基于Kriging模型的地面气温空间插值研究

This paper aims to describe spatial interpolation methods to estimate surface air temperatures (SATs). The SAT at a particular location where SAT observations are not available is estimated through a Kriging interpolation between SAT measurements from 192 meteorological sites at which daily SAT observations have been obtained. A temporal de-trending method based on a Fourier series is used to model and remove the annual trend in original data in order to ensure the stationarity of de-trended data from which kriging parameters are determined. Furthermore, a spatial or surface de-trending in terms of geographic coordinates including altitude, latitude and longitude of each location is adopted in a Kriging model. Besides a Kriging model, an inverse distance weighting (IDW) interpolation method is tested as a comparison. The accuracies of both spatial interpolation approaches are assessed by calculating and comparing their mean absolute error (MAE) and root mean square error (RMSE) when taking each meteorological site as the target location in a cross-validation procedure. The results show that the Kriging model performs better than the IDW method at 174 sites. In addition, the temporal and spatial de-trending methods make the main contribution to the accurate capture of spatial correlations of SATs in the study area in a Kriging process.