microphysics. Part I: Storm- and Tornado-Scale Numerical Forecasts

Abstract

Abstract Numerical predictions of the 3 May 1999 Oklahoma City, Oklahoma, tornadic supercell are performed within a real-data framework utilizing telescoping nested grids of 3-km, 1-km, and 250-m horizontal spacing. Radar reflectivity and radial velocity from the Oklahoma City WSR-88D are assimilated using a cloud analysis procedure coupled with a cycled 3DVAR system to analyze storms on the 1-km grid for subsequent forecast periods. Single-, double-, and triple-moment configurations of a multimoment bulk microphysics scheme are used in several experiments on the 1-km and 250-m grids to assess the impact of varying the complexity of the microphysics scheme on the storm structure, behavior, and tornadic activity (on the 250-m grid). This appears to be the first study of its type to investigate single- versus multimoment microphysics within a real-data context. It is found that the triple-moment scheme overall performs the best, producing the smallest track errors for the mesocyclone on the 1-km grid, and stronger and longer-lived tornado-like vortices (TLVs) on the 250-m grid, closest to the observed tornado. In contrast, the single-moment scheme with the default Marshall–Palmer rain intercept parameter performs poorly, producing a cold pool that is too strong, and only weak and short-lived TLVs. The results in the context of differences in latent cooling from evaporation and melting between the schemes, as well as implications for numerical prediction of tornadoes, are discussed. More generally, the feedbacks to storm thermodynamics and dynamics from increasing the prognostic detail of the hydrometeor size distributions are found to be important for improving the simulation and prediction of tornadic thunderstorms.