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Microburst divergence detection for Terminal Doppler Weather Radar (TDWR)

Author:
Published in:
MIT Lincoln Laboratory Report ATC-181

Summary

The Terminal Doppler Weather Radar (TDWR) microburst surface divergence detection algorithm has been under development and evaluation at Lincoln Laboratory since 1983. The TDWR program is sponsored by the Federal Aviation Administration (FAA), and the algorithm described in this report is a primary algorithm component of the TDWR system. The divergence algorithm processes radar velocity measurements taken near the earth's surface to identify the strong divergent outflow characteristic of microburst wind shear hazards. The algorithm uses a complex set of pattern matching and validation test criteria to locate microburst outflow signatures and to filter out false alarms from various data contamination sources. The divergence algorithm is primarily responsible for the detection of most microbursts, although the complete TDWR microburst algorithm consists of more than a dozen distinct algorithmic components. The divergence algorithm has demonstrated a very high probability of detection (POD) for strong microburst outflows, and its performance (as well as that of the complete microburst detection algorithm) was first formally assessed in the operational test and evaluation of the TDWR in Denver, CO (1988). Subsequent evaluations were performed in Kansas City, KS (1989) and Orlando, FL (1990). These evaluations have provid
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Summary

The Terminal Doppler Weather Radar (TDWR) microburst surface divergence detection algorithm has been under development and evaluation at Lincoln Laboratory since 1983. The TDWR program is sponsored by the Federal Aviation Administration (FAA), and the algorithm described in this report is a primary algorithm component of the TDWR system. The...

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Summer 1988 TDWR microburst analysis

Author:
Published in:
Proc. Airborne Wind Shear Detection and Warning Systems, Second Combined Manufacturers' and Technologists' Conf., Pt. II, 18-20 October 1988, pp. 741-751.

Summary

The Terminal Doppler Weather Radar (TDWR) testbed system was operated during the months of July-August 1988 in a live operational demonstration providing microburst (and related weather hazard) protection to the Stapleton International Airport in Deilver, CO. During this time period, the performance of the detection system was carefully monitored in an effort to determine the reliability of the system. Initial performance analysis indicates that the microburst detection component of TDWR satisfies the basic performance goals of 90% probability of detection md 10% probability of false alarm. An in-depth study of the system performance, based on analysis of both dual-Doppler radar observations and surface mesonet measurements, is in progress to provide a detailed understanding of the observability of microbursts by the radar, the ability of the algorithms to detect microbursts observed by the radar, and the timeliness and accuracy of the microburst alarms provided to operational users.
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Summary

The Terminal Doppler Weather Radar (TDWR) testbed system was operated during the months of July-August 1988 in a live operational demonstration providing microburst (and related weather hazard) protection to the Stapleton International Airport in Deilver, CO. During this time period, the performance of the detection system was carefully monitored in...

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Microburst recognition performance of TDWR operational testbed

Published in:
Proc. Third Int. Conf. on the Aviation Weather System, 30 January - 3 February 1989, pp. 25-30.

Summary

This paper describes current work in assessing the microburst recognition performance of the Terminal Doppler Weather Radar (TDWR) operational testbed. The paper is divided into three main sections: microburst recognition algorithm, performance assessment methodology and results. The first section provides an overview of the prototype TDWR microburst recognition algorithm The algorithm uses radar data from both surface scans and scans aloft to identify microburst events. The surface scan is used to identify microburst outflows, and the scans aloft provide information concerning reflectivity and velocity structures associated with microbursts to improve recognition rate and timeliness. The second section of the paper describes the methodology for assessing the recognition performance of the system. The performance of the testbed system is addressed from two viewpoints: radar detectability and pattern recognition capability. The issue of radar detectability is examined by comparing radar and mesonet data to determine if any events observed by the mesonet fail to be observed by the radar. The issue of pattern recognition performance is assessed by comparing microburst recognition algorithm outputs with truth as determined by expert radar meteorologists. The final section of the paper provides performance results for data collected by the testbed radar at Huntsville, AL and Denver, CO.
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Summary

This paper describes current work in assessing the microburst recognition performance of the Terminal Doppler Weather Radar (TDWR) operational testbed. The paper is divided into three main sections: microburst recognition algorithm, performance assessment methodology and results. The first section provides an overview of the prototype TDWR microburst recognition algorithm The...

