Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ∼25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large‐scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large‐scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large‐scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large‐scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale‐aware parameterizations, but also reveal unrecognized trade‐offs from the entanglement of precipitation frequency and total amount.

中文翻译：

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来自解析过程而不是参数化过程的降雨更好地代表了社区大气模型中中等速率的当今和气候变化响应


全球气候模型中使用的对流参数化的缺陷常常导致模拟降雨强度分布的扭曲（即降雨率弱导致降雨过多）。虽然随着社区大气模型的水平分辨率增加到约 25 公里，高百分位数降雨强度有了令人鼓舞的改善，但我们证明产生大部分累积降雨的中雨率没有相应的改善。使用旨在强调降水强度和累积降雨量之间联系（而不仅仅是频率分布）的统计框架，我们表明 CAM 无法真实地模拟中等降雨率，并且即使分辨率提高，也无法捕获其随气候变化的加剧。然而，通过区分参数化对流和大尺度解析对总降雨量的贡献，我们发现 CAM 大尺度降雨率的强度、地理格局和气候变化响应与观测结果 (TRMM 3B42)、超参数化和尽管参数化对流存在问题，但仍符合理论预期。增加 CAM 的水平分辨率确实改善了总降雨强度的表示，但并不是由于大范围降雨率强度的变化，而大范围降雨率的强度对水平分辨率却出人意料地不敏感。相反，改善是通过增加大尺度部分对累积降雨总量的相对贡献来实现的。 对对流时间尺度和夹带率的敏感性分析证实了这些参数在尺度感知参数化的可能发展中的重要性，但也揭示了降水频率和总量的纠缠中未被认识到的权衡。