基于黄河源区8个站点的年平均气温序列，利用集合经验模态分解（Ensemble Empirical Mode Decomposition，EEMD）方法，揭示了以玛多站为代表的黄河源区1953~2017年气温演变的多时间尺度特征，探讨不同时间尺度上的周期振荡对气温变化总体特征的影响程度，分析了黄河源区不同时间尺度的气温变化与海温指数，尤其是与北大西洋多年代际振荡（Atlantic Multidecadal Oscillation，AMO）间的关系。结果表明：（1）1953年以来黄河源区玛多站年平均气温以0.31 ℃/10 a的变化率表现为明显的增暖趋势，20世纪80年代后期开始转暖，尤其是进入20世纪90年代后期变暖更加明显。（2）1953~2017年，黄河源区年平均气温呈现3 a、6 a、11 a、25 a、64 a及65 a以上时间尺度的准周期变化，其中以准3 a和65 a以上时间尺度的振荡最显著，准3 a的年际振荡在21世纪以前振幅较大，而进入21世纪后年际振荡振幅减弱，65 a以上时间尺度的年代际振荡振幅明显加大。（3）1998年气候显著变暖以前，以准3 a周期为代表的年际振荡在气温演变过程中占据主导地位，1998年气候显著变暖以后，65 a以上时间尺度周期振荡的贡献率增加近5倍，与准3 a周期振荡的贡献相当。（4）气温与Nino3.4指数和PDO（Pacific Decadal Oscillation）指数的同期相关均不显著，但当气温领先PDO指数22 a时正相关最大且显著，不同于PDO指数，气温原始序列及其3个年代际尺度分量滞后AMO指数3~7 a或二者同期时相关性最高，这就意味着AMO对黄河源区气温具有显著影响。（5）AMO的正暖位相对应着包括中国的整个东亚地区偏暖，黄河源区只是受影响区域的一部分，20世纪60年代至90年代初期AMO的负冷位相期、20世纪90年代中后期至今AMO的正暖位相与黄河源区气温距平序列的负距平、正距平相对应，气温在65 a以上时间尺度的变化与AMO指数相关性更高，可见，AMO是影响黄河源区气温变化的一个重要的气候振荡，这种影响主要表现在年代际时间尺度上。
On the basis of the annual averaged surface air temperature data from eight meteorological stations in the source region of the Yellow River obtained using the ensemble empirical mode decomposition (EEMD) approach, the multi-timescale temperature features of meteorological stations, with Madoi as a representative, during 1953-2017 and their contributions to the temperature variations are revealed. The correlations between different timescale temperature oscillations and sea surface temperature (SST) indices, particularly the Atlantic Multidecadal Oscillation (AMO), are analyzed. The results indicated that: (1) The long-term temperature trend during 1953-2017 in the source region of the Yellow River was 0.31 ℃/10 years; the warming period started in the late 1980s and accelerated in the late 1990s. (2) There were 3-, 6-, 11-, 25-, 64-, and 65-year quasi-cycle oscillations for temperature during 1953-2017. Among them, the 3- and 65-year quasi-cycle oscillations were significant. The amplitude of the 3-year timescale oscillation increased before the 21st century and decreased after the 21st century. By contrast, the amplitude of the 65-year timescale oscillation increased after the 21st century. (3) The three-year quasi-cycle oscillation was dominant during 1953-1997. Moreover, the contribution of the 65-year oscillation increased nearly five times, which was equivalent to the contribution of the 3-year oscillation during the rapid warming period since 1998. (4) The correlations of temperature with the Nino3.4 and Pacific Decadal Oscillation (PDO) indices were not significant. However, the maximum significant correlation was observed during the 22-year temperature-led PDO. In contrast to PDO, the maximum significant correlation was observed when the AMO led the original temperature and its three interdecadal components 0 and 3-7 years that supported the finding that the AMO had a significant effect on the temperature variation in the source region of the Yellow River. (5) The positive warm phase of the AMO corresponded to the warming period of East Asia, including China, and the source region of the Yellow River was only a part of that area. The negative cold phase of the AMO from the early 1960s to the early 1990s and the positive warm phase of the AMO from the middle and late 1990s to the present corresponded to the negative and positive phases of the temperature in the source region of the Yellow River. The AMO highly correlated with the 65-year oscillation. These results supported the finding that the AMO was an important climatic oscillation that affects the temperature variation, particularly the interdecadal timescales, in the source region of the Yellow River.
冯晓莉,刘彩红,林鹏飞,白文蓉,余迪.2020.1953~2017年黄河源区气温变化的多尺度特征[J].气候与环境研究,25(3):333-344. FENG Xiaoli, LIU Caihong, LIN Pengfei, BAI Wenrong, YU Di.2020. Multi-Timescale Features of Surface Air Temperature in the Source Region of the Yellow River during 1953-2017[J]. Climatic and Environmental Research (in Chinese],25(3):333-344.复制