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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Seismic Study of the Dynamics of the Solar Subsurface from SoHO Observations

In collaboration with Dr. Baudin, we have developed and refined the new observational methodology for local helioseismology known as time-distance analysis. Global helioseismology study the solar oscillations as a superposition of resonant modes, whose properties (mode frequencies) reflect the global structure of the sun (sound speed stratification, rotation rate, etc). In contrast, local helioseismology look at the solar oscillations as wave packets whose propagation will be affected by perturbations of the media sampled. These local perturbations (sound speed or velocity flows) will modify the propagation time, that in turn can be used as a diagnostic tool for a given region. From a data reduction perspective, the processing of solar dopplergrams that result in time-distance maps, i.e. propagation times as a function of distance between bounces at the surface, is radically different from the methodology used for global mode analysis. We have, in a first step, further develop the programs needed to carry out such analysis. We have then applied them to NMI data set, and explore the trade-off between various averaging and filtering approaches - steps required to improve the signal-to-noise ratio of correlation maps - and the resulting stability and precision of the fitted propagation times. While excessive averaging (whether over space, propagation distance, or time) will reduce the diagnostic potential of the method, insufficient averaging lead to unstable fits, or uncertainties so large as to hide the information we seek. In a second phase, we have developed the analysis methodology required to infer local properties from perturbation in time propagation. Namely, we have developed time-distance inversion techniques, with an emphasis on inferences of velocity flows from time anomalies. Note also that during the period covered by this grant, all the investigators on this proposal (i.e., Drs. Baudin, Eff-Darwich, Korzennik, and Noyes) took part in the organization of the SOHO 6 /GONG 99 Workshop: Structure and Dynamics of the Interior of the Sun and Sunlike Stars, held on June 1-4 1999 at the Boston Park Plaza Hotel in Boston, Massachusetts, USA. it was very well attended by more than 160 participants from 26 countries from all over the world. The proceedings were published in two volumes as ESA SP-418, with Sessions I-III in Volume 1, and Sessions IV-VI in Volume 2 (1,000 pages in total). The complete contents are also included in digital form on a CD-ROM included with Volume 1. This CD-ROM also contains additional multi-media material that complements some of the contributions.

Korzennik, Sylvain G.↗
NASA NTRS2015

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Spacecraft Systems↗
DOE OSTI2022

At least it is a dry cold: the global distribution of freeze–thaw and drought stress and the traits that may impart poly-tolerance in conifers

Abstract Conifers inhabit some of the most challenging landscapes where multiple abiotic stressors (e.g., aridity, freezing temperatures) often co-occur. Physiological tolerance to multiple stressors (‘poly-tolerance’) is thought to be rare because exposure to one stress generally limits responses to another through functional trade-offs. However, the capacity to exhibit poly-tolerance may be greater when combined abiotic stressors have similar physiological impacts, such as the disruption of hydraulic function imposed by drought or freezing. Here, we reviewed empirical data in light of theoretical expectations for conifer adaptations to drought and freeze–thaw cycles with particular attention to hydraulic traits of the stem and leaf. Additionally, we examined the commonality and spatial distribution of poly-stress along indices of these combined stressors. We found that locations with the highest values of our poly-stress index (PSi) are characterized by moderate drought and moderate freeze–thaw, and most of the global conifer distribution occupies areas of moderate poly-stress. Among traits examined, we found diverse responses to the stressors. Turgor loss point did not correlate with freeze–thaw or drought stress individually, but did with the PSi, albeit inverse to what was hypothesized. Leaf mass per area was more strongly linked with drought stress than the poly-stress and not at all with freeze–thaw stress. In stems, the water potential causing 50% loss of hydraulic conductivity became more negative with increasing drought stress and poly-stress but did not correlate with freeze–thaw stress. For these traits, we identified a striking lack of coverage for substantial portions of species ranges, particularly at the upper boundaries of their respective PSis, demonstrating a critical gap in our understanding of trait prevalence and plasticity along these stress gradients. Future research should investigate traits that confer tolerance to both freeze–thaw and drought stress in a wide range of species across broad geographic scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Structural Break and Causal Analyses of U.S. Corn Use for Ethanol and Other Corn Market Variables

