Extreme weather conditions can influence the operability of electric and autonomous vehicles (EVs/AVs), affecting both safety and infrastructure resilience as these vehicles become more integrated into the transportation network. While mesoscale weather models with resolutions up to 1 km can capture broader weather patterns, they often smooth out localized extremes in dense urban environments. These fine-scale variations, such as low visibility, high winds, freezing fog, and temperature extremes, can degrade sensor performance and vehicle control, leading to safety risks and operational disruptions. This paper uses a coupled Weather Research and Forecasting (WRF) and Large Eddy Simulation (LES) modeling approach to resolve urban-scale weather hazards. The goal is to assess conditions that define operable versus inoperable days for EVs/AVs. Initial simulations over Chicago, IL, will form the basis of an operability framework. This framework aims to improve how and when EVs and AVs will be impacted by hazardous weather.

• A coupled modeling framework to assess how non-precipitating weather hazards impact the operability of electric and autonomous vehicles (EVs/AVs) in dense urban environments will be developed. A mesoscale Weather Research and Forecasting (WRF) model provides the outer forcing fields at 1-km resolution, capturing large-scale features such as lake breeze development and regional thermal gradients. These outputs are then used to initialize a nested microscale simulation with NCAR’s FastEddy® large eddy simulation (LES) model over a 15 km × 15 km domain centered on downtown Chicago. The FE model runs at 5-meter horizontal resolution and 10-second temporal resolution, resolving thermal and flow structures that are otherwise smoothed out in mesoscale models.
• Lidar-derived 3D building data are ingested into the LES to represent realistic urban canopy effects, allowing for improved simulation of turbulent exchange and flow-channeling within city blocks. Urban meteorological extremes—such as sharp thermal gradients, visibility reductions, and gusty winds—are assessed in relation to sensor degradation thresholds and EV performance constraints. Case studies focus on non-precipitating hazards including fog, dust, high wind, and temperature extremes. Preliminary results show the added value of LES in detecting weather-induced conditions that could render AVs inoperable or degrade EV range.
• This modeling system supports the development of a weather-responsive operability framework for classifying urban conditions as “operable” or “inoperable” for different vehicle configurations. The framework is intended to inform adaptive traffic management, infrastructure design, and risk communication under a changing climate.

We currently lack a clear understanding of how AVs and EVs respond to weather-related hazards compared to traditional gasoline vehicles. It remains uncertain whether these emerging vehicle types are more or less vulnerable to conditions like fog, high winds, or extreme cold. By using high-resolution simulations to define weather thresholds that impact operability, we can begin to answer these questions quantitatively. This framework provides a pathway for identifying when and where EVs and AVs may become unsafe to operate, enabling proactive routing, hazard communication, and design improvements. The broader impact of this work seeks to supports efforts to reduce weather-related fatalities and build a more climate-resilient transportation system

High-resolution simulations expect that non-precipitating weather hazards, such as sharp thermal gradients, reduced visibility, and gusty winds, can create localized conditions that may render EVs and AVs inoperable. If this pans out then it would support the development of a weather-responsive operability framework to inform adaptive traffic management, hazard communication, and climate-resilient transportation planning.

• Welch, M. B., Walker, C., & Siems-Anderson, A. (2025). Assessing Electric and Autonomous Vehicle Operability in Adverse Weather with Large Eddy Simulations. Oral presentation at the Sustainability Research and Innovation (SRI) Congress, June 2025.
• Welch, M. B., Walker, C., & Siems-Anderson, A. (2026). Assessing Electric and Autonomous Vehicle Operability in Adverse Weather with Large Eddy Simulations. Oral presentation at the 17th World Congress on Road Winter Service, Resilience, and Decarbonisation, Chambéry, France, March 10–13, 2026.

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