关键词: 路面温度, 人为热, 临近预报, 高速公路, METRo模型

Abstract: The method of road surface temperature prediction for 2022 winter Olympic demonstration station (Beijing Huilongguan station) was discussed based on the METRo model. The artificial thermal parameters of iterative training fitting with a large number of sample data were added to the METRo model as the leading parameters in order to reduce the systematic error of the METRo model and the influence of human production and life on road surface temperature prediction. The results are as follows: (1) After introduction of artificial heat parameters, the simulation ability of the METRo model was improved significantly , especially at night, the root mean square error of road surface temperature prediction could be controlled at about 1 ℃. (2) The effect of artificial heat on road surface temperature presented negative feedback during daytime and positive feedback at night. (3) The simulated road surface temperature still had some errors due to influence of limitation of radiation prediction ability of meteorological models. In the mass, it was feasible to simulate the road surface temperature, especially for low temperature of road surface at the winter Olympic expressway demonstration station by using the METRo model with pre-set anthropogenic thermal parameters, which could support the prediction and early warning ability of highway road surface temperature and road icing in winter.

Key words: road surface temperature, anthropologic heat, approach prediction, highway, METRo model