Publications

Over the past decade there have been significant improvements in the availability, volume, and quality of the sensors and technology utilized to both capture the current state of the atmosphere and generate weather forecasts. New radar systems, automated surface observing systems, satellites and advanced numerical models have all contributed to these advances. However, the practical application of this new technology for transportation decision makers has been primarily limited to aviation. Surface transportation operators, like air traffic operators, require tailored weather products and alerts and guidance on recommended remedial action (e.g. applying chemicals or adjusting traffic flow). Recognizing this deficiency, the FHWA (Federal Highway Administration) has been working to define the weather related needs and operational requirements of the surface transportation community since October 1999. A primary focus of the FHWA baseline user needs and requirements has been winter road maintenance personnel (Pisano, 2001). A key finding of the requirements process was that state DOTs (Departments of Transportation) were in need of a weather forecast system that provided them both an integrated view of their weather, road and crew operations and advanced guidance on what course of action might be required to keep traffic flowing safely. As a result, the FHWA funded a small project (~$900K/year) involving a consortium of national laboratories to aggressively research and develop a prototype integrated Maintenance Decision Support System (MDSS). The prototype MDSS uses state-of-the-art weather and road condition forecast technology and integrates it with FHWA anti-icing guidelines to provide guidance to State DOTs in planning and managing winter storm events (Mahoney, 2003). The overall flow of the MDSS is shown in Figure 1. Basic meteorological data and advanced models are ingested into the Road Weather Forecast System (RWFS). The RWFS, developed by the National Center for Atmospheric Research (NCAR), dynamically weights the ingested model and station data to produce ambient weather forecasts (temperature, precipitation, wind, etc.). More details on the RWFS system can be found in (Myers, 2002). Next, the RCTM (Road Condition Treatment Module) ingests the forecasted weather conditions from the RWFS, calculates the predicted road conditions (snow depth, pavement temperature), Once a treatment plan has been determined, the recommendations are presented in map and table form through the MDSS display. The display also allows users to examine specific road and weather parameters, and to override the algorithm recommended treatments with a user-specified plan. A brief test of the MDSS system was performed in Minnesota during the spring of 2002. Further refinements were made and an initial version of the MDSS was released by the FHWA in September 2002. While this basic system is not yet complete, it does ingest all the necessary weather data and produce an integrated view of the road conditions and recommended treatments. This paper details the RCTM algorithm and its’ components, including the current and potential capabilities of the system.

The Integrated Terminal Weather System (ITWS) is an aviation safety and air traffic management decision support system that acquires data from various FAA and NWS sensors and generates a number of products for dissemination to FAA facilities managing air traffic in the terminal area. The development and demonstrations of ITWS have been conducted over a multi-year period at several major airports (Memphis, TN, Orlando, FL, Dallas, TX, and New York, NY). Although there are many meteorological events observed at these four airports, the experimental test data sets obtained will not fully suffice for ITWS qualification testing because of limitations in the severity of the weather events and because of the sensor configurations available at these locations. This report describes the design and validation of the Synthetic Data Generator (SDG), which is a tool to provide a production ITWS system with meteorologically consistent scenarios and full ITWS sensor configurations that will create maximal computational loads that can be expected when the system is deployed. Also, the SDG will be a tool for ongoing ITWS maintenance and support. As such, the SDG will complement the extensive experimental data sets collected at the four ITWS demonstration sites. The SDG is designed to specify parameters for a collection of meteorological models describing the various weather phenomena, their motion, appearance, and growth/decay. The software creates several three-dimensional (3D) grids of reflectivity and velocity at each time-step. Finally, the SDG generates sensor (i.e., TDWR, NEXRAD, ASR-9) data by applying the model for each specific sensor's measurements to the 3D grids. The validation of the meteorological model and the sensor model data have been accomplished using a display tool and by assessing results numerically.

The National Plan for a Microwave Landing System (MLS) has specified a carrier frequency for the system in the vicinity of 5.1 GHz. At that frequency, no multipath data taken at a major civilian airport existed. The purpose of this experiment was to obtain such data at Logan International Airport in order to ascertain: 1) which objects are the major causes of measurable multipath reflections and their levels relative to the direct signal (MID level), 2) whether or not the reflections from these objects can be satisfactorily simulated by the Lincoln computer model and, if so, how complicated must that model be, and 3) if the characteristics of multipath provide a significant discriminant between the Doppler and scanning beam techniques. It was found in the experiment that regions where reflections were noted could be predicted from ray optics and diffraction. No measurable reflections were noted elsewhere. For the purpose of modeling for multipath, building surfaces could be characterized as a flat plate with a reflection coefficient determined by measurement if it were a complicated surface, or by the dielectric properties of the surface material, if a simple surface. The airplane reflection model was also found to agree well with measurements.

This document presents L-band antenna patterns for a variety of general aviation and air carrier aircraft; these pattern were based on scale-model measurements. The antenna patterns are described by aircraft-coordinate-referenced elevation vs azimuth gain-contour maps. This method of presentation conveniently displays the effects of aircraft configuration on antenna patterns and allows one to observe the changes in a pattern that result from a change in wheel, flap, or antenna location.