The EASM (East Asian summer monsoon) boundary area is active with intense interaction between the land surface process and the regional climate. However, the lack of high-quality long-term flux datasets for this region limits the study of the interaction among the land surface water, heat exchange, and climate. It is necessary to reconstruct a new dataset based on the currently available multiple flux data and then apply it in climate research. In this study, the datasets of land surface energy fluxes in the EASM boundary area in China were reconstructed by integrating the field observations conducted over northern China and several gridded datasets. Based on the selection of sites with good underlying representative surface and the investigation of the scattering distribution of simulations and observations, a set of monthly average sensible heat, latent heat, and net radiation datasets was generated using a multiple regression model. The cross-validation results showed that the accuracy of the constructed dataset was improved compared with several original gridded datasets, and the systematic deviation of the original lattice data was maximally eliminated. Further analysis suggests that among the surface energy balance components, the response of land surface turbulent flux to summer monsoon was more significant, and the interannual variation of the land surface turbulent heat flux with the summer monsoon duration in the EASM boundary area showed logarithmic distribution. The turbulent heat fluxes presented more significant interannual variations, as the summer monsoon was in a low persistent state. A weaker summer monsoon system may lead to a stronger impact of land surface processes on climate change. The new dataset based on multi-source flux data fusion can support climate change research and further clarify the interaction between land surface processes and monsoon climate.