Finer grids in global climate models could lead to an improvement in the simulation of precipitation extremes. We assess the influence on model performance of increasing spatial resolution by evaluating pairs of high‐ and low‐resolution forced atmospheric simulations from six global climate models (generally the latest CMIP6 version) on a common 1° × 1° grid. The differences in tuning between the lower and higher resolution versions are as limited as possible, which allows the influence of higher resolution to be assessed exclusively. We focus on the 1985–2014 climatology of annual extremes of daily precipitation over global land, and models are compared to observations from different sources (i.e., in situ‐based and satellite‐based) to enable consideration of observational uncertainty. Finally, we address regional features of model performance based on four indices characterizing different aspects of precipitation extremes. Our analysis highlights good agreement between models that precipitation extremes are more intense at higher resolution. We find that the spread among observations is substantial and can be as large as intermodel differences, which makes the quantitative evaluation of model performance difficult. However, consistently across the four precipitation extremes indices that we investigate, models often show lower skill at higher resolution compared to their corresponding lower resolution version. Our findings suggest that increasing spatial resolution alone is not sufficient to obtain a systematic improvement in the simulation of precipitation extremes, and other improvements (e.g., physics and tuning) may be required.

中文翻译：

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全球气候模式中较高的空间大气分辨率对陆地上极端降水的影响

全球气候模型中更精细的网格可以改善极端降水的模拟。我们通过在共同的1°×1°网格上评估来自六个全球气候模型（通常是最新的CMIP6版本）的高分辨率和低分辨率强迫大气模拟对，来评估提高空间分辨率对模型性能的影响。较低分辨率版本和高分辨率版本之间的调整差异受到了尽可能小的限制，从而可以专门评估高分辨率的影响。我们专注于1985-2014年全球陆地上每日极端降水的极端气候，并将模型与来自不同来源（即，基于现场和基于卫星）的观测结果进行比较，以考虑观测不确定性。最后，我们基于表征极端降水不同方面的四个指标来处理模型性能的区域特征。我们的分析突出显示了模型之间的良好一致性，即在高分辨率下，极端降水更为强烈。我们发现观察值之间的差异很大，并且可能与模型间的差异一样大，这使得对模型性能的定量评估变得困难。但是，在我们调查的四个极端降水指数中，与相应的较低分辨率版本相比，模型在较高分辨率下通常显示出较低的技能。我们的发现表明，仅增加空间分辨率不足以在极端降水的模拟中获得系统的改善，可能还需要其他改善（例如物理和调整）。