de Vries Iris, Sippel Sebastian, Zeder Joel, Fischer Erich, Knutti Reto
Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland.
Leipzig Institute for Meteorology, Leipzig University, Leipzig, Germany.
Commun Earth Environ. 2024;5(1):482. doi: 10.1038/s43247-024-01622-1. Epub 2024 Sep 3.
Climate events that break records by large margins are a threat to society and ecosystems. Climate change is expected to increase the probability of such events, but quantifying these probabilities is challenging due to natural variability and limited data availability, especially for observations and very rare extremes. Here we estimate the probability of precipitation events that shatter records by a margin of at least one pre-industrial standard deviation. Using large ensemble climate simulations and extreme value theory, we determine empirical and analytical record shattering probabilities and find they are in high agreement. We show that, particularly in high emission scenarios, models project much higher record-shattering precipitation probabilities in a changing relative to a stationary climate by the end of the century for almost all the global land, with the strongest increases in vulnerable regions in the tropics. We demonstrate that increasing variability is an essential driver of near-term increases in record-shattering precipitation probability, and present a framework that quantifies the influence of combined trends in mean and variability on record-shattering behaviour in extreme precipitation. Probability estimates of record-shattering precipitation events in a warming world are crucial to inform risk assessment and adaptation policies.
大幅突破纪录的气候事件对社会和生态系统构成威胁。预计气候变化将增加此类事件发生的概率,但由于自然变率和数据可用性有限,尤其是观测数据以及极为罕见的极端事件数据有限,对这些概率进行量化具有挑战性。在此,我们估算了降水量事件至少比工业化前标准差高出一个幅度从而打破纪录的概率。利用大型集合气候模拟和极值理论,我们确定了经验性和分析性的破纪录概率,并发现二者高度一致。我们表明,特别是在高排放情景下,到本世纪末,几乎全球所有陆地的模型预测,与稳定气候相比,气候变化情景下破纪录降水概率要高得多,热带脆弱地区的增幅最为显著。我们证明,变率增加是近期破纪录降水概率增加的一个重要驱动因素,并提出了一个框架,该框架量化了均值和变率的综合趋势对极端降水中破纪录行为的影响。对变暖世界中破纪录降水事件的概率估计对于风险评估和适应政策至关重要。