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Wind shear detection with pencil-beam radars

Published in:
Lincoln Laboratory Journal, Vol. 2, No. 3, Fall 1989, pp. 483-510.

Summary

Abrupt changes in the winds near the ground pose serious hazards to aircraft during approach or departure operations. Doppler weather radars can measure regions of winds and precipitation around airports, and automatically provide air traffic controllers and pilots with important warnings of hazardous weather events. Lincoln Laboratory, as one of several organizations under contract to the Federal Aviation Administration, has been instrumental in the design and development of radar systems and automated weather-hazard recognition techniques for this application. The Terminal Doppler Weather Radar (TDWR) system uses automatic computer algorithms to ident* hazardous weather signatures. TDWR detects and warns aviation users about low-altitude wind shear hazards caused by microbursts and gust fronts. It also provides advance warning of the arrival of wind shifts at the airport complex. Extensive weather radar observations, obtained from a Lincoln-built transportable testbed radar system operated at several sites, have validated the TDWR system. As a result, the Federal Aviation Administration has issued a procurement contract for the installation of 47 TDWR radar systems around the country.
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Summary

Abrupt changes in the winds near the ground pose serious hazards to aircraft during approach or departure operations. Doppler weather radars can measure regions of winds and precipitation around airports, and automatically provide air traffic controllers and pilots with important warnings of hazardous weather events. Lincoln Laboratory, as one of...

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TDWR Scan Strategy Requirements

Published in:
MIT Lincoln Laboratory Report ATC-144
Topic:

Summary

This report describes the requirements for the wan s+rategy to be employed M the
Terminal Doppler Weather Radar (TDWR). The report in divided into three main sections:
rationale, example scan strategy and requirements. The rationale for the TDWR scanstrategy
is presented in terms of 1) detection of meteorological phenomena, and 2) minimization of
range and velocity folding effects. Next, an example is provided based on an experimental scan
strategy used in Denver during the summer of 1987. Finally, the requirements for the TDWR
scan strategy are presented based on the preceding discussion. Also, an appendix is included describing the proposed criteria for switching between scan modes.
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Summary

This report describes the requirements for the wan s+rategy to be employed M the
Terminal Doppler Weather Radar (TDWR). The report in divided into three main sections:
rationale, example scan strategy and requirements. The rationale for the TDWR scanstrategy
is presented in terms of 1) detection of meteorological phenomena, and...

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Automated detection of microburst windshear for terminal doppler weather radar

Author:
Published in:
SPIE, Vol. 846, Digital Image Processing and Visual Communications Technolody in Meteorology, 27-28 October 1987, pp. 61-68.

Summary

An image analysis method is presented for use in detecting strong windshear events, called microbursts, in Doppler weather radar images. This technique has been developed for use in a completely automated surveil-lance system being procured by the Federal Aviation Administration (FAA) for the protection of airport terminal areas. The detection system must distill the rapidly evolving radar imagery into brief textual warning messages in real time, with high reliability.
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Summary

An image analysis method is presented for use in detecting strong windshear events, called microbursts, in Doppler weather radar images. This technique has been developed for use in a completely automated surveil-lance system being procured by the Federal Aviation Administration (FAA) for the protection of airport terminal areas. The detection...

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Spatial and temporal analysis of weather radar reflectivity images

Author:
Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, 6-9 April 1987, pp. 606-609.

Summary

This paper illustrates the use of a primitive symbolic description of an image to obtain more robust identification of amorphous objects than would be possible with more conventional edge or gradient-based segmentation techniques. An algorithm is described which uses a simple multi-level thresholding operation to form a symbolic representation of weather radar reflectivity images. This representation allows the use of detailed rules for the detection and quantification of the image features. A method is described for using this information to identify significant intensity peaks in an image, and examples of its performance are shown.
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Summary

This paper illustrates the use of a primitive symbolic description of an image to obtain more robust identification of amorphous objects than would be possible with more conventional edge or gradient-based segmentation techniques. An algorithm is described which uses a simple multi-level thresholding operation to form a symbolic representation of...