The causal basis for many of the relationships in models used to estimate the indirect effects of U.S. biofuels on global agricultural markets has not been adequately established. This paper addresses this gap by examining causal interactions among corn market variables through which the indirect effects of U.S. corn use for ethanol would be transmitted. Specifically, structural break and causal analyses of U.S. corn supply, uses, trade, and price are performed using quarterly data for marketing years 1986 to 2017. The structural break analysis identifies three breaks in corn use for ethanol that reflect the policy-driven evolution of U.S. corn ethanol production and other market factors. The causality analysis finds that U.S. corn use for ethanol is not a driver of the corn price and net corn exports. Changes in corn supply and domestic corn use are found to be the key factors in accommodating the large increase in corn use for ethanol between 2003 and 2010. These results mean that common assumptions linking U.S. corn ethanol production to large reductions in corn availability and exports, and higher global corn prices merit reconsideration.

09 BIOMASS FUELS↗
NASA NTRS1998

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 68: Who is Managing Knowledge? The Implications for Knowledge Production and Management of Global Strategic Alliances in Knowledge Dependent Industries

Knowledge is the foundation upon which researchers build as they innovate. Innovation lies at the core of a state's or a firm's ability to survive in a competitive world. Indeed, some economic historians ever that technological innovation, not trade, is the engine to economic growth. Despite the centrality of knowledge to corporate success, analysts have only recently shown an interest in the "knowledge capital" or "intellectual capital" of the firm, often literally trying to assign a value to this resource.

Golich, Vicki L.↗
NASA NTRS2013

Tuning and Robustness Analysis for the Orion Absolute Navigation System

The Orion Multi-Purpose Crew Vehicle (MPCV) is currently under development as NASA's next-generation spacecraft for exploration missions beyond Low Earth Orbit. The MPCV is set to perform an orbital test flight, termed Exploration Flight Test 1 (EFT-1), some time in late 2014. The navigation system for the Orion spacecraft is being designed in a Multi-Organizational Design Environment (MODE) team including contractor and NASA personnel. The system uses an Extended Kalman Filter to process measurements and determine the state. The design of the navigation system has undergone several iterations and modifications since its inception, and continues as a work-in-progress. This paper seeks to show the efforts made to-date in tuning the filter for the EFT-1 mission and instilling appropriate robustness into the system to meet the requirements of manned space ight. Filter performance is affected by many factors: data rates, sensor measurement errors, tuning, and others. This paper focuses mainly on the error characterization and tuning portion. Traditional efforts at tuning a navigation filter have centered around the observation/measurement noise and Gaussian process noise of the Extended Kalman Filter. While the Orion MODE team must certainly address those factors, the team is also looking at residual edit thresholds and measurement underweighting as tuning tools. Tuning analysis is presented with open loop Monte-Carlo simulation results showing statistical errors bounded by the 3-sigma filter uncertainty covariance. The Orion filter design uses 24 Exponentially Correlated Random Variable (ECRV) parameters to estimate the accel/gyro misalignment and nonorthogonality. By design, the time constant and noise terms of these ECRV parameters were set to manufacturer specifications and not used as tuning parameters. They are included in the filter as a more analytically correct method of modeling uncertainties than ad-hoc tuning of the process noise. Tuning is explored for the powered-flight ascent phase, where measurements are scarce and unmodelled vehicle accelerations dominate. On orbit, there are important trade-off cases between process and measurement noise. On entry, there are considerations about trading performance accuracy for robustness. Process Noise is divided into powered flight and coasting ight and can be adjusted for each phase and mode of the Orion EFT-1 mission. Measurement noise is used for the integrated velocity measurements during pad alignment. It is also used for Global Positioning System (GPS) pseudorange and delta- range measurements during the rest of the flight. The robustness effort has been focused on maintaining filter convergence and performance in the presence of unmodeled error sources. These include unmodeled forces on the vehicle and uncorrected errors on the sensor measurements. Orion uses a single-frequency, non-keyed GPS receiver, so the effects due to signal distortion in Earth's ionosphere and troposphere are present in the raw measurements. Results are presented showing the efforts to compensate for these errors as well as characterize the residual effect for measurement noise tuning. Another robustness tool in use is tuning the residual edit thresholds. The trade-off between noise tuning and edit thresholds is explored in the context of robustness to errors in dynamics models and sensor measurements. Measurement underweighting is also presented as a method of additional robustness when processing highly accurate measurements in the presence of large filter uncertainties.

