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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Analysis of a Dynamic Multi-Track Airway Concept for Air Traffic Management

The Dynamic Multi-track Airways (DMA) Concept for Air Traffic Management (ATM) proposes a network of high-altitude airways constructed of multiple, closely spaced, parallel tracks designed to increase en-route capacity in high-demand airspace corridors. Segregated from non-airway operations, these multi-track airways establish high-priority traffic flow corridors along optimal routes between major terminal areas throughout the National Airspace System (NAS). Air traffic controllers transition aircraft equipped for DMA operations to DMA entry points, the aircraft use autonomous control of airspeed to fly the continuous-airspace airway and achieve an economic benefit, and controllers then transition the aircraft from the DMA exit to the terminal area. Aircraft authority within the DMA includes responsibility for spacing and/or separation from other DMA aircraft. The DMA controller is responsible for coordinating the entry and exit of traffic to and from the DMA and for traffic flow management (TFM), including adjusting DMA routing on a daily basis to account for predicted weather and wind patterns and re-routing DMAs in real time to accommodate unpredicted weather changes. However, the DMA controller is not responsible for monitoring the DMA for traffic separation. This report defines the mature state concept, explores its feasibility and performance, and identifies potential benefits. The report also discusses (a) an analysis of a single DMA, which was modeled within the NAS to assess capacity and determine the impact of a single DMA on regional sector loads and conflict potential; (b) a demand analysis, which was conducted to determine likely city-pair candidates for a nationwide DMA network and to determine the expected demand fraction; (c) two track configurations, which were modeled and analyzed for their operational characteristic; (d) software-prototype airborne capabilities developed for DMA operations research; (e) a feasibility analysis of key attributes in the concept design; (f) a near-term, transitional application of the DMA concept as a proving ground for new airborne technologies; and (g) conclusions. The analysis indicates that the operational feasibility of a national DMA network faces significant challenges, especially for interactions between DMAs and between DMA and non-DMA traffic. Provided these issues are resolved, sectors near DMAs could experience significant local capacity benefits.

Wing, David J.↗
NASA NTRS2010

A Minimax Network Flow Model for Characterizing the Impact of Slot Restrictions

This paper proposes a model for evaluating long-term measures to reduce congestion at airports in the National Airspace System (NAS). This model is constructed with the goal of assessing the global impacts of congestion management strategies, specifically slot restrictions. We develop the Minimax Node Throughput Problem (MINNTHRU), a multicommodity network flow model that provides insight into air traffic patterns when one minimizes the worst-case operation across all airports in a given network. MINNTHRU is thus formulated as a model where congestion arises from network topology. It reflects not market-driven airline objectives, but those of a regulatory authority seeking a distribution of air traffic beneficial to all airports, in response to congestion management measures. After discussing an algorithm for solving MINNTHRU for moderate-sized (30 nodes) and larger networks, we use this model to study the impacts of slot restrictions on the operation of an entire hub-spoke airport network. For both a small example network and a medium-sized network based on 30 airports in the NAS, we use MINNTHRU to demonstrate that increasing the severity of slot restrictions increases the traffic around unconstrained hub airports as well as the worst-case level of operation over all airports.

Lee, Douglas W.↗
NASA NTRS2017

Models of Sector Aircraft Counts in the Presence of Local, Regional and Airport Constraints

Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.

