Impact of stochastically perturbed parameterization tendencies on storm-scale ensemble forecast

The present study further explores the influence of Stochastically Perturbed Parameterization Tendencies (SPPT) scheme on the storm-scale ensemble forecast. Three sensitivity experiments are performed using the Weather Research Forecast (WRF) model to investigate impacts of three parameters in the SPPT scheme. The NCEP FNL analysis product is used to provide initial and boundary conditions for WRF. Optimal parameter configuration of the SPPT scheme is obtained. Precipitation distribution characteristics simulated with the SPPT scheme are analyzed. Results show that in the SPPT scheme sensitivity experiments, when the decorrelation time scale is 6 h, simulations of the ensemble members are the most reliable and the hourly precipitation score is the best in the middle and later periods of integration. The precipitation scores are also the best for simulations of rainstorms and big rainstorms. The duration of the weather system that can lead to precipitation has great influences on the selection of decorrelation time scale. The experiment that chooses 100 km as the decorrelation spatial scale performs best and the precipitation forecasting skill scores are also the highest. At the same time, the selection of this variable is closely related to large scale information and active small and medium scale systems as well as the model spatial resolution. Analysis of spread and outliers indicates that choosing 0.525 as the disturbance amplitude is the most reasonable. The ensemble members of SPPT can significantly improve precipitation simulation in some local areas, but there still exist some limitations on accurate simulation of the precipitation area.