解缠指纹表明大西洋经向翻转环流和副极地环流没有历史性减弱
Disentangled Fingerprints suggest no historical weakening of Atlantic Overturning and Subpolar Gyre
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中文总结 AI 辅助
本研究利用统计最优指纹区分AMOC与副极地环流，发现传统指纹无法分离两者，而新指纹表明近几十年AMOC并无显著减弱，但也不排除失稳风险。
中文摘要 AI 辅助
AMOC（大西洋经向翻转环流）和副极地环流（Subpolar Gyre）是地球气候系统的关键组成部分，两者在人为强迫下都可能趋于失稳并发生突变。鉴于AMOC和SPG对全球气候的强烈影响，检测其稳定性变化至关重要，但观测记录长度有限阻碍了这一检测。在缺乏长期直接AMOC观测的情况下，已有若干基于观测的AMOC指纹被提出。然而，现有指纹未能清晰区分SPG和AMOC变率，而是反映了两者动力学的模糊混合。在此，我们评估了广泛使用的AMOC指纹在CMIP6模型中的表现，并将其与我们从海表温度和盐度中推导出的统计最优指纹进行比较。我们表明，传统AMOC指纹与AMOC和SPG强度均呈现弱相关。相比之下，我们在工业化前控制模拟上训练得到的统计最优指纹，在独立的piControl模拟段和历史实验中持续优于现有方法。这些指纹在最小化重叠的同时准确重建了AMOC和SPG变率，从而能够清晰分离这两个系统。我们的结果提供了首批能够稳健区分AMOC和SPG的定制观测指纹，展示了统计优化方法在改进大西洋环流变化（包括潜在临界行为的先兆信号）检测和归因方面的潜力。将我们的方法应用于海表温度观测，我们发现优化指纹并未证实传统指纹所暗示的近几十年AMOC显著减弱，但也不排除稳定性丧失的可能性。
英文摘要
The AMOC and the Subpolar Gyre are key components of the Earth's climate system, both potentially prone to destabilization and abrupt shifts under anthropogenic forcing.Given the strong influence of the AMOC and the SPG on global climate, detecting changes in their stability is of high importance, yet is hindered by the limited length of observational records.In the absence of long-term direct AMOC observations, several observation-based fingerprints of the AMOC have been proposed.However, existing fingerprints do not clearly distinguish between SPG and AMOC variability, instead reflecting an opaque mixture of dynamics from both systems.Here, we assess the performance of widely used AMOC fingerprints across CMIP6 models and compare them with statistically optimal fingerprints that we derive from sea surface temperature and salinity.We show that traditional AMOC fingerprints exhibit weak correlations with both AMOC and SPG strength.In contrast, our statistically optimal fingerprints, trained on pre-industrial control simulations, consistently outperform existing approaches across independent segments of piControl simulations and historical experiments.These fingerprints accurately reconstruct AMOC and SPG variability while minimizing overlap, enabling a clear separation between the two systems.Our results provide the first tailored observational fingerprints that robustly distinguish AMOC and SPG, demonstrating the potential of statistically optimized approaches to improve detection and attribution of changes in Atlantic circulation, including precursor signals of potential tipping behavior.Applying our approach to sea surface temperature observations, we find that our optimized fingerprints do not confirm the substantial AMOC weakening in the recent decades as suggested by traditional fingerprints, but also do not rule out a loss of stability.
发表机构
- University of Copenhagen, Niels Bohr Institute（哥本哈根大学尼尔斯·玻尔研究所）
- Technical University Munich（慕尼黑工业大学）
- Potsdam Institute for Climate Impact Research（波茨坦气候影响研究所）
- Seoul National University（首尔国立大学）
- Institute for Sustainable Development, Seoul National University（首尔国立大学可持续发展研究所）
- Global Systems Institute and Department of Mathematics, University of Exeter（埃克塞特大学全球系统研究所和数学系）
机构由 AI 辅助整理，请以论文原文为准。
