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Initial assessment of wind forecasts for Airport Acceptance Rate (AAR) and Ground Delay Program (GDP) planning

Published in:
MIT Lincoln Laboratory Report ATC-414

Summary

The planning and execution of the Airport Acceptance Rate (AAR) for major metroplex airports is a complex and critical function of traffic managers in the National Airspace System (NAS). Despite the importance of AAR planning, traffic managers currently have no widely available decision support to provide guidance for runway selection and the determination of a sustainable AAR. The AAR Decision Support Capability (AARDSC), currently under development as part of the Collaborative Air Traffic Management Technology Work Package 4 (CATMT WP4), will provide such guidance. This report provides an initial analysis of the impacts of surface winds and winds aloft on the key factors associated with the AAR (the selection of runway configuration and aircraft ground speed and spacing on final approach) and the capabilities of currently available weather forecasts to accurately predict those impacts. The report was limited in scope by the schedule and available resources, and is intended as a foundation for a comprehensive forecast assessment in follow-on work. Surface wind forecasts from the Terminal Aerodome Forecast (TAF) and numerical prediction models (the High Resolution Rapid Refresh [HRRR], Rapid Refresh [RAP] and Rapid Update Cycle [RUC], collectively described as "MODEL") were compared to observed winds gathered from METAR reports as Newark International Airport (EWR). TAF and METAR were compared for 639 days of operations from 2011-2013. MODEL forecasts and METAR were compared for 21 days of operation, 16 of which had Traffic Management Initiatives (TMI) in place to mitigate adverse weather impacts. Winds aloft were translated into several wind impact metrics. The impacts of winds aloft forecast errors were evaluated by comparing impact metrics calculated from MODEL forecasts with those calculated from analysis fields for the 21 case days. Forecasts were evaluated at horizons of 2, 4, 6, and 8 hours.
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Summary

The planning and execution of the Airport Acceptance Rate (AAR) for major metroplex airports is a complex and critical function of traffic managers in the National Airspace System (NAS). Despite the importance of AAR planning, traffic managers currently have no widely available decision support to provide guidance for runway selection...

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Dual-polarization challenges in weather radar requirements for multifunction phased array radar

Published in:
2013 IEEE Int. Symp. On Phased Array Systems and Technology, 15-18 October 2013.
Topic:
R&D group:

Summary

This paper summarizes the challenges in achieving (and even specifying) the antenna polarization accuracy requirements for the Multifunction Phased Array Radar (MPAR) and the progress that has been made towards meeting these requirements through demonstrations and theoretical investigations.
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Summary

This paper summarizes the challenges in achieving (and even specifying) the antenna polarization accuracy requirements for the Multifunction Phased Array Radar (MPAR) and the progress that has been made towards meeting these requirements through demonstrations and theoretical investigations.

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An applications architecture to support FAA wake turbulence mitigation systems development and deployment

Published in:
MIT Lincoln Laboratory Report ATC-412

Summary

The Wake Turbulence Program within the Federal Aviation Administration (FAA) is considering a number of new procedures for safely reducing the wake vortex spacing requirements between aircraft. One category of procedures investigates wind-dependent procedures, i.e., procedures that can be applied when wind conditions are expected to transport the wake from a lead aircraft away from the path of a trailing aircraft. MIT Lincoln Laboratory developed a Wind Forecast Algorithm (WFA) to determine when conditions allow these wind-dependent procedures to be available to traffic managers. The baseline WFA is used within the Wake Turbulence Mitigation for Departures (WTMD) system, which establishes spacing procedures for departures on closely spaced parallel runways. A number of new procedures are also under consideration, each of which will require a modification and/or expansion of the baseline WFA. With time, the volume and number of disparate data sources used in the development process has steadily increased to the point where the existing development environment has become cumbersome and inadequate. As a result, through support of the FAA Wake Turbulence Program, MIT Lincoln Laboratory has undergone a complete overhaul of the computer processing and storage architecture used for WFA development. This will serve two main purposes. First, it will greatly expedite the development process, which is highly iterative and requires increasingly large volumes of data. Second, an updated architecture design will allow for an expeditious transition of developmental systems into the operational environment within FAA's NextGen framework. A key focus of this report describes how the new design is sufficiently compatible and flexible to serve within this anticipated FAA framework. The unified application architecture and infrastructure being designed and implemented will support continuing development, playback requirements, and real-time deployments. This architecture is composed of several application components including a wind data extract-transform-loaf (ETL) application, the WFA algorithm, and a display interface to accomodate both the development process and for potential use within the FAA operational environment. The Wind-ETL application component acquires, processes, and archives wind data from a variety of NOAA-based hourly forecasts and airport-vicinity weather measurement equipment. This wind data is ingested by the WFA, which computes and disseminates its availability predictions to the WTMx Display application component, which archives these predictions and also allows for presentation to the airport tower supervisor via the WTMx display user interface decision support tool. This architecture is designed to be flexible to accepting new weather data feeds, scalable to the high bandwidth and processing and storage capabilities required, provide sufficient automation and self-healing capabilities, and portable to allow its introduction into alternate facility sites and its integration into other FAA software systems.
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Summary

The Wake Turbulence Program within the Federal Aviation Administration (FAA) is considering a number of new procedures for safely reducing the wake vortex spacing requirements between aircraft. One category of procedures investigates wind-dependent procedures, i.e., procedures that can be applied when wind conditions are expected to transport the wake from...

