三种聚类分析方法在中国温度区划分中的应用研究

韩微; 翟盘茂

doi:10.3878/j.issn.1006-9585.2014.13210

三种聚类分析方法在中国温度区划分中的应用研究

doi: 10.3878/j.issn.1006-9585.2014.13210

韩微¹,
翟盘茂^2,

1.
南京信息工程大学, 南京210044;中国气象科学研究院灾害天气国家重点实验室, 北京100081
2.
中国气象科学研究院灾害天气国家重点实验室, 北京100081

基金项目: 公益性行业(气象)科研专项GYHY201106018,国家自然科学基金项目41175080

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出版历程
- 收稿日期: 2013-12-03

Three Cluster Methods in Regionalization of Temperature Zones in China

HAN Wei¹,
ZHAI Panmao^2
,

1.
Nanjing University of Information Science and Technology, Nanjing 210044;State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081
2.
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081

摘要

摘要: 根据全国512个气象站1961～2010年的逐日气温观测资料,采用日平均气温稳定通过10 ℃的日数(≥10 ℃日数)作为划分我国温度分布的指标,经过旋转经验正交函数分析(REOF)方法处理,找出时间演变过程中变化相似的区域归为一类.在此基础上,采用快速样本聚类法(K-means法)、分层聚类法(Ward法)、聚类统计检验法(CAST法)3种聚类分析方法对全国范围的温度变化区域差异进行客观分区,结果分别将全国温度变化区划分为10个地区、9个地区、13个地区,且不同区域分界线与中国地形分布有很好的一致性.研究表明:K-means法运算简单快捷,结果会不断修正到最佳为止;Ward法聚类过程清晰明了,可以选取需要划分的类别数;CAST法使样本通过显著性检验,不但有助于气候变化的客观分区,而且在划分温度区时客观考虑气候变化对分区结果的影响也有很重要意义.
- 聚类分析 /
- 日平均气温稳定通过10℃日数 /
- 变化 /
- 分区
Abstract: A scheme for regionalization of temperature zones was established on the basis of daily surface air temperature observations from 512 stations in China during 1961-2010. Days with daily surface air temperature ≥10 ℃ were used as indicators for zoning the temperature distribution. After REOF (Rotated Empirical Orthogonal Function) analysis, areas with similar temperature changes in the time evolution were classified as one zone. The temperature zones were classified by three types of clustering analysis methods. The national area was divided into ten temperature zones by using the K-means method, nine temperature zones by using the Ward method, and 13 temperature zones by using the CAST (Cluster Analysis with Statistical Test) method. The boundaries of the various regions show a good consistency with the Chinese topography. Calculation by using the K-means method is considered to be simple and quick because, the results are revised until the best results are achieved. Moreover, the clustering process of the Ward method is clear; any number of categories may be selected. Finally, the results of the CAST method pass the significance test; therefore, this method is meaningful for zoning.
- Cluster analysis /
- Days with daily surface air temperature ≥10 ℃ /
- Change /
- Zoning

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参考文献(16)

