Under global warming, changes in extreme temperatures will manifest in more complex ways in locations where temperature distribution tails deviate from Gaussian. Confidence in global climate model (GCM) projections of temperature extremes and associated impacts therefore relies on the realism of simulated temperature distribution tail behavior under current climate conditions. This study evaluates the ability of the latest state-of-the-art ensemble of GCMs from the Coupled Model Intercomparison Project phase six (CMIP6), to capture historical global surface temperature distribution tail shape in hemispheric winter and summer seasons. Comparisons with a global reanalysis product reveal strong agreement on coherent spatial patterns of longer- and shorter-than-Gaussian tails for both sides of the temperature distribution, suggesting that CMIP6 GCMs are broadly capturing tail behavior for plausible physical and dynamical reasons. On a global scale, most GCMs are reasonably skilled a...

中文翻译：

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在模拟非高斯温度分布尾部时评估CMIP6模型的保真度

在全球变暖的情况下，极端温度的变化将在温度分布的尾部偏离高斯的位置以更复杂的方式表现出来。因此，对全球气候模型（GCM）预测极端温度和相关影响的信心取决于当前气候条件下模拟温度分布尾部行为的真实性。这项研究评估了耦合模型比较项目第六阶段（CMIP6）的最新最先进GCM集合捕获半球冬季和夏季历史全球表面温度分布尾形的能力。与全球再分析产品进行的比较表明，在温度分布的两侧，长尾短于高斯的尾巴的相干空间模式具有高度一致性，这表明CMIP6 GCM由于合理的物理和动力学原因而广泛捕获了尾巴行为。在全球范围内，大多数GCM都具有相当熟练的技能。