Publications

This report evaluates the capability of Airport Surveillance Radars (ASRs) for the detection of low altitude wind shear associated with the outflows of dry microbursts. It describes results of simulations of dry microburst observations by an ASR. These simulations incorporated weather and clutter data collected by the FL-2 pencil-beam Doppler weather radar at Denver Stapleton Airport in 1988 and 1989 and clutter data collected by the FL-3 ASR-9 emulation radar at Hunstville, Alabama. The impact of signal strength, overhanging precipitation, and ground clutter on both observability and algorithmic performance are assessed. Principal results of study are the following: 1. Overhanging precipitation and weak signal strength do not, by themselves, prohibit detection of dry outflows; however, occurence of false alarms and biases in velocity estimates indicate that improvements in the dual beam estimator that was evaluated would be required for reliable detection of these events. 2. Ground clutter tends to obscure dry outflow in regions where the difference between median effective clutter reflectivity and weather reflectivity exceeds 17-20 dB. A method for predicting the percentage of missed microburst detections due to ground clutter is used to estimate overall microburst detection probabilities for a "dry" environment such as Denver. Using measured clutter from an experimental ASR in Hunstville, AL, overall microburst detection probability is 83 percent. Using simulated Denver clutter, overall detection probability is 91 percent.

This document gives a high level functional overview of an automated flight strip management system. The current manual flight strip system at Boston's Logan Airport is reviewed and described in detail for both the Tower Cab and TRACON with emphasis on the information flow as an aircraft progresses through the system. The interfaces between the ATC elements, as they related to flight data, are explained. Finally, the system requirements are described including specific requirements for Tower Cab positions.

This paper describes a prototype microburst prediction product for the Terminal Doppler Weather Radar (TDWR). The prediction product was evaluated for microbursts observed during the spring and summer of 1989 at Kansas City. Results are presented demonstrating reliable prediction of high reflectivity microbursts of at least 15 m/s outflow intensity from single-Doppler radar data. The ability of the algorithm to predict microbursts approximately five minutes prior to the onset of surface outflow could be used to improve air traffic control (ATC) planning and to improve hazard warning time to pilots. In particular, this product could allow aircraft to avoid an impending microburst hazard, rather than penetrating it. The present TDWR microburst recognition algorithm uses features aloft such as reflectivity cores and convergence to recognize microburst precursors. The algorithm uses precursors to make a microburst declaration while the surface outflow is still weak, thereby improving the hazard warning time (Campbell, 1989). The microburst prediction product is an extension of the algorithm to predict microbursts from these precursor signatures. The prototype prediction product is tuned to predict the high reflectivity microburst typical of humid regions of the United States. The paper begins by reviewing conceptual models for microburst development and comparing them to the observed characteristics of Kansas City microbursts. The prototype prediction product is then described, and performance statistics are presented. Finally, failure mechanisms and future work are discussed.

The Federal Aviation Administration (FAA) currently uses the anemometer-based Low Level Wind Shear Alert System (LLWAS) as the primary method of wind shear detection at major U.S. airports. With the upcoming deployment of the Terminal Doppler Weather Radar (TDWR) system, potential methods for integrating the two systems are being investigated. By integrating, advantages of both sensor systems can be utilized. Advantages of the LLWAS ground sensor network include true wind direction measurements, a high measurement frequency, a lack of sensitivity to clear air reflectivity, and few false alarms from radar point targets such as planes, birds, etc. Advantages of the radar include complete scan coverage of the region of concern, the ability to predict events, fewer terrain problems such as sheltering which can reduce the wind speed readings, and almost no false alarms due to non-hazardous wind shear such as thermals. The objectives of this study are to gain a clearer understanding of the basic relationship between the wind information provided by these two very different sensing systems, and to determine the impact this relationship may have on integration of the two operational systems. A proposed mathematical technique for "correcting" LLWAS winds where needed to better match radar winds is evaluated for cases of microburst (divergent) and gust front (convergent) wind shear.

The Terminal Doppler Weather Radar (TDWR) testbed collected thunderstorm measurements in the Kansas City area from March 27 through October 6, 1989. Of the 393 microbursts detected by the radar, 21 were classified as severe, with a differential velocity > 24 m/s. None of the severe events impacted terminal operations at Kansas City International Airport (KCI). Nevertheless, there were 42 microbursts within 3 nautical miles of the airport.

