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Micro-Weather Risk Assessment for Post-Storm Roadway Safety

Project Details
STATUS

In-Progress

PROJECT NUMBER

2025-01

START DATE

09/01/25

END DATE

11/30/27

SPONSORS

Federal Highway Administration Aurora Program Transportation Pooled Fund (TPF-5(435))

PARTNERS

National Center for Atmospheric Research (NCAR)

Researchers
Principal Investigator
Amanda Siems-Anderson

About the research

Departments of Transportation (DOTs) play an important role in roadway maintenance before, during, and after hazardous weather events, working to ensure that transportation networks remain functional and safe. DOTs use tools such as mesoscale weather forecasts, combined with state and local knowledge of weather impacts, to anticipate when and where high-impact storms will degrade roadway safety. These tools enable DOTs to develop tactical approaches that inform the public and optimize the deployment of road maintenance vehicles. While these approaches help manage the immediate storm impacts, residual hazards such as flash freezing, blowing snow, localized flooding, and wind gusts may persist even after the main storm ends. These lingering hazards, often influenced by micro-weather conditions specific to regional and local terrain, can pose significant risks to drivers, particularly those unfamiliar with the area.

Mesoscale models used for storm planning and management can have difficulties capturing the localized turbulence and micro-weather effects that contribute to post-storm hazards. This research proposes to leverage large eddy simulation (LES) models, specifically the NCAR Weather Research and Forecasting (WRF) model coupled with the FastEddy® microscale model, to address this gap by simulating micro-weather phenomena at much higher grid spacings (1–10 m). LES models resolve the complex interactions between wind, temperature, and topography at very high resolution, providing transportation agencies with enhanced situational awareness to better understand the persistence of post-storm hazards.

This project’s objective is to develop a micro-weather risk assessment framework that can identify high-risk roadway segments during post-storm operations. By incorporating data from traffic incidents, roadside stations, geospatial sources, and FastEddy simulations, this framework will serve as a foundation for establishing ways to assess localized hazards like blowing snow, flash freeze, and small-scale flooding, with a goal of faster operational recovery and enhanced safety for road users

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