With the continuous development of higher resolution and more accuracy grid forecasting operation, the spatial and temporal accuracy and precision of grid forecast products need to be continuously improved. To maintain the compatibility between grid and site forecast , a fast refinement interpolation (FRI) method which takes into account both the static real terrain and the dynamic atmospheric vertical variation process was investigated. In this study, 3-36h forecast products for three models (ECMWF, CMA-GFS and CMA-MESO) from January 1, 2022 to March 31, 2022 were selected as experimental data. Individual weather process tests, FRI parameter selection tests and long-term interpolation test comparisons were conducted. From long-term interpolation tests and individual case trials, the FRI method has a clear advantage over the bilinear interpolation method. From the spatial perspective, the FRI method can improve the spatial interpolation accuracy of 2m temperature above the ground and the results are more consistent with the topographic variation. From a temporal perspective, the FRI method has significantly improved the accuracy of the 2m temperature interpolation results compared to the bilinear interpolation method, especially in the western region with complex subsurface. The loss parameter in the method can also be used as an indicator to check the 3D atmospheric vertical variability of the model product. The FRI method is fast and efficient and has a clear physical meaning, which provides an important theoretical support for more accurate reflection of near-surface meteorological forecast information.