Tuesday, 16 January 2007: 3:45 PM
Road weather sensor data validation
216AB (Henry B. Gonzalez Convention Center)
Jennifer Hanson, Surface Transportation Weather Research Center, Grand Forks, ND; and L. F. Osborne Jr. and M. Askelson
Sensor data credibility is an ongoing concern within the surface transportation community. State Departments of Transportation (DOT) winter maintenance personnel and the road weather service provider community require road weather data to be accurate to allow them to perform their jobs effectively. While other operational weather-related communities such as the aviation weather community have matured with their understanding of weather data quality available to support their needs, this is not the situation with the road weather community. Current federal efforts underway including the Federal Highway Administration's Clarus Initiative and the National Oceanic and Atmospheric Administration's Surface Weather Program are working to provide improved access to quality controlled Environmental Sensor Station (ESS) data to the road weather community. However these efforts are working more to perform quality control of data received from ESSs and not to evaluate the efficacy of the sensors utilized and the environment in which they are placed.
The University of North Dakota Surface Transportation Weather Research Center (STWRC) established a Road Weather Field Research Facility in 2004 to investigate the physical conditions found within a roadway environment. During this effort an in-depth review of sensor technology and its proper placement in a roadway has occurred. The findings present questions about the various siting issues associated with popular precipitation and pavement sensors. It has also raised questions associated with the accepted capabilities of the sensors to provide the level of information required to support expected road weather prediction efforts.
This paper presents the findings of these studies and describes implications relative to current directions in road weather data management efforts.
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