Spatial interpolation of daily minimum temperature and daily maximum temperature in Hainan Island

doi:10.11924/j.issn.1000-6850.casb17030062

Abstract

Abstract: The paper aims to find the suitable spatial interpolation method for daily minimum temperature and daily maximum temperature in Hainan Island, multiple linear regression (MLR), geographically weighted regression (GWRK), multiple linear regression-Kiging (MLRK) and geographically weighted regression-Kriging (GWRK) were compared to interpolate daily minimum temperature and daily maximum temperature in Hainan Island on January 1-June 30, 2016 by using longitude, latitude, elevation, slope, aspect, closest distance to the seaside, NDVI as covariates. The results showed that: the mean absolute errors (MAE) of the four methods for all daily minimum temperature samples were MLR> GWR>GWRK>MLRK; however, the MAEs of GWR, GWRK, and MLRK for all daily minimum temperature samples were very close, the MAEs of GWRK and MLRK for daily minimum temperature were also very close; the daily maximum temperature was the same; the MAE of MLRK for daily minimum temperature and daily maximum temperature was 0.50℃ and 0.73℃, respectively; the main differences of the spatial distributions interpolated by GWRK and MLRK for the daily minimum temperature were in the site sparse mountainous areas; the daily maximum temperature was the same. Therefore, in Hainan Island, the daily minimum temperature and daily maximum temperature should be interpolated by using MLRK.

Key words: daily minimum temperature, daily maximum temperature, geographically weighted regression Kriging, regression Kriging, Hainan Island

Zhang Guofeng, Bai Rui, Li Weiguang, Tian Guanghui, Cai Daxin, Zou Haiping, . Spatial interpolation of daily minimum temperature and daily maximum temperature in Hainan Island[J]. Chinese Agricultural Science Bulletin, 2017, 33(19): 101-109.

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