平流层异常信号与东亚气候之间的因果关系及在预测上的应用研究

目前对于气候变化中的驱动成因及影响研究依靠的手段主要是全球大气环流模式，借助于数值试验厘清不同的驱动因子对气候变化的影响。然而, 数值模式的不确定性等问题期待着人们提出和发展与数值模式并行不悖的新途径，研究气候信号间的因果关系。本项目将直接从气候时间序列出发，利用因果关系分析中新的研究方法，讨论平流层信号与东亚气候系统之间是否存在因果关系，并在此基础上建立和发展包含平流层先兆信号的东亚气候预测方法。这对于气候变化中的驱动成因与影响的分析研究来说，它不仅具有很强的针对性和科学参考，而且找到了一个很好的联系实际前沿问题的切入点，有可能为平流层-对流层相互作用的研究及平流层信号与东亚气候的机理与预测问题研究提供一个新的研究思路。

By far the main technique on studying the cause and effect of climate change is based on the general circulation model (GCM) simulations. However GCMs could not yet provide a convincing conclusion because of the limitations in representing the reality of the climate system, for improving understanding of this issue, it is highly desirable to develop a new path that compatible with GCM to enrich theories for understanding the causality of the climate change. Therefore in this proposal by using the state-of-the-art technique, we will explore the climate causality between prior climate signals in stratosphere and east Asian climate, based on this to establish a predictive model by incorporating the constructed driving forces. As a data-driven attempt, this proposal will present a scientific reference for the current issue of climate change and climate causality to make progress in stratosphere-troposphere interaction and short term prediction and in better understanding of the climate causality research from observed climate data.