Tuesday, 9 January 2018: 8:30 AM
Room 5ABC (ACC) (Austin, Texas)
The Convection-Permitting Ensemble Prediction System (CPEPS) based on GRAPES-MESO is developed, implemented and run for improving the quantitative precipitation forecasts (QPFs) skill in South China. It consists of 1 control member and 16 perturbation members at 0.03° resolution over Southern China and North of the South China Sea. The blending of downscaling (DSC), ensemble of data assimilation (EDA), and time-lagged (TLA) technique is used as the initial condition (IC) perturbation of CPEPS, and the blending of downscaling and balanced random perturbation (BR) technique is used as the lateral boundary conditions (LBCs) perturbation. Especially, the downscaling perturbations are from the Mesoscale Ensemble Prediction System (MSEPS). Additionally, the terrain height and surface temperature are also added perturbations. The model uncertainty is represented by the combination of Multi-physics (MP), Parameter Perturbation (PP) and Stochastically Perturbed Parameterization Tendencies (SPPT). CPEPS is initialed at 0000/1200 UTC, with a forecast length of 12 hours. The control member of CPEPS is the deterministic forecast with the operational settings for physical parameterization and without IC and LBCs perturbations.
The impact of CPEPS on the QPFs in Southern China was evaluated over the period of Southern China Monsoon Rainfall Experiment (SCMREX) in May 2014. The half-month batch experiment (8-23 May, 2014) was implemented, and results showed that the probability-matching forecasts of CPEPS perturbation members were superior to the ones of CPEPS control member for the heavy rainfall. The impact of different perturbation methods on QPFs were also discussed to reveal their importance in the CPEPS, by a case study.
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