摘要
热带太平洋厄尔尼诺/南方涛动(ENSO)和热带印度洋的偶极子(IOD)是全球季节到年际尺度的重要自然变率.本研究利用中国科学院大气物理研究所FGOALS-f2季节内-季节预测系统开展2018/2019年秋冬季气候异常预测.基于该预测系统从2017年7月起进行的预测显示:(1) 2018年秋冬季节IOD维持正位相,正IOD事件在10月达到最强,比常年偏高0.4℃;(2) 2018年秋冬季节赤道中东太平洋将逐渐发展成一次中等强度的厄尔尼诺事件,Ni?o3.4指数冬季达到1.3;(3) 2018年中国冬季风强度可能偏弱,冬季大部分地区气温较常年偏高,冷空气活动较弱,据此推测北方地区气象条件不利于大气污染物扩散,而南方受印度洋低层气流偏强的影响,出现暖湿气候特征.
El Ni?o-Southern Oscillation(ENSO) in the equatorial Pacific Ocean and the Indian Ocean Dipole(IOD) in the equatorial Indian Ocean are two major natural variabilities on seasonal and inter-annual timescales. In this study, the Flexible Global Ocean-Atmosphere-Land System Model, finite volume version 2(FGOALS-f2), sub-seasonal to seasonal(S2S) climate prediction system, was used to make a seasonal prediction for autumn and winter 2018–2019. The FGOALS-f2 S2 S prediction system was developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG), Institute of Atmospheric Physics(IAP), Chinese Academy of Sciences(CAS), and is run on China’s Tianhe-2 supercomputer located at the National Supercomputer Center in Guangzhou, China. The model used in the prediction system is CAS FGOALS-f2, which is a next-generation climate system model of LASG-IAP, representing the interaction between the atmosphere, oceans, land, and sea ice. The seasonal prediction products from this system have been submitted to and used operationally by the National Climate Center of the China Meteorological Administration, as well as the National Marine Environmental Forecasting Center of China, since June 2017. The FGOALS-f2 S2 S prediction system has achieved 37 a retrospective forecasts(reforecasts) covering the period 1981–2017. The reforecast experiments include 24 ensemble members, while the real-time prediction uses 35 ensemble members. The latest prediction results, in July 2018, reveal that:(1) A positive IOD will persist through autumn and winter 2018–2019, and the peak phase will be in October with an amplitude of approximately 0.4°C. Based on the 37 a reforecasts predicted from each July 20 th, the one-month-lead prediction skill of the IOD is 0.82 in the IOD prediction of July, and the five-month-lead prediction skill is 0.56.(2) In the equatorial Pacific Ocean, the prediction results reveal a Moderate El Nino is under development, and Nino3.4 index values may reach approximately 1.3°C. Based on the 37 a reforecasts predicted from each July 20 th, the one-month lead prediction skill of the Nino3.4 index is 0.97 in the ENSO prediction of July, and the six-month lead prediction skill is 0.83.(3) The Moderate El Nino and positive IOD may induce a weak China winter monsoon, characterized by a warm winter. For North China, the meteorological conditions are expected to have adverse effects on atmospheric diffusion;while for South China, warm and wet conditions are likely to prevail, since the lower-level jet of the Indian Ocean is predicted to strengthen. To better predict the equatorial sea surface temperature anomalies in the eastern Pacific and Indian oceans, the FGOALS-f2 S2 S climate prediction team will continue to update the prediction results on the 20 th of every month, releasing them(with respect to ENSO, the IOD, climate, and average monthly weather in China) on the website, and report the latest prediction results via the WeChat public platform.
作者
包庆
吴小飞
李矜霄
王磊
何编
王晓聪
刘屹岷
吴国雄
Qing Bao;Xiaofei Wu;Jinxiao Li;Lei Wang;Bian He;Xiaocong Wang;Yimin Liu;Guoxiong Wu(State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;Plateau Atmosphere and Environment Key Laboratory of Sichuan Province,School of Atmospheric Sciences,Chengdu University of Information Technology,Chengdu 610225,China;College of Earth and Planetary Sciences,University of the Chinese Academy of Sciences,Beijing 100049,China)
出处
《科学通报》
EI
CAS
CSCD
北大核心
2019年第1期73-78,共6页
Chinese Science Bulletin
基金
国家自然科学基金(91737306
41675100
91437219
91637312)
中国科学院A类战略性先导科技专项(XDA19070401
XDA11010402)资助
关键词
气候预测
厄尔尼诺
印度洋偶极子
暖冬
大气扩散条件
climate prediction
El Nino
Indian Ocean Dipole
warm winter
atmospheric diffusion conditions