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NASA NTRS2015

Characteristics of a Well Clear Definition and Alerting Criteria for Encounters Between UAS and Manned Aircraft in Class E Airspace

Unmanned aircraft systems (UAS) will be required to equip with a detect-and-avoid (DAA) system in order to satisfy the federal aviation regulations to remain well clear of other aircraft. For a DAA system to satisfy the requirement to stay well clear of other airborne traffic, a quantitative definition of well clear needs to be defined and evaluated. This study investigates the implications of UAS using proposed well clear definitions as a separation standard for conducting operations in the National Airspace System (NAS). The first analysis considers three well clear definitions and presents the relative state conditions of intruder aircraft as they encroach upon the well clear boundary. The second analysis focuses on the definition of the alerting criteria needed to inform the UAS operator of a potential loss of well clear. All analyses are conducted in a NAS-wide fast-time simulation environment using UAS aircraft models, proposed UAS missions, and historical air defense radar data to populate the background traffic operating under visual flight rules. The results presented in this study inform the safety case, requirements development, and the operational environment for DAA minimum operational performance standards.

Safety↗
NASA NTRS2015

Safety Related Considerations in Autonomy

In this talk I will describe NASA strategy and research efforts to provide safety assurance for increasingly autonomous systems used in aviation. In the near future, autonomy will play an important role in civil aviation, and its applications will range from vehicles and platforms (UAVs, transport-class, including supersonic to hypersonic, aircraft) to airspace operations, or health management systems. This infusion of autonomy is driven by a need for optimizing airspace operations to accommodate increasing traffic density (e.g., adaptive trajectory-based operations, autonomous tugs, close parallel runways, and dynamic separation assurance), reducing operation costs to ensure that US operators can compete with emergent countries, and enabling new business models (e.g., fire fighting, UAS-based package delivery and precise aerial photography). In essence virtually every component of the National Airspace System will become increasingly autonomous. Yet we need to do so in a safe manner and have techniques and processes in place to ensure the safety of the public. This talk describes NASA plans to address this problem

Air Traffic Management↗
NASA NTRS1997

A Cognitive System Model for Human/Automation Dynamics in Airspace Management

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.

Corker, Kevin M.↗
NASA NTRSDate not supplied

Preliminary Evaluation of National Campaign Scenarios for Urban Air Mobility

Urban Air Mobility and Advanced Air Mobility concepts offer a novel method for transportation of passengers and cargo. Whereas the concept may reduce congestion of roads and highways, it also introduces new complexity to the National Airspace in terms of management of such operations. NASA, in partnership with FAA and industry, approaches these complexities with research and development activities such as flight tests and simulations, in order to better understand the impacts and necessary mechanisms by which these operations could be integrated. One example of such research and development activity that NASA is conducting is the Advanced Air Mobility National Campaign effort. Flight-test scenarios were proposed as part of the National Campaign and tested in simulation for evaluation with industry partners prior to the Flight test. This simulation, exercised as an engineering evaluation, provided a data collection opportunity to better understand what iterations and modifications would be needed to successfully demonstrate the flight-test scenarios in order to mature the concept of Urban Air Mobility and Advanced Air Mobility.

urban air mobility↗
NASA NTRSDate not supplied

Preliminary Evaluation of National Campaign Scenarios for Urban Air Mobility

Urban Air Mobility and Advanced Air Mobility concepts offer a novel method for transportation of passengers and cargo. Whereas the concept may reduce congestion of roads and highways, it also introduces new complexity to the National Airspace in terms of management of such operations. NASA, in partnership with FAA and industry, approaches these complexities with research and development activities such as flight tests and simulations, in order to better understand the impacts and necessary mechanisms by which these operations could be integrated. One example of such research and development activity that NASA is conducting is the Advanced Air Mobility National Campaign effort. Flight-test scenarios were proposed as part of the National Campaign and tested in simulation for evaluation with industry partners prior to the Flight test. This simulation, exercised as an engineering evaluation, provided a data collection opportunity to better understand what iterations and modifications would be needed to successfully demonstrate the flight-test scenarios in order to mature the concept of Urban Air Mobility and Advanced Air Mobility.

