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