年际至多年代际气候变化的非线性相互作用及其对全球增暖速率的影响研究

气候系统是一个多尺度相互作用的强非线性系统，各种周期性自然振荡在全球增暖速率变化中扮演了重要角色。对气候变化非线性过程的深入研究是全面理解全球温度变化机理、准确预测未来增暖速率的关键。然而，由于研究方法的局限性，长期以来不同尺度间的非线性相互作用及其对全球温度变化的贡献并未得到足够的重视。本项目拟采用自适应数据分析方法，研究气候变化的非线性作用机理及非线性过程对全球增暖速率的影响。首先，利用经验模态分解方法，提取全球表层温度年际、年代际和多年代际这三种对全球长期增暖速率影响最大的自然气候变化信号，分析其演变特征；然后，基于高维全息谱方法，阐明这三种关键尺度在尺度内和尺度间的非线性调制机理，揭示相应的物理机制，并定量评估这些非线性过程对全球温度变化的贡献。研究结果可加深对气候变化中的非线性过程的认识，弥补气候变化研究中缺失的重要一环，为气候变化归因和未来气候预测提供新的科学依据。

Various natural climate oscillations played major roles in recent changes of global warming rate. These oscillations at different time scales interact with each other, showing strong nonlinearity, and then build the whole climate dynamic system. The intensive study of nonlinear effects should be the key for thoroughly understanding the global temperature change and making accurate future predictions of the global warming rate. However, because of the lack of available methods, the importance of the complex interactions between different scales has not still been paid enough attention to. So, this project is proposed to use adaptive methods to explore the nonlinear interactions among three key natural variabilities at interannual, interdecadal and multidecadal scales and how they affect the global warming rate. To extract three key oscillations and analyze their characteristics, the global mean surface temperature time series will first be decomposed by ensemble empirical mode decomposition (EEMD) method. Then the intra-mode and inter-mode modulations among three scales will be identified by the Holo-Hilbert spectral analysis (HHSA) method, and the mechanisms will be discussed. Based on these results, the effects of nonlinear modulations on global temperature change will be estimated quantitatively. The results of this study may provide the scientific basis for accurate attributions and future projections for climate changes.