This study considers a remapping algorithm between irregularly distributed observations and grid points based on Voronoi diagrams and examines its potential for verification of precipitation forecasts. We propose a new remapping method using Voronoi diagrams to apply conservative area-weighted remapping on grid data to station points, describing a representative area for each station point. Conservative remapping is applied to interpolate daily precipitation data between grid and station points over South Korea. The proposed method shows significant differences from bilinear interpolation, which has been widely used in modeling communities, for local maximum and mean in a given domain. It is also shown that different interpolation methods have an impact on verification results of precipitation forecast from a numerical weather prediction model against station observations. It is suggested that the proposed method has potential to be used for verifying precipitation forecasts at in situ observation points, with its conservativeness and capability to be applied in any remapping direction between grids and stations.