Weather Information for Surface Transportation (WIST) Panel 3 Technical Risks and Challenges Bill Mahoney National Center for Atmospheric Research

Weather Diagnoses & Forecasts Decision Support System Weather Data Acquisition DOT Operations Data Acquisition Technical Risks & Challenges WIST

Weather Diagnoses & Forecasts The weather information requirements of the surface transportation community are highly specialized. The weather community has not traditionally been focused to serve surface transportation needs.

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 DSS Is not sufficiently accurate, then the stakeholders will ignore DSS guidance. There are no off-the-shelf plug and play weather capabilities that can fully address the needs of the surface transportation community; however, there are several emerging technologies that are likely to provide benefits.

Weather Data Acquisition Access to surface observational data is critical as it provides input to forecast systems and 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 using non-traditional data. Quality control issues must 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 require live access to these kind of data. The technology and resources required to develop and maintain a dynamic DOT data base cannot be underestimated. There are several risks associated with managing operational data, particularly when data become old or invalid.

Decision Support System (DSS) The STWDSR process clearly illustrates that the user community is large and diverse. There is a risk associated with the assumption that a specific DSS solution will be broadly applicable across the surface transportation community.

Decision Support System (DSS) Nearly every road maintenance district has a unique operation. In addition, individuals within districts have unique needs. There is no “one-size-fits-all” DSS solution. There are significant human factor issues associated with 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 system development. Local DOT organizations need to determine the level of sophistication that is required for their specific DSS application. The FAA has and continues to experience many of these challenges in their automation programs. FAA experiences should be considered.

Summary There are numerous challenges associated with the WIST-DSS initiative; however, scientific and engineering solutions are coming to fruition that, given time and appropriate resources, are likely to produce significant benefits to the surface transportation community.

Summary (cont.) A long term, multifaceted WIST R & D program should be established in order to properly address user needs and to extract the scientific and technical capabilities that reside in organizations (government and private) across the country.