Holt, Greg N.↗
NASA NTRS1979

Shuttle Global Positioning System (GPS) system design study

The various integration problems in the Shuttle GPS system were investigated. The analysis of the Shuttle GPS link was studied. A preamplifier was designed since the Shuttle GPS antennas must be located remotely from the receiver. Several GPS receiver architecture trade-offs were discussed. The Shuttle RF harmonics and intermode that fall within the GPS receiver bandwidth were analyzed. The GPS PN code acquisition was examined. Since the receiver clock strongly affects both GPS carrier and code acquisition performance, a clock model was developed.

Nilsen, P. W.↗
DOE OSTI2025

Optimising the processing and storage of visibilities using lossy compression

The next-generation radio astronomy instruments are providing a massive increase in sensitivity and coverage, largely through increasing the number of stations in the array and the frequency span sampled. The two primary problems encountered when processing the resultant avalanche of data are the need for abundant storage and the constraints imposed by I/O, as I/O bandwidths drop significantly on cold storage. An example of this is the data deluge expected from the SKA Telescopes of more than 60 PB per day, all to be stored on the buffer filesystem. While compressing the data is an obvious solution, the impacts on the final data products are hard to predict. In this paper, we chose an error-controlled compressor – MGARD – and applied it to simulated SKA-Mid and real pathfinder visibility data, in noise-free and noise-dominated regimes. As the data have an implicit error level in the system temperature, using an error bound in compression provides a natural metric for compression. MGARD ensures the compression incurred errors adhere to the user-prescribed tolerance. To measure the degradation of images reconstructed using the lossy compressed data, we proposed a list of diagnostic measures, exploring the trade-off between these error bounds and the corresponding compression ratios, as well as the impact on science quality derived from the lossy compressed data products through a series of experiments. We studied the global and local impacts on the output images for continuum and spectral line examples. We found relative error bounds of as much as 10%, which provide compression ratios of about 20, have a limited impact on the continuum imaging as the increased noise is less than the image RMS, whereas a 1% error bound (compression ratio of 8) introduces an increase in noise of about an order of magnitude less than the image RMS. For extremely sensitive observations and for very precious data, we would recommend a 0.1% error bound with compression ratios of about 4. These have noise impacts two orders of magnitude less than the image RMS levels. At these levels, the limits are due to instabilities in the deconvolution methods. We compared the results to the alternative compression tool DYSCO, in both the impacts on the images and in the relative flexibility. MGARD provides better compression for similar error bounds and has a host of potentially powerful additional features.

