Weather Information for Surface Transportation (WIST)
Panel 3
Technical Risks and Challenges
Bill Mahoney
National Center for Atmospheric Research
WeatherDiagnoses &
Forecasts
DecisionSupport System
WeatherData
Acquisition
DOTOperations
Data Acquisition
Technical Risks & Challenges
WIST
Weather Diagnoses & Forecasts
• The weather information requirements of thesurface transportation community are highlyspecialized.
• The weather community has not traditionallybeen focused to serve surface transportationneeds.
Weather Diagnoses & Forecasts
• The transportation community requires: - Very high resolution information (misoscale = 40 m to 4 km)
- Rapid updates (minutes to hours)
- Long lead time forecasts (at least 48 hours)
Weather Diagnoses & Forecasts
• The transportation community also requires:
- Surface information (0 to 2 m AGL)
- Probability metrics for meteorological parameters
“What is the probability of receiving 3 inches of snow between mile marker x and y from 6:00 to 9:00 am tomorrow?”
Weather Diagnoses & Forecasts
• Scientific challenges:
- Boundary layer meteorology (0 to 2 m AGL)
- Thermodynamics (heat flux, mixing, etc.)
- Probability & Statistics
- Numerical modeling (meso- to misoscale)
- Verification (with limited verification data)
- Quality control of non-standard data
Weather Diagnoses & Forecasts
• If the weather information utilized by a DSSIs not sufficiently accurate, then the stakeholderswill ignore DSS guidance.
• There are no off-the-shelf plug and play weathercapabilities that can fully address the needsof the surface transportation community;however, there are several emerging technologiesthat are likely to provide benefits.
Weather Data Acquisition
• Access to surface observational data iscritical as it provides input to forecast systemsand is necessary for forecast verification.
• Without these data, there is a significant risk that the forecast output will be poor.
• There is also a risk associated with usingnon-traditional data. Quality control issuesmust be addressed.
DOT Operations & Data Acquisition
• Access to live DOT operations data is critical as it provides input to DSS systems.
• Required DOT data includes:
- Traffic (volume, speed) - Staff availability
- Road surface condition - Work schedules
- Friction - Equipment
- Road subsurface conditions - Treatment type
- Chemical concentrations - Treatment location
- Level of service - Beat completed
DOT Operations & Data Acquisition
• A DSS with even limited utility will requirelive access to these kind of data.
• The technology and resources requiredto develop and maintain a dynamic DOT data base cannot be underestimated.
• There are several risks associated withmanaging operational data, particularly whendata become old or invalid.
Decision Support System (DSS)
• The STWDSR process clearly illustrates thatthe user community is large and diverse.
• There is a risk associated with the assumptionthat a specific DSS solution will be broadly applicable across the surface transportationcommunity.
Decision Support System (DSS)
• Nearly every road maintenance district hasa unique operation. In addition, individuals withindistricts have unique needs.
• There is no “one-size-fits-all” DSS solution. Thereare significant human factor issues associatedwith DSS development that need to be addressed.
• There is also a risk that users will reject a DSS that makes too many decisions for them.
Decision Support System (DSS)
• A “bottoms-up” rather than a “tops-down”approach should be used for DSS systemdevelopment.
• Local DOT organizations need to determinethe level of sophistication that is requiredfor their specific DSS application.
• The FAA has and continues to experience manyof these challenges in their automation programs.FAA experiences should be considered.
Summary
There are numerous challenges associated withthe WIST-DSS initiative; however, scientificand engineering solutions are coming to fruitionthat, given timeand appropriateresources,are likely toproducesignificantbenefits to thesurfacetransportationcommunity.
Summary (cont.)
A long term, multifaceted WIST R & D program should be established in order to properlyaddress user needs and to extract thescientific and technicalcapabilities that residein organizations (government andprivate) across the country.