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Improved road weather forecasting by using high resolution satellite data Claus Petersen and Bent H. Sass Danish Meteorological Institute. Background.

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slide1
Improved road weather forecasting by using high resolution satellite dataClaus Petersen and Bent H. SassDanish Meteorological Institute
background
Background
  • It has been realized that prediction of cloud cover and precipitation play a key role in prediction of the road surface temperature and the road conditions.
  • Prediction of cloud cover requires a NWP model which can model clouds and data-assimilation of cloud cover and precipitation observations.
viking project
Viking project
  • Title
    • Development of new generation of cloud and precipitation analyses for the automatic Road Weather Model
  • Duration
    • 2003-2005
  • Goal
    • Improvement of the forecasts for slippery roads by developing a new prediction model
model domain of nwp model and network of road stations
Model domain of NWP model and network of road stations
  • Horizontal resolution0.15x0.15
  • Vertical levels 40
  • Number of grid points82x98=8036
  • Dynamic time step 72 s.
  • Physical time step 360 s.
  • Boundary update 1 hour
  • Boundary age 0-5 hours
  • First guess age 0-1 hour
  • Forecast frequency Every hour
  • Forecast length 5-24 hours
  • Data-assimilation period 3 hours
  • Road stations 300
slide9
Cloud mask

Cloud top temperature

Precipitation intensity

Cloud type

forecast
1 hour forecast with data-assimilation of satellite dataFORECAST

Observed cloud mask

1 hour forecast of cloud mask

1 hour forecast of wind and temperature

1 hour forecast of precipitation, mslp

forecast1
1 hour forecast without data-assimilation of satellite dataFORECAST

Observed cloud mask

1 hour forecast of cloud mask

1 hour forecast of wind and temperature

1 hour forecast of precipitation, mslp

slide14
6 hour forecast with data-assimilation of satellite data

Observed cloud mask

6 hour forecast of cloud mask

6 hour forecast of wind and temperature

6 hour forecast of precipitation, mslp

slide15
6 hour forecast without data-assimilation of satellite data

Observed cloud mask

6 hour forecast of cloud mask

6 hour forecast of wind and temperature

6 hour forecast of precipitation, mslp

slide16
21 hour forecast with data-assimilation of satellite data

Observed cloud mask

21 hour forecast of cloud mask

21 hour forecast of wind and temperature

21 hour forecast of precipitation, mslp

slide17
21 hour forecast without data-assimilation of satellite data

Observed cloud mask

21 hour forecast of cloud mask

21 hour forecast of wind and temperature

21 hour forecast of precipitation, mslp

road condition model
Road Condition Model

G: Ground heat flux

S: Direct insolation

D: Diffuse insolation

R: Infrared radiation

H: Sensible heat flux

L: Latent heat flux

F: Flux correction

verification of cloud forecast
Verification of cloud forecast
  • First two weeks of March 2005
  • Danish SYNOP stations
  • Limited MSG1 data
  • Verifcation for model run every hour
best practice
Best practice
  • A general method has been developed to assimilate cloud observations into a NWP model.
  • Verification and case studies indicate that prediction of cloud cover is improved for short range forecasting but that results can be further improved with more experience.
  • Further verification and investigation of the road surface temperature dependency of cloud cover are needed.
  • Satellite data will be used in the road weather model from this season
  • The potential use of satellite data in other road application is very large.
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QUESTIONS

CONTACT

Claus Petersen [email protected]

Danish Meteorological Institute

LINKS

www.dmi.dk

www.eumetsat.int

http://nwcsaf.inm.es

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