Improved winter conditions in SURFEX-TEB v9.0 with a multi-layer snow model and ice for road winter maintenance

Abstract. Snow-covered or icy roads increase the risk of accidents for drivers, pedestrians, and cyclists. In cities or in remote areas, to prevent these slippery conditions, road winter maintenance decisions are weather-informed by simulations. Numerical road weather models have been developed for this purpose, and mostly built to simulate the road conditions in open environments without shadowing and reflections effects. In this study, we intent to bridge the gap between road weather models and urban climate models to improve cold regions urban modeling and road condition predictions in any environment. We have refined the road surface processes related to winter conditions in the Town Energy Balance (surface externalisée; SURFEX-TEB v9.0), which is an urban climate model used for complex environment modeling. For icy conditions, we have developed an ice content to account for the freezing and melting of the water content on the surface. Additionally, we enhanced TEB's representation of snow on road, previously relying on a single-layer snow model (1-L), with a more precise multi-layer snow model known as Explicit Snow (ES). We have conducted evaluations at two distinct locations: Col de Porte in the Alps and a road weather station in southern Finland. Our findings shows that the enhanced TEB model (TEB-ES) outperforms TEB, as well as two benchmark models, ISBA-Route/CROCUS, and a multiple linear regression in open environments. This results are promising for using TEB to inform road winter maintenance decisions.