利用模糊C均值聚类法对1981-2000 年中国157 个1.6 m地温观测站的20 年平均地温值进行了客观分类,将全国1.6 m地温场分为四类,并对各类地温场20 年区域月距平值进行了集合经验模态分解。结果表明:(1)中国1.6 m地温场可以客观地分为四类区域,分别是冷区(T1.6 ≤9 ℃),包括东北地区和青藏高原地区;暖区(T1.6 ≥ 18 ℃),包括长江中下游地区和华南地区;次冷区(9 ℃ ≤T1.6 ≤15 ℃),主要包括西北地区;次暖区(15 ℃ ≤T1.6 ≤18 ℃),主要包括淮河流域地区;(2)模糊C均值聚类分析得到的四类地温场的月距平都有明显的准1.5 年和准4 年变化周期;(3)在1981-2000 年间四类地温场的变化趋势分为两种,分别是持续上升型(包括冷区和次冷区)和先降后升型(包括暖区和次暖区),并且上升的幅度随时间增大,尤其是20 世纪90 年代以后,四类地温场的增温趋势越来越明显。
Soil thermal conditions have a significant impact on weather and climate change.The temperature in soil is an indicator of the thermal condition.It represents a change in the underlying heat storage.It is very necessary to do some researches about the soil temperature.In this paper,some characteristics of soil temperature at 1.6 m depth of the whole country are discussed.The soil temperature data observed from 157 observatories at 1.6 m depth from 1981 to 2000 has been used.The FCM method was applied to study the similarities and differences of all observatories.As a result,when longitude,latitude and soil temperature of each station are concerned,all observations are classified into four types of clusters.They are thecool area with T1.6 ≤9 ℃ including northeastern China and Qinghai-Xizang Plateau,the warm area with T1.6≥18 ℃ including the southern China and the middle and lower reaches of the Yangtze River region,the secondary cool area with 9 ℃ ≤T1.6 ≤15 ℃ mainly including the northwestern China,and the secondary warm area with 15 ℃ ≤T1.6 ≤18 ℃ mainly including Huai River basin and its around,respectively.Then,the EEMD(Ensemble Empirical Mode Decomposition)was used to study the quasi-periods and nonlinear trends of the four-type areas.It shows that all areas have similar quasi-periods of 1.5 and 4 years in monthly soil temperature anomaly at 1.6 m depth.The nonlinear trends of the four types of clusters have played in two ways:the constantly warming way(in the cool and secondary cool areas)and the warming after cooling way(in the warm and secondary warm areas).The warming rate has been amplified with time,especially after 1990,and this warming is something like to be accelerated.
[1]Bezdek J C,Ehrlidh R,Full W.1984.FCM:The Fuzzy C-means clustering algorithm[J].Computers and Geosciences,10(2-3):191-203.
[2]Edward English.2005.Development of knowledge for predictive mapping using a Fuzzy C-means classification[C]//Proceedings of the Eleventh International Fuzzy Systems.Association World Congress,7:TP18.
[3]Gilichinsky D A,Barry R G,Bykhovets S S,et al.1998.A century of temperature observations of soil climate:Methods of analysis and long-term trends[C]//Lewkowicz A G,Allard M,eds.Yellowknife,Canada:Proceedings of the Seventh International Conference on Permafrost,313-317.
[4]Haeberli W,Hoclzle M,Keller F,et al.1993.Monitoring the long-term revolution of mountain permafrost in the Swiss Apls[C]//Proceedings of Six International Conference on Permafrost,July 5-9,Beijing,1993.Guangzhou:South China University of Technology Press,1:214-219.
[5]Hanesch M,Scholger R,Dekkers M J.2001.The application of Fuzzy C-means cluster analysis and non-linear mapping to a soil data set for the detection of polluted sites[J].Physics and Chemistry of the Earth,11(26):885-891.
[6]Hu Q,Feng S.2003.A daily soil temperature dataset and soil temperature climatology of the contiguous United States[J].J Appl Meteor,42(42):1139-1156.
[7]Huang N E,Wu Z H.2008.A review on Hilbert-Huang transform:Method and its applications to geophysical studies[J].Reviews of Geophysics,46(2):1-23.
[8]Huang N E,Shen S P.2005.Hilbert-Huang Transform and Its Applications[M].World Scientific Publishing Co.Pte.Ltd,56-62.
[9]Wu Bingyi,Yang Kun,Zhang Renhe.2009.Eurasian snow cover variability and its association with summer rainfall in China[J].Adv Atmos Sci,26(1):31-44.
[10]Wu Z,Huang N E.2009.Ensemble empirical mode decomposition:a noise-assisted data analysis method[J].Advances in Adaptive Data Analysis,1(1):1-41.
[11]Wu Z,Huang N E,Wallace J M.2011,On the time-varying trend in global-mean surface temperature[J].Climate Dynam,37:759-773.
[12]Bai Yanying,Thomas A S,Chen Weiping,et al.2010.Soil temperature regimes of the Mojave Desert[J].Soil Science,175(8):398-404.
[13]Zhang Yu,Chen Wenjun,Smith S L,et al.2005.Soil temperature in Canada during the twentieth century:Complex responses to atmospheric climate change[J].J Geophys Res,110(3):D03112.DOI:10.1029/2004JD004910.
