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Road Weather Severity Based on Environmental Energy

机译:基于环境能源的道路天气严重程度

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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.
机译:从公共道路的有效和高效地拆除雪和冰是冬季道路维护业务的关键结果。这一结果取决于寒冷的天气的严重程度以及用于治疗道路的资源的质量和数量。寒冷的天气条件大幅度从小到时刻,暴风雨到风暴和季节。许多不同的交通部门使用了基于天气参数的经验统计模型和机器学习方法,以开发估计冬季天气严重程度的指标。其中许多以前的研究使用了摘要统计数据,例如某些事件的天数(降雪,冰雨,霜冻),提供冬季严重程度的季节性指数。总结整个季节的冬季严重程度非常有用,提供更短的时间段的信息将允许在冬季进行更精确的维护性能评估。已经开发了一种冬季天气严重性指数,可用于评估冬季天气维护的性能。该项目涉及开发基于物理为基础的冬季严重程度分析,使用新的雪/冰的每小时沉积率和所需的能量融化。 “基于环境能源”(RWSBEE)指数的“道路天气严重程度可以被视为能量的积累,超出环境中可从环境中获得的,需要在小时内熔化在路面上的雪/冰。未被融化新雪所需的环境未提供的能量可以被认为是从路面中除去新雪所需的工作量。我们预计RWSBEE将更清楚地了解天气严重程度,允许签名更好地评估其绩效,协助对最近风暴的审查,并改善对未来天气事件的反应。冬季维护决策过程的可衡量改善是预期的。结果。在不同地区发生的冬季天气条件大幅不同于小时至小时,风暴风暴和季节。用于战斗雪和冰的道路维护方法也可以在不同的维护单位之间变化。对于能够量化冬季天气条件的严重程度的组织来说,这对于进行监测,规划和评估其性能的目的来说,这是重要的。印第安纳州的交通部(indot)目前使用冬季天气时间的估算量来量化冬季天气的严重程度。 “天气时间”的定义相当简单:在冷水沉淀(雪,冰颗粒,冷冻雨)的任何小时都落在35°F以下空气温度下。虽然这个定义是合理的,但它没有考虑到众多因素,这可能强烈影响道路状况和道路治疗所需的努力,例如:降水率,风速和阳光的可用性。因此,幕称已经确定了天气时间估计的信息估计导致印第安纳州道路治疗费用的广泛变化。为了更准确和有效地评估冬季维护的性能,重要的是要详细数据与冬季天气条件相关,这些数据提供有关冬季天气对道路状况的影响的有用信息。最先进的天气信息可以更清楚地了解天气严重程度,允许签名更好地评估其表现,协助近期风暴的行动审查,并改善对未来天气事件的反应。

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