Extraseasonal ensemble numerical predictions of winter climate over China  

作　　者：LANG Xianmei, WANG Huijun & JIANG Dabang Nansen-Zhu International Research Center and LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China 

出　　处：《Chinese Science Bulletin》2003年第19期2121-2125,共5页

基　　金：This work was jointly supported by the National Natural Science Foundation of China(Grant No.40125014);the Chinese Academy of Sciences(Grant No.KZCX2-203).

摘　　要：Using the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM) under the Chinese Academy of Sciences, 30-year extraseasonal short-term ensemble hincast of winter climate is performed, with integrations starting from annual autumn during 1969—1998. Winter climate predictability over China is then evaluated for the first time. It follows that the predictability is higher in tropics than in extratropics. Also, it is higher over ocean compared with land, especially for surface air temperature. With height increasing in troposphere, the predictability of geopotential height slightly changes zonally, but for weakening of band-ship distribution and dropping near the date line. Of all analyzed variables, the prediction skill of air temperature and geopotential height (precipitation) is the highest (smallest). In addition, the predictability of winter climate over China and even East Asia enhances obviously during ENSO cycle, especially during La Nia phase. Simulation comparison against verifying analysis for surface temperature anomaly exhibits the model抯 skill in predicting surface temperature抯 interannual variation trend in winter.Using the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM) under the Chinese Academy of Sciences, 30-year extraseasonal short-term ensemble hincast of winter climate is performed, with integrations starting from annual autumn during 1969—1998. Winter climate predictability over China is then evaluated for the first time. It follows that the predictability is higher in tropics than in extratropics. Also, it is higher over ocean compared with land, especially for surface air temperature. With height increasing in troposphere, the predictability of geopotential height slightly changes zonally, but for weakening of band-ship distribution and dropping near the date line. Of all analyzed variables, the prediction skill of air temperature and geopotential height (precipitation) is the highest (smallest). In addition, the predictability of winter climate over China and even East Asia enhances obviously during ENSO cycle, especially during La Nia phase. Simulation comparison against verifying analysis for surface temperature anomaly exhibits the model抯 skill in predicting surface temperature抯 interannual variation trend in winter.

关 键 词：冬季气候 中国 气候预报 数字模型 表面温度 

分 类 号：P457[天文地球—大气科学及气象学]