The FMI Road Weather Model, Applications and Projects

1
The FMI Road Weather Model, Applications and
Projects

• Marjo Hippi
• Meteorological research / Meteorological
  applications
• Finnish Meteorological Institute

2
Background and motivation

• Weather warning service
• road/sidewalk weather forecasting
• issuing road/sidewalk weather warnings
• Research
• road maintenance needs
• effect of climate change
• Products
• road maintenance scheduling
• specialized warning system
• route planning

3
End users of Road Weather Model (and its
applications)

• Meteorologists
• Road maintenance people
• Drivers
• Walkers

Benefits of the model

• Safety on roads
• Less injuries
• Less maintenance costs

4
Numerical model
Atmosphere weather model - weather parameters
3-D
. . .
10 km
Road model (1-D)
. . .
10 km
. . .
1-D
Road surface
Ground
4 meters
2-D
"Deep" ground
Climatological temperature
5
Model structure
Upper boundary forcing

• Atmosphere
• wind speed (Vz)
• air temperature and humidity (Ta , Rh)
• global (short wave) radiation (RS?)
• incoming long wave radiation (RL?)
• precipitation (P)
• Traffic
• mechanical wear, heating

• Turbulence
• natural
• traffic induced

• Surface heat exchange
• sensible heat flux (H)
• latent heat flux (LE)
• long wave radiation (RL)
• stability

• Ground heat transfer
• heat conductivity (?)
• specific heat (c)
• density (?)
• porosity (?)

6
Outputs

• Input data
• temperature, humidity
• wind speed
• precipitation intensity
• lighting conditions

Traffic index

• normal
• bad
• very bad

Road index
1. dry 2. damp 3. wet 4. wet snow 5. frost 6.
partly icy 7. dry snow 8. icy

• surface temperature
• storages
• - water, snow
• - ice, frost

Temperature
Road surface temperature
7
Model run
Present time
Forecast phase (24-48 h)
Observation phase (3-48 h)
SYNOP, radar precipitation
Hirlam, ECMWF etc.
Observations
Input data
Forecast (meteorologist's editor)
Road weather model
Road weather model
Simulation
Forecast initial state
Model output

• Input data
• latest observations and forecasts
• "data pool" updated automatically by a data fetch
  agent

8
Surface energy balance
Equation
9
Effect of traffic on road surface

• traffic wear
• E.g. snow packed partly to ice, partly flown away
• adjusted to main road network
• day/night variation in values
• can easily be adjusted if more detailed data
  becomes available
• traffic friction and other warming effects
• turbulence simulated by having minimum wind speed
• friction heating included in the equations (not
  used so far)

snow storage
ice storage
snowing
Storages are one of the most important part of
this model. There are storages for water, snow,
ice and deposit.
10
Road condition interaction between storages
11
Meteograms
SUM STOR x 10
12
Meteogram vs. road weather camera
13
Road condition maps
14
Traffic condition index
15
Road weather models, applications and projects

• Four kind of road weather models
• Normal road weather model
• Road maintenance model
• Pedestrian model
• Coming Road weather model using observations
  from road weather station
• Applications
• Frost model Analysis model, based on
  observations from road weather stations
• Icing model Different kind of observations
  and/or forecasts give warnings
• Varo service Special localized warnings and
  advanced route planning based on predicted road
  weather
• Projects
• Helsinki Testbed Urban measurement network
• ColdSpots More accurate forecasts for difficult
  road spots verifications and model developing
• CarLink Wireless Traffic Platform for Linking
  Cars Weather observations from cars, data
  transfer,

16
Pedestrian sidewalk conditions

• J. Ruotsalainen, R. Ruuhela, M. Kangas
• FMI, Inst. of Occupational Health
• Warning of slippery walking conditions
• Modified surface condition interpretation
• Hospital preparedness

) Työterveyslaitos
Foot gear friction measurements using a "stepping
robot"
17
Pedestrian model Background and Facts

• During wintertime in Finland occur about 50 000
  pedestrian slipping accidents with serious
  consequences
• 1/100 in Finnish population
• About 5 000 patients (1/1000) are hospitalized
• Annual costs 420 million euros

18
How to reduce the number of slipping accidents?

• Winter maintenance of pavements
• Awareness of pedestrians
• Foot wear with good grip
• Warnings of slippery pavement conditions would
  help both pedestrians and winter maintenance work

• Peak days of traffic accidents are not usually
  the same as peak days of pedestrian slipping
  accidents
• Friction between a tyre and road is different
  from the friction between foot wear and the
  underfoot surface

19
Some statistic
20
Age distribution of patients with slipperiness
injuries
Number of slipperiness injuries outside during
winter time 2003-2004 from Töölö Hospital
Emergency
21
Age distribution of patients with hip fracture
due to slipperiness accidents
22
Development of the Road Weather and Pavement
Condition Model