Kulkarni, Deepak↗
NASA NTRS2015

Methodology to Define Delivery Accuracy Under Current Day ATC Operations

In order to enable arrival management concepts and solutions in a NextGen environment, ground- based sequencing and scheduling functions have been developed to support metering operations in the National Airspace System. These sequencing and scheduling algorithms as well as tools are designed to aid air traffic controllers in developing an overall arrival strategy. The ground systems being developed will support the management of aircraft to their Scheduled Times of Arrival (STAs) at flow-constrained meter points. This paper presents a methodology for determining the undelayed delivery accuracy for current day air traffic control operations. This new method analyzes the undelayed delivery accuracy at meter points in order to understand changes of desired flow rates as well as enabling definition of metrics that will allow near-future ground automation tools to successfully achieve desired separation at the meter points. This enables aircraft to meet their STAs while performing high precision arrivals. The research presents a possible implementation that would allow delivery performance of current tools to be estimated and delivery accuracy requirements for future tools to be defined, which allows analysis of Estimated Time of Arrival (ETA) accuracy for Time-Based Flow Management (TBFM) and the FAA's Traffic Management Advisor (TMA). TMA is a deployed system that generates scheduled time-of-arrival constraints for en- route air traffic controllers in the US. This new method of automated analysis provides a repeatable evaluation of the delay metrics for current day traffic, new releases of TMA, implementation of different tools, and across different airspace environments. This method utilizes a wide set of data from the Operational TMA-TBFM Repository (OTTR) system, which processes raw data collected by the FAA from operational TMA systems at all ARTCCs in the nation. The OTTR system generates daily reports concerning ATC status, intent and actions. Due to its availability, ease of use, and vast collection of data across several airspaces it was determined that the OTTR data set would be the best method to utilize moving forward with this analysis. The particular variables needed for further analysis were determined along with the necessary OTTR reports, by working closely with the repository team additional analysis reports were developed that provided key ETA and STA information at the freeze horizon. One major benefit of the OTTR data is that using the correct reports the data across several airports could be analyzed over large periods of time. The OTTR data processes the TBFM data daily and is stored in various formats across several airspaces. This allowed us to develop our own parsing methods and raw data processing that would not rely on other computationally expensive tools that perform more in depth analysis of similar sets of data. The majority of this work consisted of the development of the ability to filter flights to create a subset of flights that could be considered undelayed, which is defined as a flight at the freeze horizon with an ETA and STA difference that was minimal or close to zero. This was a broad method that allowed the consideration of a large data set which consisted of all the traffic across a two month period in 2013, the hottest and coldest months, arriving into four airports: George Bush Intercontinental, Denver International, Los Angeles International, and Phoenix Sky Harbor.

delivery accuracy↗
NASA NTRS2003

Enabling CSPA Operations Through Pilot Involvement in Longitudinal Approach Spacing

Several major airports around the United States have, or plan to have, closely-spaced parallel runways. This project complemented current and previous research by examining the pilots ability to control their position longitudinally within their approach stream.This project s results considered spacing for separation from potential positions of wake vortices from the parallel approach. This preventive function could enable CSPA operations to very closely spaced runways. This work also considered how pilot involvement in longitudinal spacing could allow for more efficient traffic flow, by allowing pilots to keep their aircraft within tighter arrival slots then air traffic control (ATC) might be able to establish, and by maintaining space within the arrival stream for corresponding departure slots. To this end, this project conducted several research studies providing an analytic and computational basis for calculating appropriate aircraft spacings, experimental results from a piloted flight simulator test, and an experimental testbed for future simulator tests. The following sections summarize the results of these three efforts.

Battiste, Vernol↗
NASA NTRS2015

National Air Space (NAS) Data Exchange Environment Through 2060

NASA's NextGen Concepts and Technology Development (CTD) Project focuses on capabilities to improve safety, capacity and efficiency of the National Air Space (NAS). In order to achieve those objectives, NASA sought industry-Government partnerships to research and identify solutions for traffic flow management, dynamic airspace configuration, separation assurance, super density operations, airport surface operations and similar forward-looking air-traffic modernization (ATM) concepts. Data exchanges over NAS being the key enabler for most of these ATM concepts, the Sub-Topic area 3 of the CTD project sought to identify technology candidates that can satisfy air-to-air and air/ground communications needs of the NAS in the year 2060 timeframe. Honeywell, under a two-year contract with NASA, is working on this communications technology research initiative. This report summarizes Honeywell's research conducted during the second year of the study task.

