Accounting for anthropic energy flux of traffic in winter urban road surface temperature simulations with the TEB model

Abstract

Snowfall forecasts help winter maintenance of road networks, ensure better coordination between services, cost control, and a reduction in environmental impacts caused by an inappropriate use of de-icers. In order to determine the possible accumulation of snow on pavements, forecasting the road surface temperature (RST) is mandatory. Weather outstations are used along these networks to identify changes in pavement status, and to make forecasts by analyzing the data they provide. Physical numerical models provide such forecasts, and require an accurate description of the infrastructure along with meteorological parameters. The objective of this study was to build a reliable urban RST forecast with a detailed integration of traffic in the Town Energy Balance (TEB) numerical model for winter maintenance. The study first consisted in generating a physical and consistent description of traffic in the model with two approaches to evaluate traffic incidence on RST. Experiments were then conducted to measure the effect of traffic on RST increase with respect to non-circulated areas. These field data were then used for comparison with the forecast provided by this traffic-implemented TEB version.