Publications
Potential benefits of reducing wake-related aircraft spacing at the Dallas/Fort Worth International Airport
July 12, 2002
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-304
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Summary
Measurements and modeling of wake vortices reveal that the Federal Aviation Administration's (FAA) minimum separation requirements for departing aircraft are often overly conservative. If the separation times following heavy aircraft can be safely reduced, considerable savings will be realized. The Dallas/Fort Worth International Airport (DFW) experiences departure delays daily. Banks of departing aircraft often create a significant queue at the end of the runway, with aircraft waiting between 10-20 minutes to depart. Additional delays occur during weather recovery operations after the terminal airspace has been impacted by thunderstorms. This report produces projected delay and cost benefits of implementing reduced wake spacing for departing aircraft at DFW. The benefits are calculated by simulating aircraft departures during both clear weather and weather recovery operations, using current and possible reduced spacings. The difference in delay values using different separation standards is used to calculate a cost savings to the airlines. The benefits for a single day are extended to a yearly approximation based on the estimated number of days that the separation criteria could be safely reduced. Departure information from February 19, 2001 is analyzed for clear weather operations. The simulation reveals a savings of $4.7 million/yr when the separation criteria is reduced from the current practice of 110 seconds to 90 seconds. A further reduction in the separation criteria to 60 seconds pushes the maximum savings to almost $10 million/yr. The daily savings for a weather recovery operation is $19,600 for weather impacts between 15-60 minutes and a reduction in spacing fiom the current 110 seconds to 90 seconds. The average increases to $36,200 when the spacing is reduced to 60 seconds. Significant thunderstorm events impacted the DFW terminal airspace 59 times during 2001 leading to projected yearly savings of greater than $2.1 million for a 60 second separation criteria following heavies.
Summary
Measurements and modeling of wake vortices reveal that the Federal Aviation Administration's (FAA) minimum separation requirements for departing aircraft are often overly conservative. If the separation times following heavy aircraft can be safely reduced, considerable savings will be realized. The Dallas/Fort Worth International Airport (DFW) experiences departure delays daily. Banks...
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ASR-9 Weather Systems Processor (WSP) signal processing algorithms
June 25, 2002
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-255
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Summary
Thunderstorm activity and associated low-altitude wind shear constitute a significant safety hazard to aviation, particularly during operations near airport terminals where aircraft altitude is low and flight routes are constrained. The Federal Aviation Administration (FAA) has procured several dedicated meteorological sensors (Terminal Doppler Weather Radar (TDWR), Network Expansion Low Level Wind Shear Alert System (LLWAS) at major airports to enhance the safety and efficiency of operations during convective weather. A hardware and software modification to existing Airport Surveillance Radars (ASR-9)-the Weather Systems Processor (WSP)-will provide similar capabilities at much lower cost, thus allowing the FAA to extend its protection envelope to medium density airports and airports where thunderstorm activity is less frequent. Following successful operation demonstrations of a prototype ASR-WSP, the FAA has procured approximately 35 WSP's for nationwide deployment. Lincoln Laboratory was responsible for development of all data processing algorithms, which were provided as Government Furnished Equipment (GFE), to be implemented by the full-scale development (FSD) contractor without modification. This report defines the operations that are used to produce images of atmospheric reflectivity, Doppler velocity and data quality that are used by WSP's meteorological product algorithms to generate automated information on hazardous wind shear and other phenomena. Principle requirements are suppression of interference (e.g. ground clutter, moving points targets, meteorological and ground echoes originating from beyond the radar's unambiguous range), generation of meteorologically relevant images and estimates of data quality. Hereafter, these operations will be referred to as "signal processing" and the resulting images as "base data."
Summary
Thunderstorm activity and associated low-altitude wind shear constitute a significant safety hazard to aviation, particularly during operations near airport terminals where aircraft altitude is low and flight routes are constrained. The Federal Aviation Administration (FAA) has procured several dedicated meteorological sensors (Terminal Doppler Weather Radar (TDWR), Network Expansion Low Level...
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Machine intelligent gust front algorithm for the WSP
June 10, 2002
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-274
Summary
The Machine Intelligent Gust Front Algorithm (MIGFA) utilizes multi-dimensional image processing and fuzzy logic techniques to identify gust fronts in Doppler radar data generated by the ASR-9 Weather Systems Processor (WSP). The algorithm generates products that support both safety and planning functions for ATC. Outputs include current and predicted locations of gust fronts, as well as estimates of the wind shear and wind shift associated with each gust front. This document provides both high level and detailed functional descriptions of FAA build 2.0 of the WSP MIGFA. The document was written with many explicit references to data structures and routines in the actual software in order that it may serve as a useful algorithm development and programmers reference guide.