National Air Space↗
NASA NTRS2013

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

data mining↗
NASA NTRS2005

Technology-enabled Airborne Spacing and Merging

Over the last several decades, advances in airborne and groundside technologies have allowed the Air Traffic Service Provider (ATSP) to give safer and more efficient service, reduce workload and frequency congestion, and help accommodate a critically escalating traffic volume. These new technologies have included advanced radar displays, and data and communication automation to name a few. In step with such advances, NASA Langley is developing a precision spacing concept designed to increase runway throughput by enabling the flight crews to manage their inter-arrival spacing from TRACON entry to the runway threshold. This concept is being developed as part of NASA s Distributed Air/Ground Traffic Management (DAG-TM) project under the Advanced Air Transportation Technologies Program. Precision spacing is enabled by Automatic Dependent Surveillance-Broadcast (ADS-B), which provides air-to-air data exchange including position and velocity reports; real-time wind information and other necessary data. On the flight deck, a research prototype system called Airborne Merging and Spacing for Terminal Arrivals (AMSTAR) processes this information and provides speed guidance to the flight crew to achieve the desired inter-arrival spacing. AMSTAR is designed to support current ATC operations, provide operationally acceptable system-wide increases in approach spacing performance and increase runway throughput through system stability, predictability and precision spacing. This paper describes problems and costs associated with an imprecise arrival flow. It also discusses methods by which Air Traffic Controllers achieve and maintain an optimum interarrival interval, and explores means by which AMSTAR can assist in this pursuit. AMSTAR is an extension of NASA s previous work on in-trail spacing that was successfully demonstrated in a flight evaluation at Chicago O Hare International Airport in September 2002. In addition to providing for precision inter-arrival spacing, AMSTAR provides speed guidance for aircraft on converging routes to safely and smoothly merge onto a common approach. Much consideration has been given to working with operational conditions such as imperfect ADS-B data, wind prediction errors, changing winds, differing aircraft types and wake vortex separation requirements. A series of Monte Carlo simulations are planned for the spring and summer of 2004 at NASA Langley to further study the system behavior and performance under more operationally extreme and varying conditions. This will coincide with a human-in-the-loop study to investigate the flight crew interface, workload and acceptability.

Hull, James↗
NASA NTRS1998

Terminal Air Flow Planning

The Center TRACON Automation System (CTAS) will be the basis for air traffic planning and control in the terminal area. The system accepts arriving traffic within an extended terminal area and optimizes the flow based on current traffic and airport conditions. The operational use of CTAS will be presented together with results from current operations.

Denery, Dallas G.↗
NASA NTRS2005

NASA Tech Briefs, September 2005

Topivs include: Diamond-Coated Carbon Nanotubes for Efficient Field Emission; Improved Anode Coatings for Direct Methanol Fuel Cells; Advanced Ablative Insulators and Methods of Making Them; PETIs as High-Temperature Resin-Transfer-Molding Materials; Stable Polyimides for Terrestrial and Space Uses; Low-Density, Aerogel-Filled Thermal-Insulation Tiles; High-Performance Polymers Having Low Melt Viscosities; Nonflammable, Hydrophobic Aerogel Composites for Insulation; Front-Side Microstrip Line Feeding a Raised Antenna Patch; Medium-Frequency Pseudonoise Georadar; Facilitating Navigation Through Large Archives; Program for Weibull Analysis of Fatigue Data; Comprehensive Micromechanics-Analysis Code - Version 4.0; Component-Based Visualization System; Software for Engineering Simulations of a Spacecraft; LabVIEW Interface for PCI-SpaceWire Interface Card; Path Following with Slip Compensation for a Mars Rover; International Space Station Electric Power System Performance Code-SPACE; Software for Automation of Real-Time Agents, Version 2; Software for Optimizing Plans Involving Interdependent Goals; Computing Gravitational Fields of Finite-Sized Bodies; Custom Sky-Image Mosaics from NASA's Information Power Grid; ANTLR Tree Grammar Generator and Extensions; Generic Kalman Filter Software; Alignment Stage for a Cryogenic Dilatometer; Rugged Iris Mechanism; Treatments To Produce Stabilized Aluminum Mirrors for Cryogenic Uses; Making AlNx Tunnel Barriers Using a Low-Energy Nitrogen-Ion Beam; Making Wide-IF SIS Mixers with Suspended Metal-Beam Leads; Sol-Gel Glass Holographic Light-Shaping Diffusers; Automated Counting of Particles To Quantify Cleanliness; Phase Correction for GPS Antenna with Nonunique Phase Center; Compact Infrasonic Windscreen; Broadband External-Cavity Diode Laser; High-Efficiency Solar Cells Using Photonic-Bandgap Materials; Generating Solid Models from Topographical Data; Computationally Lightweight Air-Traffic-Control Simulation; Spool Valve for Switching Air Flows Between Two Beds; Partial Model of Insulator/ Insulator Contact Charging; Asymmetric Electrostatic Radiation Shielding for Spacecraft; and Reusable Hybrid Propellant Modules for Outer-Space Transport.