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Multifunction Phased Array Radar (MPAR): achieving Next Generation Surveillance and Weather Radar Capability

Published in:
J. Air Traffic Control, Vol. 55, No. 3, Fall 2013, pp. 40-7.

Summary

Within DOT, the FAA has initiated an effort known as the NextGen Surveillance and Weather Radar Capability (NSWRC) to analyze the need for the next generation radar replacement and assess viable implementation alternatives. One concept under analysis is multifunction radar using phased-array technology -- Multifunction Phased Array Radar or MPAR.
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Summary

Within DOT, the FAA has initiated an effort known as the NextGen Surveillance and Weather Radar Capability (NSWRC) to analyze the need for the next generation radar replacement and assess viable implementation alternatives. One concept under analysis is multifunction radar using phased-array technology -- Multifunction Phased Array Radar or MPAR.

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An assessment of the operational utility of a GOES lightning mapping sensor

Published in:
MIT Lincoln Laboratory Report NOAA-18A

Summary

This report evaluates the incremental operational benefits of a proposed Lightning Mapping Sensor (LMS) for NOAA's Geostationary Operational Environmental Satellites (GOES). If deployed, LMS would provide continuous, real-time surveillance of total lightning activity over large portions of the North and South American continents and surrounding oceans. In contrast to the current National Lightning Detection Network, LMS would monitor total lightning activity, including the dominant intracloud component which is estimated to occur with order of magnitude greater frequency than cloud-to-ground lightning and may occur ten minutes or more in advance of a storm's first ground flash.
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Summary

This report evaluates the incremental operational benefits of a proposed Lightning Mapping Sensor (LMS) for NOAA's Geostationary Operational Environmental Satellites (GOES). If deployed, LMS would provide continuous, real-time surveillance of total lightning activity over large portions of the North and South American continents and surrounding oceans. In contrast to the...

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Wind information requirements for NextGen applications phase 1: 4D-trajectory based operations (4D-TBO)

Published in:
MIT Lincoln Laboratory Report ATC-399

Summary

Accurate wind information is required to support some of the key applications envisioned for future air traffic concepts. A Wind Information Analysis Framework has been developed to assess wind information needs for different applications. The framework is described and then applied in a Four-Dimensional Trajectory Based Operations (4D-TBO) application using simplified versions of the framework's elements to demonstrate its utility. Realistic ranges of wind information accuracy in terms of wind forecast and Flight Management System wind representation errors are studied. Their impacts on 4D-TBO performance in terms of Required Time of Arrival compliance and fuel burn are presented. Interpretations of the findings to give insights on wind information requirements are provided, together with an outline of the planned next phase of the study to further refine the outputs.
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Summary

Accurate wind information is required to support some of the key applications envisioned for future air traffic concepts. A Wind Information Analysis Framework has been developed to assess wind information needs for different applications. The framework is described and then applied in a Four-Dimensional Trajectory Based Operations (4D-TBO) application using...

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Convective initiation forecasts through the use of machine learning methods

Published in:
11th Conf. on Artificial and Computational Intelligence and its Applications to the Environmental Sciences, 9 January 2013.

Summary

Storm initiation is a very challenging aspect of nowcasting. Rapidly forming storms that appear in areas of little to no pre-existing convection can pose a danger to aircraft, and have the potential to cause unforeseen delays in the national airspace system (NAS). As such, detection and prediction of the initial development of convective storms is critical to NAS operations and planning. The Corridor Integrated Weather System (CIWS) currently provides deterministic 0-2 hour storm forecasts over the NAS, and represents the 0-2 hour portion of the 0-8 hour deterministic CoSPA storm forecasts. CIWS includes a convective initiation (CI) module, however this module has difficulty initiating convection in areas of little or no pre-existing convection. In this study, we seek to improve the capabilities of the CI module using machine learning methods to detect regions of imminent convection and enhance the storm initiation to the 0-2 hour forecast. Improvements to the current CI detection capabilities will prove to be a benefit in the short term, as well in the longer term plans of the Federal Aviation Administration's (FAA) Next Generation Air Transportation System (NextGen). In order to improve the capabilities of the CI module in CIWS, data from a variety of sources are fused together to produce a forecast of CI. Data incorporated into the CI algorithm include: Satellite fields from NASA's Satellite Convective Analysis and Tracking (SATCAST), convective instability fields, and a collection of numerical models which includes NOAA's North America Rapid Refresh Ensemble Time Lag System (NARRE-TL), the Localized Aviation MOS Program (LAMP), Short Range Ensemble Forecasts (SREF), and High Resolution Rapid Refresh (HRRR) model forecasts. These fields are brought together in a machine learning framework to create a probabilistic model which is used to initiate new growth in the deterministic CIWS 0-2 hour forecast. A variety of machine learning classifiers, including logistic regression, neural networks, support vector machines, and random forests, are used to investigate which technique works best with the data available. The skill of this updated CI capability is being assessed over the summer of 2012 using multiple skill metrics including CSI, bias and fraction skill score.
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Summary

