With widespread influence on global climate and weather extremes, the Madden-Julian Oscillation (MJO) plays a crucial role in subseasonal prediction. Our latest global climate models (GCMs), however, have great difficulty in realistically simulating the MJO. This model inability is largely due to problems in representation of MJO’s cumulus organization. This study, based on a series of idealized aqua-planet model experiments using an atmospheric-only GCM, clearly demonstrates that MJO propagation is strongly modulated by the large-scale background state in which the lower-tropospheric mean moisture gradient and zonal winds are critical. Therefore, when tuning climate models to achieve improved MJO simulations, particular attention needs to be placed on the model large-scale mean state that is also significantly affected by cumulus parameterizations. This study indicates that model biases in representing MJO propagation may be related to the widely reported double-ITCZ (intertropical convergence zone) problem in climate models.

Madden-Julian涛动（MJO）对全球气候和极端天气有广泛的影响，在亚季节预测中起着至关重要的作用。但是，我们最新的全球气候模型（GCM）在实际模拟MJO方面有很大的困难。这种模型的无能主要是由于MJO的积云组织的代表问题。这项研究基于一系列使用纯大气层的GCM理想化的水行星模型实验，清楚地表明，MJO传播受到大尺度背景状态的强烈调节，其中对流层平均湿度梯度和纬向风至关重要。因此，在调整气候模型以改善MJO模拟时，需要特别注意模型的大规模平均状态，该状态也受累积参数化的影响很大。这项研究表明，代表MJO传播的模型偏差可能与气候模型中被广泛报道的double-ITCZ（热带收敛带）问题有关。