Abstract The impact of cloud representation on the simulation of mid-latitude recurrent large-scale flows and forecast skill of mid-latitude atmospheric teleconnections is evaluated using the Community Climate System Model, version 4 (CCSM4), and the super-parameterized CCSM4 (SP-CCSM4). Patterns of low-level atmospheric circulation anomalies and convection associated with the Madden–Julian oscillation (MJO) are affected by the method used for the representation of cloud processes. The configuration of the model using super-parameterization for the representation of cloud processes produces MJO-related patterns that agree better with observations than the configuration of the model using a conventional cloud parameterization scheme. The recurrent circulation regimes of the mid-latitudes are also sensitive to the representation of cloud processes. In the North Atlantic sector, the inability of CCSM4 to simulate the Scandinavian blocking regime is corrected in the super-parameterized version of the model. In the North Pacific sector, the strength of the clustering (measured by a variance ratio) is too large in CCSM4 compared with observations and SP-CCSM4. The SP-CCSM4 model has better forecast skill for the MJO amplitude and phase than the model with conventional representation of moist convective processes. In turn, the improved forecast skill of the super-parameterized model results in better forecast skill for mid-latitude teleconnections in 500 hPa geopotential height anomalies forced by the MJO convection.

中文翻译：

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云表示对北半球大气遥相关和首选环流制度的亚季节预报的影响

摘要 使用社区气候系统模型第 4 版 (CCSM4) 和超参数化 CCSM4 (SP -CCSM4)。与麦登-朱利安振荡 (MJO) 相关的低层大气环流异常和对流模式受到用于表示云过程的方法的影响。使用超参数化来表示云过程的模型配置产生了与 MJO 相关的模式，与使用传统云参数化方案的模型配置相比，这些模式与观测更吻合。中纬度地区的循环环流方式也对云过程的表征很敏感。在北大西洋扇区，CCSM4 无法模拟斯堪的纳维亚阻塞机制的问题在模型的超参数化版本中得到纠正。在北太平洋扇区，CCSM4 中的聚类强度（通过方差比衡量）与观测值和 SP-CCSM4 相比太大。SP-CCSM4 模型对 MJO 振幅和相位的预测能力比传统的湿对流过程表示模型更好。反过来，超参数化模型的改进预测技能导致对 MJO 对流强迫的 500 hPa 位势高度异常中的中纬度遥相关更好的预测技能。在北太平洋扇区，CCSM4 中的聚类强度（通过方差比衡量）与观测值和 SP-CCSM4 相比太大。SP-CCSM4 模型对 MJO 振幅和相位的预测能力比传统的湿对流过程表示模型更好。反过来，超参数化模型的改进预测技能导致对 MJO 对流强迫的 500 hPa 位势高度异常中的中纬度遥相关更好的预测技能。在北太平洋扇区，CCSM4 中的聚类强度（通过方差比衡量）与观测值和 SP-CCSM4 相比太大。SP-CCSM4 模型对 MJO 振幅和相位的预测能力比传统的湿对流过程表示模型更好。反过来，超参数化模型的改进预测技能导致对 MJO 对流强迫的 500 hPa 位势高度异常中的中纬度遥相关更好的预测技能。