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NASA NTRS2012

Comparison of TRMM 2A25 Products Version 6 and Version 7 with NOAA/NSSL Ground Radar-Based National Mosaic QPE

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem was addressed in a previous paper by comparison of 2A25 version 6 (V6) product with reference values derived from NOAA/NSSL's ground radar-based National Mosaic and QPE system (NMQ/Q2). The primary contribution of this study is to compare the new 2A25 version 7 (V7) products that were recently released as a replacement of V6. This new version is considered superior over land areas. Several aspects of the two versions are compared and quantified including rainfall rate distributions, systematic biases, and random errors. All analyses indicate V7 is an improvement over V6.

Kirstetter, Pierre-Emmanuel↗

NASA NTRS2013

Center-TRACON Automation System (CTAS) En Route Trajectory Predictor Requirements and Capabilities

This requirements framework document is designed to support the capture of requirements and capabilities for state-of-the-art trajectory predictors (TPs). This framework has been developed to assist TP experts in capturing a clear, consistent, and cross-comparable set of requirements and capabilities. The goal is to capture capabilities (types of trajectories that can be built), functional requirements (including inputs and outputs), non-functional requirements (including prediction accuracy and computational performance), approaches for constraint relaxation, and input uncertainties. The sections of this framework are based on the Common Trajectory Predictor structure developed by the FAA/Eurocontrol Cooperative R&D Action Plan 16 Committee on Common Trajectory Prediction. It is assumed that the reader is familiar with the Common TP Structure.1 This initial draft is intended as a first cut capture of the En Route TS Capabilities and Requirements. As such, it contains many annotations indicating possible logic errors in the CTAS code or in the description provided. It is intended to work out the details of the annotations with NASA and to update this document at a later time.

framework↗

NASA NTRS2015

Performance of a Discrete Wavelet Transform for Compressing Plasma Count Data and its Application to the Fast Plasma Investigation on NASA's Magnetospheric Multiscale Mission

Plasma measurements in space are becoming increasingly faster, higher resolution, and distributed over multiple instruments. As raw data generation rates can exceed available data transfer bandwidth, data compression is becoming a critical design component. Data compression has been a staple of imaging instruments for years, but only recently have plasma measurement designers become interested in high performance data compression. Missions will often use a simple lossless compression technique yielding compression ratios of approximately 2:1, however future missions may require compression ratios upwards of 10:1. This study aims to explore how a Discrete Wavelet Transform combined with a Bit Plane Encoder (DWT/BPE), implemented via a CCSDS standard, can be used effectively to compress count information common to plasma measurements to high compression ratios while maintaining little or no compression error. The compression ASIC used for the Fast Plasma Investigation (FPI) on board the Magnetospheric Multiscale mission (MMS) is used for this study. Plasma count data from multiple sources is examined: resampled data from previous missions, randomly generated data from distribution functions, and simulations of expected regimes. These are run through the compression routines with various parameters to yield the greatest possible compression ratio while maintaining little or no error, the latter indicates that fully lossless compression is obtained. Finally, recommendations are made for future missions as to what can be achieved when compressing plasma count data and how best to do so.

Particles↗

NASA NTRS2016

HESTIA Phase I Test Results: The Air Revitalization System

In any human spaceflight mission, a number of Environmental Control & Life Support System (ECLSS) technologies work together to provide the conditions astronauts need to live healthily, productively, and comfortably in space. In a long-duration mission, many of these ECLSS technologies may use materials supplied by In-Situ Resource Utilization (ISRU), introducing more interactions between systems. The Human Exploration Spacecraft Test-bed for Integration & Advancement (HESTIA) Project aims to create a test-bed to evaluate ECLSS and ISRU technologies and how they interact in a high-fidelity, closed-loop, human-rated analog habitat. Air purity and conditioning are essential components within any ECLSS and for HESTIA's first test they were achieved with the Air Revitalization System (ARS) described below. The ARS provided four essential functions to the test-bed chamber: cooling the air, removing humidity from the air, removing trace contaminants, and scrubbing carbon dioxide (CO2) from the air. In this case, the oxygen supply function was provided by ISRU. In the current configuration, the ARS is a collection of different subsystems. A fan circulates the air, while a condensing heat exchanger (CHX) pulls humidity out of the air. A Trace Contaminant Removal System (TCRS) filters the air of potentially harmful contaminants. Lastly, a Reactive Plastic Lithium Hydroxide (RP-LiOH) unit removes CO2 from the breathing air. During the HESTIA Phase I test in September 2015, the ARS and its individual components each functioned as expected, although further analysis is underway. During the Phase I testing and in prior bench-top tests, the energy balance of heat removed by the CHX was not equal to the cooling it received. This indicated possible instrument error and therefore recalibration of the instruments and follow-up testing is planned in 2016 to address the issue. The ARS was tested in conjunction with two other systems: the Human Metabolic Simulator (HMS) and the Electrolyzer. They behaved as anticipated as well. The HMS added humidity, CO2, and heat to the chamber while removing oxygen, and the Electrolyzer (an ISRU technology) added oxygen. The objective for HESTIA in 2015 was achieved: the creation of a high-fidelity test-bed for ECLSS and ISRU technologies. With the 'backbone' technologies installed, more technologies will be added to increase the analog habitat's fidelity over the next few years. The ARS was designed with this in mind, and as new technologies develop and mature, the strategic installation of the existing components will allow for them to be replaced with the new technologies.

