摘要：A global climate prediction system （PCCSM4） was developed based on the Community Climate System Model, version 4.0, developed by the National Center for Atmospheric Research （NCAR）, and an initialization scheme was designed by our group. Thirty-year （1981-2010） one-month-lead retrospective summer climate ensemble predictions were carded out and analyzed. The results showed that PCCSM4 can efficiently capture the main characteristics of JJA mean sea surface temperature （SST）, sea level pressure （SLP）, and precipitation. The prediction skill for SST is high, especially over the central and eastern Pacific where the influence of E1 Nino-Southem Oscillation （ENSO） is dominant. Temporal correlation coefficients between the pre- dicted Nino3.4 index and observed Nino3.4 index over the 30 years reach 0.7, exceeding the 99% statistical significance level. The prediction of 500-hPa geopotential height, 850-hPa zonal wind and SLP shows greater skill than for precipitation. Overall, the predictability in PCCSM4 is much higher in the tropics than in global terms, or over East Asia. Furthermore, PCCSM4 can simulate the summer climate in typical ENSO years and the interannual variability of the Asian summer monsoon well. These preliminary results suggest that PCCSM4 can be applied to real-time prediction after further testing and improvement.

摘要：The authors investigate possible changes of monsoon rainfall and associated seasonal (June-JulyAugust) anomaly patterns over eastern China in the late 21st century under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 emission scenario as simulated by a high-resolution regional climate model (RegCM3) nested in a general circulation model (FvGCM/CCM3).Two sets of multi-decadal simulations are performed at 20-km grid spacing for present day and future climate *** show that the RegCM3 reproduces the mean rainfall distribution;however the evolution of the monsoon rain belt from South China to North China is not well *** the rain pattern classifications,RegCM3 overestimates the occurrence of Pattern 1 (excessive rainfall in northern China) and underestimates that of Pattern 2 (increased rainfall over the Huai River basin).Under future climate conditions,RegCM3 projects less occurrence of Pattern 1,more of Pattern 2,and little change of Pattern 3 (rainfall increase along the Yangtze River).These results indicate that there might be increased rainfall over the Huai-Yellow River area and reduced rainfall over North China in the future,while rainfall over the lower reaches of the Yangtze River basin is not modified *** exist in the present study are also discussed.

摘要：The ability of six Regional Climate Models (RCMs) used in AMMA-ENSEMBLES project is assessed over six meteorological stations in C&#244te d’Ivoire. The ensemble mean of the models is also used for the prediction of climate change over West Africa. The study focused on two periods: the period 1995-2005, the present-day simulations, is used to evaluate the skills of the models over the country and the years 2010-2013, for assessment of the future climate change scenario used. The results show that the skills of the models vary from one station to another and from one season to another. None of the models considered, presents an excellent performance over the entire country and in all the seasons. Generally, the ensemble mean of all the models presents better results when compared with the observation. These results suggest that the choice of any model for study over the country may depend on the focus of interest: intensity or variability of the rain and also on area of interest. The projection for 2020-2040, future climate change over West Africa shows that the Sahel exhibits a tendency to be drier while wetter Guinean coast is observed.