Focus Group Results: Weather Providers
Facilitator: Steve Andrle, ISU/CTRE
Date: June 14, 2004
- Improving Fixed Platform Data Collection
- Improving Forecasting Models, Data, and Dissemination
- Developing Visibility Mitigations
Team Members
Steve Andrle (ISU/CTRE), John Whited (Iowa DOT), Shawn Havick (Iowa DOT), Harry Hillaker (Iowa Department of Agriculture), Elwyn Taylor (WOI Radio and ISU/Agronomy), Gene Takle (ISU/Meteorology), Bill Gallus (ISU/Meteorology), Tina Greenfield (ISU/Meteorology), Daryl Herzmann (ISU/Agronomy), Allen Czarnetzki (UNI), Craig Johnson (UNI and Iowa Academy of Science), Jeff Tilley (University of North Dakota), Brad Small (National Weather Service), Thad Warner (Goodrich Corporation), Kurt Kinion (SSI), Jim Block (Meteorlogix), Cory Block (Meridian)
Initiative #1: Improving Fixed Platform Data Collection (42 votes)
1. Background and Problem Statement
Currently, there are significant issues concerning the quality of data produced by several types of fixed-location environmental sensors stations (ESS) or observing platforms. These issues include the low density of most fixed observation platform networks, the frequency of data collection at these sites, the accuracy of the sensors (especially concerning humidity), the necessary maintenance and calibration of sensors, the existence of multiple proprietary and public data formats and networks, and the need for better access to sensor data.
In addition, many of the existing observation stations were located with little thought of the location ultimately being representative of a larger roadway segment. In many cases, road weather information systems (RWIS) were located near specific locations of concern with unique characteristics, such as an ice-prone bridge or mountain pass. As a result, several of these locations would not be representative of conditions along the adjacent roadway miles.
2. Research Objectives
The objective of this research is to improve upon these data-related issues by investigating the impact of increasing the density of sensors and frequency of sampling, investigating new sensor technologies (radiation, accumulation rate, etc.) to help improve data accuracy, improving maintenance and preservation of observation platforms (RWIS, AWOS, etc.) once they are in place, improving access to historical and real-time data, and researching ways to standardize multiple ESS data formats and create interoperable networks.
3. Resource Needs and Time Frame
This research will involve a program of research. Therefore, this activity should become a multi-year program and be housed under a consortium such as the Aurora Program. In addition, significant resources are required to proceed with the above agenda of research activities. Therefore, it is recommended that $500,000 per year be allocated to the Aurora Program to initiate activities of importance to improving the information available from fixed platform environmental sensors stations.
4. Intended Users
Ultimately all users of road weather information will benefit from better information provided by fixed platform sensors. These users include state departments of transportation, local governments, commercial and private road users, and several other users of surface weather information (railroads, contractors, etc.).
5. Implementation
Research could be implemented by member agencies of the Aurora Program and other state transportation agencies, NOAA, USDOT, sensor system integrators and vendors, value added meteorologists, and other weather service providers.
6. Other Outside Parties
Other potential parties have yet to be determined.
Initiative #2: Improving Forecasting Models, Data, and Dissemination (33 votes)
1. Background and Problem Statement
Those making travel or maintenance decisions based on weather data and/or information need accurate weather forecasting and significant lead time in order to make prudent decisions. The primary issues impacting forecasts include data ingestion, model accuracy, dissemination of model outputs, and forecast confidence (including level of probability). Important forecast components in these models include frost, humidity, radiation (pavement temperature), visibility, precipitation start and stop times, wind speed and direction. Of these elements, frost, humidity, and pavement radiation were identified as the most critical in Midwestern states.
The difficulty in using model outputs is due to the blending of two different scientific approaches to two different climatology phenomena, atmospheric weather and road weather. Each of these phenomena has unique micro-climate level features. Furthermore, in the early stages of each winter season, winter maintenance decision-makers often see less accuracy in their forecasts as models develop and adjust to the specific weather events. This problem also carries the risk of a secondary impact – the loss of confidence in forecasts that could last throughout a winter season.
2. Research Objectives
The objective of this research would be to ultimately improve forecasts by improving data ingestion, modeling practices, and forecast outputs.
3. Resource Needs and Time Frame
This is significant problem that cannot be addressed in one project. Instead, a program to improve forecasting models, data, and dissemination is recommended. It is also recommended that this program be funded at $4,000,000 per year and is based at a university, or university-like organization, but funding should be available to the private and public sector through competitive grants focusing on key road weather forecasting modeling, data, and dissemination issues. As the program matures, it will focus on program of research which builds on past findings and funds high risk, high benefit projects.
4. Intended Users
The results of the research would focus on the entire community of road weather users – private and commercial drivers, weather professionals, and road maintenance programs of local and state governments.
5. Implementation
Research results could be implemented by state departments of transportation, the national weather service, RWIS system integrators, and other providers of weather information.
6. Other Outside Parties
Other parties have yet to be determined.
Initiative #3: Developing Visibility Mitigations (12 votes)
1. Background and Problem Statement
There are numerous potential causes of poor roadway visibility, both natural and man-made. Fog, smoke, dust, and precipitation can all significantly impact driver visibility. In addition, factors such as wind, roadway geometrics, and land cover can contribute to serious visibility issues, especially during snow events. Lastly, travelers and vehicles can also contribute to poor visibility with exhaust and road spray. All of these sources can be serious safety concerns on a given roadway. To complicate matters, many instances of poor visibility can be localized and difficult to predict.
2. Research Objectives
The objective of this research is to investigate possible solutions (roadway design, technologies, etc.) to improve driver visibility during certain weather events. Possible solutions include lane guidance technologies (markings or night vision), technology to disperse local fog conditions, and improvements in roadway and bridge design (living snow fences).
3. Resource Needs and Time Frame
This research is more likely possible as a program to improve roadway visibility through a variety of strategies. It is recommended that a program be funded at $1,000,000 per year.
The program will seek proposals from the public and private sectors to develop and test technology, design solutions, and methodologies to improve driver visibility.
4. Intended Users
On-board vehicle technology developed will be used by vehicle manufactures, by after market equipment manufacturers, and by vehicle operators. Infrastructure-based improvements will be used by highway agencies at the state and local levels.
5. Implementation
Depending on the type of improvement, the developments will be implemented by either the public or private sectors.
6. Other Outside Parties
Other parties could include the American Automobile Association (AAA), vehicle manufacturer association, the United States Congress, USDOT, and others.
