We use the Weather Research and Forecasting (WRF) model to generate coarse-grid climate predictions. The WRF model is a numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. It has been “urbanized” via the inclusion of empirical urban canopy parameterizations. Recently the urban canopy parameterizations have been coupled with building energy models to enable the estimation of the buildings’ energy use. The results of a WRF simulation can be interpreted directly or provide boundary conditions for a micro-scale CFD model such as PALM-4U.
WRF incorporates, among other modules, a fully coupled land surface model to simulate column land surface processes: WRF model results of atmospheric conditions, short-wave/long-wave radiation, and precipitation are used to update the land state, which in turn influences the WRF simulation of atmospheric conditions. Over urban areas, an urban canopy parameterization will be invoked to properly account for urban morphological and thermo-physical features. Given the critical importance of soil moisture conditions in most European cities, we improve the standard implementation of WRF by incorporating the uncoupled high-resolution land data assimilation system (HRLDAS) in order to initialize the land state variables. The HRLDAS simulation time required to reach equilibrium can exceed one year, which makes it practically impossible to couple the HRLDAS with the computationally intensive WRF atmospheric model.
Two off-shoots of WRF, significant to urban climate studies, are WRF-Chem and WRF-Hydro. WRF-Hydro can simulate floods, hydrological states and spatial distribution of water resources. It is a physics-based hydro-meteorological model that receives meteorological forcing (land surface states and fluxes) from WRF. WRF-Hydro using assimilated precipitation based on WRF achieves generally satisfactory results for flood forecasting. WRF-Hydro output can inform decision makers on location, timing and duration of inundations while fully accounting for landscape dynamics. WRF-Chem can simulate meteorological conditions together with air pollutant concentrations, with a focus on Nitrogen oxides, particulate matter and Ozone (O3). To create WRF-Chem, various gas-phase chemistry and aerosol mechanisms have been added to the base WRF model. One important application of WRF-Chem in an urban setting is the simulation of near-surface atmospheric concentreations of Ozone. Ozone present in in urban areas is, in large part, a secondary pollutant produced in the presence of precursors such as nitrogen oxide and carbon monoxide. The urban production of Ozone is driven by intense photochemical activity and the prevailing urban micro-climatic conditions.