Publications

As part of the Aviation Weather Development Program of the Federal Aviation Administration, a high resolution winds analysis system was demonstrated at Orlando International Airport (MCO) in the summer of 1992. The purpose of this demonstration was to illustrate the winds analysis capability possible from operational sensors in the mid '90s. An important part of the design of this system was the development of a procedure for the assimilation of Doppler data from multiple radars. This procedure had to be able to automatically handle regions with missing data from one or more radars, as well as avoid baseline instability. The two operational radars scanning the analysis region were the National Weather Service WSR-88D (NEXRAD) radar located approximately 65 km east and slightly south of MCO, and the MIT prototype Terminal Doppler Weather Radar (TDWR) located 7 km due south of the airport. The base data from these two Doppler radars were the major information component for the analysis system. Our system includes the most recent improvements in the winds analysis portion of the Local Analysis and Prediction System (LAPS) developed by the Forecast Systems Laboratory (McGinely et al., 1991). LAPS is designed to run locally on systems affordable for operational weather offices and takes advantages of all sources of local data at the highest possible resolution. Our implementation for the airport terminal region id called the Terminal-area LAPS (T-LAPS). LAPS formerly had a technique for the assimilation of data from a single Doppler radar. We have modified that technique for the assimilation of data from the two available radars. Our approach, using a Multiple Single Doppler Analysis (MSDA) technique, is more suited for unsupervised operational analysis than traditional Dual Doppler Analysis (DDA), because it is able to handle such problems as incomplete data and baseline instability. We will describe the T-LAPS analysis, with particular attention to our implementation of ASDA, and give some examples from our demonstration.

For reasons of aviation safety and airport operations efficiency, gust front detection and tracking is an important product of Doppler weather radars developed for use in airport terminal areas. Previous gust front algorithms, which have relied on the detection of one or two conspicuous signatures in Doppler radar imagery, have worked reasonably well in images generated by the high-resolution, pencil-beam Terminal Doppler Weather Radar (TDWR). The latest Airport Surveillance Radar, enhanced with a Wind Shear Processor (ASR-9 WSP), is being developed as a less expensive alternative weather radar. Although gust fronts are visible to human observers in ASR-9 WSP imagery, the lower sensitivity and less reliable Doppler measurements of this radar make automated gust front detection a much more challenging problem. Using machine intelligence and knowledge-based signal processing techniques developed in the context of automatic target recognition, a Machine Intelligent Gust Front Algorithm (MIGFA) has been constructed that is radically different from the previous algorithms. Developed initially for use with ASR-9 WSP data, MIGFA substantially outperforms a state-of-the-art gust front detection algorithm based on earlier approaches. These results also indirectly suggest that MIGFA performance may be nearly as good as human performance. Preliminary results of an operational test period (two months, approximately 15000 scans processed) are presented.

When weather events are expected to produce significant delays at destination airports, the traffic flow management system in the United States holds departing aircraft on the ground in an attempt to reduce delay costs to the operator and to alleviate airborne congestion. Selecting the correct amount of ground holding is made difficult because of uncertainty in predicting weather events that produce congestion. In general, decision-makers must strike a balance between the amount of predicted delay absorbed on the ground and the amount absorbed in the air. This paper first addresses the question of how uncertainty in the required delay should influence the amount of ground holding. It then establishes the relationship between delay uncertainty and uncertainties in predicting the onset and duration of weather events. Delay costs are minimized under an assumption that there is a fixed ratio between the cost of a unit of ground delay and a unit of airborne delay and that the landing sequence employed at the destination terminal is based upon the originally scheduled landing order. The analysis indicates that uncertainty in the delay prediction must be considered in selecting the optimum amount of ground holding for an individual flight. In predicting delays, it is desirable to keep the ratio of the standard error to the mean delay (σ / μ) well below 1.0 in order to avoid loss of benefits. A corresponding figure of merit for weather systems is shown to be the ratio of the uncertainty in onset/termination times to the duration of the weather event. Weather prediction systems must keep this ratio well below one-third to avoid significant loss of ground-holding benefits. The analysis indicates that reductions in the delay uncertainty through improved weather forecasting and traffic management systems can result in better decision-making and significant cost savings.