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Clutter suppression for low altitude wind shear detection by doppler weather radars

Published in:
23rd Conf. on Radar Meteorology, Vol. 1, 22-26 September 1986, pp. 9-13.

Summary

Low altitude wind shear (LAWS) has been recognized as a major cause of commercial airline aircraft accidents in the United States. The FAA is actively conducting the Terminal Doppler Weather Radar (TDWR) program to detect and identify dangerous wind fields at and around airports using Doppler radar techniques. Clutter poses a major challenge to successful operation of such a system due to the need to measure the return from low cross section wind tracers in the presence of close-in clutter from stationary objects. The paper describes the overall LAWS detection scenario with particular emphasis on microburst and gust front detection before presenting detailed experimental and analytical results on the suppression of ground clutter using a combination of: 1) subclutter visibility in excess of 50 dB by the use of high pass digital filters with narrow stopbands, and 2) interclutter visibility (ICV) algorithms which utilize the spatially distributed nature of the weather phenomena being measured, and 3) pencil beam antennas with readily achievable sidelobes.
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Summary

Low altitude wind shear (LAWS) has been recognized as a major cause of commercial airline aircraft accidents in the United States. The FAA is actively conducting the Terminal Doppler Weather Radar (TDWR) program to detect and identify dangerous wind fields at and around airports using Doppler radar techniques. Clutter poses...

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Short-term prediction of high reflectivity contours for aviation safety

Published in:
Proc. Ninth Conf. Aerospace and Aeronautical Meteorology, 6-9 June 1983, pp. 118-122.

Summary

Airspace utilization and safety could benefit significantly from accurate, real-time, short-term predictions of hazardous weather regions (e.g., 5-30 minutes). For some hazards, such as heavy turbulence, the detection process itself is in an immature stage. No universally accepted algorithm exists for indicating the regions of current turbulence - let alone predicting it. For other hazards, such as hail and more particularly for heavy rain, the detection process is in a more mature state. In fact heavy rain may be unambiguously associated with high dBZ (reflectivity), if no ice phases are present. Hail is also associated with high reflectivities. We have therefore chosen to place our initial emphasis on the prediction of reflectivity contours in the context of ATC (air traffic control) operations. For all or our prediction techniques, we begin by collecting fixed dBZ-level contours on a fixed-elevation scan by fixed-elevation scan basis, and then combining these elevation cell slices into volume cells as is done in the algorithm of Bjerkaas and Forsyth (1980). To these volume cells we attach translations vectors to make the desired prediction: at this time no provision is made for the growth or decay of reflectivity cells. We generate our translation vectors using each of several algorithms which have already been described elsewhere. Firstly, we use the centroid-tracking approach of Bjerkaas and Forsyth (1980). This is the current tracker of choice in the NEXRAD (Next Generation Weather Radar) program. Secondly, we use tracking vectors of clusters of volume cells, as described ny Crane (1979): much of this work was performed under the sponsorship of the Federal Aviation Administration (FAA). Thirdly, we generate translation vectors by cross-correlating low-altitude (0-4 cm) CAPPIs (constant-altitude plan position indicators): this correlation is done either for the entire storm, or for 30 km by 30 km segments of the storm. This approach has been motivated by the work of Rinehart and Garvey (1978), although we generally use a CAPPI of liquid water content. Fourthly, we use as a prediction the current, composite reflectivity map - our so-called status-quo prediction.
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Summary

Airspace utilization and safety could benefit significantly from accurate, real-time, short-term predictions of hazardous weather regions (e.g., 5-30 minutes). For some hazards, such as heavy turbulence, the detection process itself is in an immature stage. No universally accepted algorithm exists for indicating the regions of current turbulence - let alone...

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