[14]高新波.2004.模糊聚类分析及其应用[M].西安:西安电子科技大学出版社,102 -108.Gao Xinbo.2004.Fuzzy cluster analysis and its applications[M].Xi′an:Xi′an University of Electronic Science and Technology Press,102-108.
[15]徐国昌,李梅芳.1985.青藏高原温度与东亚环流.高原气象,4(2):185 -198.Xu Guochang,Li Meifang.Temperature in Qinghai-Xizang Plateau and East Asian circulation[J].Plateau Meteor,4(2):185-189.
[16]黄忠恕.1986.青藏高原热状况与大气超长波的关系[J].地理研究,5(1):32-41.Huang Zhongshu.1986.A Preliminary Analysis of the correlation between the state of heat and ultra-long wave in the Qinghai-Xizang Plateau[J].Geographical Research,5(1):32-41.
[17]姜伦,丁华福.2010.关于模糊C-均值(FCM)聚类算法的改进[J].计算机与数字工程,38(2):4-8.Jiang Lun,Ding Huafu.2010.Improvement of the Fuzzy C-means clustering algorithm[J].Computer & Digital Engineering,38(2):4-8.
[18]刘伟东,尤焕苓,任国玉,等.2014.北京地区自动站降水特征的聚类分析[J].气象,40(7):844-851.Liu Weidong,You Huanling,Ren Guoyu,et al.2014.AWS precipitation characteristics based on K-means cluster method in Beijing area[J].Meteor Mon,40(7):844-851.
[19]刘晓东,罗四维,钱永甫.1989.青藏高原地表热状况对夏季东亚大气环流影响的数值模拟[J].高原气象,8(3):205-216.Liu Xiaodong,Luo Siwei,Qian Yongfu.1989.Numerical simulations of influences of different thermal characteristics on ground surface of Tibetan Plateau on the SE-ASIA[J].Plateau Meteor,8(3):205-216.
[20]刘晓东,韦志刚.1992.地温异常的气候学分析[J].高原气象,11(3):312-320.Liu Xiaodong,Wei Zhigang.1992.Climatological analyses of anomaly of soil temperature[J].Plateau Meteor,11(3):312-320.
[21]陆晓波,徐海明,孙丞虎,等.2006.中国近50 a地温的变化特征[J].南京气象学院学报,29(5):706-712.Lu Xiaobo,Xu Minghai,Sun Chenghu,et al.2006.Characteristics of soil temperature variations in China in recent 50 years[J].J Nanjing Insti Meteor,29(5):706-712.
[22]闵文彬,李跃清,周纪.2015.青藏高原东侧MODIS地表温度产品验证[J].高原气象,34(6):1511-1516.Min Wenbin,Li Yueqing,Zhou Ji.2015.Validation of MODIS land surface temperature products in east of the Qinghai-Xizang Plateau[J].Plateau Meteor,34(6):1511-1516.DOI:10.7522/j.issn.1000-0534.2014.00082.
[23]秦艳慧,吴通华,李韧,等.2015.ERA-Interim地表温度资料在青藏高原多年冻土区的适用性[J].高原气象,34(3):666-675.Qin Yanhui,Wu Tonghua,Li Ren,et al.2015.Application of ERA product of land surface temperature in permafrost regions of Qinghai-Xizang Plateau[J].Plateau Meteor,34(3):666-675.DOI:10.7522/j.issn.1000-0534.2014.00151.
[24]师华定,高庆先,齐永清,等.2009.蒙古高原土壤风蚀危险度的FCM模糊聚类研究[J].自然资源学报,24(5):881-889.Shi Huading,Gao Qingxian,Qi Yongqing,et al.2009.Wind erosion hazard assessment of Mongolian Plateau by using Fuzzy Cluster Method[J].Journal of Natural Resources,24(5):881-889.
[25]汤懋苍,成青燕,张东方,等.2008.地气图预测全国月降水的实践总结[J].高原气象,27(5):1054-1059.Tang Maocang,Cheng Qingyan,Zhang Dongfang,et al.2008.Summary of applying soil temperature of forecast monthly precipitation[J].Plateau Meteor,27(5):1054-1059.
[26]王兵,李晓东.2011.基于EEMD分解的欧洲温度序列的多尺度分析[J].北京大学学报:自然科学版,47(4):627-635.Wang Bing,Li Xiaodong.2011.Multi-scale fluctuation of European Temperature revealed by EEMD analysis[J].ACTA Scientiarum Naturalium Universitatis Pekinensis,47(4):627-635.
[27]玄兆燕,杨公训.2008.经验模态分解法在大气时间序列预测中的应用[J].自动化学报,34(1):97-101.Xuan Zhaoyan,Yang Gongxun.2008.Application of EMD in the atmosphere time series prediction[J].ACTA Automatica Sinica,34(1):97-101.
[28]于剑.2003.论模糊C均值算法的模糊指标[J].计算机学报,26(8):968-973.Yu Jian.2003.On the Fuzziness index of the FCM algorithms[J].Chinese Journal of Computer,26(8):968-973.
