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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

A-Train Based Observational Metrics for Model Evaluation in Extratropical Cyclones

Extratropical cyclones contribute most of the precipitation in the midlatitudes, i.e. up to 70 during winter in the northern hemisphere, and can generate flooding, extreme winds, blizzards and have large socio-economic impacts. As such, it is important that general circulation models (GCMs) accurately represent these systems so their evolution in a warming climate can be understood. However, there are still uncertainties on whether warming will increase their frequency of occurrence, their intensity and how much rain or snow they bring. Part of the issue is that models have trouble representing their strength, but models also have biases in the amount of clouds and precipitation they produce. This is caused by potential issues in various aspects of the models: convection, boundary layer, and cloud scheme to only mention a few. In order to pinpoint which aspects of the models need improvement for a better representation of extratropical cyclone precipitation and cloudiness, we will present A-train based observational metrics: cyclone-centered, warm and cold frontal composites of cloud amount and type, precipitation rate and frequency of occurrence. Using the same method to extract similar fields from the model, we will present an evaluation of the GISS-ModelE2 and the IPSL-LMDZ-5B models, based on their AR5 and more recent versions. The AR5 version of the GISS model underestimates cloud cover in extratropical cyclones while the IPSL AR5 version overestimates it. In addition, we will show how the observed CloudSat-CALIPSO cloud vertical distribution across cold fronts changes with moisture amount and cyclone strength, and test if the two models successfully represent these changes. We will also show how CloudSat-CALIPSO derived cloud type (i.e. convective vs. stratiform) evolves across warm fronts as cyclones age, and again how this is represented in the models. Our third process-based analysis concerns cumulus clouds in the post-cold frontal region and how their amount relates to the stability of the boundary layer. This test uses Aqua cloud and vertical atmospheric profiles and when applied to the model output can help assess the accuracy of the convection, boundary layer and cloud scheme.

Convection clouds↗
NASA NTRS2017

It's All Relative: A Validation of Radiation Quality Comparison Metrics

Historically, the relative biological effectiveness (RBE) has been calculated to quantify the difference between heavy ion and gamma ray radiation. The RBE is then applied to gamma ray data to predict the effects of heavy ions in humans. The RBE is an iso-effect dose-to-dose ratio which, due to its counterintuitive nature, has been commonly miscalculated as an iso-dose effect-to-effect ratio. A paper recently published by Shuryak et al described this second measure intentionally for the first time in 2017, referring to it as the radiation effects ratio (RER). In this study, we utilized simulations to test the ability of both the RBE and the RER to predict known heavy ion effects. RBEs and RERs were calculated using mouse data from Chang et al, and the ability of the RBE and RER to predict the heavy ion data from which they were calculated was verified. Statistical transformations often utilized during data analysis were applied to the gamma and heavy ion data to determine whether RBE and RER are each uniquely defined measures. Scale changes are expected when translating effects from mice to humans and between human populations; gamma and heavy ion data were transformed to represent potential scale changes. The ability of the RBE and RER to predict the transformed heavy ion data from the transformed gamma data was then tested. The RBE but not the RER was uniquely defined after all statistical transformations. The RBE correctly predicted the scale-transformed heavy ion data, while the RER did not. This presentation describes potential implications for both metrics in light of these findings.

Chappell, L. J.↗
NASA NTRS2016

Assessing Woody Vegetation Trends in Sahelian Drylands Using MODIS Based Seasonal Metrics

Woody plants play a major role for the resilience of drylands and in peoples' livelihoods. However, due to their scattered distribution, quantifying and monitoring woody cover over space and time is challenging. We develop a phenology driven model and train/validate MODIS (MCD43A4, 500m) derived metrics with 178 ground observations from Niger, Senegal and Mali to estimate woody cover trends from 2000 to 2014 over the entire Sahel. The annual woody cover estimation at 500 m scale is fairly accurate with an RMSE of 4.3 (woody cover %) and r(exp 2) = 0.74. Over the 15 year period we observed an average increase of 1.7 (+/- 5.0) woody cover (%) with large spatial differences: No clear change can be observed in densely populated areas (0.2 +/- 4.2), whereas a positive change is seen in sparsely populated areas (2.1 +/- 5.2). Woody cover is generally stable in cropland areas (0.9 +/- 4.6), reflecting the protective management of parkland trees by the farmers. Positive changes are observed in savannas (2.5 +/- 5.4) and woodland areas (3.9 +/- 7.3). The major pattern of woody cover change reveals strong increases in the sparsely populated Sahel zones of eastern Senegal, western Mali and central Chad, but a decreasing trend is observed in the densely populated western parts of Senegal, northern Nigeria, Sudan and southwestern Niger. This decrease is often local and limited to woodlands, being an indication of ongoing expansion of cultivated areas and selective logging.We show that an overall positive trend is found in areas of low anthropogenic pressure demonstrating the potential of these ecosystems to provide services such as carbon storage, if not over-utilized. Taken together, our results provide an unprecedented synthesis of woody cover dynamics in theSahel, and point to land use and human population density as important drivers, however only partially and locally offsetting a general post-drought increase.

