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Surface Transportation Weather
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L. Surface Transportation Weather
[Background] [Winter Road Maintenance]
[US
Army - Meteorological Measuring System]
[Dynamic,
Integrated Weather Forecast System (DICAST)]
[Rail
Weather]
1. Background
NCAR/RAP continued to develop technologies that include Intelligent Weather System (IWS) concepts, including the blending of real-time observations, numerical weather prediction model output, climatological, and statistical data to improve weather forecasts. The first operational demonstration of this concept using a fuzzy logic integration process occurred during the Hong Kong project (1994-1998) when RAP scientists and engineers significantly improved the quality and timeliness of wind data derived from wind profilers operating in the challenging environment of Hong Kong harbor. This year, the use of the IWS approach was expanded with the introduction of ensemble methods.
2. Winter Road Maintenance Decision Support System (MDSS)
In
2000, RAP, led by Bill Mahoney and Rich Wagoner began working with
the Federal Highway Administration (FHWA), Office of Transportation
Operations (HOTO) Road Weather Management Program to develop a comprehensive
set of user requirements for surface transportation weather capabilities.
These activities led to the FHWA Surface Transportation Weather Decision
Support Requirements (STWDSR) initiative. In 2001, national research
centers were selected to participate in the development of a conceptual
prototype winter road MDSS. The participating national labs are the
Cold Regions Research and Engineering Laboratory (CRREL), RAP, Lincoln
Laboratory (MIT/LL), National Severe Storms Laboratory (NSSL), and
Forecast Systems Laboratory (FSL). RAP is the technical lead for the
project.
Figure 1. MDSS prototype
The objective of the MDSS effort is to produce a prototype tool for decision support to winter road maintenance managers. The MDSS is based on leading diagnostic and prognostic weather and road condition capabilities (surface and subsurface) and standards of practice for effective road anti-icing and deicing. The MDSS provides a decision support tool which provides recommendations on road maintenance courses of action together with anticipated consequences of action or inaction.
In 2002, a functional prototype MDSS was successfully developed using road segments and winter storm cases from Minnesota. The RAP development team included Bill Mahoney, Bill Myers, Jim Cowie, Ben Bernstein, Paddy McCarthy, Arnaud Dumont, Jamie Wolff, Jamie Yee, and Seth Linden. A quick-look analysis of the results suggest that the weather and road condition prediction components have accuracy within the measurement error of the road weather observation systems. For example, 24-hour predictions of air and road temperature predictions were within 2.0 and 2.5° C, respectively. Wind speed was predicted within 2.5 ms. The accuracy of the winter road deicing and anti-icing treatment recommendations generated by the system will be evaluated during winter 2003 in Iowa.
3. US Army - Meteorological Measuring System
A RAP team, led by Bob Barron, continued to collaborate with Pennsylvania State University and the Environmental Technology Group Corporation (ETG) to develop a Meteorological Measuring System (MMS) for the United States Army. The MMS will be deployed worldwide and will produce highly accurate state of the atmosphere data in a 250 x 250 x 30-km grid.
The Army system units will be deployed in an electronics shelter mounted on the back of a standard US Army Humvee. The MMS uses local radiosondes, a surface measurement station, and data receivers to collect data that is fed into a local MM5 atmospheric model and fuzzy logic data fusion processor to produce the state of the atmosphere data.
The wind, temperature, humidity, precipitation, and other data from the system are used for a variety of defense applications including improved fire control systems that help to minimize collateral civilian damage as well as chemical or biological dispersion plume modeling. RAP's participation in this project concluded this year with the successful delivery of software components to ETG.
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4. Dynamic, Integrated Weather Forecast System
(DICAST)
In 1999, NCAR/RAP contracted with a large private weather firm to develop an automated weather forecasting system utilizing intelligent weather system technology. The requirement was to build a system that: 1) provides timely, accurate worldwide forecasts; 2) is dynamic and modular so as to adapt to a rapidly changing forecast environment; 3) is applicable to a wide variety of forecast problems; 4) uses state-of-the-art scientific and engineering principles; and 5) requires only modest computing systems and common data sources. The forecast system, called DICAST, was completed and delivered to the sponsor in October 2000. DICAST was configured to generate 1 to10-day forecasts at more than 26,000 sites worldwide, and is used by more than 50 million people per day. The RAP effort was led by Bill Myers and included Jim Cowie, Jamie Yee, Claudia Tebaldi, Seth Linden, and Barb Brown.
In 2002, DICAST was enhanced with the introduction of ensemble techniques, addition of forward error correction, and quality control techniques, and was expanded to accept additional inputs. DICAST also became a core component of the MDSS; in this application, it is called the Road Weather Forecast System (RWFS).
Figure 2. DICAST Forecast graphic
The DICAST system ingests raw or processed weather data, generates an ensemble of forecasts by applying a forecast generation technique to each data set, and integrates those forecasts using a fuzzy-logic intelligent combination of this ensemble of forecasts. The resultant forecasts then undergo quality control checks before they are exported. The system currently generates a new set of forecasts every three hours. Each new set of forecasts contains predictions for the next 60 hours. The interval between forecast data points is three hours out to the 60-hour limit. Hourly data can be generated if necessary by interpolation. The system runs on a single stand-alone computer system with a connection to the Internet for receiving input data and optionally distributing the end products.
Figure 3. DICAST processing schematic
5. Rail Weather
The surface transportation weather research program expanded at RAP this year when Rich Wagoner and Rose Lundeen of RAP hosted a rail weather workshop. Participants included the Federal Railroad Administration (FRA), The Association of American Railroads (AAR), Federal Highway Administration (FHWA), several railroad companies, private sector meteorological companies, and national laboratories. The goal of the event was to explore user needs for advanced weather capabilities, identify unmet needs and raise the awareness of the participants about weather technologies that may be applicable for their operation. Additional work will be performed in 2003 to define research and development activities that could benefit the rail community.
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