预测临界点：非平衡的多种面貌与早期预警的进退两难

中文摘要 AI 辅助

气候临界点（TP）被跨越的可能性已引起许多研究人员和公众的关注。一方面，这种担忧的基础正在加强，模拟表明即使在中度排放情景下也可能发生突变。另一方面，我们对这类转变在数学上构成何种条件的理解正变得更加细致入微。这给早期预警信号（EWS）的保真度带来了挑战，这些信号伴随在缓慢变化的稳态附近紧密跟踪的系统中发生的分岔。快速变化的气候中不同类型的非平衡动力学以及混沌，模糊了临界阈值，并意味着可预测性的限制。使用EWS从数据中检测局部稳定性的丧失需要在高维系统中进行仔细评估，并且在高度多稳态的气候中可能具有有限的预测能力，因为那里存在不止一个众所周知的替代状态。这要求使用非平衡统计力学和动力系统的新方法，以有效探测气候模型和观测的全局稳定性特性。

英文摘要

The potential of crossing climate tipping points (TP) has reached the attention of many researchers and the general public. On the one hand, the basis for this concern is strengthening, with simulations showing that abrupt transitions might occur even for moderate emission scenarios. On the other hand, our understanding of what constitutes such transitions mathematically is becoming more nuanced. This leads to challenges for the fidelity of early-warning signals (EWS), which accompany bifurcations in systems that closely track a slowly changing steady state. Different kinds of out-of-equilibrium dynamics in a rapidly changing climate, as well as chaos, blur the critical tipping threshold and imply limits in predictability. Using EWS to detect loss of local stability from data requires careful evaluation in the high-dimensional system, and may have limited predictive power in a highly multistable climate, where there is more than a single, well-known alternative state. This calls for new methods using non-equilibrium statistical mechanics and dynamical systems to efficiently probe the global stability properties of climate models and observations.

发表机构

• Niels Bohr Institute, University of Copenhagen（哥本哈根大学尼尔斯·玻尔研究所）

机构由 AI 辅助整理，请以论文原文为准。