Brandt, Martin↗
NASA NTRS2017

Metrics for NASA Aeronautics Research Mission Directorate (ARMD) Strategic Thrust 3B Vertical Lift Strategic Direction

The NASA Aeronautics Research Mission Directorate (ARMD) Strategic Implementation Plan details an ambitious plan for aeronautical research for the next quarter century and beyond. It includes a number of advanced technologies needed to address requirements of the overall aviation community (domestic and international), with an emphasis on safety, efficiency, operational flexibility, and alternative propulsion air transport options. The six ARMD Strategic Thrust Areas (STAs) represent a specific set of multi-decade research agendas for creating the global aviation improvements most in demand by the aviation service consumers and the general public. To provide NASA with a measurement of the preeminent value of these research areas, it was necessary to identify and quantify the measurable benefits to the aviation community from capabilities delivered by the research programs. This paper will describe the processes used and the conclusions reached in defining the principal metrics for ARMD Strategic Thrust Area 3B "Vertical Lift Strategic Direction."

Hochstetler, Ronald D.↗
NASA NTRS2017

Kepler Planet Reliability Metrics: Astrophysical Positional Probabilities for Data Release 25

This document is very similar to KSCI-19092-003, Planet Reliability Metrics: Astrophysical Positional Probabilities, which describes the previous release of the astrophysical positional probabilities for Data Release 24. The important changes for Data Release 25 are:1. The computation of the astrophysical positional probabilities uses the Data Release 25 processed pixel data for all Kepler Objects of Interest.2. Computed probabilities now have associated uncertainties, whose computation is described in x4.1.3.3. The scene modeling described in x4.1.2 uses background stars detected via ground-based high-resolution imaging, described in x5.1, that are not in the Kepler Input Catalog or UKIRT catalog. These newly detected stars are presented in Appendix B. Otherwise the text describing the algorithms and examples is largely unchanged from KSCI-19092-003.

APP↗
NASA NTRS2017

Oculomotor Behavior Metrics Change According to Circadian Phase and Time Awake

There is a need for non-invasive, objective measures to forecast performance impairment arising from sleep loss and circadian misalignment, particularly in safety-sensitive occupations. Eye-tracking devices have been used in some operational scenarios, but such devices typically focus on eyelid closures and slow rolling eye movements and are susceptible to the intrusion of head movement artifacts. We hypothesized that an expanded suite of oculomotor behavior metrics, collected during a visual tracking task, would change according to circadian phase and time awake, and could be used as a marker of performance impairment.

sleep deprivation↗
NASA NTRS2017

Daily Ambient Air Pollution Metrics for Five Cities: Evaluation of Data Fusion-Based Estimates and Uncertainties

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associatedcorrelations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM (sub10), PM (sub 2.5), and five PM (sub 2.5) components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, andmeteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM (sub 2.5). Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R-squared equal to 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM (sub 2.5)), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM (sub 10)). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

spatiotemporal fusion↗
NASA NTRS2018

NASA GMAO GEOS S2S Prediction System: Metrics, Post-Processing and Products

In this presentation we present an overview of the GMAO Sub-Seasonal and Seasonal Prediction System, current users and products, and methods for validation and evaluation of the system. Methods for evaluation include baseline evaluations metrics, the ability to simulate key modes of variability, and evaluation of new development areas.

Molod, Andrea M.↗
NASA NTRS2018

Uncertainty in Heart Rate Complexity Metrics Caused by R-Peak Perturbations

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.

Napoli, Nicholas J.↗
NASA NTRS2019

Space Radiation and Plasma Effects on Satellites and Aviation: Quantities and Metrics for Tracking Performance of Space Weather Environment Models

The Community Coordinated Modeling Center has been leading communitywide space science and space weather model validation projects for many years. These efforts have been broadened and extended via the newly launched International Forum for Space Weather Modeling Capabilities Assessment (https://ccmc.gsfc.nasa.gov/assessment/). Its objective is to track space weather models' progress and performance over time, a capability that is critically needed in space weather operations and different user communities in general. The Space Radiation and Plasma Effects Working Team of the afore mentioned International Forum works on one of the many focused evaluation topics and deals with five different subtopics (https://ccmc.gsfc.nasa.gov/assessment/topics/radiationall.php) and varieties of particle populations: Surface Charging from tens of eV to 50keV electrons and internal charging due to energetic electrons from hundreds keV to several MeVs. Single event effects from solar energetic particles and galactic cosmic rays (several MeV to TeV), total dose due to accumulation of doses from electrons (>100 keV) and protons (>1 MeV) in a broad energy range, and radiation effects from solar energetic particles and galactic cosmic rays at aviation altitudes. A unique aspect of the Space Radiation and Plasma Effects focus area is that it bridges the space environments, engineering, and user communities. The intent of the paper is to provide an overview of the current status and to suggest a guide for how to best validate space environment models for operational/engineering use, which includes selection of essential space environment and effect quantities and appropriate metrics.

