北大西洋多年代际振荡对中国北方夏季降水年代际变化的影响及机理

北大西洋多年代际振荡（AMO）作为年代际时间尺度上海洋变率的强信号，对全球许多地区气候产生重要影响，但对于中国尤其是北方地区（华北、东北）夏季降水年代际变化的影响及其机理尚不清楚。本项目拟基于观测分析、动力诊断和数值试验三个方面，从中高纬角度，对之进行系统研究。首先利用20世纪大气再分析数据，分析AMO对于东亚中高纬夏季大气环流异常以及东北冷涡和鄂霍次克海阻塞高压强度、频次等年代际变异的影响；然后研究近139年（1880-2018年）AMO位相转换是如何通过中高纬路径影响我国华北、东北夏季降水年代际变化，并揭示其影响的关键过程。在此基础上，研究AMO位相转换对于20世纪60年代之后我国华北的干旱少雨以及90年代末以来北方降水增多的影响；最后通过进行数值试验，弄清影响的动力过程和其中的物理机制，深入认识中国北方夏季降水年代际变化的机理，为我国气候的年代际变化的研究和预测提供科学依据。

The Atlantic Multidecadal Oscillation (AMO) is the strongest interdecadal timescale oceanic signal. Multiple previous studies have indicated the significant role that AMO has played in the global climate change in the recent decades, while its impacts on the interdecadal variability of the summer rainfall over North China and northeast China are still not very clear. Based on the observational analysis, dynamical diagnosis and numerical simulation, this proposal is intended to investigate these potential impacts and reveal the key processes and mechanism involved. First, this proposal will examine the influence of the AMO on the summer circulation patterns at mid-high latitudes of East Asian and intensity and frequency of the cold vortex in Northeast China and blocking high in Okhotsk Sea by using the twentieth century reanalysis datasets. Then, the mid-high latitudes teleconnection between the AMO phase transition and the interdecadal variation of the summer rainfall over North China and northeast China during 1880-2018 and related process will be explored. After that, we will further investigate into the contribution of the AMO to the drying trend in North China since 1960s and the wetting trend to the north of the Yangtze River of China since the late 1990s. Finally, the sensitive numerical experiments on dynamical processes and physical mechanisms involved in this impact will be performed, in order to deepen the understanding the intrinsic mechanisms responsible for the interdecadal variability of the summer rainfall in northern China. This proposal will provide important clues to help understand and further improve our ability to predict interdecadal climate change in northern China.