Zhang Chenwei, Wu Guocan, Zhao Runze
State Key Laboratory of Earth Surface Processes and Hazards Risk Governance, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Sci Rep. 2025 Apr 21;15(1):13661. doi: 10.1038/s41598-025-98672-y.
The rise in surface air temperature is one of the most profound manifestations of global warming, and its annual cycle in mid-latitudes, has been a key focus in climate related research. This study aims to assess the performances of the CMIP6 models in terms of simulating historical and predicting future annual cycles of surface air temperature over China. The historical (1961 - 2014) and future monthly temperatures (2015 - 2100) under three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) from 13 models were analyzed. The position of the maximum (minimum) value of the temperature (shorted as phase-max and phase-min, respectively) and amplitude were obtained through a Fourier smoothing of the monthly temperature, and their long-term trends were calculated and compared with historical CMIP6 monthly data and gauge observations from meteorological stations. It was found that under the three future shared socioeconomic pathways, the amplitude of the temperature annual cycle decreased in the future period compared to historical stage. It shows an obvious north-south gradient in the long-term phase and amplitude trends. The mean trends were 0.11, 0.12 and 0.36 days/10 years under SSP1-2.6, SSP2-4.5, and SSP5-8.5 for phase-max of the study area, respectively, larger than those of 0.04, 0.04, and 0.06 days/10 years for phase-min. Regionally, the amplitude in the northeastern China (NE), northern China (NC), southern China (SC) and southwestern China (SW) regions decrease under all the scenarios, which was related to the asymmetric increase of temperature between the winter and summer. Besides, there were large discrepancies in the phase and amplitude trends among different CMIP6 models.
地表气温上升是全球变暖最显著的表现之一,其在中纬度地区的年循环一直是气候相关研究的重点。本研究旨在评估CMIP6模型在模拟中国历史地表气温年循环和预测未来地表气温年循环方面的表现。分析了13个模型在三种共享社会经济路径(SSP1-2.6、SSP2-4.5和SSP5-8.5)下的历史(1961—2014年)和未来月气温(2015—2100年)。通过对月气温进行傅里叶平滑处理,得到气温最大值(最小值)的位置(分别简称为相位最大值和相位最小值)和振幅,并计算其长期趋势,与CMIP6历史月数据和气象站的实测数据进行比较。研究发现,在三种未来共享社会经济路径下,未来时期气温年循环的振幅相对于历史阶段有所减小。在长期相位和振幅趋势上呈现出明显的南北梯度。研究区域相位最大值在SSP1-2.6、SSP2-4.5和SSP5-8.5下的平均趋势分别为0.11、0.12和0.36天/10年,大于相位最小值的0.04、0.04和0.06天/10年。在区域上,所有情景下中国东北(NE)、华北(NC)、华南(SC)和西南(SW)地区的振幅均减小,这与冬夏气温的不对称增加有关。此外,不同CMIP6模型在相位和振幅趋势上存在较大差异。