Techniques: interferometric↗
DOE OSTI2020

Argonne’s global critical materials agent-based model (GCMat)

Several studies have identified rare earths as critical materials. Although reasonably abundant in the Earth’s crust, rare earths typically occur in low concentrations of mined ores. Processes for recovering rare earth concentrates from these ores are complex and capital intensive. Further, lead times for deposit development, licensing, and construction are long, with reports of 10- 15 years. China is a major player in the rare earths supply chain, both in production capacity and technology innovation. In 2017, China supplied more than 80% of global rare earth oxide demand. Rare earth elements (REEs) have unique magnetic, catalytic, and phosphorescent properties that significantly improve performance of a wide range of technologies. These technologies span aerospace, energy, telecommunications, electronics, transportation, defense, and other diverse applications. Consequently, disruptions in rare earth supply can have a significant societal impact. Estimating that impact requires understanding of the dynamics across the supply chain, from rare earth oxide extraction to end use application. This report documents Argonne’s Global Critical Materials model (GCMat), first described by Riddle et al. 2015. GCMat provides capabilities to explore supply chain dynamics and uncertainty under scenarios of demand growth or shrinkage, technology adoption, supply disruptions, and trade policies and mitigation strategies of new supply sources, product substitution, consumer thrifting, and stockpiling. Supply chain participants from rare earth mining through final demand are modeled as interacting agents who make market decisions independently as time progresses. Since the version documented in Riddle et al. 2015, GCMat has been expanded to cover additional REEs, derived products and supply chains that use these REEs, and includes new agent behaviors and modeling capabilities. Section 2 provides a summary of the GCMat model design, including the structure of the model and key assumptions, section 3 summarizes methods used for model calibration and sensitivity analysis, and section 4 provides examples of model results.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Business Case Evaluation of Gas Switching Reforming (GSR) Technology: A Promising Technology for Natural Gas Reforming with Integrated CO2 Capture

Hydrogen is essential in the transition to sustainable energy, and developing low-carbon production methods is a key research focus. Traditional steam methane reforming (SMR) dominates the hydrogen industry but contributes substantially to CO2 emissions. In response, Gas Switching Reforming (GSR) has emerged as a novel process that integrates carbon capture and utilizes process heat more efficiently. Unlike other reforming methods, GSR consolidates oxidation and reduction reactions within a single reactor, which minimizes external energy inputs and simplifies scaling. Like conventional steam methane reforming (SMR), GSR can be integrated with water-gas shift and pressure swing adsorption units for pure hydrogen production. This work presents a comprehensive business case analysis of GSR technology based on experimental results in Technology Readiness Level 3, Life Cycle Assessment (LCA) and Techno-Economic (TEA) evaluation incorporating ASPEN Plus process modeling considering different configurations and energy scenarios. The TEA incorporates data from kinetic experiments from various catalysts to evaluate the GSR process under various conditions. The goal of this work is to evaluate GSR’s potential to serve as a low-carbon alternative to SMR, focusing on global warming potential and additional impact categories to evaluate a wide spectrum of environmental impacts. Comparative assessments were conducted with SMR, chemical loop reforming (CLR), and proton exchange membrane (PEM) electrolysis to explore trade-offs across environmental metrics. The environmental impact assessment of this work encompasses the entire hydrogen production lifecycle from raw material extraction to plant decommissioning, using a cradle-to-gate boundary. Preliminary findings highlight that GSR, when integrated with low-carbon energy sources, could significantly reduce environmental impacts, making it a promising candidate for low-carbon hydrogen infrastructure. The insights from this business case evaluation aim to guide industry in scale-up and commercialization of this promising clean energy technology.

03 NATURAL GAS↗
DOE OSTI2025

QuadTune version 1: a regional tuner for global atmospheric models

When a new, better-formulated physical parameterization is introduced into a global atmospheric model, aspects of the global model solutions are sometimes degraded. Then, in order to use the new global model to address science questions, there is an incentive to restore its accuracy. Oftentimes this restoration is achieved by tuning of model parameter values. Unfortunately, the retuning process is expensive because characterizing the parameter dependence requires numerous time-consuming global simulations. To reduce the cost of tuning, this manuscript introduces a “poor man's” model tuner, “QuadTune”. QuadTune carves the globe into regions and approximates the model parameter dependence through the use of an uncorrelated quadratic emulator (i.e., response surface). The simplicity of the emulator reduces the required number of global model simulations and aids explainability of tuner behavior. Tuning removes parametric error but leaves behind model structural error. Structural error manifests itself as regional residual biases, such as stubborn biases and tuning trade-offs. To visualize these residual biases, QuadTune's software includes a set of diagnostic plots. This paper illustrates the use of the plots for characterizing residual biases with an example tuning problem.

