Comparison of interpolation methods for typical meteorological factors based on GIS — A case study in JiTai basin, China

This study aims to estimate the spatial distribution patterns of three typical meteorological factors: maximum temperature, minimum temperature and precipitation in JiTai basin. Forty-seven-year monthly mean meteorological data were interpolated using Inverse distance weight (IDW), Ordinary kriging (OK) and Tension spline function (TPF). Cross-validation was applied to evaluate the accuracy of the above methods, and three indices including mean absolute error (MAE), mean relative error (MRE) and root mean squared error (RMSE) were used to compare the accuracy. The results reveal that the OK realization is the optimal method for interpolating mean values of both minimum temperature and precipitation monthly data over the past 47 years. Besides, the TPF is the proper method for maximum temperature with least MAE(1.37°C) and RMSE(1.73°C). Clearly indicating the tendency, the grid map based on the OK method appears to be much smoother, whereas the other two kinds which contain jaggies and “buphthalmos” look rough.