发表机构
University of Bologna; Princeton University; University of Colorado（博洛尼亚大学; 普林斯顿大学; 科罗拉多大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出OU过程的粗粒化随机热力学框架，应用于MJO，发现可预测性与路径作用相关，且MJO变得更可预测、更不可逆、更活跃。
AI 中文摘要
气候振荡本质上是非平衡现象，然而其可预测性与非平衡热力学性质之间的联系尚未被探索。我们为Ornstein-Uhlenbeck（OU）过程开发了一个粗粒化的随机热力学框架，并通过线性逆模型（LIMs）将该框架应用于气候数据，将可预测性、熵产生、动力学活性和路径作用联系起来。气候振荡通常在以气候指数构成的二维相空间中研究，这些指数在时间反演下是对称的，这促使我们关注具有偶变量的二维OU动力学。我们发现，二维OU过程的坐标不变性质可以简化为一个最少三个参数的描述：两个扩散系数和一个相空间旋转。我们表明，这些量从根本上刻画了动力学的不同方面。我们发现，更高的不可逆性和动力学活性并不一定意味着可预测性的降低。相反，与常用的可预测性度量——异常相关系数（ACC）——最密切相关的是路径作用。作为示例，我们将此框架应用于二十世纪的马登-朱利安振荡（MJO）。我们发现，MJO同时变得更具可预测性（正如先前所见），同时变得更加不可逆和更加活跃。可预测性主要由平均扩散的减小驱动。熵产生反映了所有三个参数的综合演变。这些结果表明，随机热力学为研究非平衡气候现象提供了一个强有力的视角。
英文摘要
Climate oscillations are intrinsically out-of-equilibrium phenomena, yet the connection between their predictability and nonequilibrium thermodynamic properties remains unexplored. We develop a coarse-grained stochastic thermodynamic framework for Ornstein-Uhlenbeck (OU) processes and apply this framework to climate data via linear inverse models (LIMs), linking predictability, entropy production, dynamical activity, and path action. Climate oscillations are often studied in a 2d phase space of climate indices, which are even under time-reversal, motivating our focus on 2d OU dynamics with even variables. We find that coordinate-invariant properties of 2d OU processes can be reduced to a minimal three-parameter description: two diffusivities and a phase-space rotation. We show that these quantities fundamentally characterize distinct aspects of the dynamics. We find that higher irreversibility and dynamical activity do not necessarily imply reduced predictability. Rather, it is the path action which is most closely connected to a commonly used measure of predictability, the anomaly correlation coefficient (ACC). As an illustrative example, we apply this framework to the Madden-Julian Oscillation (MJO) over the twentieth century. We find that the MJO has become simultaneously more predictable, as seen previously, while at the same time becoming more irreversible and more active. Predictability is driven predominantly by the reduced mean diffusion. Entropy production reflects the combined evolution of all three parameters. These results suggest that stochastic thermodynamics provides a powerful lens for studying nonequilibrium climate phenomena.
CommentsThis work was submitted to Physical Review E on September 29, 2026
