The breaking of the United Kingdom's daily rainfall record in October 2020 made a striking addition to the list of recent heavy precipitation events in the country. Mounting evidence from attribution research suggests that such extremes become more frequent and intense in a warming climate. Although most studies consider extreme events in specific months or seasons, here we investigate for the first time how extremes of the wettest day of the year may be influenced by anthropogenic forcings. Data from large multimodel ensembles indicate that the moderate historical trend towards wetter conditions will emerge more strongly in coming decades, while a notable anthropogenic influence on the variability of the wettest day may be identified as early as the 1900s. Experiments with different forcings are employed to estimate the changing probability of extremes due to anthropogenic climate change in a risk-based attribution framework. We introduce a new methodology of estimating probabilities of extremes in the present and future that calibrates data from long simulations of the preindustrial climate to the mean state and variability of the reference climatic period. The new approach utilises larger samples of rainfall data than alternative methods, which is a major advantage when analysing extremely rare events. The record rainfall of the wettest day in year 2020 is estimated to have become about 2.5 times more likely because of human influence, while its return time, currently about 100 years, will decrease to only about 30 years by 2100. Compared to a hypothetical natural climate, we estimate a 10-fold increase in the chances of such extreme rainfall events in the United Kingdom by the end of this century, which underlines the need for effective adaptation planning.

中文翻译：

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英国破纪录的日降雨量和人为强迫的作用

英国在 2020 年 10 月打破了每日降雨量记录，在该国最近的强降水事件清单中又增加了一个惊人的补充。越来越多的归因研究证据表明，在气候变暖的情况下，此类极端事件变得更加频繁和强烈。尽管大多数研究都考虑了特定月份或季节的极端事件，但我们在这里首次调查了一年中最潮湿一天的极端事件如何受到人为强迫的影响。来自大型多模式集合的数据表明，在未来几十年中，更潮湿条件的温和历史趋势将更加强烈，而最早可能在 1900 年代确定对最潮湿日变化的显着人为影响。在基于风险的归因框架中，采用不同强迫的实验来估计由于人为气候变化引起的极端事件的变化概率。我们引入了一种估计当前和未来极端事件概率的新方法，该方法将来自工业化前气候长期模拟的数据校准到参考气候时期的平均状态和可变性。与替代方法相比，新方法利用了更大的降雨数据样本，这在分析极其罕见的事件时是一个主要优势。预计 2020 年最潮湿日的创纪录降雨由于人类影响而增加约 2.5 倍，而其重现时间目前约为 100 年，到 2100 年将减少至仅约 30 年。气候，