Source record↗
NASA NTRS2006

Impact of Probabilistic Weather on Flight Routing Decisions

Flight delays in the United States have been found to increase year after year, along with the increase in air traffic. During the four-month period from May through August of 2005, weather related delays accounted for roughly 70% of all reported delays, The current weather prediction in tactical (within 2 hours) timeframe is at manageable levels, however, the state of forecasting weather for strategic (2-6 hours) timeframe is still not dependable for long-term planning. In the absence of reliable severe weather forecasts, the decision-making for flights longer than two hours is challenging. This paper deals with an approach of using probabilistic weather prediction for Traffic Flow Management use, and a general method using this prediction for estimating expected values of flight length and delays in the National Airspace System (NAS). The current state-of-the-art convective weather forecasting is employed to aid the decision makers in arriving at decisions for traffic flow and flight planing. The six-agency effort working on the Next Generation Air Transportation System (NGATS) have considered weather-assimilated decision-making as one of the principal foci out of a list of eight. The weather Integrated Product Team has considered integrated weather information and improved aviation weather forecasts as two of the main efforts (Ref. 1, 2). Recently, research has focused on the concept of operations for strategic traffic flow management (Ref. 3) and how weather data can be integrated for improved decision-making for efficient traffic management initiatives (Ref. 4, 5). An overview of the weather data needs and benefits of various participants in the air traffic system along with available products can be found in Ref. 6. Previous work related to use of weather data in identifying and categorizing pilot intrusions into severe weather regions (Ref. 7, 8) has demonstrated a need for better forecasting in the strategic planning timeframes and moving towards a probabilistic description of weather (Ref. 9). This paper focuses on. specified probability in a local region for flight intrusion/deviation decision-making. The process uses a probabilistic weather description, implements that in a air traffic assessment system to study trajectories of aircraft crossing a cut-off probability contour. This value would be useful for meteorologists in creating optimum distribution profiles for severe weather, Once available, the expected values of flight path and aggregate delays are calculated for efficient operations. The current research, however, does not deal with the issue of multiple cell encounters, as well as echo tops, and will be a topic of future work.

Sheth, Kapil↗
NASA NTRS2012

Air Traffic Management Research at NASA Ames

The Aviation Systems Division at the NASA Ames Research Center conducts leading edge research in air traffic management concepts and technologies. This overview will present concepts and simulation results for research in traffic flow management, safe and efficient airport surface operations, super density terminal area operations, separation assurance and system wide modeling and simulation. A brief review of the ongoing air traffic management technology demonstration (ATD-1) will also be presented. A panel discussion, with Mr. Davis serving as a panelist, on air traffic research will follow the briefing.

Davis, Thomas J.↗
NASA NTRS2017

Applying Graph Theory to Problems in Air Traffic Management

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it is shown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

precision arrival scheduling↗
NASA NTRS2008

A Performance Assessment of an Airborne Separation Assistance System Using Realistic Complex Traffic Flows

This paper presents the results from a study that investigates the performance of a tactical Airborne Separation Assistance System (ASAS) in en route airspace, under varying demand levels, with realistic traffic flows. The ASAS concept studied here allows flight crews of equipped aircraft to perform separation from other air traffic autonomously. This study addresses the tactical aspects of an ASAS using aircraft state data (i.e. position and velocity) to detect and resolve projected conflicts. In addition, use of a conflict prevention system helps ASAS-equipped aircraft avoid maneuvers that may cause new conflicts. ASAS-capable aircraft are equipped with satellite-based navigation and Automatic Dependent Surveillance Broadcast (ADS-B) for transmission and receipt of aircraft state data. In addition to tactical conflict detection and resolution (CD&R), a complete, integrated ASAS is likely to incorporate a strategic CD&R component with a longer look-ahead time, using trajectory intent information. A system-wide traffic flow management (TFM) component, located at the FAA command center helps aircraft to avoid regions of excessive traffic density and complexity. A Traffic Alert and Collision Avoidance System (TCAS), as used today is the system of last resort. This integrated approach avoids sole reliance on the use of the tactical CD&R studied here, but the tactical component remains a critical element of the complete ASAS. The focus of this paper is to determine to what extent the proposed tactical component of ASAS alone can maintain aircraft separation at demand levels up to three times that of current traffic. The study also investigates the effect of mixing ASAS-equipped aircraft with unequipped aircraft (i.e. current day) that do not have the capability to self-separate. Position and velocity data for unequipped aircraft needs to be available to ASASequipped. Most likely, for this future concept, state data would be available from instrument flight rules (IFR) aircraft, equipped with at least ADS-B transmission capability. The objective is to reduce the number of losses of separation to a minimum and investigate the limits of tactical-only CD&R. Thus, the objective is not, expressly, to achieve zero losses of separation with tactical ASAS because this is one component of an integrated ASAS.

