Identifying Representative Weather-Impact Scenarios for Flow Contingency Management

Flow contingency management aims to improve the strategic traffic flow management decision making processes. This research effort has focused on developing quantitative analysis methods for predicting weather impact and designing mitigation strategies in response. Due to significant weather uncertainty present in the strategic planning horizon, probabilistic forecasts are developed to capture the range of weather outcomes. However, to facilitate the strategic planning process and the design of specific traffic management initiatives, these outcomes need to be characterized and grouped into a small number of representative scenarios. A mechanism for clustering weather-impact scenarios based on an ensemble weather forecast product is thus proposed that develops weather-impact metrics and applies a clustering approach to identify the representative groups. The identified groups will be evaluated using the Flow Contingency Management Framework under various delay mitigation strategies for examining the effectiveness of the scenario clustering mechanism.