Parameter investigation for urban surface‐energy balance: A large‐eddy simulation study

This work investigates the impact of microscale surface variability on the surface‐energy balance (SEB) in vegetated urban areas, evaluates the suitability of several commonly used morphological variables (, , and ) in terms of their ability to parameterise the SEB, and investigates a set of alternative parameters. This is done by performing large‐eddy simulations for an ensemble of randomly generated urban geometries (produced using a landscape generator) and comparing the results. The geometries would be considered identical by most numerical weather prediction (NWP) land‐surface models (LSMs), but are uniquely different when resolved at the microscale. We find that variations in the SEB fluxes are relatively small, suggesting that assumptions made by existing LSMs are valid—namely that , , and alone do give a reasonable parameterisation of the urban surface from a mesoscale perspective. Using Gaussian‐process‐based machine learning to enable formal sensitivity analysis, we find that the maximum building height is important in determining all of the fluxes, with the exception of the latent heat flux, which depends predominantly on the fraction of shaded green space. The average building height and albedo of sunlit surfaces are also found to be of importance.