Design and testing of a global climate prediction system based on a coupled climate model  

作　　者：MA JieHua WANG HuiJun 

机构地区：[1]Climate Change Research Center, Chinese Academy of Sciences [2]Nansen-Zhu International Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences

出　　处：《Science China Earth Sciences》2014年第10期2417-2427,共11页中国科学（地球科学英文版）

基　　金：supported by National Natural Science Foundation of China(Grant No.41130103);Special Fund for Public Welfare Industry(Meteorology)(Grant No.GYHY201306026)

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.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 carried 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 El Ni?o-Southern Oscillation(ENSO) is dominant. Temporal correlation coefficients between the predicted Ni?o3.4 index and observed Ni?o3.4 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.

关 键 词：climate model climate prediction ENSO MONSOON 

分 类 号：P45[天文地球—大气科学及气象学] P409