Development of an Index for Estimating Road Weather Severity Based on Energy

Effective and efficient removal of snow and ice from public roadways is a key outcome for winter road maintenance operations. This outcome depends on the severity of the wintry weather as well as the quality and quantity of resources used to treat the roadways. Wintry weather conditions vary substantially from hour-to-hour, storm-to-storm, and season-to-season. Many different transportation departments have used empirical statistical models and machine learning methods based upon weather parameters to develop indices to estimate the severity of winter weather. Many of these previous studies used summary statistics, such as the number of days with certain events (snowfall, freezing rain, frost), to provide a seasonal index of winter severity. While summarizing the winter severity for the entire season is quite useful, providing information over shorter time periods will allow for more precise evaluation of maintenance performance during a winter season.

We are working with the Indiana Department of Transportation (INDOT) to develop a winter weather severity index that can be used to evaluate the performance of winter weather maintenance. For this project, INDOT specifically requested that the severity index should be based solely on weather/environmental information, in order to provide information that is independent of specific road treatment actions and traffic patterns. This project involves the development of a physically-based analysis of winter severity, using estimates of the hourly rate of deposition of new snow/ice and the energy required melt it. The “Road Weather Severity Based on Energy” (RWSBE) index can be considered an accumulation of energy, beyond that which is available from the environment, needed to melt snow/ice that has been deposited on the road surface on an hourly basis. The environment can assist with snow removal in several ways (i.e., radiation, fluxes of heat, sublimation). The energy not provided by the environment that would be required to melt new snow can be thought of as a measure of the work required to remove the new snow from the road surface. We expect that RWSBE will provide a clearer understanding of the severity of the weather, allowing INDOT to better evaluate their performance, assist with after-action review of recent storms, and improve the reaction to future weather events. Measurable improvements in the winter maintenance decision-making process are expected as a result.