The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.

中文翻译：

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辐射对流平衡模拟多模型系综中的云和对流自聚集


辐射对流平衡模型比对项目（RCEMIP）是对辐射对流平衡（RCE）中配置的多种类型数值模型的比对。 RCE 是热带大气的理想化，长期以来一直用于研究气候科学的基本问题。在这里，我们利用 RCE 来研究云和对流活动在确定云反馈、气候敏感性、对流聚集状态和平衡气候方面所起的作用。 RCEMIP 在比较中的独特之处在于它包含广泛的模型类型，包括大气环流模型 (GCM)、单柱模型 (SCM)、云解析模型 (CRM)、大涡模拟 (LES) 和全球云‐解析模型（GCRM）。第一个结果来自 30 多个模型的 RCMIP 集合。虽然 RCEMIP 系综在温度、湿度和云量平均剖面的表示方面存在很大差异，但在大多数模型中，砧云会随着海面温度（SST）的增加而上升、变暖和面积覆盖范围的减少。 ）。几乎所有模型都在大范围内表现出自聚集，并一致认为自聚集会导致对流层干燥和变暖、减少高云量并增加太空冷却。自聚集程度随变暖没有表现出明显的趋势。气候敏感性范围很广，但参数化对流模型的气候敏感性往往比显式对流模型的气候敏感性低。在参数化对流模型中，聚合模拟的气候敏感性低于非聚合模拟。