MJO prediction skill, predictability, and teleconnection impacts in the Beijing Climate Center Atmospheric General Circulation Model

This study evaluates performance of Madden-Julian oscillation (KO) prediction in the Beijing Climate Center Atmospheric General Circulation Model (BCC_AGCM2.2). By using the real-time multivariate MJO (RMM) indices, it is shown that the MJO prediction skill of BCC_AGCM2.2 extends to about 16-17 days before the bivariate anomaly correlation coefficient drops to 0.5 and the root-mean-square error increases to the level of the climatological prediction. The prediction skill showed a seasonal dependence, with the highest skill occurring in boreal autumn, and a phase dependence with higher skill for predictions initiated from phases 2-4. The results of the MJO predictability analysis showed that the upper bounds of the prediction skill can be extended to 26 days by using a single-member estimate, and to 42 days by using the ensemble-mean estimate, which also exhibited an initial amplitude and phase dependence. The observed relationship between the MJO and the North Atlantic Oscillation was accurately reproduced by BCC_AGCM2.2 for most initial phases of the MJO, accompanied with the Rossby wave trains in the Northern Hemisphere extratropics driven by KO convection forcing. Overall, BCC_AGCM2.2 displayed a significant ability to predict the MJO and its teleconnections without interacting with the ocean, which provided a useful tool for fully extracting the predictability source of subseasonal prediction. (C) 2016 The Author(s). Published by Elsevier B.V.