Extreme and impactful weather events of the recent past provide a vital but under-utilised data source for understanding present and future climate risks. Extreme event attribution (EEA) enables us to quantify the influence of anthropogenic climate change (ACC) on a given event in a way that can be tailored to stakeholder needs, thereby enhancing the potential utility of studying past events. Here we set out a framework for systematically recording key details of high-impact events on a national scale (using the UK and Puerto Rico as examples), combining recent advances in event attribution with the risk framework. These ‘inventories’ inherently provide useful information depending on a user’s interest. For example, as a compilation of the impacts of ACC, we find that in the UK since 2000, at least 1500 excess deaths are directly attributable to human-induced climate change, while in Puerto Rico the increased intensity of Hurricane Maria alone led to the deaths of up to 3670 people. We also explore how inventories form a foundation for further analysis, learning from past events. This involves identifying the most damaging hazards and crucially also vulnerabilities and exposure characteristics over time. To build a risk assessment for heat-related mortality in the UK we focus on a vulnerable group, elderly urban populations, and project changes in the hazard and exposure within the same framework. Without improved preparedness, the risk to this group is likely to increase by ~50% by 2028 and ~150% by 2043. In addition, the framework allows the exploration of the likelihood of otherwise unprecedented events, or 'Black Swans’. Finally, not only does it aid disaster preparedness and adaptation at local and national scales, such inventories also provide a new source of evidence for global stocktakes on adaptation and loss and damage such as mandated by the Paris Climate Agreement.

最近的极端极端天气事件为理解当前和未来的气候风险提供了重要但未充分利用的数据源。极端事件归因（EEA）使我们能够以适合利益相关者需求的方式量化人为气候变化（ACC）对给定事件的影响，从而增强研究过去事件的潜在效用。在这里，我们建立了一个框架，将事件归因的最新进展与风险框架相结合，从而在全国范围内系统地记录高影响事件的关键细节（以英国和波多黎各为例）。这些“清单”根据用户的兴趣固有地提供有用的信息。例如，根据ACC的影响汇编，我们发现自2000年以来，在英国，至少有1500多例额外死亡直接归因于人为引起的气候变化，而在波多黎各，仅飓风玛丽亚的强度增加导致多达3670人死亡。我们还将探讨库存如何形成基础，以便从过去的事件中吸取教训，进行进一步的分析。随着时间的推移，这涉及确定最具破坏性的危害，以及至关重要的脆弱性和暴露特征。为了在英国建立与热相关的死亡率的风险评估，我们将重点放在弱势群体，城市老年人群上，并在同一框架内预测危害和暴露的变化。如果没有更好的准备，该群体的风险到2028年可能会增加约50％，到2043年会增加约150％。此外，该框架还允许探索否则会发生前所未有的事件或“黑天鹅”的可能性。