Environmental sciences↗
NASA NTRS1993

Distribution of tropical tropospheric water vapor

Utilizing a conceptual model for tropical convection and observational data for water vapor, the maintenance of the vertical distribution of the tropical tropospheric water vapor is discussed. While deep convection induces large-scale subsidence that constrains the turbulent downgradient mixing to within the convective boundary layer and effectively dries the troposphere through downward advection, it also pumps hydrometeors into the upper troposphere, whose subsequent evaporation appears to be the major source of moisture for the large-scale subsiding motion. The development of upper-level clouds and precipitation from these clouds may also act to dry the outflow, thus explaining the low relative humidity near the tropopause. A one-dimensional model is developed to simulate the mean vertical structure of water vapor in the tropical troposphere. It is also shown that the horizontal variation of water vapor in the tropical troposphere above the trade-wind boundary layer can be explained by the variation of a moisture source that is proportional to the amount of upper-level clouds. Implications for the nature of water vapor feedback in global warming are discussed.

Sun, De-Zheng↗
NASA NTRS2004

The Impact of Current and Future Polar Orbiting Satellite Data on Numerical Weather Prediction at NASA/GSFC

The lack of adequate observational data continues to be recognized as a major factor limiting both atmospheric research and numerical prediction on a variety of temporal and spatial scales. Since the advent of meteorological satellites in the 1960's, a considerable research effort has been directed toward the design of space-borne meteorological sensors, the development of optimal methods for the utilization of these data, (and an assessment of the influence of existing satellite data and the potential influence of future satellite observations on numerical weather prediction. This has included both Observing System Experiments (OSEs) and Observing System Simulation Experiments (OSSEs). OSEs are conducted to evaluate the impact of specific observations or classes of observations on analyses and forecasts. While OSEs are performed with existing data, OSSEs are conducted to evaluate the potential for future observing systems to improve-NWP, as well as to evaluate trade-offs in observing system design, and to develop and test improved methods for data assimilation. At the conference, results from OSEs to evaluate satellite data sets that have recently become available to the global observing system, such as AIRS and Seawinds, and results from OSSEs to determine the potential impact of space-based lidar winds will be presented.

Atlas, Robert↗
DOE OSTI2024

A globally sampled high-resolution hand-labeled validation dataset for evaluating surface water extent maps

Effective monitoring of global water resources is increasingly critical due to climate change and population growth. Advancements in remote sensing technology, specifically in spatial, spectral, and temporal resolutions, are revolutionizing water resource monitoring, leading to more frequent and high-quality surface water extent maps using various techniques such as traditional image processing and machine learning algorithms. However, satellite imagery datasets contain trade-offs that result in inconsistencies in performance, such as disparities in measurement principles between optical (e.g., Sentinel-2) and radar (e.g., Sentinel-1) sensors and differences in spatial and spectral resolutions among optical sensors. Therefore, developing accurate and robust surface water mapping solutions requires independent validations from multiple datasets to identify potential biases within the imagery and algorithms. However, high-quality validation datasets are expensive to build, and few contain information on water resources. For this purpose, we introduce a globally sampled, high-spatial-resolution dataset labeled using 3 m PlanetScope imagery. Our surface water extent dataset comprises 100 images, each with a size of 1024×1024 pixels, which were sampled using a stratified random sampling strategy covering all 14 biomes. We highlighted urban and rural regions, lakes, and rivers, including braided rivers and coastal regions. We evaluated two surface water extent mapping methods using our dataset – Dynamic World, based on Sentinel-2, and the NASA IMPACT model, based on Sentinel-1. Dynamic World achieved a mean intersection over union (IoU) of 72.16 % and F1 score of 79.70 %, while the NASA IMPACT model had a mean IoU of 57.61 % and F1 score of 65.79 %. Performance varied substantially across biomes, highlighting the importance of evaluating models on diverse landscapes to assess their generalizability and robustness. Our dataset can be used to analyze satellite products and methods, providing insights into their advantages and drawbacks. Our dataset offers a unique tool for analyzing satellite products, aiding the development of more accurate and robust surface water monitoring solutions. The dataset can be accessed via https://doi.org/10.25739/03nt-4f29.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Shifting Trade-offs: Finding the Sustainable Nexus of Hydropower and Environmental Flows in the San Joaquin River Watershed, California

