Publications

We have developed an algorithm that automatically and reliably predicts microburst wind shear. The algorithm, developed as part of the FAA Integrated Terminal Weather System (ITWS), can provide warnings several minutes in advance of hazardous low-altitude wind-shear conditions. Our approach to the algorithm emphasizes fundamental principles of thunderstorm evolution and downdraft development and incorporates heuristic and statistical methods as needed for refinement. In the algorithm, machine-intelligent image processing and data-fusion techniques are applied to Doppler radar data to detect those regions of growing thunderstorms and intensifying downdrafts which lead to microbursts. The algorithm then uses measurements of the ambient temperature/humidity structure in the atmosphere to aid in predicting a microburst's peak outflow strength. The algorithm has been tested in real time as part of the ITWS operational test and evaluation at Memphis, Tennessee, and Orlando, Florida, in 1994.

Lincoln Laboratory is developing a prototype of the Federal Aviation Administration (FAA) Integrated Terminal Weather System (ITWS) to provide improved aviation weather information in the terminal area by integrating data and products from various FAA and National Weather Service (NWS) sensors and weather information systems. The ITWS Microburst Prediction product is intended to provide and additional margin of safety for pilots in avoiding microburst wind shear hazards (Fig. 1). The product is envisioned for use by traffic managers, supervisors, controllers, and pilots (directly via datalink). Our objective is to accurately predict the onset of microburst wind shear several minutes in advance. The approach we have chosen in developing the ITWS Microburst Prediction algorithm emphasizes fundamental physical principles of thunderstorm evolution and downdraft development, incorporating heuristic and/or statistical methods as needed for refinement. Image processing and data fusion techniques are used to produce an "interest" image (Delanoy etal., 1991, 1992) that reveals developing downdrafts. We use Doppler radar data to identify regions of growing thunderstorms and probable regions of downdraft, and combine these with measures of the ambient temperature structure (height of the freezing level, lapse rate in the lower atmosphere; Wolfson 1990), total lightning flash rate, and storm motion to predict the microburst location, timing, and outflow strength. There is also a simple feedback system based on the results of the Microburst Detection algorithm that desensitizes prediction thresholds if false predictions are being reported. The following slides describe the preliminary ITWS Microburst Prediction algorithm design, and show examples of feature detector, and the algorithm output on one test case. Results from off-line testing on 17 days of data from Orlando are also presented.

Under Federal Aviation Administration (FAA) sponsorship, Lincoln Laboratory conducted an aviation weather hazard measurement and operational demonstration program during the summer of 1991 near the Orlando International Airport. Three Doppler radars were sited in a triangle around the airport, allowing triple Doppler coverage of thunderstorms and microbursts occurring there. This report contains a summary of all of the microburst producing thunderstorms that occurred within the triple Doppler region that were scanned in a coordinated fashion, during the months of June, July, August, and September, 1991. Statistics on the microburst events are presented to give an overall picture of the available data for use in analysis. The bulk of the report consists of detailed information about each triple Doppler day, including the time, location, and strength of microbursts within the triple Doppler period as well as the availability of data from supporting sensors including the ASR-9-WSR Doppler radar, radiosondes, LLWAS, Mesonet, AWOS, instrumented aircraft, ACARS, interferometer, and corona points.

The characteristics of microbursts and gust fronts, two forms of aviation-hazardous low altitude wind shear, are presented. Data were collected with a prototype terminal Doppler weather radar and a network of surface weather stations in Memphis, Huntsville, Denver, Kansas City, and Orlando. Regional differences and features that could be exploited in detection systems such as the associated reflectivity, surface wind shear, and temperature change are emphasized.

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.