Road Temperature Modelling Without In-Situ Sensors

Karol Opara, Jan Zieliński


Modelling of the pavement temperature facilitates winter road maintenance. It is used for predicting the glaze formation and for scheduling the spraying of the de-icing brine. The road weather is commonly forecasted by solving the energy balance equations. It requires setting the initial vertical profile of the pavement temperature, which is often obtained from the Road Weather Information Stations. The paper proposes the use of average air temperature from seven preceding days as a pseudo-observation of the subsurface temperature. Next, the road weather model is run with a few days offset. It first uses the recent, historical weather data and then the available forecasts. This approach exploits the fact that the energy balance models tend to “forget” their initial conditions and converge to the baseline solution. The experimental verification was conducted using the Model of the Environment and Temperature of Roads and the data from a road weather station in Warsaw over a period of two years. The additional forecast error introduced by the proposed pseudo-observational initialization averages 1.2 °C in the first prediction hour and then decreases in time. The paper also discusses the use of Digital Surface Models to take into account the shading effects, which are an essential source of forecast errors in urban areas. Limiting the use of in-situ sensors opens a perspective for an economical, large-scale implementation of road meteorological models.


ice formation; initial conditions; pavement temperature; road meteorology; road weather stations; shading effects.

Full Text:



Aguilar, M. A.; del Mar Saldana, M.; Aguilar, F. J. 2014. Generation and Quality Assessment of Stereo-Extracted DSM from GeoEye-1 and WorldView-2 Imagery, IEEE Transactions on Geoscience and Remote Sensing 52(2): 1259–1271.

Bouilloud, L.; Martin, E.; Habets, F.; Boone, A. A.; Le Moigne, P.; Livet, J.; Marchetti, M.; Foidart, A.; Franchistéguy, L.; Morel, S.; Noilhan, J.; Pettré, P. 2009. Road Surface Condition Forecasting in France, Journal of Applied Meteorology and Climatology 48(12): 2513–2527.

Crevier, L. P.; Delage, Y. 2001. METRo: a New Model for Road- Condition Forecasting in Canada, Journal of Applied Meteorology 40(11): 2026–2037. 0450(2001)040<2026:MANMFR>2.0.CO;2

Hu, Y.; Almkvist, E.; Lindberg, F.; Bogren, J.; Gustavsson, T. 2016. The Use of Screening Effects in Modelling Route-Based Daytime Road Surface Temperature, Theoretical and Applied Climatology 125: 303–319.

Karsisto, V.; Nurmi, P.; Kangas, M.; Hippi, M.; Fortelius, C.; Nie- melä, S.; Järvinen, H. 2016. Improving Road Weather Model Forecasts by Adjusting the Radiation Input, Meteorological Applications 23(3): 503–513.

Karanko, S.; Alanko, I.; Manninen, M. 2012. Integrating METRo into a Winter Maintenance Weather Forecast System Covering Finland, Sweden and Russia, in Proc. of 16th International Road Weather Conference SIRWEC, 23–25 May 2012, Helsinki, Finland. 1–5.

Kršmanc, R.; Slak, A. Š.; Čarman, S.; Korošec, M. 2012. METRo Model Testing at Slovenian Road Weather Stations and Suggestions for Further Improvements, in Proc. of 16th International Road Weather Conference SIRWEC, 23−25 May 2012, Helsinki, Finland.

Kršmanc, R.; Slak, A. Š.; Demšar, J. 2013. Statistical Approach for Forecasting Road Surface Temperature, Meteorological Applications 20(4): 439–446.

Kršmanc, R.; Tarjáni, V.; Habrovský, R.; Slak, A. Š. 2014. Upgraded METRo Model within the METRoSTAT Project, in Proc. of the 17th SIRWEC Conference, 30 January–1 February 2014, Andorra, Andorra. 1–8.

Linden, S. K.; Drobot, S. D. 2010. The Evolution of METRo in a Roadway DSS, in Proc. of 15th International Road Weather Conference SIRWEC, 5–7 February 2010, Quebec, Canada. 1–8.

Linden, S. K.; Petty, K. R. 2008. The Use of METRo (Model of the Environment and Temperature of the Roads) in Roadway Operation Decision Support Systems, in Proc. of the 24th Conference on IIPS. Ed. by Diamond, H. J.; Seguin, W. R., 20–24 January 2008, Seatlle, Washington. 1–11.

Sass, B. H. 1992. A Numerical Model for Prediction of Road Temperature and Ice, Journal of Applied Meteorology 31(12): 1499–1506.<1499:ANMFP O>2.0.CO;2

Sirmacek, B.; Taubenbock, H.; Reinartz, P.; Ehlers, M. 2012. Performance Evaluation for 3-D City Model Generation of Six Different DSMs from Air- and Spaceborne Sensors, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5(1): 59–70.

Sokol, Z.; Zacharov, P.; Sedlák, P.; Hošek, J.; Bližňák, V.; Chlá- dová, Z.; Pešice, P.; Škuthan, M. 2014. First Experience with the Application of the METRo Model in the Czech Republic, Atmospheric Research 143: 1–16.

Sokol, Z.; Bližňák, V.; Sedlák, P.; Zacharov, P.; Pešice, P.; Škuthan, M. 2017. Ensemble Forecasts of Road Surface Temperatures, Atmospheric Research 187: 33–41.

Shao, J.; Swanson, J. C.; Patterson, R.; Lister, P. J.; McDonald, A. N. 1997. Variation of Winter Road Surface Temperature Due to Topography and Application of Thermal Mapping, Meteorological Applications 4(2): 131–137.

Ząbczyk, K. 2006. Meteorologia drogowa a bezpieczeństwo ruchu, in Proc. of 6th International Conference on Road Safety GAMBIT, 17–19 May 2006, Gdańsk, Poland. (in Polish)

DOI: 10.3846/bjrbe.2017.30


1. Measurement of Temperature Distribution Within Steel Box Girder of Vistula River Bridge in Central Europe
Maciej Hildebrand, Łukasz Nowak
The Baltic Journal of Road and Bridge Engineering  vol: 15  issue: 4  first page: 71  year: 2020  
doi: 10.7250/bjrbe.2020-15.495


  • There are currently no refbacks.

Copyright (c) 2017 Vilnius Gediminas Technical University (VGTU) Press Technika