# Evaluation of the Urban Weather Generator on the City of Toulouse (France)
###### Abstract  
This article addresses the simulation of urban air temperatures with a focus on evaluating the Urban Weather Generator (UWG) model over Toulouse, France. As urban temperatures, influenced by factors like urbanization, anthropogenic heat release, and complex urban geometry, exhibit an urban heat island (UHI) effect, understanding and mitigating UHI become crucial. With increasing global warming and urban populations, aiding urban planners necessitates accurate simulations requiring data at the canyon level. The paper evaluates UWG's performance in simulating air temperatures under realistic conditions, emphasizing an operational context and a non-specialist user's perspective. The evaluation includes selecting the most suitable meteorological station, assessing the impact of the rural station choice, and conducting a sensitivity analysis of input parameters. The validation demonstrates good agreement, with a mean bias error (MBE) of 0.02 \({}^{\circ}\)C and a root mean square error (RMSE) of 1.73 \({}^{\circ}\)C. However, we highlight the fact that UWG performs better in a densely urbanized area, and exhibits limitations in sensitivity to urban surface parameter variations, particularly in less urbanized areas. U rban Weather Generator; urban heat island; air temperature; sensitivity analysis; validation 2024 1485 18  
Urban air temperatures strongly depend on the environment (building, vegetation, traffic, water body, etc.) and the scale at which it is studied from a building to a city level. It is also important to highlight that, faced with the difficulty of extracting precise air temperature measurements, perceptual research has been performed to derive qualitative criteria able to interpret the inconveniences caused by UHI (see (2018) for a list of indexes and associated techniques to estimate them). As a consequence, many studies have been developed either to _(i)_ simulate urban temperatures with physical models (see (2018) for a recent review); _(ii)_ monitor them with the implementation of local networks ((2018, 2019) or based on crowdsourcing (2020)), or _(iii)_ make statistical models that mix local information (land cover, urban morphology) with local measurements to generate maps of UHI (2019, 2020, 2021). The reader can find in (2021, 2021, 2021, 2021) recent reviews on UHI prediction approaches. In an application context, and inspired by the description in various review papers, simulation approaches can be classified into three main categories (2021):  
1. Building-scale models: like EUReCA (2021) (relies on energy balance applied to the building volume)
2. Micro-scale models: for example, Solene microclimate (2021) and Laser-F (2019, 2019) (both based on a modeling of the urban surface geometry at a metric resolution, the Solene microclimate is coupled with an urban airflow model)
3. City-scale models (of the order of 100 m resolution): among others, we can mention (2019, 2021) (takes into account many physical processes, with an efficient parameterization approach allowing fast numerical simulations over large areas), Solweig (2021) (essentially based on radiative exchanges modeling), CitySim (2019, 2021) (based on radiative exchanges and building thermal dynamics modeling), and Envi-met (2021) (originally based on airflow modeling, it is the most often used model for microclimate studies. One of its limitations is the calculation of radiation fluxes due to the geometric representation of the urban fabric in an orthogonal grid). The various microclimatic models differ in the phenomena and scales addressed, ranging from canyon to city level. In some cases, simulations can be very expensive in terms of computer resources and time. Moreover, the data needed for the simulations (physical properties of materials, radiative forcing, etc.) are not always available. Among existing models, Urban Weather Generator (UWG) (2019) is an appealing compromise since it is open source, easy to operate, and applicable at a city scale.