气象学报2026，Vol.84Issue(4)：694-710,17.DOI:10.11676/qxxb2026.20250235
CMA-CPSv3集合方案介绍
Introduction of the ensemble prediction scheme in the CMA Climate Prediction System version 3(CMA-CPSv3)
摘要
Abstract
Ensemble prediction has been an important tool for weather forecasting,sub-seasonal to seasonal prediction,seasonal prediction,interannual prediction and even simulation of climate change,which has garnered widespread attention in the field of meteorology.This paper introduces the ensemble prediction scheme of China Meteorological Administration Climate Prediction System version 3(CMA-CPSv3).In this scheme,we adopt the approach of combining stochastic perturbations of physical process tendencies in the atmosphere and the air-sea flux with time-lagged initial value perturbation.Based upon the version 2 of High-Resolution Beijing Climate Centre Climate System Model(BCC-CSM2-HR),we have developed a multi-layer random perturbation ensemble prediction system with relatively good ensemble sample dispersion,stability,and reliability.Results of evaluation for hindcasts over the past 20 years show that this ensemble prediction system significantly improves the prediction of precipitation and 2 m air temperature over China,as well as the El Niño-Southern Oscillation(ENSO),Indian Ocean Dipole(IOD)and Asian Monsoon.In particular,the random perturbation of air-sea flux shows a positive effect on improving the prediction skills of ENSO and Southeast Asian Monsoon(SEAM)and Western North Pacific Summer Monsoon(WNPSM)indices.This study offers useful insights for further characterizing uncertainty in other component models of the climate system.关键词
随机扰动/模式不确定性/集合预测/季节预测Key words
Random perturbation/Model uncertainty/Ensemble prediction/Seasonal prediction分类
天文与地球科学引用本文复制引用
颉卫华,程彦杰,颜京辉,赵鹤,张馨丹,房永杰,辛晓歌,张洁,吴统文,李巧萍,梁潇云,李晓莉,朱跃建,刘向文,路屹雄,姚隽琛..CMA-CPSv3集合方案介绍[J].气象学报,2026,84(4):694-710,17.基金项目
国家自然科学基金重点项目(42230608)、国家自然科学基金面上项目(42275056). （42230608）
