Estimation of Road Surface Temperature Using NOAA Gridded Forecast Weather Data for Snowplow Operations Management
Publication: Journal of Cold Regions Engineering
Volume 37, Issue 4
Abstract
Monitoring road surface temperatures is crucial to establishing winter maintenance strategies by the State Departments of Transportation (State DOTs) in the United States. Traditionally, transportation agencies rely on the information provided by Road Weather Information Systems (RWIS) for road surface temperatures along roadways. However, these systems are costly and only provide estimates at specific locations, resulting in distant areas being under-represented. In recent years, some interpolation techniques have been considered to address this gap by estimating the road surface temperatures between the RWIS stations. Nevertheless, these techniques are only valid when the RWIS data are available. This study aims to estimate the road surface temperatures using forecast weather data which are available at high spatial resolution in the National Weather Service Database maintained by the National Oceanic and Atmospheric Administration (NOAA). To this end, road surface temperature data were collected from roadways using a vehicle-mounted infrared temperature sensor. Furthermore, the associated forecast weather parameters from the National Weather Service database were used to develop relationships between the publicly available weather forecast data and the actual road surface temperatures using multiple linear regression. The authors developed two estimation models for dark and light groups and leveraged the gridded forecast weather data from the national weather service database to visualize the estimated road surface temperatures along roadways using a GIS approach. The results showed that the ambient temperature, relative humidity, wind speed, average temperature of the previous day, and road surface conditions (wet/dry) are statistically significant in estimating the road surface temperatures using gridded forecast weather data. The performance of the models was validated, and satisfactory accuracy metrics (i.e., mean absolute error) of approximately 1°C and 2°C were achieved for the dark and light groups, respectively. The proposed method was implemented in the TxDOT Wichita Falls district as a part of a Snowplow Operations Management System to provide information about the estimated road surface temperatures to transportation managers for the 2021–2022 winter season. This information facilitates establishing proactive anti-icing measures in locations where possible low surface temperatures are expected. The findings of this research contribute to a better understanding of the influence of publicly available weather forecast parameters on road surface temperatures.
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Data Availability Statement
Some data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request. These data include the collected road surface temperatures, the associated meteorological forecast weather data, and the codes used to download and process the meteorological forecast weather data from the National Digital Forecast Database as described in the “Methodology” section of the paper.
Acknowledgments
This study is based on project 5-6996-01 (Grant Numbers 1265022380, 1265022381, and 1265022382), supported by the Research and Technology Implementation (RTI) division of the Texas Department of Transportation (TxDOT). The authors are grateful for the support and guidance provided by Ms. Joanne Steele, Project Manager of the Research and Technology Implementation (RTI) division and TxDOT advisory committee. Special thanks to the TxDOT Wichita Falls district representatives, Mr. Aaron Williams and Mr. David Rohmer, for providing prompt assistance and advice on this research.
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Journal of Cold Regions Engineering
Volume 37 • Issue 4 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Jul 27, 2022
Accepted: Feb 2, 2023
Published online: Jul 31, 2023
Published in print: Dec 1, 2023
Discussion open until: Dec 31, 2023
ASCE Technical Topics:
- Business management
- Climates
- Computing in civil engineering
- Databases
- Engineering fundamentals
- Environmental engineering
- Federal government
- Forecasting
- Government
- Highway and road management
- Highway transportation
- Highways and roads
- Information systems
- Information Technology (IT)
- Infrastructure
- Mathematics
- Measurement (by type)
- Meteorology
- Organizations
- Practice and Profession
- Statistics
- Systems engineering
- Temperature effects
- Temperature measurement
- Transportation engineering
- Weather forecasting
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