Urban Air Mobility↗
NASA NTRS2014

Benefits Analysis of Multi-Center Dynamic Weather Routes

Dynamic weather routes are flight plan corrections that can provide airborne flights more than user-specified minutes of flying-time savings, compared to their current flight plan. These routes are computed from the aircraft's current location to a flight plan fix downstream (within a predefined limit region), while avoiding forecasted convective weather regions. The Dynamic Weather Routes automation has been continuously running with live air traffic data for a field evaluation at the American Airlines Integrated Operations Center in Fort Worth, TX since July 31, 2012, where flights within the Fort Worth Air Route Traffic Control Center are evaluated for time savings. This paper extends the methodology to all Centers in United States and presents benefits analysis of Dynamic Weather Routes automation, if it was implemented in multiple airspace Centers individually and concurrently. The current computation of dynamic weather routes requires a limit rectangle so that a downstream capture fix can be selected, preventing very large route changes spanning several Centers. In this paper, first, a method of computing a limit polygon (as opposed to a rectangle used for Fort Worth Center) is described for each of the 20 Centers in the National Airspace System. The Future ATM Concepts Evaluation Tool, a nationwide simulation and analysis tool, is used for this purpose. After a comparison of results with the Center-based Dynamic Weather Routes automation in Fort Worth Center, results are presented for 11 Centers in the contiguous United States. These Centers are generally most impacted by convective weather. A breakdown of individual Center and airline savings is presented and the results indicate an overall average savings of about 10 minutes of flying time are obtained per flight.

NAS based Benefits Analysis↗
NASA NTRSDate not supplied

The In-time Aviation Safety Management System Concept for Part 135 Operators

Transformations of the National Airspace System, such as envisioned with Advanced Air Mobility, will enable improvements for managing and assuring safety for Part 135 transportation of passengers and cargo. The purpose of this paper is to describe the In-time Aviation Safety Management System (IASMS) Concept of Operations (ConOps) and how its innovations such as using predictive analytics could benefit operators for risk management and safety assurance. The National Academies recommended development of an IASMS ConOps to secure a safe future NAS. Part 135 operators are currently not required to have a formal safety management system.

Kyle K. Ellis↗
NASA NTRS2017

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗
NASA NTRS2018

Operational Impact of the Baseline Integrated Arrival, Departure and Surface System Field Demonstration

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA (Federal Aviation Administration) and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

air traffic optimization↗
NASA NTRS2018

Narrowband Propagation Statistics of Aeronautical Mobile-Ground Links in the L- and C-Bands

To provide for the safe integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS), command and control (C2) links must be highly reliable. Hence, protected aviation spectrum is required to support such links for UAS that are integrated into controlled non-segregated airspace. For air-ground (i.e., non-satellite) links, protected aviation spectrum to support C2 links is available in the 960-1164 MHz (L) and 5030-5091 MHz (C) bands. The performance of any C2 system is critically dependent upon the characteristics of the air-ground (AG) channel. Therefore, as part of its UAS Integration in the NAS (UAS in the NAS) project, the U.S. National Aeronautics and Space Administration (NASA) performed a series of air-ground propagation flight tests to collect AG channel data for model development and analysis of potential C2 communications links capable of providing the required reliability. NASA's Glenn Research Center (GRC) conducted an extensive air-ground channel propagation measurement campaign (at altitude) for frequencies in the 960-977 MHz and 5030-5091 MHz ranges, for seven different terrain environments. The measurements were conducted in 2013, and produced the largest set of AG channel data ever gathered to date. This data was subsequently processed to develop models for the AG channel. The statistics collected enabled the derivation of channel model parameters for both narrowband and wideband channels. In order to make the propagation data widely available, the resulting narrowband statistics were processed and submitted to the International Telecommunications Union - Radiocommunication Sector (ITU-R) Study Group 3 Data Banks. Formats for data tables were developed, and tables of the aggregate narrowband propagation statistics for the seven ground site terrain environments were prepared, submitted to, and approved by, the ITU-R Study Group 3. This paper provides brief background on the measurement campaign, collection and processing of data, and development of the narrowband data tables. It further provides examples of the data and its use.

radiofrequency spectrum↗
NASA NTRS2018

Narrowband Propagation Statistics of Aeronautical Mobile-Ground Links in the L- and C-Bands

To provide for the safe integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS), command and control (C2) links must be highly reliable. Hence, protected aviation spectrum is required to support such links for UAS that are integrated into controlled non-segregated airspace. For air-ground (i.e., non-satellite) links, protected aviation spectrum to support C2 links is available in the 960-1164 MHz (L) and 5030-5091 MHz (C) bands. The performance of any C2 system is critically dependent upon the characteristics of the air-ground (AG) channel. Therefore, as part of its UAS Integration in the NAS (UAS in the NAS) project, the U.S. National Aeronautics and Space Administration (NASA) performed a series of air-ground propagation flight tests to collect AG channel data for model development and analysis of potential C2 communications links capable of providing the required reliability. NASA's Glenn Research Center (GRC) conducted an extensive air-ground channel propagation measurement campaign (at altitude) for frequencies in the 960-977 MHz and 5030-5091 MHz ranges, for seven different terrain environments. The measurements were conducted in 2013, and produced the largest set of AG channel data ever gathered to date. This data was subsequently processed to develop models for the AG channel. The statistics collected enabled the derivation of channel model parameters for both narrowband and wideband channels. In order to make the propagation data widely available, the resulting narrowband statistics were processed and submitted to the International Telecommunications Union Radiocommunication Sector (ITU-R) Study Group 3 Data Banks. Formats for data tables were developed, and tables of the aggregate narrowband propagation statistics for the seven ground site terrain environments were prepared, submitted to, and approved by, the ITU-R Study Group 3. This paper provides brief background on the measurement campaign, collection and processing of data, and development of the narrowband data tables. It further provides examples of the data and its use.

