The simulation of the Asian monsoon rainfall and its extreme events with high fidelity remains a challenge even for the present day state-of-the-art models with conventional treatment of convection. A multi-scale approach vis-à-vis the super-parameterization appears to overcome the uncertainty of convective parameterization and thereby improve models ability to simulate rainfall. In this study, performance of super-parameterized community climate system model’s atmospheric only (SPCAM) forced with observed SST and coupled (SPCCSM) versions have been evaluated to capture Indian summer monsoon rainfall characteristics. Analyses show that, simulation of rainfall and its extremes are better represented in the atmospheric model (SPCAM) over the Indian landmass. This is largely because of better representation of convection in the uncoupled version. It is also observed that 2–10 day synoptic mode of the summer monsoon has a large variance over Indian region which may be broadly responsible for extreme events, and SPCAM captures this synoptic variability reasonably well. Our study also indicates that models may have poor moisture holding capacity. This problem is more prominent in SPCCSM.

即使对于当今采用常规对流处理的最先进模型，对亚洲季风降雨及其高保真度极端事件的模拟仍然是一个挑战。相对于超参数化的多尺度方法似乎克服了对流参数化的不确定性，从而提高了模型模拟降雨的能力。在这项研究中，评估了超参数化社区气候系统模型的仅大气（SPCAM）和观测到的海温（SST）和耦合（SPCCSM）版本的性能，以捕获印度夏季风的降雨特征。分析表明，印度陆地上空的大气模型（SPCAM）较好地表示了降雨及其极端情况的模拟。这主要是因为在非耦合版本中对流的更好表示。还观察到，夏季风的2-10天天气模式在印度地区的变化很大，这可能是造成极端事件的主要原因，而SPCAM可以很好地捕获这一天气变化。我们的研究还表明，模型的持湿能力可能很差。此问题在SPCCSM中更为突出。