Summary
The Machine Intelligent Gust Front Algorithm (MIGFA) utilizes multi-dimensional image processing and fuzzy logic techniques to identify gust fronts in Doppler radar data generated by the ASR-9 Weather Systems Processor (WSP). The algorithm generates products that support both safety and planning functions for ATC. Outputs include current and predicted locations...
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A comparison of boundary layer wind estimation techniques
May 13, 2002
Conference Paper
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10th Conf. on Aviation, Range, and Aerospace Meteorology, 13-16 May 2002, pp. 331-33334.
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Accurate, short-term (0-2 hour) forecasts of convective initiation provide critical information about weather that has a major impact on aviation safety and system capacity. The Terminal Convective Weather Forecast (TCWF) algorithm is a key component of the FAA's operational Integrated Terminal Weather System (ITWS). Convective forecasts rely, in part, upon detection of convergence zones in the boundary layer. Detection of convergence requires accurate, high-resolution wind estimates, which may be based on measurements from many sources, including Terminal Doppler Weather Radar (TDWR), Next Generation Weather Radar (NEXRAD), Automatic Weather Observation System/Automatic Surface Observation System (AWOS/ASOS), aircraft (via the Meteorological Data Collection and Reporting System, MDCRS) and Low Level Wind Shear Alert System (LLWAS). These data may be directly analyzed, combined with satellite and sounding data or ingested into physical models that estimate winds and produce short term forecasts. We compare two windfield estimation techniques: Terminal Winds (TWINDS) [Cole et. al., 2000], an optimal estimation algorithm developed at Lincoln Laboratory that is deployed operationally in ITWS, and Variational Doppler Radar Analysis System (VDRAS) [Sun and Crook, 2001], a 4DVAR algorithm developed and fielded by the Research Applications Program (RAP) at NCAR. These techniques differ markedly in their use of physical models: TWINDS applies no physical constraints to its analysis, while VDRAS uses a 4DVAR technique to fit the data with a boundary layer model as a strong constraint. The techniques also differ in their computational requirements: TWINDS requires substantially less computational power than VDRAS. We were able to run TWINDS at higher horizontal resolution and update rate (1km grid spacing, 5 minute update) than VDRAS (2km and 12 minutes).
Summary
Accurate, short-term (0-2 hour) forecasts of convective initiation provide critical information about weather that has a major impact on aviation safety and system capacity. The Terminal Convective Weather Forecast (TCWF) algorithm is a key component of the FAA's operational Integrated Terminal Weather System (ITWS). Convective forecasts rely, in part, upon...
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Using ORPG to enhance NEXRAD products to support FAA critical systems
May 13, 2002
Conference Paper
Published in:
10th Conf. on Aviation, Range, and Aerospace Meteorology, 13-16 May 2002, pp. 77-80.
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The initial release of a new operational open architecture is currently being phased into the national WSR-88D (NEXRAD) radar network. This new Common Operations and Development Environment (CODE) includes the Open Radar Product Generator (ORPG) that replaces the existing NEXRAD Radar Product Generator. The new ORPG includes all the algorithms of the RPG it replaces. Future algorithms designed for use within NEXRAD also will be processed by the ORPG. CODE can also be used in a research capacity to significantly enhance the process of ORPG meteorological algorithm development. When used independently of a NEXRAD installation, CODE/ORPG provides multiple playback options for accessing real-time base data streams. This allows development and testing of new algorithms under the same environment an algorithm would encounter in an operational setting. This establishes a flow relationship from algorithm development through operational implementation within the common environment of CODE/ORPG. A six-month Build cycle for future CODE/ORPG releases has been established. An algorithm developed in a research CODE/ORPG capacity has an opportunity, at six-month intervals, to garner agency approval and undergo final preparation for operational release. The NEXRAD Radar Operations Center (ROC) needs about eight months preparation time from algorithm submission until release of the next CODE/ORPG version. For instance. Build 2 is to be released September 30. 2002. Algorithms for Build 2 inclusion had to be submitted by January 31, 2002. It will take about three months after the release for the entire NEXRAD network to be updated. The deadline for Build 3 submission is in July 2002 with a release date set in March 2003. Multiple Federal Aviation Administration (FAA) critical systems rely on products from NEXRAD algorithms. These projects include ITWS (Integrated Airport Weather System), WARP (Weather and Radar Processing), and ClWS (Corridor Integrated Weather System). Some of the NEXRAD products used include severe storm information, composite reflectivity factor depictions, and velocity data. In this paper, we discuss new algorithms and modifications to existing algorithms earmarked for the first few releases of the CODE/ORPG that produce products of importance to these FAA systems. They include modifications to the existing Anomalous Propagation Edited Composite Reflectivity algorithm released during Build 1 upgrades, a new high resolution, digital VIL (Vertically Integrated Liquid) algorithm slated for Build 2, and a Data Quality Assurance algorithm anticipated for Build 3.
