基于改进版NUIST CFS1.1的热带大气季节内信号及其对中国气温降水影响的预测评估  

Prediction of tropical intraseasonal oscillations and their impacts on air temperature and precipitation in China using the upgraded version of NUIST CFS1.1

作　　者：伍继业 谢欣芮 罗京佳 WU Jiye;XIE Xinrui;LUO Jing-Jia(Key Laboratory of Meteorological Disaster,Ministry of Education(KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)/Institute of Climate Application Research(ICAR),Nanjing University of Information Science and Technology,Nanjing 210044,China)

机构地区：[1]南京信息工程大学气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心/气候与应用前沿研究院,江苏南京210044

出　　处：《大气科学学报》2024年第2期284-299,共16页Transactions of Atmospheric Sciences

基　　金：国家自然科学基金资助项目(42088101,42030605)。

摘　　要：基于南京信息工程大学次季节气候预测系统(NUIST CFS1.1),通过调整成员的大气初始化方案并优化了集合预测方案,构建了性能更优、计算成本更低的9成员NUIST CFS1.1 Pro系统。进一步基于实时多变量Madden-Julian Oscillation(MJO)指数和两类北半球夏季季节内振荡(Boreal Summer Intraseasonal Oscillation,BSISO)指数BSISO1和BSISO2,评估了该预测系统对热带不同季节的大气季节内振荡(ISO)的预测技巧。结果表明,NUIST CFS1.1 Pro能分别提前26、17、12 d有效预测(距平相关高于0.5)MJO、BSISO1、BSISO2,对强事件(振幅>1)的有效预测时长能分别延长到30、21、13 d。此预测性能对比国内其他最新次季节动力模式如BCC_CSM2和FGOALS-f2有一定优势,同时在与国际S2S计划的8个主要业务预测系统的技巧对比中,NUIST CFS1.1 Pro在冬季MJO和夏季BSISO1预测上处于较为领先的水平,BSISO2的预测则处于中等水平;对不同位相的计算技巧显示,冬季MJO和夏季BSISO1的2、3、6、7位相较其他位相技巧更高。进一步的分析表明,NUIST CFS1.1 Pro能提前5候准确把握冬季MJO的东传特征,并能在一定程度上预测出其对我国气温异常的影响,尤其是对位相2、3时候的冷异常预测;而在夏季,则能提前4候正确预测BSISO1的北传、西北传特征,尤其能较好地预测西北太平洋上的对流和低层环流异常,从而成功预测出BSISO1造成的我国东部地区降水异常的空间形态。然而预测的强度较观测偏弱,这需要进一步的工作来改进。Beyond conventional weather forecasts and seasonal climate predictions,a continuum of prediction across all timescales,known as weather-climate seamless prediction,has garnered considerable attention and progressed over the last decades.However,among predictions on various timescales,subseasonal predictions,bridging weather forecasts and short-term climate predictions still face challenges.This timescale typically extends beyond two weeks but falls short of a season,where the influence of initial conditions has faded away while the forcing from boundary conditions remains insignificant.Consequently,understanding the sources of subseasonal predictability and achieving effective subseasonal predictions encounter significant challenges.As reported in numerous previous studies,tropical intraseasonal oscillations(ISO),comprising the Madden-Julian Oscillation(MJO)and Boreal Summer Intraseasonal Oscillation(BSISO),can provide dominant sources of global subseasonal-to-seasonal(S2S)predictability.

关 键 词：热带大气季节内振荡 次季节预测 中国气温降水 

分 类 号：P461[天文地球—大气科学及气象学]