improved road weather forecasting by using high resolution satellite data claus petersen and bent h....
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Improved road weather forecasting by using high resolution satellite data
Claus Petersen and Bent H. SassDanish Meteorological Institute
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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.
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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
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Numerical Weather Prediction (NWP) model
Horizontal resolution
0.15x0.15 (degree)
Vertical levels 40
Rotation of south pole
Lon.=80 Lat.=0 (degree)
Number of grid points
610x568=346480
Dynamic time step
360 (s)
Physical time step
360 (s)
Boundary update Every 3rd hour
Boundary age 0-6 hours
First guess age 3 or 6 hours
Forecast frequency
Every 4th hour
Forecast length 60 hours
Data-assimilation 4 times daily+2 reassimilation cycles
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Already used observations
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Model domain of NWP model and network of road stations
•Horizontal resolution 0.15x0.15•Vertical levels 40•Number of grid points 82x98=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
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Data sources
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Single channels or composite
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Cloud mask Cloud top temperature
Precipitation intensity Cloud type
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Application of cloud observations
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Application of cloud observations
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FORECAST
1 hour forecast of cloud mask
1 hour forecast of precipitation, mslp1 hour forecast of wind and temperature
Observed cloud mask
1 hour forecast with data-assimilation of satellite data
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FORECAST
1 hour forecast of cloud mask
1 hour forecast of precipitation, mslp1 hour forecast of wind and temperature
Observed cloud mask
1 hour forecast without data-assimilation of satellite data
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6 hour forecast of cloud mask
6 hour forecast of precipitation, mslp6 hour forecast of wind and temperature
Observed cloud mask
6 hour forecast with data-assimilation of satellite data
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6 hour forecast of cloud mask
6 hour forecast of precipitation, mslp6 hour forecast of wind and temperature
Observed cloud mask
6 hour forecast without data-assimilation of satellite data
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21 hour forecast of cloud mask
21 hour forecast of precipitation, mslp21 hour forecast of wind and temperature
Observed cloud mask
21 hour forecast with data-assimilation of satellite data
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21 hour forecast of cloud mask
21 hour forecast of precipitation, mslp21 hour forecast of wind and temperature
Observed cloud mask
21 hour forecast without data-assimilation of satellite data
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Road Condition Model
G: Ground heat fluxS: Direct insolationD: Diffuse insolationR: Infrared radiationH: Sensible heat fluxL: Latent heat fluxF: Flux correction
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User interface
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Verification of cloud forecast
•First two weeks of March 2005•Danish SYNOP stations•Limited MSG1 data•Verifcation for model run every hour
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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
CONTACTClaus Petersen [email protected]
Danish Meteorological InstituteLINKS
www.dmi.dkwww.eumetsat.int
http://nwcsaf.inm.es