MIT Lincoln Laboratory is being sponsored by the Federal Aviation Administration (FAA) to develop and test the Terminal Doppler Weather Radar (TDWR) wind shear surveillance system. As part of this program Lincoln has developed algorithms for automatically detecting microbursts, or thunderstorm outflows using the radial velocity data gathered from a single TDWR. Output from the detection algorithms will be used to warn aircraft of microburst hazards. While the success in automatically detecting microbursts using the Lincoln Laboratory microburst detection algorithm has been encouraging, one issue which continues to cause concern is microburst asymmetry. Asymmetry, or aspect angle dependence, in microbursts refers to outflows that have a divergent surface outflow strength or extent what varies depending on the aspect (or viewing) angle of the radar. The TDWR detection algorithms utilize input from a single Doppler radar; therefore, an asymmetric microburst may be underestimated or go undetected if the radar is viewing the event from an aspect angle where the strength of the outflow is weak. Additionally, the size and location of the event may be distorted when the outflow extent is significantly asymmetric. Most of the present outflow modeling and detection methods are based on the assumption of axial symmetry both in the strength and extent of outflows. Asymmetry in microbursts, therefore, is a major concern for TDWR microburst detection performance. Past work by Wilson et al. and Eilts has indicated that some microbursts are highly asymmetric, for at least a portion of their lifetime. However, this previous work has been limited in scope to single "snap-shots" of the microbursts, generally at their peak outflow strength. Strength asymmetries from these previous studies indicated asymmetry ratios (maximum over minimum strength) ranging from 1.3:1 to as high as 6:1. None of the studies dealt with shape (or extent) asymmetries. This paper describes the results from a detailed study of 96 individual observations from 27 microburst events. Measurements were taken to determine both the strength and extent of each microburst at multiple aspect angles. The data clearly show that microbursts, on average, have maximum strengths and extents which are 1.9:1 and 1.5:1 asymmetric, respectively.

The Terminal Doppler Weather Radar (TDWR) testbed radar (known as FL-2) collected data near Denver's Stapleton Airport during 1988 and near the Kansas City International Airport (MCI) during 1989. One objective of the TDWR Program is to detect gust fronts and their associated wind shifts. This information can be used by an Air Traffic Control (ATC) supervisor to plan runway changes and for warnings of potentially-hazardous gust front-related wind shears to arriving and departing pilots. This function is performed by the gust front detection algorithm. An ongoing assessment of the performance of the current TDWR gust front algorithm is necessary to ensure that the algorithm performs consistently in different environments. Such assessments were performed after the 1988 TDWR Operational Test and Evaluation in Denver and after the 1989 operational season in Kansas City. This paper presents a comparison of gust front characteristics such as length, duration, strength, and propagation speed and direction that occurred in Denver and Kansas City and a comparison of algorithm performance at each location. In the following, the term gust front refers to the leading edge of the thunderstorm outflow throughout its life cycle. A gust front event is a single observation of a gust front (on a radar volume scan) by the National Severe Storms Laboratory (NSSL) ground-truth analyst.

Low-altitude wind shear, specifically, the aviation-hazardous form of wind shear known as the microburst, has been cited as the cause of several aviation disasters over the past two decades. Microbursts are strong, small-scale convective storm downdrafts that impact the ground and cause a violent divergent outflow of wind. The Federal Aviation Administration (FAA) recently awarded a contract for the production of 47 Terminal Doppler Weather Radars (TDWRs) to detect microbursts. Since the TDWR systems are expensive, only a limited number will be available for use at major U.S. airports. In deciding which airports will receive the TDWRs or any other advanced detection equipment, such as the ASR-9 with wind shear detection capability or the Enhanced Low Level Wind Shear Alert System, a detailed cost-benefit study will be performed. One factor that would aid in determining the benefit of advanced wind shear detection equipment is a knowledge of the average relative microburst threat at each major airport. Using "thunderstorm day" statistics and the results of measurements by the FAA TDWR testbed systems, we propose a method for predicting this threat.

