Climate Change Research ›› 2019, Vol. 15 ›› Issue (1): 1-11.doi: 10.12006/j.issn.1673-1719.2018.004

• Changes in Climate System •     Next Articles

Preliminary assessment on the seasonal hindcast skill of the Arctic Oscillation with decadal experiment by BCC_CSM1.1 climate model

Li-Quan WU1,2,Qing-Quan LI1,2,Yi-Hui DING2,Li-Juan WANG1,Xiao-Ge XIN2,Min WEI3   

  1. 1 Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science &Technology (NUIST), Nanjing 210044, China;
    2 Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081, China
    3 National Meteorological Information Center, China Meteorological Administration, Beijing 100081, China;
  • Received:2018-01-12 Revised:2018-04-13 Online:2019-01-30 Published:2019-01-30


This study assesses projection skill of Arctic Oscillation (AO) in initialized decadal experiment with the Beijing Climate Center Climate System Model (BCC_CSM1.1). As compared with the observations and uninitialized historical experiment, the contribution of climate model initialization to predict the seasonal scale AO and its interannual variations is estimated. Results show that the spatial correlation coefficient of AO mode, which depicts the dominant mode of the extra-tropical atmospheric variability, simulated by the decadal experiment is higher than that in the historical experiment. The two groups of experiments can basically reproduce the characteristics of the strongest winter AO index and the weakest summer index. Compared with historical experiment, the correlation coefficient of the monthly and winter AO index is higher in the decadal experiment. In particular, the correlation coefficient of the monthly AO index between the decadal simulations and the observation reached 0.1 significant level. Furthermore, the periodicity of the monthly and spring AO index are achieved only in the decadal experiment. Hence, the hindcast skill of AO is robust when the initial state is initialized by sea surface temperature data.

Key words: BCC_CSM1.1, Climate model, Decadal, Arctic Oscillation (AO), Seasonal hindcast

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