Weather extremes pose major societal risks, especially in a changing climate, but due to their rarity, they are difficult to study using limited observations or complex climate models. We introduce AI+RES, a framework coupling fast AI weather forecasts with a high-fidelity physics model using a rare-event algorithm to efficiently characterize extremes. This approach enables the study of the statistics and physics of very rare events, such as once per millennium heatwaves at two orders-of-magnitude lower computational cost. AI+RES can be applied broadly across climate science and other fields concerned with rare events.

翻译：极端天气事件构成了重大的社会风险，尤其在气候变化背景下，但由于其罕见性，难以通过有限的观测数据或复杂的气候模型进行研究。我们提出了AI+RES框架，该框架通过罕见事件算法将快速AI天气预报与高保真物理模型耦合，以高效表征极端事件。该方法能够以降低两个数量级的计算成本，研究诸如千年一遇的热浪等极其罕见事件的统计特征与物理机制。AI+RES可广泛应用于气候科学及其他关注罕见事件的领域。