详情

原文传递 Road Weather Severity Based on Environmental Energy.

题名：	Road Weather Severity Based on Environmental Energy.
作者：	Baldwin, M.; Snyder, D.; Miller, C.; Hoogewind, K.
关键词：	Road weather, Weather severity, Environmental energy, Winter roadway maintenance, Winter severity index, Weather, Empirical statistical modeling, Snowfall data, Indiana
摘要：	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. A winter weather severity index has been developed that can be used to evaluate the performance of winter weather maintenance. 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 Environmental Energy” (RWSBEE) 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 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 RWSBEE 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. Winter weather conditions that occur across different regions vary substantially from hour-to-hour, storm-to-storm, and season-to-season. The methods of road maintenance for fighting snow and ice can also vary between different maintenance units. It is important for organizations that perform road maintenance to be able to quantify the severity of the winter weather conditions, for purposes of monitoring, planning, and evaluating their performance. The Indiana Department of Transportation (INDOT) currently uses estimates of winter weather hours to quantify the severity of winter weather. The definition of a “weather hour” is fairly straightforward: any hour when wintry precipitation (snow, ice pellets, freezing rain) is falling with air temperatures below 35 °F. While this definition is reasonable, it does not take into account numerous factors that can strongly affect road conditions and subsequent efforts needed for road treatment, such as: precipitation rate, wind speed, and availability of sunshine. Consequently, INDOT has determined that the information provided by the weather hour estimates result in wide variations in roadway treatment expenses across Indiana. In order to more accurately and effectively evaluate the performance of winter maintenance, it is important to have detailed data related to winter weather conditions that provide useful information regarding the impact of winter weather on road conditions. State-of-the-art weather information can 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.
总页数：	Baldwin, M.; Snyder, D.; Miller, C.; Hoogewind, K.
报告类型：	科技报告