Abstract : 3P.1
A mesoscale ensemble prediction system of precipitation for the East Tibet Plateau

Jing Chen, Hanzhong Feng, Guangbi He
Institute of Plateau Meteorology, CMA

An super ensemble prediction system, based on the PSU/NCAR non-hydrodynamic Mesoscale Model (MM5) has been developed with an emphasis on heavy rainfall event prediction applications in the East Tibet Plateau in Institute of Plateau Meteorology(IPM), China Meteorology Administration, Chengdu. Considering the impact of physics and initial conditions errors of numerical model on heavy rainfall in monsoon season, the multi-physics perturbation schemes were consisted of different Cumulus Convective Parameterization(CCP) and Planetary Boundary Layer(PBL) schemes. The multi-initial condition perturbation method adopted Different Physical Mode Method (DPMM),which was developed by Chen Jing et al focusing on the uncertainty of heavy rainfall events prediction in East Asia in monsoon season. There were 8 ensemble members. The rainfall ensemble mean, probability of category rainfall and the spread are yielded and transferred to the third and forth category data of MICAPS graph system ( operational data processing and visualizing system popular used in China ) .

The system currently run daily in an experimental mode. Some objective scores and case studies for precipitation prediction for the East Tibet Plateau in 2005 summer season will be given to provide an indication of precipitation prediction performance of the super ensemble system. Compared with global model T213 of National Meteorology Center, China, the mesoscale ensemble precipitation prediction have a little more skillful than global model with the prediction of 25mm and 50mm category precipitation. Ensemble mean and probabilistic prediction for heavy rainfall events could provide more useful guidance in the mesoscale characteristics and higher application value in mesoscale heavy rainfall prediction. Finally some future plans are discussed.

Key Words: East Tibet Plateau ,precipitation, mesoscale ensemble prediction system.