Global mean precipitation is expected to increase with increasing temperatures, a process which is fairly well understood. In contrast, local precipitation changes, which are key for society and ecosystems, demonstrate a large spread in predictions by climate models, can be of both signs and have much larger magnitude than the global mean change. Previously, two top-down approaches to constrain precipitation changes were proposed, using either the atmospheric water or energy budget. Here, using an ensemble of 27 climate models, we study the relative importance of these two budgetary constraints and present analysis of the spatial scales at which they hold. We show that specific geographical locations are more constrained by either one of the budgets and that the combination of water and energy budgets provides a significantly stronger constraint on the spatial scale of precipitation changes under anthropogenic climate change (on average about 3000 km, above which changes in precipitation approach the global mean change). These results could also provide an objective way to define the scale of ‘regional’ climate change.

众所周知，全球平均降水量将随着温度的升高而增加。相反，对社会和生态系统至关重要的局部降水变化，在气候模型的预测中显示出很大的扩散，可能是两个迹象，而且幅度要比全球平均变化大得多。以前，提出了两种使用大气水或能源预算来约束降水变化的自上而下的方法。在这里，我们使用27个气候模型的集合，研究了这两个预算约束的相对重要性，并提出了它们所占空间尺度的分析。我们显示，特定地理位置受到预算之一的限制更大，而水和能源预算的组合对人为气候变化（平均约3000 km，高于该距离的降水量）的降水变化的空间尺度提供了明显更强的约束。在降水方法中，全球平均变化）。这些结果也可以提供一种客观的方法来定义“区域性”气候变化的规模。