气候与环境研究  2018, Vol. 23 Issue (6): 670-682 PDF

1 中国科学院东亚区域气候-环境重点实验室, 中国科学院大气物理研究所, 北京 100029;
2 中国科学院大学, 北京 100049;
3 中国气象局国家气象信息中心, 北京 100081

Climatic Changes in the Twenty-Four Solar Terms Based on Temperature Observations Back to 1873
QIAN Cheng1,2, YAN Zhongwei1,2, CAO Lijuan3, LI Zhen1
1 Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;
2 University of Chinese Academy of Sciences, Beijing 100049;
3 National Meteorological Information Center, China Meteorological Administration, Beijing 100081
Abstract: Twenty-four Solar Terms (24STs) have been widely used for guiding human activities in China over more than 2000 years. However, the implication of the conventional 24STs has been changing under global warming. The climatic 24STs proposed recently impose a time-varying characteristic on the conventional 24STs, thus they can better serve as guidance for people under current situation. Previous studies only focused on linear trend of the 24STs since 1960. In this study, climatic changes in the 24STs back to 1873 are analyzed based on homogenized daily temperature series at Beijing station for the period 1940-2017 and at Shanghai station for the period 1873-2017. The results show that the annual mean temperature as well as temperatures of the 24STs at Beijing station for the period 1941-2016 and at Shanghai station for the period 1874-2016 all show warming trends, thus resulting in advancing trends during the warming stage (around spring) and delaying trends during the cooling stage (around autumn) in the timings of the climatic Solar Terms in the seasonal cycle. Most of these trends are statistically significant. The occurrence of extreme cold days shows a significant decreasing trend at both stations of Beijing and Shanghai, whereas the occurrence of extreme hot days at Shanghai station shows a significant increasing trend. In addition to the long-term trend, there exists apparent multi-decadal variability with a period of 60-80 years in both the occurrence of extreme hot days and summer temperature at Shanghai station, which is correlated with the Atlantic Multi-decadal Oscillation. These results can provide an important scientific base for climate change adaptation and benefit the understanding of modern climatic warming in China from a perspective of fine evolution of the seasonal cycle.
Keywords: Twenty-four Solar Terms     Climate change     Extreme temperature     Multi-decadal variability     Ensemble Empirical Mode Decomposition (EEMD)
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1 引言

2016年11月30日，中国申报的“二十四节气”入选了联合国教科文组织人类非物质文化遗产代表作名录。“二十四节气”是古人通过观察太阳周年运动，认知一年中时令、气候、物候等方面变化规律所形成的知识体系和社会实践。它指导着传统农业生产和日常生活，也是中国传统历法体系及其相关实践活动的重要组成部分，已沿用2000多年，现在仍然发挥着指示作用。

 图 1 拼接后的（a）北京和（b）上海百年逐日平均气温序列计算的年平均值及其和相关数据的比较。黑色为拼接后数据；绿色为数据1，其中（b）调整了一个偏差；红色为数据2（a）和数据3（b）的近60年数据；蓝色为数据4，其中（b）调整了一个偏差 Fig. 1 Time series of annual mean temperature calculated from the connected daily mean temperature data (black lines) at (a) Beijing and (b) Shanghai stations and the comparisons with related data, including data from Yan et al. (2001) (green lines, with an adjust in the lower figure), Li et al. (2015) (a) and Cao et al. (2016) (b) (red lines), and Cao et al. (2013) (blue lines, with an adjust in the lower figure)
2 数据和方法 2.1 数据

2.2 方法 2.2.1 数据拼接方法

2.2.2 气候学二十四节气的确定和分析方法

 ${N_e} = \left\{ {\begin{array}{*{20}{c}} {N\frac{{1 - {r_1}}}{{1 + {r_1}}}, }&{{r_1} > 0}\\ {N, {\rm{ }}}&{{r_1} \le 0} \end{array}} \right.$ (1)

 $b = \hat b \pm q{\hat \sigma _b},$ (2)

 ${\hat \sigma _b} = {\left[ {\frac{{\sum\limits_{t = 1}^N {\hat e{{(t)}^2}} }}{{{N_e} - 2}}/\sum\limits_{t = 1}^N {(t - \bar t} {)^2}} \right]^{\frac{1}{2}}},$ (3)

