从时间序列数据估计非线性稳定性
Estimating nonlinear stability from time series data
摘要：
流域稳定性（BS）是多稳定动力系统非线性稳定性的度量。BS先前已经使用蒙特卡罗模拟来估计，这需要动力学模型的明确知识。我们讨论了强扰动存在下，从时间序列数据估计BS的要求，并说明了我们的方法，两个简单的模型的气候翻转元素：亚马逊雨林和温盐海洋环流。我们讨论了我们的方法的适用性的观测数据的相关时间尺度的总观测时间，典型的返回时间的扰动和内部收敛时间尺度的系统的兴趣和其他因素的约束。
英文摘要：
Basin stability (BS) is a measure of nonlinear stability in multi-stable dynamical systems. BS has previously been estimated using Monte-Carlo simulations, which requires the explicit knowledge of a dynamical model. We discuss the requirements for estimating BS from time series data in the presence of strong perturbations, and illustrate our approach for two simple models of climate tipping elements: the Amazon rain forest and the thermohaline ocean circulation. We discuss the applicability of our method to observational data as constrained by the relevant time scales of total observation time, typical return time of perturbations and internal convergence time scale of the system of interest and other factors.
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