• Changes in storage terms were adjusted for
  pavements
• e.g. snow -gt ice, maintenance
• Three-valued index for slipperiness was developed
• Normal, slippery, very slippery
• Most slippery conditions for pedestrians are
• Light, dry snow on the smooth layer of ice
• Water on the smooth layer of ice
• Melting
• Raining
• Humid, heavy snowfall made slippery by
• - pedestrians
• - or wrong maintenance equipments
• The pedestrian model was taken in operational use
  winter 2004-2005
• The service was extended to cover whole Finland

23
Road maintenance scheduling
Time to next snow removal

• Co-operation with FMI and Finnish Road
  Enterprise
• Enhanced snow manipulation
• Advance warning of snow accumulation for
  maintenance scheduling
• Snow removal (ploughing) included in the model
• Coming later scheduling for salting
• New style of thinking Model does not predict the
  weather, it predict what should be done

) Tieliikelaitos
24
VARO service - Driver Alert for drivers

• FMI (M.Hippi, M.Kangas), FMI/Cust.Serv., Finnish
  Road Enterprise, Road Authorities, VTT,
  Telia-Sonera, transport companies
• Special localized warnings

Road model

• rapidly changing weather, freezing rain, heavy
  snowfall, etc.
• mobile phone based localization of the vehicles
• warnings come to users via mobile phone, to the
  car navigators in the near future
• warning to those who are in the warning area
• Also advanced route planning based on predicted
  road weather

25
VARO service - Route planning
26
Project ColdSpots

• Co-operation with FMI, Foreca and Finnish Road
  Enterprise
• Funding from MINTC (Ministry of Transport and
  Communications), partners and Finnish Road
  Authority
• Initiated after a serious wintertime road
  accident
• Objective to further improve winter weather and
  road condition forecasts
• Concentrating in the problem points of the
  Finnish road network

27
ColdSpots Benefits and risks

• Less traffic accidents, saving money and lives
• Winter road maintenance becomes more efficient
• Scheduling and planning maintenance actions
  becomes easier
• We take a risk on the quality of new forecasts.
  As this is a pilot project, we do not know how
  much improvement (if any) can be made
• What we want to do
• During this project we do also friction
  measurements and thermal mapping along the roads
  (Vaisalas optical measurements)

• more accurate forecasts on road conditions
• more effectively warn to drivers, especially
  about the problem spots
• want to learn how much the road conditions differ
  locally along the road network and why
• want to learn more about the influence of weather
  to road accidents

28
What is a ColdSpot?

• A spot with accidents due to slipperiness
• Or a spot which is difficult for road maintenance
  people
• Can be an open area -gt large sky-view factor,
  radiation cooling
• A valley with cool air pooling at night
• Coastal area near the sea or lake -gt lots of
  moisture advection
• Elevated spot, a hill top -gt lower temperature,
  forced uplift of moving air (not a common problem
  in Finland)
• A bridge, curve, ramp,
• Many spots have passing lanes (a cause or a
  result?)

29
How much temperature can differ in near situated
road weather stations
Distance between road weather stations is about
25-30 km.
30
Part II
31
How does a ColdSpot look like?
Aneriojärvi an open area, a lake on the right
Ikela hill an open area ending to a hill
Bridge of Halikko may be slippery, strong wind
can cause extra risk
Curve of Koikkala Road curving on a hill poor
visibility
32
ColdSpots do not look like much but they may
kill you...

• Drivers cannot sense the danger while driving
• One good way to warn variable signs

33
Conclusions aboutFMIs road weather modeling

• The basic road weather model operative since 2000
• a total of 66 model runs/day
• Worked well, stable and reliable
• Spin-offs and model developments
• special traffic and pedestrian warnings
• Cust.Services 10-20 commercial products
• road maintenance, VARO etc.
• Interest from abroad
• Interest from Lithuania, Czech, Luxemburg,
  Barbados (considering mud slides)...

34
... and future

• Road weather observations
• improved localization
• Ideas friction output, EPS, road salting,
  feedback from maintenance vehicles,
• Problem radiation observation availability
• FMI decrease of cloud/radiation observations
  since summer 2006 gt analysis to grid impossible
• gt no more radiation observations for the model
• radiation observations replaced by forecasts
• forecast quality ?

35
More about road weather modeling in the future

• We want to better and do more accurate forecasts
  to different kind of places (bridges, hills,
  valleys, ramps, )
• need observations of different kind of places
• need information of terrain
• need information about the structure of road and
  ground
• need to but into the model those things
• need also observations from city area and
  pavements
• In project ColdSpots we research is it possible
  to do more accurate forecasts already
• Friction model
• Now we know if the surface is icy. We would like
  to know also how slippery it is.
• Now there are friction measurements available

36
What happens to road maintenance costs in the
future?

• Because of global warming winter time road
  maintenance costs will increase in Finland
• Summer time season will be longer. Less costs on
  Nov, Dec, Mar.
• In the middle of the winter (Jan, Feb) the costs
  will increase
• The number of near zero temperatures will
  increase in the middle of the winter ? Need more
  salting because of icy roads
• The total sum of maintenance costs in the winter
  season will increase

37
Thank You for Your Interest!