Analysis and interpretation of roadway weather data for winter highway maintenance

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2001-01-01
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Knollhoff, David
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Results show that the urban pavement temperatures near both Des Moines and Cedar Rapids are generally higher than rural pavement temperatures under different sky conditions. The heat island impact on surface temperatures in Des Moines was found to be slightly larger than that of Cedar Rapids. Pavement temperature cooling patterns differed among the months analyzed, and the roadways had different cooling characteristics compared to the bridge decks. A model based on simple concepts of moisture flux to the surface was developed that uses current road weather data and forecasts of dew-point temperature, air temperature, surface temperature, and wind speed to calculate frost accumulation on bridge decks in Iowa. The analysis showed that the model has sufficient accuracy to be used as an operational tool to forecast bridge deck frost. A logistical regression procedure was developed to determine the probability that a maintenance worker will observe frost for a given calculated frost depth.Formation frost on pavement surfaces presents a potential hazard to the motoring public in cold climates. Pavement temperatures are not measured routinely by the National Weather Service and are not part of public forecasts of winter conditions, but highway maintenance personnel must make frost suppression decisions based on expectations of future pavement temperatures. The Road Weather Information System measures pavement, air, and dew point temperatures, pavement conditions, and wind data at numerous locations in the state of Iowa and reports the data in real-time to maintenance offices. The surface and near-surface data from the road weather system were analyzed to develop winter weather forecast procedures to compliment anti-icing techniques already practiced within the Iowa Department of Transportation. Nocturnal pavement temperatures as reported by temperature sensors located in and near Des Moines and Cedar Rapids were analyzed under different classifications of cloud cover and for seasonal variations.

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Mon Jan 01 00:00:00 UTC 2001