Zheng, Yihua↗
NASA NTRS2020

PCB Quality Metrics that Drive Reliability (PD 18)

Risk based technology infusion is a deliberate and systematic process which defines the analysis and communication methodology by which new technology is applied and integrated into existing and new designs, identifies technology development needs based on trends analysis and facilitates the identification of shortfalls against performance objectives. This presentation at IPC Works Asia Aerospace 2019 Events provides the audience a snapshot of quality variations in printed wiring board quality, as assessed, using experiences in processing and risk analysis of PWB structural integrity coupons. The presentation will focus on printed wiring board quality metrics used, the relative type and number of non-conformances observed and trend analysis using statistical methods. Trend analysis shows the top five non-conformances observed across PWB suppliers, the root cause(s) behind these non-conformance and suggestions of mitigation plans. The trends will then be matched with the current state of the PWB supplier base and its challenges and opportunities. The presentation further discusses the risk based SMA approaches and methods being applied at GSFC for evaluating candidate printed wiring board technologies which promote the adoption of higher throughput and faster processing technology for GSFC missions.

Sood, Bhanu↗
NASA NTRSDate not supplied

Impact of ATD-2 Tools on Human Factors Metrics at Charlotte Douglas International Airport

New decision support tools were introduced at Charlotte Douglas International Airport (CLT) as part of NASA’s Air Traffic Demonstration 2 (ATD-2) project. ATD-2 is based on concepts which enable integrated arrival, departures, and surface (IADS) operations in a metroplex environment. Metrics on environmental benefits from ATD-2’s surface metering at CLT have shown impressive reductions in fuel consumption and CO2 emissions. Questions have remained on 1) the human factors impact of these new ATD-2 tools and surface metering and 2) the users’ perceptions of how these tools affect operations. To address these questions, post-bank surveys were designed for the four types of users of the new tools at CLT: Ramp Controllers, Ramp Managers, Tower Traffic Management Coordinators (TMCs) and Terminal Radar Approach Control (TRACON) TMCs. These surveys were administered during five-day blocks at three different times. Three types of banks were compared: No ATD-2 tool use, ATD-2 tool use, and ATD-2 use plus surface metering. Results indicate that higher workload or decreased situation awareness was not significantly associated with ATD-2 tool use more than no ATD-2 tool use--in fact for many users the opposite was true. Also, acceptability and operational efficiency measures indicate that the users did not perceive that banks with ATD-2 tools were significantly less acceptable or less efficient than banks without ATD-2 tools.

Airspace Technology Demonstration 2↗
NASA NTRSDate not supplied

The System Complexity Metric (SCM) Predicts System Costs and Failure Rates

A complex system has many parts and interactions and so is difficult to understand. Systems with higher complexity generally have higher costs and failure rates. A System Complexity Metric (SCM) is defined to be the sum of the number of nodes, N, in the system block diagram plus the number of one-way interactions, I, between the nodes. SCM = N + I. SCMs are easily determined by direct inspection of high level block diagrams of life support systems. System cost was found to be directly proportional to SCM. The system MTBF (Mean Time Before Failure) is the inverse of the system failure rate. MTBF = 1/f. The system MTBF was found to be proportional to SCM^(-2.2) for estimated preflight MTBFs. As is typical for systems that are not extensively tested and redesigned to eliminate unexpected failure modes, the life support flight failure rates were about ten times higher than the preflight estimates and the MTBFs one-tenth the preflight estimates. The system MTBF was found to be proportional to SCM^(-2.6) for observed flight MTBFs.

System compleity↗
NASA NTRS2020

Impact of ATD-2 Tools on Human Factor Metrics at Charlotte Douglas International Airport

New decision support tools were introduced at Charlotte Douglas International Airport (CLT) as part of NASA’s Air Traffic Demonstration 2 (ATD-2) project. ATD-2 is based on concepts which enable integrated arrival, departures, and surface (IADS) operations in a metroplex environment. Metrics on environmental benefits from ATD-2’s surface metering at CLT have shown impressive reductions in fuel consumption and CO2 emissions. Questions have remained on 1) the human factors impact of these new ATD-2 tools and surface metering and 2) the users’ perceptions of how these tools affect operations. To address these questions, post-bank surveys were designed for the four types of users of the new tools at CLT: Ramp Controllers, Ramp Managers, Tower Traffic Management Coordinators (TMCs) and Terminal Radar Approach Control (TRACON) TMCs. These surveys were administered during five-day blocks at three different times. Three types of banks were compared: No ATD-2 tool use, ATD-2 tool use, and ATD-2 use plus surface metering. Results indicate that higher workload or decreased situation awareness was not significantly associated with ATD-2 tool use more than no ATD-2 tool use--in fact for many users the opposite was true. Also, acceptability and operational efficiency measures indicate that the users did not perceive that banks with ATD-2 tools were significantly less acceptable or less efficient than banks without ATD-2 tools.

Bonny K Parke↗