逐日气象要素空间插值方法的比较  

Comparison of spatial interpolation methods for daily meteorological elements

作　　者：姜晓剑[1] 刘小军[1] 黄芬[1] 姜海燕[1] 曹卫星[1] 朱艳[1] 

机构地区：[1]南京农业大学江苏省信息农业高技术研究重点实验室,南京210095

出　　处：《应用生态学报》2010年第3期624-630,共7页Chinese Journal of Applied Ecology

基　　金：教育部新世纪优秀人才支持计划项目(NCET-08-0797);国家自然科学基金项目(30871448);国家高技术研究发展计划项目(2006AA10Z219);国家重点基础研究发展规划项目(2009CB118608);江苏省自然科学基金项目(BK2008330)资助

摘　　要：采用距离反比权重法(IDW)、协克里格法(CK)和薄盘样条法(TPS)3种不同的空间插值方法,对我国1951—2005年气象数据完整的559个气象站点逐月第15日的平均基本气象要素(最高气温、最低气温、日照时数和降水量)进行了插值分析与评价.结果表明:3种插值方法中,TPS法对最高气温和最低气温插值的根均方差(RMSE)最小(1.02℃和1.12℃)、R2最大(0.9916和0.9913);不同季节中,TPS法对秋季最高气温、夏季最低气温进行插值的RMSE均最小(0.83℃、0.86℃),R2均为秋季最高.对于日照时数和降水量而言,TPS法的RMSE最小(0.59h和1.01mm)、R2最大(0.9118和0.8135);不同季节中,TPS法对冬季日照时数进行插值的RMSE最小(0.49h)、R2最大(0.9293),TPS法对冬季降水量进行插值的RMSE最小(0.33mm),IDW法对夏季降水量进行插值的RMSE最小(2.01mm),CK法对春季降水量进行插值的R2最大(0.8781).TPS法可作为我国大量逐日基本气象要素的最优空间插值方法.A comparative study was made to evaluate the methods of inverse distance weighting （IDW）, co-kriging （CK）, and thin plate spline （TPS） in interpolating the average meteorological elements （including maximum air temperature, minimum air temperature, sunshine hours, and precipitation） of the 15th day per month from the 1951-2005 comprehensive observation data of 559 meteorological stations in China. The results showed that the RMSEs for the maximum and minimum air temperature in a year interpolated by TPS were the smallest （1.02 ℃ and 1.12 ℃, respectively）, and the R^2 between the observed and predicted values were the highest （0.9916 and 0.9913, respectively）, compared with those interpolated by IDW and CK. In four seasons, the smallest RMSEs for the maximum and minimum air temperature interpolated by TPS were observed in autumn （0.83 ℃） and summer （0.86 ℃）, respectively, and the R^2 between the observed and predicted values interpolated by TPS were higher in autumn than in other seasons. The RMSEs for the sunshine hours and precipitation in a year interpolated by TPS were the smallest （0.59 h and 1.01 mm, respectively）, and the R^2 between the observed and predicted values were the highest （0.9118 and 0.8135, respectively）, compared with those interpolated by IDW and CK. In four seasons, the RMSE for the sunshine hours in winter interpolated by TPS was the smallest （0.49 h）, and the R^2 between the observed and predicted sunshine hours was the smallest （0.9293）. The RMSE for the precipitation in winter interpolated by TPS was the smallest （0.33 mm）, while the RMSE for the precipitation in summer interpolated by IDW was the smallest （2.01 mm）. The R^2 between the observed and predicted precipitation in winter interpolated by CK was the highest （0.8781）. It was suggested that TPS could be the optimal spatial interpolation method in interpolating and rasterizing the daily meteorological elements in China.

关 键 词：逐日气象要素 空间插值方法 栅格化 

分 类 号：S161[农业科学—农业气象学]