Environmental flow management in watersheds with multi-objective reservoirs is often presented as an additional constraint to an already strained and over-allocated stream system. Nevertheless, environmental flow legislation and regulatory policies are increasingly being developed and implemented globally. In California, USA, recent legislative and regulatory policies place environmental flows at the forefront of the state’s water management objectives; however, the increased reliance on hydropower to support climate change mitigation goals may complicate efforts on both issues. This study modelled alternative environmental flow strategies in the major tributaries to the San Joaquin River in California. Strategies included detailed water management rules for hydropower production, flood control, and water deliveries, and three methodological approaches to environmental flow releases: minimum instream flows (“baseline”) year-round, 40% of full natural flow (FNF) during the spring runoff season and minimum releases the remainder of the year, and functional flows year-round. Results show that environmental flow strategies affect downstream flow releases in each of the San Joaquin’s four sub-basins differently depending on infrastructure capacity, water management objectives, and hydrologic year types. While hydropower production was comparable or declined in the Stanislaus, Tuolumne, and Merced basins, functional flow and 40% FNF strategies increased hydropower production in the Upper San Joaquin basin by 11%. Uncontrolled spill of high flow events decreased when high flow releases were based on hydrologic cues rather than exclusively on flood storage capacity. Water deliveries were reduced in all years regardless of environmental flow strategy. The 40% FNF and functional flow strategies both increased water released to the river relative to baseline, but in different ways. The functional flow strategy allocated water in a holistic approach that enhanced ecological functions in all years, but particularly in moderate and wet years. In contrast, the 40% FNF strategy provided increased flows relative to baseline and some ecological benefit in dry years, but less ecological benefit in other years. This study shows that alternative environmental flow strategies will have different and important trade-offs for integrated water management, and may mutually benefit seemingly conflicting objectives.

13 HYDRO ENERGY↗
NASA NTRS1991

Autonomous rendezvous targeting techniques for national launch system application

The rendezvous targeting techniques that can be utilized to achieve autonomous guidance for delivering a cargo to Space Station Freedom (SSF) using the National Launch System's (NLS) Heavy Lift Launch Vehicle (HLLV) and the on-orbit Cargo Transfer Vehicle (CTV) are described. This capability is made possible by advancements in autonomous navigation (Global Positioning System - GPS) on-board the CTV and SSF as well as the new generation flight computers. How the HLLV launch window can be decoupled from the CTV phasing window is described. The performance trades that have to be made to determine the length of the launch window and the phasing window between the CTV and SSF are identified and recommendations made that affect mission timelines.

