Abstract ID: 094
Progress of MJO Prediction at CMA during phase I to phase II of Sub-seasonal to Seasonal Prediction Project
Lead Author: Xiangwen Liu
Center for Earth System Modeling and prediction of China Meteorological Administration, China
Keywords: Madden-Julian oscillation (MJO), Subseasonal to Seasonal (S2S), Prediction skill, Improvement, Initial phase
Abstract: As one of the participants in the Subseasonal to Seasonal (S2S) Prediction Project, China Meteorological Administration (CMA) has adopted several model versions to participate in the S2S Project. We evaluate the models’ capability in simulating and predicting the Madden-Julian Oscillation (MJO). Three versions of the Beijing Climate Center Climate System Model (BCC-CSM) are used to conduct historical simulations and reforecast experiments (referred to as EXP1, EXP1-M, and EXP2, respectively). In simulating MJO characteristics, the newly-developed high-resolution BCC-CSM outperforms its predecessors. As for MJO prediction, the useful prediction skill of MJO index is enhanced from 15 days in EXP1 to 22 days in EXP1-M, and further to 24 days in EXP2. Within the first forecast week, the better initial condition in EXP2 largely contributes to the enhancement of MJO prediction skill. However, during forecast weeks 2–3, EXP2 shows little advantage compared with EXP1-M, because the increased skill at MJO initial phases 6–7 is largely offset by the degraded skill at MJO initial phases 2–3. Particular at initial phases 2–3, EXP1-M skillfully captures the wind field and Kelvin-wave response to MJO convection, leading to the highest prediction skill of MJO. Our results reveal that, during the CMA models’ participation in the S2S Project, both the improved model initialization and updated model physics play positive roles in improving MJO prediction. Future efforts should pay more attention to the model physics for better simulating MJO convection over the Maritime Continent and further improving MJO prediction at long lead time.
Co-authors:
Junchen Yao (Center for Earth System Modeling and prediction of China Meteorological Administration)
Tongwen Wu (Center for Earth System Modeling and prediction of China Meteorological Administration)
Jinghui Yan (Center for Earth System Modeling and prediction of China Meteorological Administration)
Qiaoping Li (Center for Earth System Modeling and prediction of China Meteorological Administration)
Weihua Jie (Center for Earth System Modeling and prediction of China Meteorological Administration)
