在CMIP6模式中更好地表征印度夏季风降水：对MISO和MJO模拟的评估
Towards better representation of Indian summer monsoon rainfall in CMIP6 models: Evaluation of MISO and MJO simulation
AI总结：
本研究评估了CMIP6模式对印度夏季风MISO和MJO的模拟能力，发现TaiESM1和IITM-ESM因更好地刻画对流和总云量而表现更优，为改进ISM气候预测提供了方向。
摘要：
印度夏季风（ISM）和季风季节内振荡（MISO），以及强烈调制MISO的Madden-Julian振荡（MJO）的季节预测，对该国的水资源和作物管理具有重要意义。我们分析了第六次耦合模式比较计划（CMIP6）中的降水、对流和总云量（TCF）。本研究揭示了两组所选CMIP6模式在模拟MISO和MJO方面的显著差异及其背后的物理原因。CMIP6模式中MISO和MJO的平均态和季节内特征差异显著，这与对流和总云量的更好刻画有关。CMIP6模式中降水和OLR的概率分布表明，在模拟ISM降水云方面存在显著差异。TaiESM1和IITM-ESM在捕捉MISO特征方面表现出改进。TaiESM1在夏季和冬季都表现出更好的MJO东传特征。IITM-ESM和TaiESM1模式中OLR和TCF的偏差也小于CanESM5和FGOALS-g3。结果表明，云和对流在CMIP6模式中对刻画真实的MISO和MJO至关重要，并为改进ISM气候预测和预估提供了路线图。
英文摘要：
The seasonal prediction of the Indian summer monsoon (ISM) and Monsoon Intraseasonal Oscillations (MISO), as well as the Madden Julian Oscillations (MJO) that strongly modulate MISO, is important to the country for water and crop management. We have analyzed the precipitation, convection, and total cloud fraction (TCF) in the sixth Coupled Model Intercomparison Projects (CMIP6). This study highlights the significant differences in simulating MISO and MJO between the two groups of selected CMIP6 models and physical reasons behind them. The mean and intraseasonal features of MISO and MJO varied significantly in CMIP6 models, which are linked with a better depiction of convection and total cloud fraction. The probability distributions of rainfall and OLR in CMIP6 models indicate significant variations in simulating ISM precipitating clouds. TaiESM1 and IITM-ESM demonstrate improvements in capturing the MISO features. TaiESM1 depicts better eastward propagation of MJO during both summer and winter. The biases in OLR and TCF are also less in the IITM-ESM and TaiESM1 models than in CanESM5 and FGOALS-g3. The results demonstrate the importance of cloud and convection in CMIP6 models to depict realistic MISO and MJO and provide a road map for improving ISM climate prediction and projections. Keywords: ISM rainfall, CMIP6 models, MISO, MJO
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