The North Atlantic Oscillation (NAO) is predictable in climate models at near-decadal timescales. Predictive skill derives from ocean initialization, which can capture variability internal to the climate system, and from external radiative forcing. Herein, we show that predictive skill for the NAO in a very large uninitialized multi-model ensemble is commensurate with previously reported skill from a state-of-the-art initialized prediction system. The uninitialized ensemble and initialized prediction system produce similar levels of skill for northern European precipitation and North Atlantic SSTs. Identifying these predictable components becomes possible in a very large ensemble, confirming the erroneously low signal-to-noise ratio previously identified in both initialized and uninitialized climate models. Though the results here imply that external radiative forcing is a major source of predictive skill for the NAO, they also indicate that ocean initialization may be important for particular NAO events (the mid-1990s strong positive NAO), and, as previously suggested, in certain ocean regions such as the subpolar North Atlantic ocean. Overall, we suggest that improving climate models’ response to external radiative forcing may help resolve the known signal-to-noise error in climate models.

在近十年的时间尺度上，北半球涛动（NAO）在气候模型中是可预测的。预测技能源于海洋初始化（可捕获气候系统内部的变化）和外部辐射强迫。本文中，我们显示了在非常大的未初始化多模型集合中，NAO的预测技能与最新报告的来自最先进的初始化预测系统的技能相当。未初始化的集合和初始化的预测系统对北欧的降水和北大西洋的SST产生了相似的技能。在非常大的整体中识别这些可预测的成分成为可能，从而确认了先前在初始化和未初始化的气候模型中识别出的错误的低信噪比。尽管这里的结果暗示着外部辐射强迫是NAO预测技能的主要来源，但它们也表明海洋初始化对于特定的NAO事件（1990年代中期强阳性NAO）可能是重要的，并且，如先前所建议，某些海洋区域，例如北极亚极洋。总体而言，我们建议改善气候模型对外部辐射强迫的响应可能有助于解决气候模型中已知的信噪比误差。