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 of much importance to the agriculture sectors of the Indian Sub-continent. This study highlights the importance of selecting proper “autoconversion” coefficients for precipitation formation in Coupled Global Climate Model's convective and microphysical schemes in simulating MISO and MJO. With a series of sensitivity experiments, we systematically examined the convective autoconversion and microphysical autoconversion coefficients in the National Centers for Environmental Prediction Coupled Forecast System version 2 (CFSv2). The mean and intraseasonal features of MISO and MJO are improved with a proper combination of autoconversion coefficients, which not only provide a better partition of cloud water and ice but also better feedback between the large-scale condensation and convective parameterization. The results demonstrate a road map for the improvement of MISO as well as MJO simulation using a coupled climate model.

中文翻译：

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微物理学和对流自转换在更好地模拟热带季节内振荡（MISO 和 MJO）中的作用

印度夏季风 (ISM) 和季风季节内振荡 (MISO) 以及强烈调节 MISO 的马登朱利安振荡 (MJO) 的季节性预测对印度次大陆的农业部门非常重要。本研究强调了在模拟 MISO 和 MJO 的耦合全球气候模型的对流和微物理方案中为降水形成选择合适的“自动转换”系数的重要性。通过一系列灵敏度实验，我们系统地检查了国家环境预测中心耦合预报系统第 2 版 (CFSv2) 中的对流自动转换和微物理自动转换系数。MISO 和 MJO 的平均和季节内特征通过自动转换系数的适当组合得到改善，这不仅提供了更好的云水和冰分区，而且在大规模凝结和对流参数化之间提供了更好的反馈。结果展示了使用耦合气候模型改进 MISO 和 MJO 模拟的路线图。