7.8 The global ensemble prediction system(GEPS) and regional ensemble prediction system (REPS) at CMA and its application in monsoon season

Tuesday, 25 January 2011: 5:15 PM
613/614 (Washington State Convention Center)
Jing Chen, Chinese Meteorological Administration, Beijing, China; and H. Tian, G. Deng, X. Li, J. Gong, Y. Li, X. Wang, and J. Hu

The development of GEPS and REPS at CMA was launched in 2002 based on the T213 Global model and WMO B08RDP project sponsored by WWRP. From 2005-2010, We develop the GEPS based T213 global model and BGM initial perturbation method. From 2009 to 2010, we start to develop the REPS for China based on the B08RDP REPS system. This system has 15 members and runs twice a day at 00 and 12 UTC with 3-h of model output frequency.

The REPS system is based on WRF model with BGM as initial perturbation method. The multi-physics technique is deployed to present the model uncertainty. Eight types of combinations were conducted by use of two different cumulus convective (Betts-miller and Kain-Fritsch schemes), two planetary boundary layer schemes (YSU and MJY), and two land surface schemes (Noah and 5-layer thermal diffusion scheme), and two microphysics schemes (Lin and WSM6). This system has 15 members with 15km horizontal resolution covering China, and runs twice a day at 00 and 12 UTC with 3-h of model output frequency. The lateral boundary conditions of REPS are provided by CMA T213 model-based GEPS. The REPS also includes every 6-h 3D-VAR data assimilation and rescaling cycle for BGM. The conventional ensemble products and some specific tailored probabilistic products for severe weather forecast (such as convective risk index) are provided. The REPS has been operationally running since Jun 2010.

The evaluations of performance of GEPS and REPS for some typical heavy rainfall processes in monsoon season in China are performed in this study. The results show that compared to T213 model-based GEPS system the REPS has significant advantages for the forecasts of precipitation and high impact weather at short-range. Moreover, the Ensemble mean and probabilistic products for heavy rainfall events are able to provide more useful guidance information at the mesoscale. Finally the future plan for CMA REPS is discussed.

Key Words: GEPS and REPS at CMA, probabilistic products, heavy rainfall

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