Using past episodes of climate change as a source of evidence to inform our projections about contemporary climate change requires establishing the extent to which episodes in the deep past are analogous to the current crisis. However, many scientists claim that contemporary rates of climate change (e.g., rates of carbon emissions or temperature change) are unprecedented, including compared to episodes in the deep past. If so, this would limit the utility of paleoclimate analogues. In this paper, I show how a data adjustment procedure called "temporal scaling," which must be applied to both contemporary and past rate data, complicates the claim that contemporary rates are truly unprecedented. On top of giving actionable recommendations to scientists, this paper advances the philosophical literature concerning the use of models that are known to be somewhat disanalogous to their target systems.

中文翻译：

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气候科学中的缩放程序：使用时间缩放来识别古气候类似物。

使用过去的气候变化事件作为证据来源来为我们对当代气候变化的预测提供信息，需要确定过去的事件与当前危机的相似程度。然而，许多科学家声称，当代气候变化的速度（例如碳排放或温度变化的速度）是前所未有的，包括与遥远的过去相比。如果是这样，这将限制古气候类似物的实用性。在本文中，我展示了一种称为“时间缩放”的数据调整程序，它必须应用于当代和过去的利率数据，如何使当代利率确实史无前例的主张变得复杂。除了向科学家提供可行的建议之外，本文还提出了有关使用已知与其目标系统有些不相似的模型的哲学文献。