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The potential availability of millions of surface observations from passenger vehicles and fleets represents a potentially significant opportunity for the weather community. The success of this opportunity rests with the weather community's technical understanding and eventual adoption of these unique datasets and their level of participation in connected vehicle initiatives within the transportation community. All sectors of the weather enterprise (e.g., public, private, and academic) must become involved to help define, shape, and support the effort to realize a distinct and positive outcome on the weather and transportation communities. For this reason, the American Meteorological Society (AMS) Board on Enterprise Planning (BEP), under the Commission on the Weather and Climate Enterprise (CWCE), established an Annual Partnership Topic (APT) Committee in 2009 focused on mobile observations and their potential for use by the weather and transportation communities. The primary finding of the committee is that high-quality weather information about the roadway environment, including both current observations and forecasts, communicated in a timely and effective manner will help drivers make better and safer decisions regarding travel plans and react properly when faced with potentially compromised conditions; however, there are several technical, financial, societal, and institutional barriers that must be overcome before the full potential of mobile observations can be realized. This paper discusses several key issues important in advancing this concept, including potential benefits, barriers to acceptance, research needs, data quality and metadata, and business models.

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One of the goals of RITA's IntelliDrive initiative is utilization by the public and private organizations that collect, process, and generate weather products of vehicle sensor data to improve weather and road condition hazard products. Some users may not be able to, or not want to, contend with the complexities associated with vehicle data, such as data quality, representativeness, and format. With funding and support from the U.S. Department of Transportation's RITA IntelliDrive initiative and direction from FHWA's Road Weather Management Program, the National Center for Atmospheric Research is conducting research to develop a vehicle data translator (VDT) to address these vehicle-based data challenges. This paper first describes the VDT quality check (QCh) concept and then examines QCh pass rates for temperature and pressure data collected from 11 specially equipped vehicles operating in the Detroit test bed in April 2009. Results show that temperature pass rates are higher than pressure pass rates. Additionally, pass rates are somewhat affected by vehicle type, vehicle speed, ambient temperature, and precipitation occurrence for both temperature and pressure.

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