Investigating the ENSO prediction skills of the Beijing Climate Center climate prediction system version 2  

作　　者：Yanjie Cheng Youmin Tang Tongwen Wu Xiaoge Xin Xiangwen Liu Jianglong Li Xiaoyun Liang Qiaoping Li Junchen Yao Jinghui Yan 

机构地区：[1]CMA Earth System Modeling and Prediction Centre,China Meteorological Administration(CMA),Beijing,100081,China [2]State Key Laboratory of Severe Weather,China Meteorological Administration,Beijing,100081,China [3]College of Environmental Science and Engineering,University of Northern British Columbia,Prince George,V2N 4Z9,Canada

出　　处：《Acta Oceanologica Sinica》2022年第5期99-109,共11页海洋学报（英文版）

基　　金：The National Key Research and Development Program under contract No.2017YFA0604200;the National Program on Global Change and Air-Sea Interaction under contract No.GASI-IPOVAI-06;the National Natural Science Foundation of China under contract No.41530961.

摘　　要：The El Niño-Southern Oscillation(ENSO)ensemble prediction skills of the Beijing Climate Center(BCC)climate prediction system version 2(BCC-CPS2)are examined for the period from 1991 to 2018.The upper-limit ENSO predictability of this system is quantified by measuring its“potential”predictability using information-based metrics,whereas the actual prediction skill is evaluated using deterministic and probabilistic skill measures.Results show that:(1)In general,the current operational BCC model achieves an effective 10-month lead predictability for ENSO.Moreover,prediction skills are up to 10–11 months for the warm and cold ENSO phases,while the normal phase has a prediction skill of just 6 months.(2)Similar to previous results of the intermediate coupled models,the relative entropy(RE)with a dominating ENSO signal component can more effectively quantify correlation-based prediction skills compared to the predictive information(PI)and the predictive power(PP).(3)An evaluation of the signal-dependent feature of the prediction skill scores suggests the relationship between the“Spring predictability barrier(SPB)”of ENSO prediction and the weak ENSO signal phase during boreal spring and early summer.

关 键 词：ENSO ensemble prediction skill potential predictability measure BCC-CPS2 climate model 

分 类 号：P732.4[天文地球—海洋科学]