Lomas, James J.↗
NASA NTRSDate not supplied

Preliminary SnowSAR Results from SnowEx 2017

SnowEx 2017 was the first in a multi-year series of airborne remote sensing campaigns, designed to address gaps in snow retrieval techniques in preparation for a future snow satellite mission. A variety of sensor types were flown to collect multi-sensor airborne data. In combination with detailed ground truth, this multi-sensor dataset enables critical trade studies to determine optimum sensor-plus-model combinations for different snow conditions and confounding factors. Up to half of terrestrial snow-covered areas are forested, and forests are a major confounding factor for global snow retrievals. Therefore, the main focus of SnowEx 2017 was evaluating the performance of the various sensing techniques to retrieve snow water equivalent (SWE) under steadily increasing amounts of forest cover. The primary site of Grand Mesa, Colorado, USA was selected for its natural gradients of forest density and SWE with a minimum of other factors. Radar retrievals of SWE relying on volume scattering have been studied for three decades, using a variety of frequencies, with varying degrees of success. The most recent volume scattering algorithms have focused on using 2 to 3 frequencies and both co- and cross-polarizations in the 9—18 GHz range (X through Ku bands). As such, one of the primary SnowEx 2017 airborne sensors was a dual-band (X & Ku) radar, the SnowSAR. Earlier versions of SnowSAR were used in 2011 and 2012 campaigns in Finland as well as a 2013 campaign in Canada. For SnowEx 2017, SnowSAR was installed on a P-3 aircraft from the US Naval Research Laboratory. Challenges associated with the aircraft, the installation, schedule, and flying weather all contrived to limit the amount of data collected. However, months of painstaking processing has yielded data that should be of value to the original objectives of SnowEx 2017. This paper will describe in detail the SnowSAR data that were collected, and provide quality assessments of the backscatter coefficient in terms of date, time, location, frequency, polarization, snow conditions, overlap with ground truth sites, forest density, etc. The challenges as well as potential remedies/caveats will be described in order to help guide users and maximize exploitation of this valuable data.

airborne sensors↗
NASA NTRS2015

Simulation and Analysis of Technology and Operational Procedures to Reduce the Combined Effects of Emissions and Contrails

The development and evaluation of concepts and technology to support future air traffic management systems require a hierarchy of models ranging from real-time simulations to extensive field evaluations. Air traffic simulation models such as Airspace Concept Evaluation System, Center Tracon Automation System, Future Air traffic management Concept Evaluation Tool and others are used to design air traffic systems balancing the conflicting objectives of maximizing safety, meeting future demands for airports and airspace and increase efficiency of traffic flows in the presence of uncertain weather. The impact of aviation emissions and contrails on climate imposes another constraint on the design of aircraft and aviation operations. The understanding of the complex interaction between physical climate system, the carbon and other greenhouse gas emissions and aviation activity can be improved by the development of integrated assessment models that include emission and climate models together with air traffic simulations. The modeling of aircraft emissions and their interaction with each other to change the concentration levels of different gasses in the atmosphere and the resulting impact of the radiative forcing on the equilibrium of the Earth's atmosphere is complex and requires the use of coupled atmosphere-ocean general circulation models together with three-dimensional models of carbon cycle and chemistry of other non-CO2 greenhouse gases. These models are computationally intensive and unsuitable for studies involving the generation of multiple scenarios. Simple emission and climate models, based on the input-output relations of linear systems, capture the fundamental emission to climate impact behavior by careful selection of key variables and their dynamics. The impact of various greenhouse gases depends on the total concentration, effect per unit change in atmospheric concentration and the spatial distribution of the gas. All these quantities are influenced by the lifetime of the gas. The impact of a greenhouse gas depends on the interval of assessment, which may vary from a few decades to a few centuries. Climate metrics are aimed at providing a common scale to compare different greenhouse gases. If the metrics are to be used as a tool in developing and evaluating aviation operations, they should be transparent and easy to apply. Global Warming Potential and Aggregate Global Temperature Potential are some of the commonly used metrics. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability brings together metrics, which are useful in aviation operations together with metrics used in climate studies. The capability can be used to make trade-offs between extra fuel cost and reduction in climate impact. There is considerable uncertainty in our understanding of the radiative forcing associated with emissions and contrails. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails. It can also be used to evaluate the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA's Aviation Environmental Portfolio Management Tool for Impacts.

impact of aviation on the environment↗