Knowledge of soil–vegetation–atmosphere energy exchange processes is essential for examining the response of agriculture to changes in climate in both the short and long term. However, there are relatively few sites where all the flux measurements necessary for evaluating these responses are available; where they exist, data are often incomplete and/or of limited duration. At the same time, there is often an extensive observation network available that has gathered key meteorological data (sunshine, wind, rainfall, etc.) over decades. Simulating the terms of the surface energy balance (SEB) using available meteorological, soil and vegetation data can improve our understanding of how agricultural systems respond to climate and how this response will vary spatially. Here, we employ a physically-based scheme to simulate the SEB fluxes over a mid-latitude, maritime temperate environment using routine weather observations. The latent heat flux is a critical SEB term as it incorporates the response of the plant to environmental conditions including available energy and soil water. This response is represented in modelling schemes through surface resistance (rs), which is usually expressed as a function of nearsurface water vapor alone. In this study, we simulate the SEB over two grassland sites, where eddy flux observations are available, representing imperfectly- and poorly- drained soils. We employ three different formulations of rs, representing varying degrees of sophistication, to estimate the surface fluxes. Due to differences in soil moisture characteristics between the sites, we ultimately focused our attention on an rs formulation that accounted for soil water retention capacity, based on the Jarvis conductance model; the results at both hourly and daily intervals are in good agreement, with RMSE values of ≈ 40 W m−2 for sensible and latent heat fluxes at both sites. The findings show the potential value of using routine weather observations to generate the SEB where flux observations are not available and the importance of soil properties in estimating surface fluxes. These findings could contribute to the assessment of past and future climate change on grassland ecosystems.