关键词: 降水, 空间插值, DAYMET模型

Abstract:

Based on daily records of precipitation from 687 weather stations over China from 1990 to 2000, we interpolate and validate daily precipitation interpolation using DAYMET. The technique interpolates on a systematic grid daily precipitation from surrounding stations based on the principles of a weighted Gaussian filter. In this study we calibrated DAYMET using the China climate data base and modified DAYMET considering the different effects of the dimensional orientation of surrounding stations on the local point interpolation, which allows us to interpolate daily precipitation for any location within the country. We validated the technique using crossing validation, and compared the MAE to the result of the methods named gradient plus inverse distance squared (GIDS). Our results can be summarized as follows: without modification, the mean absolute error(MAE) of daily precipitation interpolation using DAYMET is 1.8mm, the value for GIDS is 2.2mm,and the MAE for annual total precipitation is 29.8% for DATMET. After modification, the MAE of annual precipitation for DAYMET is 27%. The reason for considering high MAE of the two methods is that the weather stations in China are sparsely distributed in space, especially in Western China. To decrease the MAE of interpolation, the addition of the precipitation observations from hydrological station network should be considered. We chose Wudinghe Basin located in Western China with an area of 30261 km², only 3 weather stations, but 93 precipitaition stations of hydrological station network, to test it. With the surrounding 30 climate stations, the interpolation MAE of annual precipitation is 77mm(28%) for DAYMET,but aided by precipitation stations of hydrological station network, the MAE is 48mm(12.1%)。

Key words: precipitation, spatial interpolation, DAYMET model