Many parameters within an urban model have uncertainty estimates which could potentially have impacts on the quality of the simulations. Given observational data, it should be possible to optimise these parameters to give the most accurate solution. However, in the simplest urban model design there are a number of fluxes that contribute to the energy balance. So which of these fluxes should be used for an optimisation? Whilst the answer to this question depends upon the application of the model, the impact on the accuracy of the non optimised fluxes is not obvious? As part of the urban model comparison experiments, the Joint UK Land Environment Simulator (JULES) has been optimised on different combinations of the fluxes that contribute to the surface energy balance. The impact of these optimisations on the accuracy of all of the components of the energy balance will be discussed, along with the spread of the resultant parameters within the model. This spread in parameter values will also be considered relative to a priory uncertainties that can be established based upon observations.