The program will acquire, evaluate, and test a road surface model developed at the University of Washington. The pavement prediction models will first be integrated with the MM5 land surface model for testing and evaluation. These tools and information will then be used to describe and predict roadway conditions. For example, data on existing and forecast conditions will be used in pavement temperature models that will predict the potential for roadway icing. This will allow road crews to know when and where to apply anti-icing compounds.
Timing is critical because applying the compound too early or too late is ineffective.
In addition, being able to target problem areas is important because it is too costly to apply anti-icer to all roads in an area. It's a matter of being pro-active instead of reactive. A clickable state map will allow users to find the information at the level of detail they need in the locations they require, with statewide, regional, and local views. Such information is predicted to save costs by reducing worker hours and use of resources. The greater amount of information also will aid marine and aviation interests.