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基于地统计方法的中国西部气温空间插值研究
引用本文:钞振华,杨永顺.基于地统计方法的中国西部气温空间插值研究[J].湖北大学学报(自然科学版),2011,33(2):209-213,255.
作者姓名:钞振华  杨永顺
作者单位:1. 中国科学院寒区旱区环境与工程研究所,甘肃兰州730000;南通大学地理科学学院,江苏南通226007
2. 青海省环境监测中心站,青海西宁,810007
基金项目:国家自然科学基金,冰冻圈科学国家重点实验室开放基金
摘    要:利用基于地统计学的简单克里格、普通克里格、协克里格及综合方法4种插值方法对中国西部地区的气温估计结果进行比较研究.气温的空间分布格局和交叉验证结果表明在考虑高程信息后协克里格和综合方法比简单克里格和普通克里格的效果好.相比之下,协克里格比综合方法有更多奇异值出现;其他指标也表明综合方法优于其他3种插值方法.

关 键 词:地统计方法  变异函数  综合方法  交叉验证

Interpolation methods based on geostatistics for air temperature in western China
CHAO Zhenhua,YANG Yongshun.Interpolation methods based on geostatistics for air temperature in western China[J].Journal of Hubei University(Natural Science Edition),2011,33(2):209-213,255.
Authors:CHAO Zhenhua  YANG Yongshun
Institution:1.Cold and Arid Regions Environmental and Engineering Research Institute,Chinese Academy of Sciences, Lanzhou 730000,China;2.College of Geographical Science,Nantong University,Nantong 226007,China; 3.Qinghai Environment Monitoring Center,Xining 810007,China)
Abstract:More attention had been paid to interpolation methods based on geostatistics for climate variables.Four interpolation methods for air temperature in western China,namely,simple kriging,ordinary kriging,co-kriging and combined approach,were compared with their temperature distribution and cross-validated.The temperature distribution provided by cokriging and combined approach considering altitude information was better than simple krging and ordinary kriging.The details were well reflected.But more extreme singular values appeared in co-kriging than in combined approach.Further analysis showed that mean errors of simple kriging,ordinary kriging and co-kriging method were less than the combined approach,while their root mean squared error and correlation coefficient were lower than the combined approach.Although co-kriging method could show more details than simple kriging and ordinary kriging,the other indicators showed that there were many restraints to use in western China.In contrast,the performance of the combined approach was optimal.
Keywords:geostatistics  semivariogram  combined approach  cross validation
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