Investigations into the role of anthropogenic emissions in the occurrence of extreme weather often use a method that compares simulations of atmospheric climate models run under a factual scenario of historical boundary conditions observed during the period of the event against simulations run under a counterfactual scenario of what those boundary conditions might naturally have been over that same period in the absence of anthropogenic emissions. A particular requirement for this experiment design is an accurate estimation of ocean surface boundary conditions for use by the counterfactual natural simulations. Here we use output from the CMIP5 multi‐climate‐model archive to develop a robust estimate of sea surface temperatures and sea ice conditions for use in counterfactual natural simulations, intended as a benchmark estimate to facilitate comparison across climate models and across studies. This development includes tests to ensure that the final estimate is stable from year‐to‐year and stable against other perturbations to the methodology, as well as consideration of the strengths and weaknesses in comparison to other available attributable warming estimates. While this estimate is tailored specifically for the International CLIVAR C20C+ Detection and Attribution Project, it can be used by related projects as well.

中文翻译：

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人为排放对海洋表面影响的基准估计

对人为排放在极端天气发生中的作用的调查通常使用一种方法，该方法将在事件期间观察到的历史边界条件的事实场景下运行的大气气候模型模拟与在那些事件的反事实场景下运行的模拟进行比较。在没有人为排放的情况下，边界条件自然可能在同一时期。该实验设计的一个特殊要求是要对反面自然模拟所使用的海洋表面边界条件进行准确的估算。在这里，我们使用CMIP5多气候模型档案库的输出来开发可靠的海面温度和海冰条件估计，以用于反事实自然模拟中，旨在作为基准估计数，以促进跨气候模型和跨研究的比较。这项开发包括进行测试以确保最终估计值每年都稳定，并且不受方法的其他干扰影响，以及与其他可归因的变暖估计值相比要考虑的优缺点。尽管此估计是专门为国际CLIVAR C20C +检测和归因项目量身定制的，但也可以由相关项目使用。