Internal variability arising from the inherently chaotic nature of the climate system has amplified or obscured human-caused changes, especially at regional scales in the extratropics, where its contribution to climate variability is the largest. It is virtually certain that this will continue in the near-term. We here focus on the Northern Europe region, whose variability is largely controlled by the North Atlantic Oscillation (NAO) and the Atlantic Meridional Overturning Circulation (AMOC) through remote dynamical and thermodynamic processes, and introduce the concept of internal variability storylines (IVS) to explore, understand, and quantify the role of the two combined drivers of internal variability in the modulation of the anthropogenic warming by 2040 in winter. Based on a large ensemble of historical-scenario simulations, we show that the high-impact IVS, characterised by weak AMOC decline and a decadal shift of the NAO toward dominant positive phase, leads faster to warmer-wetter conditions independently of actual and future greenhouse gases emissions. By contrast, amplified AMOC reduction and more recurrent negative NAO can considerably damp both warming and wettening at near-term. In the latter IVS, we provide evidence that winter-severe conditions similar to those in 2010, that had been responsible for widespread socio-economic disruptions, remain almost as likely to occur by 2040. Reframing the uncertain climate outcomes into the physical science space in a conditional form through the prism of IVS makes climate information relevant for accurate risk assessments and adaptation planning.

气候系统固有的混乱性质引起的内部变率放大或掩盖了人为变化，尤其是在热带以外的区域尺度上，它对气候变率的贡献最大。几乎可以肯定，这种情况将在短期内持续下去。我们在这里关注北欧地区，该地区的变率主要由北大西洋涛动 （NAO） 和大西洋经向翻转环流 （AMOC） 通过远程动力学和热力学过程控制，并引入内部变率故事情节 （IVS） 的概念，以探索、理解和量化内部变率的两个综合驱动因素在 2040 年冬季人为变暖调节中的作用。基于大量历史情景模拟，我们表明，高影响的 IVS，其特征是 AMOC 下降较弱和 NAO 向占主导地位的正相位的年代际转移，导致更快的温暖-潮湿条件，而与实际和未来的温室气体排放无关。相比之下，放大的 AMOC 减少和更反复的负 NAO 可以在短期内大大抑制变暖和变湿。在后一份 IVS 中，我们提供的证据表明，到 2040 年，与 2010 年类似的冬季严酷条件（造成了广泛的社会经济破坏）的可能性几乎相同。通过 IVS 的棱镜，将不确定的气候结果以条件形式重新构建到物理科学领域，使气候信息与准确的风险评估和适应规划相关。