A numerical forecast model for road meteorology

Meng, Chunlei

doi:10.1007/s00703-017-0527-8

Cited by 8 publications

(6 citation statements)

References 35 publications

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“…In this study, the performance evaluation of TEB and its modified version TEB-ES has been carried out in open surrounding areas to investigate whether this urban climate model can accurately reproduce the road conditions predicted by road weather models. The TEB-ES road surface temperature performance shown in this study appears similar to heat-balance road weather models at other locations (Meng, 2017;Nuijten, 2016;Denby et al, 2013). Some of these models have been tested in open environments, while others have been tested in urban areas.…”

supporting

confidence: 58%

“…On the other hand, road weather models fail to compute accurate road conditions in an urban environment. Some urban climate models bridge part of the gap by including snow and ice accumulation in the road component (Meng, 2017). There are also road weather models that take into account sky-view factors and radiation trapping (Karsisto and Horttanainen, 2023;Denby et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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

Colas,

Masson,

Bouttier

et al. 2024

Preprint

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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.

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supporting

confidence: 58%

Section: Introductionmentioning

confidence: 99%

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

Colas,

Masson,

Bouttier

et al. 2024

Preprint

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“…Voldborg developed a forecasting model that can generate short-term indicators such as air temperature, humidity, and road surface temperature for each of the more than 200 road weather stations in Denmark [7]. Meng developed a refined numerical model for the prediction of pavement parameters, taking into account the influence of pavement factors and basic urban properties, and the results showed that solar radiation correction factors, asphalt depth, and asphalt thermal conductivity are important parameters for the simulation of road interface temperatures [8]. Chen J et al proposed an innovative time-varying function to predict pavement temperature in relation to solar radiation and air temperature [9].…”

Section: Literature Reviewmentioning

confidence: 99%

Attention-Based BiLSTM Model for Pavement Temperature Prediction of Asphalt Pavement in Winter

Bai

Yang

Zhang³

et al. 2022

Atmosphere

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Pavement temperature is the main factor determining road icing, and accurate and timely pavement temperature prediction is of significant importance to regional traffic safety management and preventive maintenance. The prediction of pavement temperature at the micro-scale has been a challenge to be tackled. To solve this problem, a bidirectional extended short-term memory network model based on the attention mechanism (Att-BiLSTM) was proposed to improve the prediction performance by using the time series features of pavement temperature and meteorological factors. Pavement temperature data and climatic data were collected from a road weather station in Yunnan, China. The results show that the MAE, MSE, and MAPE of the proposed Att-BiLSTM model were 0.330, 0.339, and 10.1%, respectively, which were better than the other baseline models. It was shown that 93.4% of the predicted values had an error less than 1 °C, and 82.1% had an error less than 0.5 °C, indicating that the proposed Att-BiLSTM model enables significant performance improvement. In addition, this paper quantified and analyzed the effects of parameters such as the size of the sliding window, the number of hidden layer neurons, and the optimizer on the performance of the prediction model.

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“…where E p is the potential evaporation (m·s −1 ). Because surface runoff depends on topography and drainage, the drainage was evaluated based on the sensitivity analysis result in 18 road sites in Beijing during a whole summer season, which is approximately 10 mm·d −1 [24]. E p can be parameterized as follows:…”

Section: Urban Water Balance Modelmentioning

confidence: 99%

Local and Regional Scale Evaluation of the Integrated Urban Land Model by Comparing with the Common Land Model

Meng

Zhang

2019

Advances in Meteorology

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Land surface evaporation is not only an important parameter in natural land surface modeling, but a crucial important parameter in urban hydrology modeling. A whole-layer soil evaporation scheme was developed in the integrated urban land model (IUM) to improve the soil evaporation simulation. e impervious surface evaporation (ISE) was used as a component of urban water balance equation. In this paper, the integrated urban land model was validated at one desert site and six urban road sites to emphasize the improvement in the evaporation simulations for arid and urban areas. A sensitivity analysis was implemented in seven basins to expand the utility of the whole layer soil evaporation scheme. For the urban road sites, the validation results indicate that imperious surface evaporation (ISE) plays a crucial role in road surface temperature (RST) simulations on rainy days. For the desert site, the validation results show that the inner layer evaporation is very important in arid regions. For the basins, the analysis results indicate that the relative monthly mean differences in the evapotranspiration (ET) between the simulations with (IUM) and without (Common Land Model (CoLM)) considering the inner layer evaporation range from −8% to 8%, which is proportional to the degree of dryness. In arid areas, especially deserts, the inner layer soil evaporation could not be neglected.

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A numerical forecast model for road meteorology

Cited by 8 publications

References 35 publications

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

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

Attention-Based BiLSTM Model for Pavement Temperature Prediction of Asphalt Pavement in Winter

Local and Regional Scale Evaluation of the Integrated Urban Land Model by Comparing with the Common Land Model

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