Abstract ID: 136
Madden–Julian Oscillation prediction skill of CAS-IAP model
Lead Author: Yangke Liu
Keywords: MJO prediction skill, CAS-IAP model, Four types of MJO, A Time-varying Nudging method
Abstract: Madden–Julian Oscillation (MJO) prediction skill of the Chinese Academy of Sciences (CAS), Institute of Atmospheric Physics (IAP) (CAS-IAP) model is comprehensively accessed in this study. CAS-IAP model has participated in the second phase of the S2S project since 2021, and real-time forecast and re-forecast results were available on the S2S database in early 2022. The forecast model is the second finite-volume version of the Flexible Global Ocean-Atmosphere-Land system (FGOALS-f2), developed in IAP, CAS. FGOALS-f2 represents the interaction between the atmosphere, oceans, land, and sea ice. As for the 20 years of re-forecast from 1999 to 2018, four ensemble members were initialed with a time-varying nudging technology.
Firstly, to access the MJO prediction skill in the CAS-IAP model, the real-time multivariate MJO (RMM) index was used. Then the fast-propagating, slow-propagating, standing, and jumping patterns of MJO events in the CAS-IAP model were evaluated individually. Last, in the discussion session, a group of sensitivity experiments with an improved initialization scheme was used to investigate the potential improvement of MJO prediction skills in the CAS-IAP model.
The evaluation results indicate that the prediction skill of MJO for the CAS-IAP model is approximately 23 days. It is also worth pointing out that MJO events with more substantial initial MJO amplitude are typically better predicted. Further analysis shows that FGOALS-f2 reasonably captures the main features of the MJO, such as the eastward-propagating signal in the MJO frequency band, the symmetric and asymmetric structures of the MJO, several convectively coupled equatorial waves, and the MJO life cycle. However, the IAP-CAS model underestimates the outgoing longwave radiation (OLR) amplitude and overestimates 850hPa zonal wind. In addition, MJO predicted by the model also shows a faster propagation speed than the observations. Based on the MJO diagnostic theory, the four types of MJO prediction skills, fast-propagating, slow-propagating, standing, and jumping patterns of MJO, are 32, 22, 19, and 29 days. The dynamic analysis indicated that the prediction in the low-level moisture field of slow-propagating MJO was worse than that of the fast-propagating MJO. Finally, the sensitivity experiments reveal that the initialization with a moisture field can effectively improve the prediction skills of slow-propagating MJO, which substantially contribute to the improvement of MJO prediction skill in the CAS-IAP model.
Yangke Liu，Qing Bao，Lingjun Zeng，Bian He， Xiaofei Wu， Yimin Liu and Guoxiong Wu