Increased air travel in recent years has resulted in a steady increase in the number and duration of flight delays. In an attempt to increase airport capacity, MIT Lincoln Laboratory, under the sponsorship of the Federal Aviation Administration (FAA), has supported the development of a Precision Runway Monitor (PRM). The PRM is an advanced radar monitoring system designed to increase utilization of closely-spaced, multiple, parallel runways during adverse weather conditions. The PRM consists of radar which has higher accuracy and a faster update interval than the current system, and a high resolution, color display that informs the Monitor Controller of the occurrence of hazardous flight path deviations by means of automated visual and vocal warning alerts. Studies of air traffic controller reaction to the PRM were conducted at Memphis Airport and Raleigh-Durham Airport in order to evaluate system effectiveness and to assess the effects of key variables on controller reaction time. This paper documents the results of the controller studies conducted at Memphis by MIT Lincoln Laboratory. The testing consisted of the presentation of real-time simulations, and measurement of air traffic controllers were surveyed regarding the acceptability of the PRM.

The Federal Aviation Administration (FAA) is developing a number of terminal weather sensors and a terminal weather information system which can make important contributions toward an operational wake vortex advisory service. Although these systems have been developed to meet other important weather information needs, their existence/development offers the possibility of a more cost effective wake vortex advisory system than would be possible with a standalone system such as was tested in the 1970's. Specifically, we postulate an advisory system in which the aircraft separation during IFR conditions is adjusted to account for the advection of vortices by the wind on the approach path and/or the breakup of vortices due to air instability and in which the desired aircraft separation is achieved by the Terminal Air Traffic Automation (TATCA) system. When reduced separations are obtained with such a system, it is important to be able to anticipate that the winds/vortex stability in the terminal area will continue to meet the reduced spacing criteria for an appropriate time interval (e.g., at least 15 minutes) in the future.

There is a need for a real-time volcanic ash advisory system for aviation which could provide improved accuracy and timeliness in warnings to planes in flight as well as to air traffic controllers for flight planning. To provide an operationally useful capability at reasonable cost, it is essential that the system elements take maximum advantage of the weather sensing and information dissemination system under development by the FAA and NWS. Volcanic ash should be treated as a type of weather hazard similar to regions of icing and thunderstorms. Real-time information from ground sensors, unmanned air vehicles, air carriers, and satellites would be used to estimate current and predicted ash systems to pilots in flight, ATC controllers, traffic management units and airlines. Future research should focus on defining the ash densities and time exposures of concern to aircraft, resolving the sensor mix for measuring the ash density and extent, and validating models for ash transport.

This paper describes an experimental system for cockpit display of Terminal Doppler Weather Radar (TDWR) wind shear warnings. The TDWR is a ground-based system for detecting wind shear hazards that pose a threat to aviation, During the Summer of 1990, wind shear warnings generated by the Lincoln-operated TDWR testbed radar at Orlando, Florida were transmitted in real-time to a research aircraft performing microburst penetrations. This test marks a milestone as being the first time that TDWR wind shear warnings were successfully transmitted and displayed in an aircraft in real-time. This effort was supported by NASA Langley Research Center as part of a program to investigate techniques for integrating airborne and ground-based wind shear information for aircrew alerting. The three main goals for 1990 were 1) to conduct microburst penetrations with an instrumented aircraft, 2) to compare a hazard estimate called the F factor (Bowles, 1990) for airborne and TDWR data, and 3) demonstrate real-time data link and cockpit display of TDWR warnings. All three of these goals were successfully carried out. The research aircraft, a Cessna Citation II operated by the University of North Dakota (UND) Center for Aerospace Sciences conducted over 80 microburst penetrations in Orlando over a six week period with TDWR testbed radar surveillance. Initial post-processing analysis in comparing the aircraft and TDWR F factors has begun. The cockpit display system was operated during the latter part of the flight test period, and proved useful in aiding the Citation crew in locating microburst and gust front events. There were three main objectives in the development of the cockpit display system. First, the real-time display was intended to aid the Citation crew in locating microburst and gust front events. This capability was desired both to aid the crew in locating events to penetrate, and to improve safety by providing a better information about the location of the wind shear events. A second objective was to demonstrate the feasibility of transmitting TDWR wind shear warnings to aircraft in real-time. This demonstration is an important element in the eventual development of an integrated aircrew alerting procedure incorporating both airborne and ground-based wind shear information. This study marks the first successful demonstration of real-time transmission of TDWR wind-shear warnings to an aircraft in flight. A third objective was to demonstrate the desirability of transmitting TDWR wind shear warnings to aircraft in real-time. Currently, the TDWR provides these warnings to controllers as textual messages, which are then relayed to pilots via voice communications. The TDWR also includes graphical displays of wind shear and precipitation products but these are only provided currently to the Tower and TRACON supervisors. A potential use of Mod S Data Link (or other ground-to-air data link systems) is to provide TDWR wind shear warnings directly to pilots, Automatic delivery of TDWR wind shear warnings potentially result in decreased controller workload and improved pilot information. Mode S Data Link is currently planned to provide textual wind shear warnings only. However, studies by Wanke and Hansman (1990) show that pilots substantially prefer graphical presentation of wind shear warnings over textual presentation. The paper will first describe the organization of the system, including the process of generating the display messages in the TDWR testbed and data linking them to the aircraft. Second, the display format and operation of the cockpit display will be described. Next, an example of the operational use of the cockpit display will be presented, along with initial F factor results. Finally, the paper will conclude with a summary and plans for future work.

