A modification of HASM for interpolating precipitation in China

Based on the spatial distribution of precipitation in China, this study gives a modification of High Accuracy Surface Modeling (HASM) method for improving interpolation of precipitation. To assess the feasibility of this modified model, namely, HASM-PRE, we use precipitation data measured at 712 stations for the period 1951-2010, using 605 stations for function development and reserving 107 for validation tests. The performance of HASM-PRE is compared with those of HASM and other classical methods: kriging, inverse distance weighted (IDW) method and spline. Results show that HASM-PRE has less root mean square error (RMSE) and mean absolute error (MAE) than the other techniques tested in this study. The precipitation map obtained from HASM-PRE is better than that obtained using other methods. Therefore, HASM-PRE can be seen as an alternative to the popular interpolation techniques, particularly if we focus on simulation accuracy. In addition, the effective way to combine the strengths of both human expert and differential geometry in this study can be applied for calculating precipitation for other areas in other temporal scales. For better improvement, HASM-PRE can be combined with ancillary variables and implemented in parallel environments.