A decision-support system for winter weather maintenance of roads, bridges, and runways

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Monday, 18 January 2010: 11:30 AM
B312 (GWCC)
Michael B. Chapman, NCAR, Boulder, CO; and S. D. Drobot and W. P. Mahoney III

Maintaining control of snow/ice buildup on roadway surfaces during winter storms is challenging for road maintenance entities. Some of the more critical challenges include making effective and efficient decisions for treatment types, timing of treatments, and location of greatest impact to the roadway based on precipitation rates/types and other weather conditions. These decisions are critical because of the implications to roadway safety, as well as economic impacts to the agency and the environmental impacts of treatments. In order mitigate the challenges associated with winter road maintenance, the United States Department of Transportation (USDOT) Federal Highway Administration (FHWA) initiated the development of the Maintenance Decision Support System (MDSS) in 2001.

MDSS provides a single platform, which blends existing road and weather data sources with numerical weather and road condition models in order to provide a display of the diagnostic and prognostic state of the atmosphere and roadway (with emphasis on the 1- to 48-hour time period) as well as a decision-support tool for roadway maintenance treatment options. In the past, the system has been used mainly for strategic purposes 12-24 hours prior to a storm's arrival in order to prepare the maintenance vehicles and schedule personnel. However, during the 2008–2009 winter season, MDSS has been modified and applied for use over Denver International Airport (DIA), including all six runways and the main arterials leading into the airport. The users at DIA want to utilize MDSS for strategic decision-making but also have a need for a more accurate tactical (0-6 hours) component to the system.

Currently, MDSS uses three numerical weather models, model output statistics from two models, and various pavement and weather–related surface observations in order to generate both weather and road surface forecasts. In order to address the short-term forecasting needs, radar data assimilation and/or high resolution mesoscale numerical weather models are being assessed for possible inclusion into MDSS. Additionally, a non-wintertime MDSS is also being developed that may also require the addition of other nowcasting capabilities, such as lightning data and radar storm-tracking (e.g. TITAN).

The objective of this presentation is to provide an overview of the present and future capabilities of the MDSS system as they relate to the diagnoses and short-term forecasting of weather that may impact the roadway/runway maintenance operations for various decision-makers.