aircraft communications↗
NASA NTRS2012

NASA's UAS [Unmanned Aircraft Systems] Related Activities

NASA continues to operate all sizes of UAS in all classes of airspace both domestically and internationally. Missions range from highly complex operations in coordination with piloted aircraft, ground, and space systems in support of science objectives to single aircraft operations in support of aeronautics research. One such example is a scaled commercial transport aircraft being used to study recovery techniques due to large upsets. NASA's efforts to support routine UAS operations continued on several fronts last year. At the national level in the United States (U.S.), NASA continued its support of the UAS Executive Committee (ExCom) comprised of the Federal Aviation Administration (FAA), Department of Defense (DoD), Department of Homeland Security (DHS), and NASA. The committee was formed in recognition of the need of UAS operated by these agencies to access to the National Airspace System (NAS) to support operational, training, development and research requirements. Recommendations were received on how to operate both manned and unmanned aircraft in class D airspace and plans are being developed to validate and implement those recommendations. In addition the UAS ExCom has begun developing recommendations for how to achieve routine operations in remote areas as well as for small UAS operations in class G airspace. As well as supporting the UAS ExCom, NASA is a participant in the recently formed Aviation Rule Making Committee for UAS. This committee, established by the FAA, is intended to propose regulatory guidance which would enable routine civil UAS operations. As that effort matures NASA stands ready to supply the necessary technical expertise to help that committee achieve its objectives. By supporting both the UAS ExCom and UAS ARC, NASA is positioned to provide its technical expertise across the full spectrum of UAS airspace access related topic areas. The UAS NAS Access Project got underway this past year under the leadership of NASA s Aeronautics Research Mission Directorate. This project is focused on advancing the state of the art and providing research and analysis results in the areas of Separation Assurance, Communications (non-governmental spectrum allocation for UAS), Certification, and Human System Integration (ground control station design/pilot interfaces). The project is working in close coordination with the FAA and industry standards organizations (e.g. RTCA SC 203). More details on this project are provided in a separate article in this year's yearbook

Bauer, Jeffrey↗
NASA NTRSDate not supplied

NASA’s Secured Airspace for Urban Air Mobility (UAM)

The Urban Air Mobility (UAM) architecture is leveraged from the Unmanned Traffic Management (UTM) concept of operations. Within the UAM environment, UAM operators work collaboratively to manage aerial vehicles in the urban environment. Providers of Services for UAM (PSU), UAM operators, and Supplemental Data Service Providers (SDSP) provide services to support flight operations within that environment. As a recognized need, various views of UAM flight information are provided to the public and public safety entities. To accomplish this, among other goals, the Federal Aviation Administration (FAA) can coordinate flight information between the FAA controlled National Airspace System (NAS) and the UAM environments through the FAA-Industry Data Exchange Protocol (FIDXP). This concept of UAM proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical take-off and landing (VTOL) or short take-off and landing (STOL) aircraft to overcome increasing surface congestion. To garner the support of UAM and to realize its potential, an assurance of cybersecurity is critical for public acceptance. Understanding the various components communicating with one-another cybersecurity, like in other industries, has come to the forefront highlighting the need to protect these networks and systems from cyberattacks. With the planned growth and reach of UAM systems, it’s clear that the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. Consequently, as these threats evolve, the UAM cybersecurity capabilities must adapt to these changes as well. While learning is always the goal, the overall intent of this workshop is to make recommendations on the following: (1) how future UAM environments can be protected against cyber-attacks, and (2) what mechanisms should be put in place to detect attacks against UAM environments.

