Efficient urban canopy parametrization for atmospheric modelling: description and application with the COSMO-CLM model (version 5.0_clm6) for a Belgian Summer

This paper presents the Semi-empirical URban-canopY parametrization SURY, which bridges the gap between bulk urban land-surface schemes and explicit-canyon schemes. Based on detailed observational studies, modelling experiments and available parameter inventories, it offers a robust translation of urban canopy parameters containing the three-dimensional information into bulk parameters. It is extremely suitable for an intrinsic representation of canopy-dependent urban physics in existing bulk urban land-surface schemes of atmospheric models. At the same time, it delivers high efficiency in terms of computational cost for long-term climate modelling and numerical weather prediction. SURY enables versatility and consistency in choosing between the urban canopy parameters from bottom-up inventories and bulk parameters from top-down estimates. SURY is tested for Belgium at 2.8 km resolution with the COSMO-CLM model (version 5.0_clm6) that is extended with the bulk urban land-surface scheme TERRA_URB (version 2). The model reproduces very well the urban heat islands observed from in-situ urban-climate observations, satellite imagery and tower observations, which is in contrast to the original COSMO-CLM model without an urban land-surface scheme. As an application of SURY, the sensitivity of the COSMO-CLM model in terms of land-surface temperatures, air temperatures and associated urban heat islands is quantified for the urban canopy parameter ranges from the Local Climate Zones classification system. On the one hand, their city-scale effect shows that additional urban canopy information has potential for improving regional atmospheric modelling. On the other hand, the model performance and its sensitivity to the different urban canopy parameters largely depend on the temperature quantity considered. Such an ambiguity demonstrates that a multi-variable model evaluation is a requirement for improving and comparing online urban atmospheric modelling strategies.