发表机构
University of Exeter（埃克塞特大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文探讨并扩展了受迫非线性系统中临界转变预警的技巧与实用性，强调将基于稳定性趋势的预警转化为高技巧预测的挑战，并提出量化行动后果、有限时间预测及外推假设等关键要点，以提升预测性能。
AI 中文摘要
本文探讨并扩展了受迫非线性系统中临界转变（临界点）预警技巧与实用性的最新研究进展。我们强调了将基于稳定性或韧性趋势的动力学预警系统估计转化为高技巧预测所面临的一些挑战与机遇。我们强调了以下几点的重要性：（a）量化针对可能为假阴性或假阳性的预警所采取行动的可能后果；（b）考虑有限时间范围的预测以提供可验证的预测；（c）有效外推趋势所需的假设。我们评估了提升预测技巧与实用性的方法。
英文摘要
In this paper we explore and extend the state of the art for understanding the skill and utility of early warnings of critical transitions (tipping points) in forced nonlinear systems. We highlight some of the challenges and opportunities of transforming estimates of a dynamics-based early warning system, based on trends in stability or resilience into forecasts with high skill. We highlight the importance of (a) quantifying consequences of possible actions in response to warnings that may be false negatives or positives (b) considering finite time horizon predictions to give verifiable predictions (c) assumptions necessary for valid extrapolations of trends. We evaluate approaches to improving the skill and utility of the forecast.
Comments37 pages, 5 figures
