Zscheischler Jakob, Seneviratne Sonia I
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland.
Sci Adv. 2017 Jun 28;3(6):e1700263. doi: 10.1126/sciadv.1700263. eCollection 2017 Jun.
Compound climate extremes are receiving increasing attention because of their disproportionate impacts on humans and ecosystems. However, risks assessments generally focus on univariate statistics. We analyze the co-occurrence of hot and dry summers and show that these are correlated, inducing a much higher frequency of concurrent hot and dry summers than what would be assumed from the independent combination of the univariate statistics. Our results demonstrate how the dependence structure between variables affects the occurrence frequency of multivariate extremes. Assessments based on univariate statistics can thus strongly underestimate risks associated with given extremes, if impacts depend on multiple (dependent) variables. We conclude that a multivariate perspective is necessary to appropriately assess changes in climate extremes and their impacts and to design adaptation strategies.
复合气候极端事件因其对人类和生态系统产生的不成比例影响而受到越来越多的关注。然而，风险评估通常侧重于单变量统计。我们分析了炎热干燥夏季的同时出现情况，并表明它们是相关的，导致炎热干燥夏季同时出现的频率远高于单变量统计独立组合所假设的频率。我们的结果表明变量之间的依赖结构如何影响多变量极端事件的发生频率。因此，如果影响取决于多个（相关）变量，基于单变量统计的评估可能会严重低估与特定极端事件相关的风险。我们得出结论，多元视角对于适当评估气候极端事件的变化及其影响以及设计适应策略是必要的。