A gust front is the leading edge of a thunderstorm outflow. A gust frontal passage is typically characterized by a drop in temperature, a rise in relative humidity and pressure, and an increase in wind speed and gustiness. Gust front detection is of concern for both Terminal Doppler Weather Radar (TDWR) and Next Generation Weather Radar (NEXRAD) systems. In addition, airborne systems using radar, lidar, and infrared sensors to detect hazardous wind shears are being developed. The automatic detection of gust fronts is desirable in the airport terminal environment so that warnings of potentially hazardous gust front-related wind shears can be delivered to arriving and departing pilots. Information about estimated time of arrival and accompanying wind shifts can be used by an Air Traffic Control (ATC) supervisor to plan runway changes. Information on expected wind shifts and runway changes is also important for terminal capacity programs such as Terminal Air Traffic Control Automation (TATCA) and wake vortex advisory systems. In addition, the convergence associated with gust fronts is often a factor in thunderstorm initiation and intensification. Knowledge of gust front locations, strengths, and movement can aid forecasters with thunderstorm-specific predictions. Current gust front detection systems generally are reliable in that the probability of false alarms is low. However the probability of detecting gust fronts with these systems is less than desired. Improved characterization of gust fronts is a key element in improving detection capability. Typically, the basic products from the algorithms are the location of the gust front (for hazard assessment) and its propagation characteristics (for forecasting). This paper discusses the thermodynamic and radar characteristics of gust fronts from three climatic regimes, highlighting regional differences and similarities of gust fronts. It also compares propagation speeds, estimated by two techniques, to measured propagation speeds.

Gust front detection is of concern for both Terminal Doppler Weather Radar (TDWR) and Next Generation Weather Radar (NEXRAD) systems. The automatic detection of gust fronts is desirable in the airport terminal environment because warnings of potentially hazardous gust front-related wind shears can be delivered to arriving and departing pilots. Information about estimated time of arrival and accompanying wind shifts can be used by an Air Traffic Control (ATC) supervisor to plan runway changes. Information on expected wind shifts and runway changes are also important for terminal capacity programs such as Terminal Air Traffic Control Automation (TATCA) and wake vortex advisory systems. In addition, the convergence. associated with gust fronts is often a factor in thunderstorm initiation and intensification. Knowledge of their locations and strengths can aid forecasters with thunderstorm forecasts. Experienced radar meteorologists can identify gust fronts in single Doppler radar data by the presence or radial convergence, azimuthal shear, and thin lines of reflectivity. The radial convergence signature is the most reliable of all of the signatures. Therefore, the formally-documented TDWR gust front algorithm is designed to automatically detect gust fronts through radial convergence.

The estimation of air and particle motions in storms from multiple Doppler radar measurement is a long standing problem in radar meteorology. Our research interest in understanding the relationship of electrical change generation processes above the freezing level to thunderstorm life cycle, and in the detailed quantification of the eventual low altitude divergent outflow produced by the storm, demands an accurate retrieval of air and particle motions at essentially all altitudes within the storm. We found that existing approaches had deficiencies for our needs, and have developed an improved "hybrid" approach which attempts to provide high quality estimates throughout the storm volume.