uDALES 1.0: a large-eddy simulation model for urban environments

Abstract

Abstract. Urban environments are of increasing importance in climate and air quality research due to their central role in the population's health and well-being. Tools to model the local environmental conditions, urban morphology and interaction with the atmospheric boundary layer play an important role for sustainable urban planning and policy making. uDALES is a high-resolution, building-resolving, large-eddy simulation code for urban microclimate and air quality. uDALES solves a surface energy balance for each urban facet and models multi-reflection shortwave radiation, longwave radiation, heat storage and conductance, as well as turbulent latent and sensible heat fluxes. Vegetated surfaces and their effect on outdoor temperatures and energy demand can be studied. Furthermore, a scheme to simulate emissions and transport of passive and reactive gas species is present. The energy balance has been tested against idealised cases and the dispersion against wind tunnel experiments of the Dispersion of Air Pollution and its Penetration into the Local Environment (DAPPLE) field study, yielding satisfying results. uDALES can be used to study the effect of new buildings and other changes to the urban landscape on the local flow and microclimate and to gain fundamental insight into the effect of urban morphology on local climate, ventilation and dispersion. uDALES is available online under the GNU General Public License and remains under active maintenance and development.

A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0

“…The governing equations for the LES are unchanged from Suter et al (2022), and are discretised using the finite difference method on a Cartesian grid. The presence of obstacles are modelled using the IBM approach, and wall functions are used to parametrise processes near the immersed boundary.…”

“…uDALES has been used for studies concerning atmospheric boundary layer processes (Grylls et al, 2020), air quality (Grylls et al, 2019;Lim et al, 2022), the effect of trees (Grylls and van Reeuwijk, 2022), and parametrisations for larger-scale models (Sützl et al, 2021a, b). The framework has been described in detail in (Suter et al, 2022), so this work only discusses novel or improved aspects and relevant concepts.…”

“…IBMs for LES have different requirements because unlike DNS, the flow near the obstacle is not fully-resolved. LES frameworks opting for an IBM with a Cartesian mesh approach have typically evolved from atmospheric flow solvers and have been equipped with multi-physics surface schemes capturing urban processes, for example PALM-USM (Resler et al, 2017;Maronga et al, 2020), City-LES (Watanabe et al, 2021), and uDALES v1.0 (Suter et al, 2022). These frameworks can currently only model obstacles that align with the Cartesian grid, so urban geometries that do not actually meet this requirement are approximated as doing so using a voxel representation.…”

“…For example, in Sect. 4.3 of Suter et al (2022), the geometry was generated using a raster of a surface elevation map (obtained from GIS data), and the shape of buildings Figure 1. Temperature at street level in a realistic urban environment; simulated using uDALES v1.0 (Suter et al, 2022).…”

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

“…The urban computational fluid dynamics (CFD) models (e.g., Toparlar et al., 2017), on the other hand, consider the detailed urban morphology and simulate the turbulence field at an extremely high resolution (∼10 m) by solving the simplified Reynolds‐averaged Navier‐Stokes (RANS) equations or using Large Eddy Simulation (LES, e.g., Maronga et al., 2020; Suter et al., 2022) and Detached Eddy Simulation approaches (Dadioti & Rees, 2017). Though urban CFD models can provide the most detailed flow field to street level, their applications are limited in spatiotemporal coverages due to the restrictions on computational resources.…”