2.2.3 EEMD多时间尺度分析

3 结果分析 3.1 二十四节气气候变化特征

 图 2 北京1941~2016年（蓝色）和上海1874~2016年（红色）的年平均气温距平序列（实线）及其线性趋势（虚线）。天蓝色和紫色分别是北京和上海各自的最长序列 Fig. 2 Time series of annual mean temperature anomalies at Beijing station during 1941-2016 (blue solid line) and Shanghai station during 1874-2016 (red solid lines), and their corresponding linear trends (dashed lines). Cyan and magenta lines are the longest series for Beijing and Shanghai stations, respectivelys

 图 3 （a、b）北京1941~2016年和（c、d）上海1874~2016年的气候学二十四节气提前或推迟的演变（左列：季节性升温时段；右列：季节性降温时段）。实线表示各个气候节气每年的时间序号，虚线表示线性趋势。其中，上海的气候学雨水、处暑和大雪[见Qian et al.（2016）的表 1]有的年份没有达到阈值，设为缺测 Fig. 3 Linear trends (dashed lines) in the timing (solid lines) of the Solar Terms in the seasonal warming period (left panel) and the seasonal cooling period (right panel) at (a, b) Beijing station during 1941-2016 and (c, d) Shanghai station during 1874-2016. There are years in which no intersects with the thresholds are found for three timings, including Rain Water, Limit of Heat, and Great Snow [see the Table 1 in Qian et al. (2016) for the explanations] in Fig. 3c and Fig. 3d. They are considered as missing values
3.2 极端冷、暖的频数变化

 图 4 （a、b）北京1941~2016年和（c、d）上海1874~2016年达到大寒标准（左列）和达到大暑标准（右列）的频数演变（蓝实线）、相应的线性趋势（蓝虚线）、EEMD趋势（黑实线）和EEMD多年代际以上尺度低频变率（红实线，只分析上海） Fig. 4 Time series (blue solid lines) of the occurrence of extreme cold day (left column) and extreme hot day (right column) at (a, b) Beijing station for the period 1941-2016 and (c, d) Shanghai station for the period 1874-2016, and their corresponding linear trends (dashed lines), EEMD trends (black lines) and low-frequency variations with a period equal to or longer than multi-decadal timescale calculated from EEMD filter (red lines and only Shanghai is analyzed)

 图 5 （a、b）北京1941~2016年和（c、d）上海1874~2016年达到大寒和大暑标准的极端冷（左列）、暖（右列）日发生频次和冬季、夏季平均气温的关系 Fig. 5 Relationships between the occurrence of extreme cold days and winter temperature (left column) or between the occurrence of extreme hot days and summer temperature (right column) at Beijing station for the period 1941-2016 (upper) and Shanghai station for the period 1874-2016 (lower)

 图 6 北京1941~2016年（蓝色）和上海1874~2016年（红实线）夏季平均气温距平序列以及上海相应的线性趋势（红虚线）、EEMD趋势（黑实线）、EEMD多年代际以上尺度低频变率（紫色） Fig. 6 Time series of summer temperature anomaly at Beijing station during 1941-2016 (blue line) and Shanghai station during 1874-2016 (red solid line). Along with the linear trend (red dashed line), EEMD trend (black solid line), and low-frequency variations with a period equal to or longer than multi-decadal timescale calculated from EEMD filter (magenta line) for Shanghai station

 图 7 上海1880~2016年夏季平均气温的多年代际变率和全球海表温度场的相关系数分布 Fig. 7 Correlation coefficients between multi-decadal variability in summer temperature at Shanghai station and global gridded sea surface temperature during 1880-2016
4 结论和讨论

（1）北京1941~2016年和上海1874~2016年的年平均气温和二十四节气气温都呈现变暖趋势，导致早春到初夏阶段的气候学节气呈现提前趋势，而夏末到初冬阶段的节气呈现推迟趋势，这些趋势大部分是统计显著的。

（2）北京1941~2016年和上海1874~2016年的极端冷事件（以大寒标准定义）均呈现显著的减少趋势，上海的极端热事件（以大暑标准定义）呈现显著的增多趋势。

（3）上海极端热事件频数和夏季平均气温演变中都存在明显的60~80 a周期的多年代际变率，和大西洋多年代际振荡相关。