The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top-of-the-atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all-sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less-negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes.

中文翻译：

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大气层顶部短波北极云反馈：诊断方法的比较

云反馈可能会导致北极变暖的放大或减弱。用于诊断顶层云反馈的两种常用技术是调整云辐射效应（AdjCRE）方法和云辐射核（CRK）方法。我们将其应用于 CMIP5 和 CMIP6 模型数据，发现 AdjCRE 计算的北极短波云反馈与 CMIP5 中海冰损失的相关性是 CRK 方法的两倍，在 CMIP6 中是四倍。我们发现，CRK 方法在 18 个模型中的 15 个模型中产生的北极全天空剩余百分比超过 20%。我们使用CRK方法分解CMIP5和CMIP6中的反馈，发现其中值在负值较小的云光学深度反馈的驱动下从负值变为正值。尽管缺乏封闭性，我们得出的结论是，CRK 方法更适合北极 SW 反馈，因为它受地表反照率变化的影响较小。