arXiv 2503.028082025-03-04physics.ao-ph

使用不稳定周期轨道理解低阶陆气模型中的阻塞行为

Using Unstable Periodic Orbits to Understand Blocking Behaviour in a Low Order Land-Atmosphere Model

Oisín Hamilton, Jonathan Demaeyer, Michel Crucifix, Stéphane Vannitsem

AI总结：

本文利用不稳定周期轨道（UPOs）对降阶陆气谱模型的混沌吸引子进行聚类，提出累积阴影概念识别描述各聚类生命周期的UPOs集合，并揭示吸引子区域转换与大气阻塞特征的关联。

摘要：

不稳定周期轨道（UPOs）被用于识别一个降阶耦合大气-陆地谱模型中的状态区域及区域间的转换。本文描述了如何利用数值推导的UPOs集合对该模型的混沌吸引子进行聚类。使用延续软件，还研究了这些聚类的起源。利用UPOs可以近似模型轨迹的流动，这一概念被称为阴影。在此我们将该思想扩展，考察在固定时间段内UPO阴影化模型轨迹的次数，称之为累积阴影。该概念被用于识别描述每个聚类不同生命周期的UPOs集合。当前工作中识别出的吸引子不同区域及其间的转换，与被称为大气阻塞的特定大气特征相关联。

英文摘要：

Unstable Periodic Orbits (UPOs) were used to identify regimes, and transitions between regimes, in a reduced-order coupled atmosphere-land spectral model. In this paper we describe how the chaotic attractor of this model was clustered using the numerically derived set of UPOs. Using continuation software, the origin of these clusters were also investigated. The flow of model trajectories can be approximated using UPOs, a concept known as shadowing. Here we extend that idea to look at the number of times a UPO shadows a model trajectory over a fixed time period, which we call cumulative shadowing. This concept was used to identify sets of UPOs that describe different life cycles of each cluster. The different regions of the attractor that were identified in the current work, and the transitions between these regions, are linked to specific atmospheric features known as atmospheric blocks.

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