UAM↗
NASA NTRS2001

Operational Concept for the Smart Landing Facility (SLF)

The purpose of this document is to describe an operational concept for the Smart Landing Facility (SLF). The SLF is proposed as a component of the Small Aircraft Transportation System (SATS) and is envisioned to utilize Communication, Navigation, Surveillance and Air Traffic Management (CNS/ATM) technologies to support higher-volume air traffic operations in a wider variety of weather conditions than are currently possible at airports without an Air Traffic Control Tower (ATCT) or Terminal Radar Approach Control (TRACON). In order to accomplish this, the SLF will provide aircraft sequencing and separation within its terminal airspace (the SLF traffic area) and on the airport surface. The approach taken in this report is to first define and describe the SLF environment and the type of operations and aircraft that must be supported. Services currently provided by an ATCT and TRACON are reviewed and assembled into a set of high-level operational functions. A description of the applicable CNS/ATM technologies that have been deployed in the NAS (National Airspace System) or have been demonstrated to be operationally feasible is presented. A candidate SLF system concept that employs the CNS/ATM technologies is described. This is followed by SLF operational scenarios for minimally-equipped aircraft and for aircraft fully-equipped to make full use of SLF services. An assessment is made of the SLF technology and key research issues are identified.

Thompson, S. D.↗
NASA NTRSDate not supplied

A Blockchain Case Study for Urban Air Mobility Operational Intent

The next generation of aerial passenger and cargo transportation may leverage the concept of Urban Air Mobility (UAM). UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) or short takeoff and landing (STOL) aircraft to overcome increasing surface congestion [1]. The UAM concept leverages a decentralized service-based architecture for airspace solutions. Within the environment, UAM operators work collaboratively to manage aerial vehicles in the urban environment. Providers of Services for UAM (PSU), UAM operators, and Supplemental Data Service Providers (SDSP) provide services to support flight operations within the UAM environment. Also, various views of UAM flight information are provided to the public and public safety entities [2]. The Federal Aviation Administration (FAA) can coordinate flight information between the FAA controlled National Airspace System (NAS) and the UAM environments through the FAA-Industry Data Exchange Protocol (FIDXP). To realize the potential of UAM, an assurance of cybersecurity is critical for public acceptance. Cybersecurity has come to the forefront highlighting the need to protect these networks and systems from cyberattacks. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. As these threats evolve, the UAM cybersecurity capabilities must adapt to these changes as well [3]. This research focuses on the secure data exchange and storage of this decentralized UAM environment to address these challenges. This research intends to leverage a permissioned blockchain approach to address cybersecurity threats that may impact a UAM environment. Blockchain technologies can be used for tracking transactions and verifying negotiated agreements between stakeholders in the NAS environment. For example, the record of the submitted flight plan and the approved flight plan could be verified using the Blockchain-based immutable ledger.

UAM↗
NASA NTRS2015

System-Oriented Runway Management Concept of Operations

This document describes a concept for runway management that maximizes the overall efficiency of arrival and departure operations at an airport or group of airports. Specifically, by planning airport runway configurations/usage, it focuses on the efficiency with which arrival flights reach their parking gates from their arrival fixes and departure flights exit the terminal airspace from their parking gates. In the future, the concept could be expanded to include the management of other limited airport resources. While most easily described in the context of a single airport, the concept applies equally well to a group of airports that comprise a metroplex (i.e., airports in close proximity that share resources such that operations at the airports are at least partially dependent) by including the coordination of runway usage decisions between the airports. In fact, the potential benefit of the concept is expected to be larger in future metroplex environments due to the increasing need to coordinate the operations at proximate airports to more efficiently share limited airspace resources. This concept, called System-Oriented Runway Management (SORM), is further broken down into a set of airport traffic management functions that share the principle that operational performance must be measured over the complete surface and airborne trajectories of the airport's arrivals and departures. The "system-oriented" term derives from the belief that the traffic management objective must consider the efficiency of operations over a wide range of aircraft movements and National Airspace System (NAS) dynamics. The SORM concept is comprised of three primary elements: strategic airport capacity planning, airport configuration management, and combined arrival/departure runway planning. Some aspects of the SORM concept, such as using airport configuration management1 as a mechanism for improving aircraft efficiency, are novel. Other elements (e.g., runway scheduling, which is a part of combined arrival/departure runway scheduling) have been well studied, but are included in the concept for completeness and to allow the concept to define the necessary relationship among the elements. The goal of this document is to describe the overall SORM concept and how it would apply both within the NAS and potential future Next Generation Air Traffic System (NextGen) environments, including research conducted to date. Note that the concept is based on the belief that runways are the primary constraint and the decision point for controlling efficiency, but the efficiency of runway management must be measured over a wide range of space and time. Implementation of the SORM concept is envisioned through a collection of complementary, necessary capabilities collectively focused on ensuring efficient arrival and departure traffic management, where that efficiency is measured not only in terms of runway efficiency but in terms of the overall trajectories between parking gates and transition fixes. For the more original elements of the concept-airport configuration management-this document proposes specific air traffic management (ATM) decision-support automation for realizing the concept.

Lohr, Gary W.↗
NASA NTRSDate not supplied

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗
NASA NTRSDate not supplied

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