关键词: ANUSPLIN软件, 气象要素, 插值方法, 插值评估

Abstract: Meteorological elements are the basic data for the study on resources, environment, disaster and global change fields, and their gridding data become more and more important for the study at large scale. The daily air temperature and precipitation were interpolated by spline interpolating method from ANUSPLIN software based on the data from 667 weather stations of China from 1961 to 2006 in order to get the gridding data, and the interpolating results were validated by the data from other 1667 dense observation stations. The interpolating results were compared with those data based on intense distance weight method and ordinary kriging method. It indicates that the errors within 2.0 ℃ for daily average air temperature account for 92.0%, and those within 2.0 ℃ and over 5.0 ℃ are 75.0% and 0.9%, respectively. The mean absolute error is 0.8℃. On the other hand, the errors within 5.0 mm and 10.0 mm for daily precipitation account for 75.0% and 85.0%, respectively, and the mean absolute error is 6.4 mm. The relationship between the error ranges of gridding precipitation and observation values of precipitation are positive, and interpolating accuracy decreases for local strong precipitation, which maybe result from the insufficient observation values. Furthermore, the interpolating accuracy for air temperature is higher in summer than in winter, while that for precipitation is higher in winter than in summer. The validation results indicate that the accuracy of gridding data based on spline interpolation method of ANUSPLIN software is higher than that based on intense distance weight method and ordinary kriging method. It also indicates that more observation data and finer resolution DEM can improve the accuracy of the spline interpolation method of ANUSPLIN software.