AI 中文总结
本研究以midHolocene实验数据测试海洋气候模拟器，发现其可泛化到新轨道强迫但低估振幅，无法重现海洋内部内部驱动演化，确立midHolocene为诊断模拟器强迫响应失败的场景。
AI 中文摘要
AI天气模拟器因明确的目标和指标受益，推动其发展速度远超传统基准。相比之下，长期气候模拟器必须可靠重现数月至数百年的强迫响应，却依赖仅覆盖少量模型时间步长的训练目标。我们利用数值气候模型的midHolocene（中全新世）实验数据评估自回归全深度海洋模拟器，检验其对来自分布内样本外气候的地表强迫的响应能力。研究表明，这些模拟器可泛化到新的轨道强迫，重现大尺度响应的空间结构，以及季节模式和海洋变率空间结构的变化，但会低估其振幅。直接从边界强迫推断海洋状态的基准模型也能恢复大部分大尺度模式，但仅在近地表区域，无法捕捉季节或变率变化，说明这些基准需要一定的动力学表征。尽管取得这些成功，模拟器仍无法重现海洋内部缓慢的内部驱动演化。随后我们发现，模拟器的总强迫响应可通过线性组合其对每个强迫分量的独立响应良好重建。跟踪训练轮次的响应可知，训练气候中平均状态指标的收敛并不能保证模拟器能捕捉到实现熟练响应所需的动力学。综上，这些实验确立了midHolocene作为受控、有真实值的场景，可在模拟器被推向分布外气候前，用于诊断其强迫响应失败问题。
英文摘要
AI weather emulators benefit from clear objectives and metrics, which have led to the rapid development of models that outperform traditional benchmarks. In contrast, long-term climate emulators must reliably reproduce forced responses over months to centuries, while relying on training objectives that span a small number of model time steps. We assess autoregressive, full-depth ocean emulators using data from the midHolocene experiment of a numerical climate model to examine their skill in responding to surface forcings from an in-distribution, out-of-sample climate. We demonstrate that these emulators generalize to new orbital forcings, reproducing the spatial structure of the large-scale response as well as changes in seasonal patterns and in the spatial structure of ocean variability, while underestimating their amplitude. Baselines that infer the ocean state directly from the boundary forcings also recover much of the large-scale pattern, but only near the surface, and capture neither the seasonal nor the variability changes, indicating that these require some representation of dynamics. Despite these successes, the emulators fail to reproduce the slow, internally driven evolution of the ocean interior. We then show that the emulators' total forced response is well reconstructed by linearly composing their independent responses to each forcing component. Tracking response across training epochs, we find that convergence on mean state metrics in the training climate does not guarantee that the emulators capture the dynamics necessary for a skillful response. Together, these experiments establish the midHolocene as a controlled, ground-truthed setting for diagnosing forced-response failures before emulators are pushed to out-of-distribution climates.