Summary
The initial release of a new operational open architecture is currently being phased into the national WSR-88D (NEXRAD) radar network. This new Common Operations and Development Environment (CODE) includes the Open Radar Product Generator (ORPG) that replaces the existing NEXRAD Radar Product Generator. The new ORPG includes all the algorithms...
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An automated, operational two hour convective weather forecast for the Corridor Integrated Weather
May 13, 2002
Conference Paper
Published in:
10th Conf. on Aviation, Range and Aerospace Meteorology, 13-16 May 2002, pp. 116-119.
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The FAA Aviation Weather Research Program (AWRP) is an initiative of the Weather and Flight Service Systems Integrated Product Team, AUA400. One of the goals of the AWRP is to create accurate and accessible forecasts of hazardous weather tailored to the needs of the aviation community. Pursuant to this goal, the AWRP has sponsored the collaboration of the Research Applications Program (RAP) of the National Center for Atmospheric Research (NCAR), the Aviation and Forecast Research Divisions at the NOAA Forecast Systems Laboratory (FSL), the Weather Sensing Group of the Massachusetts Institute of Technology's Lincoln Laboratory (MIT/LL) and the National Severe Storm Laboratory (NSSL) on a Product Development Team (PDT). This Convective Weather PDT is developing an automated system that combines real-time weather- radar data with the current "state-of-the-art" convective weather prediction algorithms to produce forecasts of convective weather for the heavily traveled air traffic routes in the Great Lakes/Northeast corridor (Chicago to New York). This Regional Convective Weather Forecast (RCWF) will be provided to traffic flow management decision-makers as part of the proof-of-concept Corridor Integrated Weather System (CIWS), which began operations in July 2001 with a l-hr animated Regional Convective Weather Forecast (RCWF).
Summary
The FAA Aviation Weather Research Program (AWRP) is an initiative of the Weather and Flight Service Systems Integrated Product Team, AUA400. One of the goals of the AWRP is to create accurate and accessible forecasts of hazardous weather tailored to the needs of the aviation community. Pursuant to this goal...
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An improved gust front detection capability for the ASR-9 WSP
May 13, 2002
Conference Paper
Published in:
10th Conf. on Aviation, Range, and Aerospace Meteorology, 13-16 May 2002, pp. 379-382.
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The Weather Systems Processor (WSP) is being deployed by FAA at 35 medium and high-density ASR-9 equipped airports across the United States. The Machine Intelligent Gust Front Algorithm (MIGFA) developed at Lincoln Laboratory provides important gust front detection and tracking capability for this system as well as other FAA systems including Terminal Doppler Weather Radar (TDWR) and Integrated Terminal Weather System (ITWS). The algorithm utilizes multidimensional image processing, data fusion, and fuzzy logic techniques to recognize gust fronts observed in Doppler radar data. Some deficiencies in algorithm performance have been identified through ongoing analysis of data from two initial limited production WSP sites in Austin, TX (AUS) and Albuquerque, NM (ABQ). At AUS, the most common cause of false alarms is bands of low-reflectivity rain echoes having shapes and intensities similar to gust front thin line echoes. Missed or late detections have occasionally occurred when gust fronts are near or embedded in the leading edge of approaching line storms, where direct radar evidence of the gust front (e.g.. thin line echo, velocity convergence) may be fragmented or absent altogether. In ABQ, "canyon wind" events emanating, from mountains located just east of the airport occur with very little lead time, and often with little or no radar signatures, making timely detection on the basis of the radar data alone difficult. MIGFA is equipped with numerous parameters and thresholds that can be adjusted dynamically based on recognition of the local or regional weather context in which it is operating. Through additional contextual weather information processing, this dynamic sensitization capability has been further exploited to address the deficiencies noted above, resulting in an appreciable improvement in performance on data collected at the two WSP sites.
Summary
The Weather Systems Processor (WSP) is being deployed by FAA at 35 medium and high-density ASR-9 equipped airports across the United States. The Machine Intelligent Gust Front Algorithm (MIGFA) developed at Lincoln Laboratory provides important gust front detection and tracking capability for this system as well as other FAA systems...
