A spatial interpolation by combining the Barnes scheme and precipitation frequency is developed according to daily rainfall characteristics. With the interpolation, a daily grid precipitation dataset, which covers a domain ranging from 99° to 123°E and 24° to 36°N and has a 0.1 longitudinal and latitudinal resolution, is obtained by utilizing daily precipitation data of basic observation stations in China and ordinary observation stations in 15 provinces in the vicinity of the Changjiang valley during 1971 to 2005. The error estimation of the grid dataset is accessed through cross-validation statistics. The statistics show the combining scheme for daily precipitation interpolation is not only with small mean biased error, mean absolute error and mean square error as well as high correction coefficient, but also close to the observation variation and frequency. The primary analysis indicates that the datasets provide a finer precipitation distribution. And the years with the greatness (smallness) of the annual area precipitation, in particularly the summertime area precipitation, correspond to the distinguished flooding (drought) processes occurred in the Changjiang valley. So the daily precipitation datasets can be applied to meteorology and relative field with realistic, continuum grid data.
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