Daily net surface shortwave radiation (DNSSR) is one of the most important parameters in various global land process and hydrological models and is required in climate change, energy balance, ecological, and atmospheric circulation research. This study constructed a daily net surface shortwave radiation model using the random forest (RF) method and MODIS twin-satellite products. 15531 pairs of samples containing 18 independent variables were extracted by matching MODIS twin-satellite products and FLUXNET daily observations. The Bias, RMSE (root mean square error), and R² for the proposed DNSSR model using the RF method are -0.1W/m², 27.8 W/m², and 0.90, respectively. Based on the process, MODIS-DNSSR global distribution in different seasons were presented. Verification with field observations shows that the results are similar to the ERA5 reanalysis data, which are closely related to the seasonal distribution of solar energy. To further verify the results, ERA5-DNSSR were compared with the FLUXNET-DNSSR. The result shows that the proposed DNSSR model has also better accuracy and higher resolution than the ERA5 data. The RF-based DNSSR model has a good retrieval accuracy, high spatial resolution, and good temporal continuity. It can be effectively transplanted to the retrieval of other climatic resources.