The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: Description and application with the COSMO-CLM model for a Belgian summer

Abstract

This paper presents the Semi-empirical URban canopY parametrization (SURY) v1.0, 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. As a result, it brings canopy-dependent urban physics to existing bulk urban land-surface schemes of atmospheric models. At the same time, SURY preserves a low computational cost of bulk schemes for efficient numerical weather prediction and climate modelling at the convection-permitting scales. It offers versatility and consistency for employing both 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 (v5.0-clm6) that is extended with the bulk urban land-surface scheme TERRA-URB (v2.0). 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 atmospheric modelling with the COSMO-CLM model is addressed for the urban canopy parameter ranges from the local climate zones of http://WUDAPT.org. City-scale effects are found in modelling the land-surface temperatures, air temperatures and associated urban heat islands. Recommendations are formulated for more precise urban atmospheric modelling at the convection-permitting scales. It is concluded that urban canopy parametrizations including SURY, combined with the deployment of the WUDAPT urban database platform and advancements in atmospheric modelling systems, are essential.