Publications

Lincoln Laboratory, under funding from the Federal Aviation Administration (FAA) Terminal Doppler Weather Radar program, has developed algorithms for automatically detecting microbursts. While microburst detection algorithms provide highly reliable warnings of microbursts. there still remains a period of time between microburst onset and pilot reaction during which aircraft are at risk. This latency is due to the time needed for the automated algorithms to operate on the radar data, for air traffic controllers to relay any warnings and for pilots to react to the warnings. Lincoln Laboratory research and development has yielded an algorithm for accurately predicting when microburst outflows will occur. The Microburst Prediction Algorithm is part of a suite of weather detection algorithms within the Integrated Terminal Weather System. This paper details the performance of the Microburst Prediction Algorithm over a wide range of geographical and climatological environments. The paper also discusses the full range of the Microburst Prediction Algorithm's capabilities and limitations in varied weather environments. This paper does not discuss the overall rationale for a prediction algorithm or the detailed methodology used to generate predictions.

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.