The FAA is deploying over 100 next generation airport surveillance radars (ASR-9) at selected major airports across the country. Like previous ASRs, the ASR-9 utilizes dual broad elevation fan beams Figure 1) along with a rapid scan rate (12.5 RPM to exercise its primary function of detecting aircraft over a 60 nmi radius. In addition, the ASR-9 has a separate dedicated weather reflectivity channel which allows air traffic controllers to display quantitative precipitation intensity reports corresponding to the NWS six-level intensity scale on their PPI display. The 30 second update rate of the weather channel coupled with the large sample volume swept by the ASR-9 fan-beam combine to provide timely and useful indications of precipitation intensity within the terminal airspace. The PPI display of precipitation intensity which is presented to the air traffic controller is essentially a 2-D representation of the 3-D reflectivity field sampled by the fan-shaped beam of the ASR-9. Since the antenna gain varies with elevation angle (Figure 1), the parameter reopned by the ASR-9 weather channel represents a beam-weighted, vertically averaged estimate of storm intensity. Previous research has shown that the vertically integrated reflectivity automatically reported by fan-beam radars such as the ASR-9 correlates well with estimates of vertically integrated liquid water content (VIL), a useful meteorological parameter which is a measure of overall storm intensity. Dobson found a linear relationship between W and fan-beam reflectivity from 30 to 60 dBZ assuming the beam is filled with precipitation (see discussion in Section 4). If the beam is non-uniformly or only partially filled with precipitation, then the inherent vertical integration introduced by the fan-beam may cause an underestimation of the storm intensity. This beam filling loss is most acute at long range, where the vertical extent of the beam intercepts more than 10 km of altitude. The magnitude of this error depends on the complex interaction between the vertical reflectivity structure of the storm and its interception by the fan-shaped beam. If the shape and altitude extent of the vertical reflectivity profile (such as could be provided by a pencil-beam radar) are known, then a suitable adjustment can be calculated and applied to the fan-beam reflectivity estimate in order to produce the desired reflectivity report. The six-level weather thresholds are stored in processor memory for each range sate as functions of receive beam (high or low). The thresholds can be adjusted to compensate for beam filling losses. The adjustments initially implemented in the ASR-9 were derived using a reflectivity profile model which assumes the maximum reflectivity of the storm is distributed constantly from the surface up to 4 km, and then falls off at 3 dBZ per km above 4 km. The success of the reflectivity correction depends on how well the model profile matches actual storm profiles. If regional variations in general storm morphology are significant, then different beam filling loss correction models may need to be developed for specific regions. Understanding the significance of these regional variations in storm vertical reflectivity structure and their impact on ASR-9 weather report accuracy provided the motivation for this study.

Wind shear is a major cause of aircarrier accidents in the United States, and most of these accidents have been caused by one particular form of wind shear called a microburst (Zorpette, 1986). Microbursts have been defined as small scale, low-altitude, intense downdrafts which impact the surface and cause strong divergent outflows of wind. We know they are associated with thunderstorms and are usually but not always accompanied by heavy rainfall at the ground. However, a number of meteorologically distinct phenomena associated with thunderstorms can give rise to strong downdrafts and high surface winds. Most microburst research has focused on the main precipitation driven downdraft of thunderstorms, both with and without significant surface rainfall. But other downdraft types such as the dynamically driven downdrafts at low altitude associated with "vortices" at the leading edge of expanding thunderstorm outflows and with "roll clouds" have also been associated with the microburst problem. In this paper, I discuss these two primary forms of low altitude downdraft phenomena in thunderstorms. This differentiation is essential to discovering exactly what atmospheric conditions lead to the development of the most hazardous microbursts. A physically based predictive model for thunderstorm downdraft strength is presented which shows that the radar reflectivity of a storm alone cannot be used as a hazard index; information about the static stability of the atmosphere is also essential. I then show that the downdrafts associated with the gust front around a cold outflow from a small isolated thunderstorm, a microburst, are inherently stronger at low altitudes than those found in more straight-line gust fronts. Finally, I reexamine the most recent fatal U.S. microburst accident, the crash of Delta 191 at Dallas/Ft. Worth in 1985, and show that both types of low altitude downdrafts were encountered as part of the "microburst", although the downdrafts came from different storms.