中国农业气象 ›› 2015, Vol. 36 ›› Issue (02): 234-241.doi: 10.3969/j.issn.1000-6362.2015.02.015

• 论文 • 上一篇    下一篇

不同空间插值方法在区域气温序列中的应用评估:以东北地区为例

陈思宁,郭军   

  1. 天津市气候中心,天津300074
  • 收稿日期:2014-11-19 出版日期:2015-04-20 发布日期:2015-06-25
  • 作者简介:陈思宁(1983-),女,哈尔滨人,博士,工程师,主要从事应用气象及农业遥感研究。Email:siningchen@126.com
  • 基金资助:

    科技部行业专项“近百年全球陆地气候变化监测技术与应用(201206024)

Evaluation of Different Spatial Interpolation Methods in Regional Temperature Sequence: A Case Study in Northeast China

CHEN Sining,GUO Jun   

  1. Tianjin Climate Center,Tianjin300074,China
  • Received:2014-11-19 Online:2015-04-20 Published:2015-06-25

摘要: 建立高精度、长时间序列的气温数据集对研究气候变化、作物生长发育、灾害评估等都有着十分重要的意义。本文以1971-2000年东北地区104个气象站点的气候标准值数据及年值观测资料为基础,利用空间插值方法对该区年平均气温进行插值,并结合参考格点气温数据集,从误差指标、气温特征值及气温时序变化曲线等方面评估时、空尺度上各方法的插值精度。结果表明:空间尺度上,基于局部薄盘光滑样条(PTPSS)函数且以高程为协变量的年平均气温插值结果最优,其均方根误差为0.341℃,平均绝对误差为0.264℃,其次为协同克里格(以高程为协变量),再次为普通克里格;时间尺度上,基于PTPSS以高程为协变量的年平均气温时序曲线与参考格点气温曲线的变化趋势最符合,两个数据集的年平均气温平均值、最大值和最小值时序变化曲线的相关系数均大于0.9。可见,以高程为协变量的局部薄盘光滑样条函数法最适于东北地区年平均气温插值。

关键词: 区域平均气温, 空间插值, 精度评估

Abstract: It is significant to establish high accuracy temperature grid data set with long time series to study climate change,crop growth and development,disaster impact and assessment. Based on observed climate standard values data from 104 meteorological stations and annual temperature data in Northeast China from 1971 to 2000,by using the spatial interpolation methods,the annual mean temperature temporal and spatial distribution in Northeast China were studied and the accuracy of the interpolation methods was evaluated with the error indicators,temperature characteristic values and time series temperature curves. The result showed that,on the spatial scale,the interpolation results based on the Partial Thin Plate Smoothing Splines(PTPSS)with the elevation as the covariate was better than other methods,with the RMSE 0.341℃,and the MAE 0.264℃,followed by Cokriging method(with the elevation as covariates),again as the ordinary Kriging method. On the temporal scale,the time series annual mean temperature curve form 1971 to 2000 based on PTPSS(with the elevation as the covariate)was consistent with the time series temperature curve extracted from the reference grid temperature data set. The correlation coefficients of the mean temperature,maximum temperature and minimum temperature curves extracted from the interpolated temperature grid set based on PTPSS and the corresponding curves from the reference grid temperature set were greater than 0.9. The results indicated that the PTPSS interpolation method with the elevation as the covariate was the most suitable for the construction of the annual mean temperature surface in Northeast China.

Key words: Regional average temperature, Spatial interpolation, Accuracy evaluation