Surface Transportation Weather: Assessment of Current Capabilities and Future Trends William Mahoney...
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Transcript of Surface Transportation Weather: Assessment of Current Capabilities and Future Trends William Mahoney...
Surface Transportation Weather: Assessment of Surface Transportation Weather: Assessment of Current Capabilities and Future TrendsCurrent Capabilities and Future Trends
William MahoneyRichard Wagoner
National Center For Atmospheric Research(NCAR)
ITSAAnnual MeetingPhoenix, AZApril 2005
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Surface transportation weather continues to gain national attention!
Several road weather initiatives are in progress and new concepts are being developed.
Surface Transportation Weather Trends
Building a Community
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Stakeholder
involvement is
expanding!
Surface TransportationWeather Capabilities
State DOTs
NationalLabs
AMS
NOAA &
NASA
PrivateSector
Auto Companies
Universities
AASHTO
ITSA
TRB
Surface Transportation Weather Trends
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Where are we heading?
What are the requirements?
What are the opportunities?
What can the science support?
Surface Transportation Weather Trends
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WANTED!
A seamless, high resolution, weather & road condition database of current and future conditions that can feed advanced ITS technologies such as:
• 511• Operations decision support• Traveler information systems• In-vehicle information systems• Traffic management systems• Control systems
Surface Transportation Weather Trends
Rest area kiosk
Traffic Management Center
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NEEDED!
Improvements in:• Weather sensing (all scales)• Road condition sensing• Weather prediction• Data fusion• Information dissemination• Human factors• Benefits assessments
Surface Transportation Weather Trends
Passive surface sensor
Sub pavement probe
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Weather Prediction Trends
• Improved horizontal resolution – 12 km heading to 5 km CONUS
• Need improved vertical resolution – now ~32 levels (surface to 40,000 ft)
• Coupled models- Land surface models
- Air chemistry (pollution)
- Transportation models
- Fire
Surface Transportation Weather Trends
• WRF model precipitation prediction• over Colorado for MDSS
Hurricane Isabel
September 2003
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• Data– Soil moisture
– Snow cover
– Albedo
– Vegetation type
– Greenness fraction
– Soil type
– Many others
• Feedback important for model initialization – especially for near road surface predictions.
Land Surface Modeling
Volumetric soil moisture at 5 cm below the ground surface simulated by HRLDAS; valid at 1200 UTC 31 May 2002.
Soil Moisture
Surface Transportation Weather Trends
Feedback from snowfall needs
to be factored into next model run!
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Surface Transportation Weather Trends
Remote Sensing
Acquired: October 22, 2003VNIR – 15m
IA005
IA003
IA017
IA016
Des Moines, Iowa
•ASTER •AST07 (Surface Reflectance)•AST08 (Surface Temperature)•EROS Data Center
NASA and NOAA satellite
data:
• Road temperature
• Land surface character– Temperature
– Vegetation type
– Greenness fraction
– Albedo
– Snow cover
– Land use
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Sensing Weather and Road Conditions
Improvements expected in:
• Weather sensing (all scales)- winter precipitation gauges- video imagery
• Road condition sensing- optical based sensors- laser based sensors- active sensors (freeze point)
• Data fusion methods• Information dissemination• Human factors
Surface Transportation Weather Trends
SSI Ice Camera
Vaisala Spectro
Yankee Total
Precipitation Sensor
Lincoln Lab video
Image Processing
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Surface Transportation Weather Trends
Extracting & derivingweather data fromvehicles:
• Air temperature• Road friction from ABS• Precip. (Y/N) from wipers• Precip. intensity (wiper
speed)• Radar (collision avoidance)• Air density
Vehicle Infrastructure Integration
45oF
44oF
43oF
45oF
44oF 38oF
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In-Vehicle Weather Information
Real time weather hazard information will be part of in-vehicle information systems• Weather hazards
- High winds
- Tornado
- Heavy snow/rain
• Road Hazards
- Black ice
- Drifting
- Flooding
Real-timeWeather Information
Here
Surface Transportation Weather Trends
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Surface Transportation Weather Trends
Data Fusion – Road Weather Impact Products
New weather and road condition data (incl. VII and Clarus data) will be integrated into a seamless information database(s) to support:
• 511• In-vehicle information• Traveler information• Highway operations• Control systems
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Surface Transportation Weather Trends
Weather and Transportation Modeling
Dynamic control strategies will be developed and adopted to optimize operations during poor weather conditions.
Important for determining:• Signal timing• Ramp metering• Variable speed limits• Other control strategies
Courtesy of the FHWA
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Surface Transportation Weather Trends
Weather Challenges
• Need systematic approach to weather research
• Partnership between weather and transportation
communities
Targets of Opportunity Improved road weather observing capabilities More sophisticated forecasting systems
Applications tailored to transportation managers and users
From Jeff Paniati (ITSA 2003)