[1]	陈咸吉. 1982. 中国气候区划新探 [J]. 气象学报, 40 (1): 35-48. Chen Xianji. 1982. A new approach to the climate division of China [J]. Acta Meteorologica Sinica (in Chinese), 40 (1): 35-48.
[2]	陈志鹏, 朱瑞兆, 尹晓荣. 1991. 中国气候数值区划的研究 [J]. 应用气象学报, 2 (3): 271-279. Chen Zhipeng, Zhu Ruizhao, Yin Xiaorong. 1991. A study of the numerical classification of the climates in China [J]. Journal of Applied Meteorological Science (in Chinese), 2 (3): 271-279.
[3]	丁裕国, 张耀存, 刘吉峰. 2007. 一种新的气候分型区划方法 [J]. 大气科学, 31 (1): 129-136. Ding Yuguo, Zhang Yaocun, Liu Jifeng. 2007. A new cluster method for climatic classification and compartment using the conjunction between CAST and REOF [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 31 (1): 129-136.
[4]	方开泰. 1978. 聚类分析(Ⅰ) [J]. 数学的实践与认识, (1): 66-80. Fang Kaitai. 1978. Cluster analysis (I) [J]. Mathematics in Practice and Theory (in Chinese), (1): 66-80.
[5]	韩翠华, 郝志新, 郑景云. 2013. 1951～2010年中国温度变化分区及其区域特征 [J]. 地理科学进展, 32 (6): 887-896. Han Cuihua, Hao Zhixin, Zheng Jingyun. 2013. Regionalization of temperature changes in China and characteristics of temperature in different regions during 1951-2010 [J]. Progress in Geography (in Chinese), 32 (6): 887-896.
[6]	黄嘉佑. 2000. 气象统计分析与预报方法 [M]. 北京: 气象出版社, 181-191. Huang Jiayou. 2000. Meteorological Statistics Analysis and Predictive Method (in Chinese) [M]. Beijing: China Meteorological Press, 181-191.
[7]	刘伟东, 杨萍, 尤焕苓, 等. 2013. 北京地区热岛效应及日较差特征[J]. 气候与环境研究, 18 (2): 171-177. Liu Weidong, Yang Ping, You Huanling, et al. 2013. Heat island effect and diurnal temperature range in Beijing area [J]. Climatic and Environmental Research (in Chinese), 18 (2): 171-177.
[8]	Michelangeli P A, Vautard R, Legras B. 1995. Weather regimes: Recurrence and quasi stationarity [J]. J. Atmos. Sci., 52 (8): 1237-1256.
[9]	秦爱民, 钱维宏, 蔡亲波. 2005. 1960～2000年中国不同季节的气温分区及趋势 [J]. 气象科学, 25 (4): 4338-4345. Qin Aimin, Qian Weihong, Cai Qinbo. 2005. Seasonal division and trend characteristic of air temperature in China in the last 41 years [J]. Meteorological Science and Technology (in Chinese), 25 (4): 4338-4345.
[10]	任国玉, 初子莹, 周雅清, 等. 2005. 中国气温变化研究最新进展 [J]. 气候与环境研究, 10 (4): 701-716. Ren Guoyu, Chu Ziying, Zhou Yaqing, et al. 2005. Recent progresses in studies of regional temperature changes in China [J]. Climatic and Environmental Research (in Chinese), 10 (4): 701-716.
[11]	吴洪宝, 吴蕾. 2005. 气候变率诊断和预测方法 [M]. 北京: 气象出版社, 37-48. Wu Hongbao, Wu Lei. 2005. Methods for Diagnosing and Forecasting Climate Variability (in Chinese) [M]. Beijing: China Meteorological Press, 37-48.
[12]	么枕生. 1994. 用于数值分类的聚类分析 [J]. 海洋湖沼通报, (2): 1-12. Yao Zhensheng. 1994. Cluster analysis used in numerical classification [J]. Transactions of Oceanology and Limnology (in Chinese), (2): 1-12.
[13]	章基嘉, 孙照渤, 陈松军. 1984. 应用K均值聚类法对东亚各自然天气季节500毫巴候平均环流的分型试验 [J]. 气象学报, 42 (3): 311-319. Zhang Jijia, Sun Zhaobo, Chen Songjun. 1984. A pattern classification of the mean pentad circulations at 500mb level over East Asia for each NSS by the method of K-means cluster analysis [J]. Acta Meteorologica Sinica (in Chinese), 42 (3): 311-319.
[14]	赵春雨, 王冀, 严晓瑜, 等. 2009. 东北地区冬季降雪的气候特征及其区划 [J]. 自然灾害学报, 18 (5): 29-35. Zhao Chunyu, Wang Ji, Yan Xiaoyu, et al. 2009. Climatic characteristics and regionalization of winter snowfall in Northeast China [J]. Journal of Natural Disasters (in Chinese), 18 (5): 29-35.
[15]	郑景云, 尹云鹤, 李炳元. 2010. 中国气候区划新方案 [J]. 地理学报, 65 (1): 3-12. Zheng Jingyun, Yin Yunhe, Li Bingyuan. 2010. A new scheme for climate regionalization in China [J]. Acta Geographica Sinica (in Chinese), 65 (1): 3-12.
[16]	中央气象局. 1979. 中华人民共和国气候图集 [Z]. 北京: 地图出版社, 222-223. China Meteorological Administration. 1979. Climatological Atlas of the People's Republic of China (in Chinese) [Z]. Beijing: China Atlas Press, 222-223.