METRo: A New Model for Road-Condition Forecasting in Canada

Crevier, Louis-Philippe; Delage, Yves

doi:10.1175/1520-0450(2001)040<2026:manmfr>2.0.co;2

Cited by 118 publications

(88 citation statements)

References 10 publications

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“…Through training and standard productions, they have begun to make infrastructure managers aware of the need to control the amounts spread. Many studies are dedicated to forecasting of the road surface temperature (RST) (Shao and Lister, 1995;Sass, 1997;Paumier and Arnal, 1998;Chapman et al, 2001;Crevier and Delage, 2001;Raatz and Niebrügge, 2002;Bouilloud and Martin, 2006;Bouilloud et al, 2010). A forecast of the snowfall and RST helps coordination of winter maintenance services, optimizing their costs, and reduces the environmental impacts caused by an inappropriate use of de-icers.…”

Section: Introductionmentioning

confidence: 99%

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

Khalifa

Marchetti

Bouilloud³

et al. 2016

Geosci. Model Dev.

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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.

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Section: Introductionmentioning

confidence: 99%

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

Khalifa

Marchetti

Bouilloud³

et al. 2016

Geosci. Model Dev.

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“…Commonly, road ice is forecast using mathematical models that reproduce the physical interactions between the road and the atmosphere (Sass 1992;Shao and Lister 1995;Best 1998;Chapman, Thornes, and Bradley 2001b;Crevier and Delage 2001;Korotenko 2002). Such models take into account meteorological parameters, such as air temperature, precipitation, wind direction, wind speed, humidity, and dew point, and predict both road surface temperature and road conditions (Chapman, Thornes, and Bradley 2001b).…”

Section: Discussionmentioning

confidence: 99%

Probabilistic Weather Forecasting for Winter Road Maintenance

Berrocal

Raftery

Gneiting

et al. 2010

Journal of the American Statistical Association

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Winter road maintenance is one of the main tasks for the Washington State Department of Transportation. Anti-icing, that is, the preemptive application of chemicals, is often used to keep the roadways free of ice. Given the preventive nature of anti-icing, accurate predictions of road ice are needed. Currently, anti-icing decisions are usually based on deterministic weather forecasts. However, the costs of the two kinds of errors are highly asymmetric because the cost of a road closure due to ice is much greater than that of taking anti-icing measures. As a result, probabilistic forecasts are needed to optimize decision making.We propose two methods for forecasting the probability of ice formation. Starting with deterministic numerical weather predictions, we model temperature and precipitation using distributions centered around the bias-corrected forecasts. This produces a joint predictive probability distribution of temperature and precipitation, which then yields the probability of ice formation, defined here as the occurrence of precipitation when the temperature is below freezing. The first method assumes that temperatures, as well as precipitation, at different spatial locations are conditionally independent given the numerical weather predictions. The second method models the spatial dependence between forecast errors at different locations. The model parameters are estimated using a Bayesian approach via Markov chain Monte Carlo.We evaluate both methods by comparing their probabilistic forecasts with observations of ice formation for Interstate Highway 90 in Washington State for the 2003-2004 and 2004-2005 winter seasons. The use of the probabilistic forecasts reduces costs by about 50% when compared to deterministic forecasts. The spatial method improves the reliability of the forecasts, but does not result in further cost reduction when compared to the first method.

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“…. Some radiation parameterisations in these models are highly detailed, including information about aerosols, ozone and shading effects (Rayer 1987;Sass 1997;Crevier & Delage 2001). However, no radiation measurements are made at typical roadside weather stations and we have found no comparisons of observed and predicted values of any of the road surface flux terms.…”

Section: Boundary Condition Validation In Road Model Systemsmentioning

confidence: 97%

“…Rayer 1987;Sass 1997;Crevier & Delage 2001). Other road models also use statistical techniques with current and historical data (e.g.…”

Section: Boundary Condition Validation In Road Model Systemsmentioning

confidence: 99%

Modelling the interaction between the atmosphere and curing concrete bridge decks with the SLABS model

2003

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METRo: A New Model for Road-Condition Forecasting in Canada

Cited by 118 publications

References 10 publications

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

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

Probabilistic Weather Forecasting for Winter Road Maintenance

Modelling the interaction between the atmosphere and curing concrete bridge decks with the SLABS model

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