The management of blowing and drifting snow onto and across roadways has received considerable attention over the past two decades. Significant research on the design and implementation of barriers to control the drifting of snow onto roadways has resulted in dramatic growth in their application since the early 1990s. It is estimated that it costs one-hundred times more to plow snow drifts from the pavement than to construct and maintain snow fences. However, as effective as snow fences can be, it is not conceivable to construct snow fences in all areas. As a result the impact of drifting snow onto highways continues to be a major winter maintenance concern. In addition, the presence of blowing snow aids in the reduction of driver visibility and presents a significant transportation safety concern. In lieu of widespread mechanical blowing and drifting snow suppression, the use of computational methods is required to provide guidance on the degree of blowing snow that can be expected during specific winter weather conditions. The need for such computational support within a maintenance decision support environment has been identified through testing of the Federal Highway Administration’s Maintenance Decision Support System (MDSS) Functional Prototype development efforts. The limitations of current one-dimensional prediction schemes and a lack of a full atmospheric sciences physics package within blowing snow models, significantly limits the ability to effectively predict blowing and drifting snow across the spatial regions necessary to support an operational MDSS and provide guidance within an advanced traveler information system (ATIS).

Research efforts are underway at the University of North Dakota that build upon earlier research in blowing and drifting snow simulation and prediction found within the snow pack hydrology community in order to transfer the technologies to a roadway environment. Current efforts include a robust atmospheric sciences physics package closely coupled with a mesoscale weather prediction model to simulate blowing and drifting snow conditions. This effort is being tested during winter 2004-05 MDSS field experiments across the Upper Midwest. A field validation effort is being conducted to measure the effectiveness of the blowing and drifting snow algorithm in supporting maintenance decision making. Further, the blowing snow prediction system serves as a significant input into a roadway visibility analysis and prediction system presently under development as a companion research effort for MDSS and ATIS evaluation.