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Road Stretch Forecasting

Using High Resolution Databases for Road Stretch Forecasting Torben Strunge Pedersen, Claus Petersen, Alexander Mahura, Kai Sattler Research and Development Department Danmarks meteorologiske institut (DMI) Contakt: tsp@dmi.dk. Road Stretch Forecasting. 370 Road stations 153 Routes

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Road Stretch Forecasting

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  1. Using High Resolution Databases for Road Stretch ForecastingTorben Strunge Pedersen, Claus Petersen, Alexander Mahura, Kai SattlerResearch and Development Department Danmarks meteorologiske institut (DMI)Contakt: tsp@dmi.dk

  2. Road Stretch Forecasting 370 Road stations 153 Routes 22840 Parts with 500 m or less between points

  3. Road Stretch Forecasting 370 Road stations 153 Routes 22840 Parts with 500 m or less between Points Atmospheric model With 5 km resolution

  4. Atmospheric state provided by the Numerical Weather Prediction Model Cloud Cover Radiation Vertical structure of wind, temperature and humidity Average grid point temperature NWP Models provide information for a fixed grid Site specific model Shadows Sky view Local observations Local cold air pooling ’Random’ distributed points Local wind conditions Local near surface temperature Local terrain features Height Vegetation type and height Buildings Terrain type Traffic Road characteristics Material Road type (bridge, elevated road etc.) Road Stretch forecastingLarge scale and local features

  5. OBTAINING LOCAL INFORMATIONTHE DANISH HEIGHT MODEL Horizontal Resolution: 1.6 x 1.6 meter Vertical accuracy: 3 cm Coverage: Denmark Laser scanning from airplane

  6. OBTAINING LOCAL INFORMATIONTHE DANISH HEIGHT MODEL Horizontal Resolution: 1.6 x 1.6 meter Vertical accuracy: 3 cm Coverage: Denmark Laser scanning from airplane • Deduced parameters • Height • Shadows • Sky view • Terrain type • Valley • Dimensions • Orientation • Slope • Hill top • …

  7. OBTAINING LOCAL INFORMATIONTHE DANISH HEIGHT MODEL Horizontal Resolution: 1.6 x 1.6 meter Vertical accuracy: 3 cm Coverage: Denmark Laser scanning from airplane • Deduced parameters An alternative approach (fish eye) • Height • Shadows • Sky view • Terrain type • Valley • Dimensions • Orientation • Slope • Hill top • …

  8. OBTAINING LOCAL INFORMATION Application of the Danish Height Model at a single site Øster Voldgade (station number 1543)

  9. Height profile and shadow effects

  10. Height profile and shadow effects

  11. Height profile and shadow effects

  12. Height profile and shadow effects

  13. Height profile and shadow effects

  14. Height profile and shadow effects

  15. Height profile and shadow effects

  16. Height profile and shadow effects

  17. Height profile and shadow effects

  18. Height profile and shadow effects

  19. Height profile and shadow effects

  20. Height profile and shadow effects

  21. Height profile and shadow effects

  22. Height profile and shadow effects

  23. Height profile and shadow effects

  24. Height profile and shadow effects

  25. Height profile and shadow effects

  26. Height profile and shadow effects

  27. Height profile and shadow effects

  28. Height profile and shadow effects

  29. Height profile and shadow effects

  30. Height profile and shadow effects

  31. Height profile and shadow effects

  32. Height profile and shadow effects

  33. Height profile and shadow effects

  34. Height profile and shadow effects

  35. Height profile and shadow effects

  36. Height profile and shadow effects

  37. Different methods to obtain shadow and skyview angle

  38. Different methods to obtain shadow and skyview angle

  39. Different methods to obtain shadow and skyview angle - Transparency properties

  40. Application of the High Resolution Databases: Kort & MatrikelStyrelsen (KMS) 10x10 meter resolution database of terrain coverage such as building, water objects, forrest, individual trees, road and many other types. Global Self-consistent Hierarchical High-resolution Shorelines (GSHHS) database (evaluate distance and direction to seashore – transport of cool/warm, most/dry air); COoRdinate INformation on the Environment (CORINE) database on detailed land cover and use characteristics (classify road stations/ stretches and their surroundings at local and remote scales – clarification on shadowing effects, sky view factor). DRD database on driving lanes characteristics (albedo, density, heat conductivity, heat capacity – direct input into RCModel). Other Databases

  41. High resolution databases can provide physiographic data for road stretch forecasting Apart from terrain elevation and slope also shadowing and sky view effects can be deduced This approach can eliminate manual measurements Summery

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