Smith, Jeremy C.↗
NASA NTRS2002

Newly Enacted Intent Changes to ADS-B MASPS: Emphasis on Operations, Compatibility, and Integrity

Significant changes to the intent reporting structure in the Minimum Aviation System Performance Standards (MASPS) for Automatic Dependent Surveillance Broadcast (ADS-B) have recently been approved by RTCA Special Committee 186. The re-structured intent formats incorporate two major changes to the current MASPS (DO-242): addition of a Target State (TS) report that provides information on the horizontal and vertical targets for the current flight segment and replacement of the current Trajectory Change Point (TCP) and TCP+1 reports with Trajectory Change (TC) reports. TC reports include expanded information about TCPs and their connecting flight segments, in addition to making provisions for trajectory conformance elements. New intent elements are designed to accommodate a greater range of intent information, better reflect operational use and capabilities of existing and future aircraft avionics, and aid trajectory synthesis and conformance monitoring systems. These elements are expected to benefit near-term and future Air Traffic Management (ATM) applications, including separation assurance, local traffic flow management, and conformance monitoring. The current MASPS revision (DO-242A) implements those intent elements that are supported by current avionics standards and data buses. Additional elements are provisioned for inclusion in future MASPS revisions (beyond DO-242A) as avionics systems are evolved.

Barhydt, Richard↗
NASA NTRS2017

Development and Validation of an Automated Simulation Capability in Support of Integrated Demand Management

Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies that will inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. This paper also describes the initial validation of individual components of the automated simulation capability, and an example application comparing the performance of the IDM concept under two TBFM scheduling paradigms. The results and conclusions from this simulation compare closely to those from previous HITL simulations using similar scenarios, providing an initial validation of the automated simulation capability.

Integrated Demand Management↗
NASA NTRS2005

Remotely Operated Aircraft (ROA) Impact on the National Airspace System (NAS) Work Package: Automation Impacts of ROA's in the NAS

The purpose of this document is to analyze the impact of Remotely Operated Aircraft (ROA) operations on current and planned Air Traffic Control (ATC) automation systems in the En Route, Terminal, and Traffic Flow Management domains. The operational aspects of ROA flight, while similar, are not entirely identical to their manned counterparts and may not have been considered within the time-horizons of the automation tools. This analysis was performed to determine if flight characteristics of ROAs would be compatible with current and future NAS automation tools. Improvements to existing systems / processes are recommended that would give Air Traffic Controllers an indication that a particular aircraft is an ROA and modifications to IFR flight plan processing algorithms and / or designation of airspace where an ROA will be operating for long periods of time.

Source record↗
NASA NTRS2010

Predicting Airspace Capacity Impacts Using the Consolidated Storm Prediction for Aviation

Convective weather is currently the largest contributor to air traffic delays in the United States. In order to make effective traffic flow management decisions to mitigate these delays, weather forecasts must be made as early and as accurately as possible. A forecast product that could be used to mitigate convective weather impacts is the Consolidated Storm Prediction for Aviation. This product provides forecasts of cloud water content and convective top heights at 0- to 8-hour look-ahead times. The objective of this study was to examine a method of predicting the impact of convective weather on air traffic sector capacities using these forecasts. Polygons representing forecast convective weather were overlaid at multiple flight levels on a sector map to calculate the fraction of each sector covered by weather. The fractional volume coverage was used as the primary metric to determine convection s impact on sectors. Results reveal that the forecasts can be used to predict the probability and magnitude of weather impacts on sector capacity up to eight hours in advance.

Russell, Carl↗