A large parameter-perturbed ensemble (PPE) of the Met Office climate model is used to explore the relationship between radiative feedbacks and the present-day simulation of the associated physical processes. We highlight three tropical regimes (deep convection over ocean and land, and marine stratocumulus) in which the same set of processes drives the present-day simulation of clouds and their feedbacks. In each case, the amount of the dominant cloud types reduces in response to warming and the reduction is approximately proportional to the amount simulated in the present day. In deep convective regions, convective process parameters lead the spread among multiple contributing processes, with vegetation processes contributing as well for the land regions. Multiple parameters, such as boundary layer processes, drive stratocumulus regions. However, the low-thick clouds are systematically overestimated, suggesting a structural error in their process representations which would limit the efficacy of the constraint. The influence of convection is largely confined to the tropical deep convective regions in the present day but extends to mid-latitudes under warming. Because of this, contributing processes to the spread in the present-day and the response are different in the extra-tropics, making it much more difficult to establish links between the present-day and the feedback within the region. This suggests that identifying a constraint on convective processes in the tropics for the present-day simulations could constrain both the tropical feedbacks and feedbacks in the extra-tropics. A parameter representing deep-convective entrainment links the present-day tropical mean high cloud and clear-sky longwave flux to their feedbacks in our model, suggesting a potential process constraint from the observations. Understanding and improving the detailed processes controlling feedbacks is ultimately only possible in individual models. Different process-based constraints might be inferred for different models. The approach described here could usefully extended to other single model ensembles and the collective understandings could be valuable for improving model process and feedbacks more generally.

大都会办公室气候模型的一个大参数扰动集合体（PPE）用于探索辐射反馈与相关物理过程的当前模拟之间的关系。我们重点介绍了三种热带气候模式（海洋和陆地的深对流以及海洋平流积云），其中相同的过程集合驱动了当今对云及其反馈的模拟。在每种情况下，主要云类型的数量都随着变暖而减少，并且减少量与当前模拟的数量大致成比例。在深对流地区，对流过程参数导致了多个贡献过程之间的扩散，而植被过程对陆地区域也有贡献。诸如边界层过程之类的多个参数驱动平积层区域。然而，低层云被系统地高估，表明它们的过程表示存在结构错误，这将限制约束的有效性。对流的影响目前主要局限于热带深对流地区，但在变暖的情况下扩展到中纬度地区。因此，在热带地区，对当今传播的贡献过程和响应有所不同，这使得在当今与区域内的反馈之间建立联系变得更加困难。这表明，为当前的模拟确定对热带对流过程的约束可能会同时约束热带反馈和热带外反馈。在我们的模型中，代表深对流夹带的参数将当今的热带平均高云和晴空长波通量与它们的反馈联系起来，暗示了观测的潜在过程约束。最终只有在单个模型中才能理解和改进控制反馈的详细过程。对于不同的模型，可以推断出不同的基于过程的约束。此处描述的方法可以有效地扩展到其他单个模型集合，并且集体理解对于更广泛地改进模型过程和反馈可能是有价值的。对于不同的模型，可以推断出不同的基于过程的约束。此处描述的方法可以有效地扩展到其他单个模型集合，并且集体理解对于更广泛地改进模型过程和反馈可能是有价值的。对于不同的模型，可以推断出不同的基于过程的约束。此处描述的方法可以有效地扩展到其他单个模型集合，并且集体理解对于更广泛地改进模型过程和反馈可能是有价值的。