Using a New Inventory of Extreme Weather Events to Understand Changing Risks: Implications for Future Climate Resilience

使用新的极端天气事件清单来了解不断变化的风险：对未来气候适应能力的影响

• 批准号: 2099950
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2099950
• 关键词: Using; New; Inventory; Extreme; Weather

Changing patterns of extreme weather are among the most visible effects of climate change, and the earliest to appear. There is a vast array of stakeholders, from public to policy-makers, with vested interests in understanding the nature and magnitude of these changes. Attribution science arose as a way of providing these stakeholders with accessible, useful and reliable information, and as the science continues to develop, ever-increasing emphasis is being put on the requirements of the end user. In particular, this suggests a need for greater focus on the extent to which the actual impacts of extreme weather can be attributed to climate change; how risks are changing, rather than simply event likelihoods. This view is more informative for policy-makers, makes liability more evident for civil society, and is simply a more accessible form of data. To this end, attribution analyses that provide impact-based information have become more common, and a recent pathfinder report commissioned by the New-Zealand government made an estimate of the attributable cost of extreme weather for NZ over the past decade using a simple probabilistic approach. Given these advances in the literature and increasingly well-established multi-method frameworks for attribution statements, it is concluded that the time is ripe for a more comprehensive study of the impacts that can be directly attributed to anthropogenic climate change. The UK is an obvious area to test this concept, thanks to the wealth of existing event attribution literature, high availability of meteorological data and range of geographically specific, high-resolution impact models that can accurately reproduce meteorological hazards such as flooding.

极端天气模式的变化是气候变化最明显的影响之一，也是最早出现的。从公众到政策制定者，各种各样的利益攸关方在了解这些变化的性质和规模方面都有既得利益。归因科学的出现是为了向这些利益相关者提供可访问的、有用的和可靠的信息，随着科学的不断发展，越来越多的重点放在最终用户的要求上。特别是，这表明需要更加关注极端天气的实际影响在多大程度上可归因于气候变化;风险如何变化，而不仅仅是事件的可能性。这一观点对决策者来说信息量更大，使民间社会的责任更加明显，而且只是一种更容易获得的数据形式。为此，提供基于影响的信息的归因分析变得越来越普遍，新西兰政府最近委托的一份探路者报告使用简单的概率方法对新西兰过去十年极端天气的归因成本进行了估计。鉴于这些进展的文献和日益完善的多方法框架归因声明，它的结论是，时机已经成熟，可以直接归因于人为气候变化的影响进行更全面的研究。英国是一个明显的测试这一概念的地区，这要归功于丰富的现有事件归因文献，高可用性的气象数据和范围的地理特定的，高分辨率的影响模型，可以准确地再现气象灾害，如洪水。