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Enhancement to Terminal Doppler Weather Radar to improve aviation weather services
May 13, 2002
Conference Paper
Published in:
10th Conf. on Aviation, Range, and Aerospace Meteorology, 13-16 May 2002, pp. 28-31.
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This paper has described work underway to enhance the TDWRs capability to provide wind shear detection services in challenging conditions, and to provide a flexible platform with COTS hardware that would support future improvements. A Radar Data Acquisition (RDA) system retrofit will upgrade the transmitter, receiver and digital signal processing subsystems of the radar to improve the quality of the reflectivity and Doppler imagery generated by the system and to extend its instrumented range. Algorithms have been described for achieving improved rejection of ground clutter and range-folded weather echoes, and reduction of Doppler velocity aliasing. An open COTS-based processing architecture was presented for the TDWR RDA retrofit, and a test program was outlined that is commencing in Oklahoma in the spring of 2002.
Summary
This paper has described work underway to enhance the TDWRs capability to provide wind shear detection services in challenging conditions, and to provide a flexible platform with COTS hardware that would support future improvements. A Radar Data Acquisition (RDA) system retrofit will upgrade the transmitter, receiver and digital signal processing...
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Forecasting convective weather using multi-scale detectors and weather Classification - enhancements to the MIT Lincoln Laboratory Terminal Weather Forecast
May 13, 2002
Conference Paper
Published in:
10th Conf. on Aviation, Range, and Aerospace Meteorology, 13-16 May 2002, pp. 132-135.
Summary
Over the past decade the United States has seen drastic increases in air traffic delays resulting in enormous economic loses. Analysis shows that more then 50% of air traffic delays are due to convective weather. In response the FAA has assembled scientific and engineering teams from MIT Lincoln Laboratory, NCAR. NSSL, FSL and several universities to develop convective weather forecast systems to aid air traffic managers in delay reduction. A user-needs study conducted by Lincoln Laboratory identified that a major source of air traffic delay was due to line thunderstorms (Forman et al., 1999). Recognizing that the line storm envelope motion was distinct from the local cell motion was the impetus for developing the Growth and Decay Storm Tracker' (Wolfson et al., 1999). The algorithm produces forecasts by extracting large-scale features from two dimensional precipitation images. These images are tracked, using either correlation techniques (Terminal Convective Weather Forecast or TCWF) or centroid techniques (National Convective Weather Forecast or NCWF). In TCWF, the track vector field is used to advect the current precipitation images formed to produce a series of forecasts into minute increments up to 60 minutes. The TCWF forecasts are highly skilled for large scale persistent line storms. However, detailed performance analysis of the algorithm has shown that in cases dominated by airmass storms, the algorithm occasionally performed poorly (Theriault et al., 2001). In this paper we describe the sources of error discovered in the TCWF algorithm during the Memphis 2000 performance evaluation, and describe recent enhancements designed to address these problems.
Summary
Over the past decade the United States has seen drastic increases in air traffic delays resulting in enormous economic loses. Analysis shows that more then 50% of air traffic delays are due to convective weather. In response the FAA has assembled scientific and engineering teams from MIT Lincoln Laboratory, NCAR...
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The 2001 demonstration of automated cloud forecast guidance products for San Francisco International Airport
May 13, 2002
Conference Paper
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10th Conf. on Aviation, Range, and Aerospace Meteorology (13th Conf. on Applied Climatology), 13-16 May 2002, pp. J99-J102.
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A system for providing cloud prediction guidance to aviation weather forecasters was demonstrated during the summer of 2001. The system was sponsored by the FAA, and developed by MIT Lincoln Laboratory in collaboration with SJSU, the University of Quebec at Montreal, Penn State University, and the Central Weather Service Unit (CWSU) at Oakland Center. Products were provided to forecasters at the CWSU, the NWS in Monterey, and the Weather Center at United Airlines. Real-time data are processed to support a display of weather graphics, and to provide input to a suite of four independent cloud forecast models developed specifically for the marine stratus application. The forecast models were run hourly each morning to provide updated forecasts during the evolution of cloud dissipation int he Bay area. As part of each update cycle, the four model forecasts were combined to provide a Consensus Forecast product. Weather observations and forecasts were provided to users on a web browser display.
Summary
A system for providing cloud prediction guidance to aviation weather forecasters was demonstrated during the summer of 2001. The system was sponsored by the FAA, and developed by MIT Lincoln Laboratory in collaboration with SJSU, the University of Quebec at Montreal, Penn State University, and the Central Weather Service Unit...
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