Storm initiation is a very challenging aspect of nowcasting. Rapidly forming storms that appear in areas of little to no pre-existing convection can pose a danger to aircraft, and have the potential to cause unforeseen delays in the national airspace system (NAS). As such, detection and prediction of the initial...

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Evaluation of Consolidated Storm Prediction for Aviation (CoSPA) 0-8 hour convective weather forecast using the airspace flow program blockage-based capacity forecast ("The Matrix")

Published in:
MIT Lincoln Laboratory Report ATC-385

Summary

The CoSPA 0-8 hour convective weather forecast provides deterministic forecast products that can be used by strategic traffic management planners, and can be readily translated into forecasts of aviation capacity impacts for use in automated decision support tools. An operational CoSPA prototype was evaluated at several FAA Air Traffic Control facilities during the summer of 2010. As part of this evaluation, CoSPA forecasts were translated into forecasts of capacity impacts on traffic flows through two Flow Constrained Areas (FCAA05 and FCAA08) commonly used to control arrival traffic into the highly congested northeastern United States. This report describes an objective and operationally relevant evaluation of the accurancy of CoSPA-based forecasts of FCA capacity.
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Summary

The CoSPA 0-8 hour convective weather forecast provides deterministic forecast products that can be used by strategic traffic management planners, and can be readily translated into forecasts of aviation capacity impacts for use in automated decision support tools. An operational CoSPA prototype was evaluated at several FAA Air Traffic Control...

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Convective weather avoidance modeling for low-altitude routes

Published in:
MIT Lincoln Laboratory Report ATC-376

Summary

Thunderstorms are a leading cause of delay in the National Airspace System (NAS), and significant research has been conducted to predict the areas pilots will avoid during a storm. An example of such research is the Convective Weather Avoidance Model (CWAM), which provides the likelihood of pilot deviation due to convective weather in a given area. This report extends the scope of CWAM to include low-altitude flights, which typically occur below the tops of convective weather and have slightly differentoperational constraints. In general, the set of low-altitude flights include short-hop routes and low-altitude escape routes used to reduce the impact of convective weather in the termnial area. For classification, low altitude flights are identified as either deviations or non-deviations, and the corresponding weather features are analyzed. Precipitation intensity is observed to be the best predictor of deviation in the low-altitude flight regime, as compared to the differenc ein altitude between the flight and the echo tops for en route flights. Additionally, the low-altitude CWAM performs better than the departure CWAM currently used in the Route Availability Planning Tool (RAPT) when tested on deterministic weather data.
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Summary

Thunderstorms are a leading cause of delay in the National Airspace System (NAS), and significant research has been conducted to predict the areas pilots will avoid during a storm. An example of such research is the Convective Weather Avoidance Model (CWAM), which provides the likelihood of pilot deviation due to...

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Estimation of potential IDRP benefits during convective weather SWAP

Published in:
MIT Lincoln Laboratory Report ATC-381

Summary

This document presents a preliminary analysis of potential departure delay reduction benefits in New York as the result of the use of the Integrated Departure Route Planning (IDRP) tool during convective severe weather avoidance programs (SWAP). The analysis is based on weather impact and air traffic data from operations between May and September 2010 in the New York metroplex region. Two methodologies were employed in the analysis: "flight pool" and "resource pool." In the flight pool methodology, individual flights with excessive taxi times were identified, and opportunities to find potential alternative reroutes using information that IDRP will provide were assessed. In the resource pool methodology, route impact minutes were tallied over several days, based on the judgment of a human analysis, and opportunities to recover capacity lost to route impacts via IDRP-identified reroutes were estimated. The flight pool methodology estimated that approximately 156 hours of delay could be saved through the use of IDRP over a full SWAP season. The resource pool methodology estimated that approximately 15% of capacity lost to convective weather impacts could be recovered via IDRP-based reroutes. It should be noted that the potential benefits are based on several assumptions that are described in detail in the text of the report. The estimation of delay savings due to reroute is also speculative. It is very difficult to ascertain when the assignment of a reroute actually makes use of underutilized capacity and when the reroute simply shifts the problem from one congested resource to another. Further research is needed to develop reliable metrics that can guide the assessment of reroute impacts on overall traffic management performance.
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Summary

This document presents a preliminary analysis of potential departure delay reduction benefits in New York as the result of the use of the Integrated Departure Route Planning (IDRP) tool during convective severe weather avoidance programs (SWAP). The analysis is based on weather impact and air traffic data from operations between...

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