Most attribution studies tend to focus on the impact of anthropogenic forcing on individual variables. However, studies have already established that many climate variables are interrelated, and therefore, multidimensional changes can occur in response to climate change. Here, we propose a multivariate method which uses copula theory to account for underlying climate conditions while attributing the impact of anthropogenic forcing on a given climate variable. This method can be applied to any relevant pair of climate variables; here we apply the methodology to study high temperature exceedances given specified precipitation conditions (e.g., hot droughts). With this method, we introduce a new conditional probability ratio indicator, which communicates the impact of anthropogenic forcing on the likelihood of conditional exceedances. Since changes in temperatures under droughts have already accelerated faster than average climate conditions in many regions, quantifying anthropogenic impacts on conditional climate behavior is important to better understand climate change.

中文翻译：

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用于检测和归因复合气候极端事件的多元条件概率比框架

大多数归因研究倾向于关注人为强迫对个体变量的影响。然而，研究已经确定，许多气候变量是相互关联的，因此，应对气候变化可能会发生多维变化。在这里，我们提出了一种多变量方法，该方法使用 copula 理论来解释潜在的气候条件，同时将人为强迫的影响归因于给定的气候变量。这种方法可以应用于任何相关的气候变量对；在这里，我们应用该方法研究给定特定降水条件（例如，炎热干旱）的高温超标。通过这种方法，我们引入了一个新的条件概率比率指标，它传达了人为强迫对条件超标可能性的影响。