Journal of Ecology and Rural Environment ›› 2019, Vol. 35 ›› Issue (6): 801-808.doi: 10.19741/j.issn.1673-4831.2018.0271

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Study on Interpolation Model of Monthly Temperature in Sichuan Province Under the Influence of Complex Topography

HE Peng1,2, JIAN Dong-nan2, LI Xiao1,2, LIN Zheng-yu3   

  1. 1. Agricultural Information and Rural Economy Institute, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China;
    2. Big Data Center, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China;
    3. College of Resources, Sichuan Agricultural University, Chengdu 611130, China
  • Received:2018-05-17 Online:2019-06-25 Published:2019-06-25


Sichuan Province has a great variety in topography, which has significant influences on regional climate distribution. Based on the data of monthly air temperature of 144 meteorological stations in Sichuan Province, seven interpolation methods including spline (SP), inverse distance weighting (IDW), ordinary kriging (OK), spline function method considering elevation effect (SPE), inverse distance weighing considering elevation effect (IDWE), ordinary kriging considering elevation effect (OKE) and multivariable linear regression method (MRM) were applied in current study to spatialize the monthly temperature. Meanwhile, the cross validation method was used to evaluate the accuracy of seven interpolation methods. The results show that the monthly temperature in Sichuan Province was significantly correlated with altitude, and correlation coefficient changed seasonally, with greater change in summer than in winter. The average temperature of each month decreased with the increase of altitude, and lapse rate of summer was greater than that of winter. The lapse rate for different months varied from 0. 308 to 0. 443℃·hm-1. The interpolation methods considering elevation effect achieved better accuracy than that without considering elevation effect. Among four interpolation methods considering elevation effect, MRM had the best accuracy, followed by IDWE and OKE, and SPE had the worst accuracy.

Key words: monthly temperature, spatial interpolation method, DEM, Sichuan Province

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