Sky View Factor and Screening Impacts on the Forecast Accuracy of Road Surface Temperatures in Finland

Abstract

Abstract Forecasting road conditions is important, especially in areas with wintry conditions and rapidly changing weather. Accurate forecasts help authorities keep roads safe and optimize maintenance. Considering local features is important when making the forecast because the road surface temperature can vary significantly depending on the road surroundings. For example, in a shadowed location, the road surface temperature can be significantly lower than in open surroundings. A road weather model developed at the Finnish Meteorological Institute is used to forecast the road surface temperature and road conditions. However, the model still assumes open road surroundings. In this study, sky view factor and screening are included in the model, and their effects on the forecast road surface temperature is tested. Road surface temperature hindcasts were performed for 23 selected road weather stations in Finland for three winter periods (October–March) between 2018 and 2021. The results were location dependent, and even changing the lane had a great effect on the verification results in some cases. At best, the screening considerably decreased RMSE values during the day. However, there were many cases in which the screening increased RMSE. In general, the used shadowing algorithm increased the already negative bias during the day. Nevertheless, there were also cases in which the shadowing algorithm improved the bias, especially in February. During the night, the sky view factor made the forecast generally a little warmer, which often slightly decreased the negative bias in the forecast. Significance Statement The screening caused by objects surrounding a road has a great effect on the road surface temperature. Recently, a screening algorithm was added to the Finnish Meteorological Institute’s model that forecasts road conditions. The purpose of this study was to test how the algorithm affects the accuracy of road surface temperature forecasts. According to the results, the screening greatly improved the forecast accuracy in some cases. However, in some cases, the screening made the already overly cold forecast even colder. The study has increased our understanding of the effect of shadowing in the modeled road surface temperatures and helps to create more accurate forecasts in the future.