Wright, Sarah E.↗

NASA NTRS2018

Toward Long-Term Aquatic Science Products from Heritage Landsat Missions

This paper aims at generating a long-term consistent record of Landsat-derived remote sensing reflectance (Rrs) products, which are central for producing downstream aquatic science products (e.g., concentrations of total suspended solids). The products are derived from Landsat-5 and Landsat-7 observations leading to Landsat-8 era to enable retrospective analyses of inland and nearshore coastal waters. In doing so, the data processing was built into the SeaWiFS Data Analysis System (SeaDAS) followed by vicariously calibrating Landsat-7 and -5 data using reference in situ measurements and near-concurrent ocean color products, respectively. The derived Rrs products are then validated using (a) matchups using the Aerosol Robotic Network (AERONET) data measured by in situ radiometers, i.e., AERONET-OC, and (b) ocean color products at select sites in North America. Following the vicarious calibration adjustments, it is found that the overall biases in Rrs products are significantly reduced. The root-mean-square errors (RMSE), however, indicate noticeable uncertainties due to random and systematic noise. Long-term (since 1984) seasonal Rrs composites over 12 coastal and inland systems are further evaluated to explore the utility of Landsat archive processed via SeaDAS. With all the qualitative and quantitative assessments, it is concluded that with careful algorithm developments, it is possible to discern natural variability in historic water quality conditions using heritage Landsat missions. This requires the changes in Rrs exceed maximum expected uncertainties, i.e., 0.0015 [1/sr], estimated from mean RMSEs associated with the matchups and intercomparison analyses. It is also anticipated that Landsat-5 products will be less susceptible to uncertainties in turbid waters with Rrs(660) > 0.004 [1/sr], which is equivalent of ~1.2% reflectance. Overall, end-users may utilize heritage Rrs products with "fitness-for-purpose" concept in mind, i.e., products could be valuable for one application but may not be viable for another. Further research should be dedicated to enhancing atmospheric correction to account for non-negligible near-infrared reflectance in CDOM-rich and extremely turbid waters.

Pahlevan, Nima↗

NASA NTRS1993

A Proposed Update to the Solar Irradiance Spectrum Used in LOWTRAN and MODTRAN

The calibrated upwelling radiance spectra measured by AVIRIS are increasingly being analyzed with radiative transfer codes. Analysis of AVIRIS data with the LOWTRAN and MODTRAN radiative transfer codes has led to indications of an error in the solar irradiance spectra used by these codes. This paper presents evidence for the error and a proposed update to the solar irradiance spectra used by LOWTRAN and MODTRAN.

AVIRIS↗

NASA NTRS2021

Sky-Scanning Sun-Tracking Airborne Radiometer (3STAR): Instrument Design, Flight Testing, and Tracking Performance

The Sky-Scanning, Sun-Tracking Airborne Radiometer (3STAR) adapts commercial radiometer technology developed for the ocean color research community to airborne measurement of spectrally resolved solar irradiance and sky radiance. These atmospheric observations are used to derive aerosol optical depth (AOD), supporting localized AOD inputs for atmospheric correction of satellite and airborne data over terrestrial and aquatic (including optically dark) targets. The ability to regionally “tune” atmospheric correction schemes with relevant spatial AOD supports constraining atmospheric correction of remote sensing reflectance. Very wide dynamic range has been achieved for multi-channel band-pass-filter-radiometers originally designed for deployment into the water column. By actively tracking and directly pointing to the Sun, the light attenuation by aerosol particles in the atmospheric column can be quantified. These measurements improve knowledge of atmospheric constituents and the atmospheric corrections required to improve remote sensing capabilities for interpreting reflectance measurements from the Earth surface. 3STAR incorporates a custom Sun-tracking/sky-scanning pointing head, a Sun-tracking camera, and a commercially available, cylindrical, 19-channel radiometer tube assembly. An accurate and responsive mount and tracking system has been developed and certified to NASA and Naval Air Systems Command (NAVAIR) airworthiness standards for deployment into the aircraft slipstream. Ground and flight testing indicate typical tracking errors of less than 0.1 degrees, well within the field of view of the radiometer as required to minimize measurement uncertainty from alignment error. Preliminary AOD measurements compare to within 0.013 with 15 measurements from an Aerosol Robotic Network (AERONET) Cimel instrument at 500 nm wavelength and low solar angle.

Atmosphere↗

NASA NTRS2021

Experimental Results and Interfacial Lift-off Model Predictions of Critical Heat Flux for Flow Boiling with Subcooled Inlet Conditions – In Preparation for Experiments Onboard the International Space Station

This study investigates critical heat flux (CHF) for subcooled flow boiling of n-Perfluorohexane based on results of pre-launch Earth-gravity Mission Sequence Tests (MSTs) of the Flow Boiling and Condensation Experiment (FBCE), which was launched to the International Space Station (ISS) in August 2021. CHF measurements were made in a rectangular channel having a 2.5 mm by 5 mm cross-section and a 114.6-mm long heated segment. Both single-sided and double-sided heating were tested in vertical upflow in Earth gravity for a variety of inlet conditions. The inlet subcooling was varied in the range of 0.4 – 32.0°C and encompassed both near-saturated and highly subcooled conditions. Experimental trends and high-speed video records were investigated to better understand the mechanism of CHF. Overall trends show CHF increases as flow rate and/or inlet subcooling are increased. Flow features from the events around CHF justify the applicability of the Interfacial Lift-off Model and the determination of limiting criteria for its application. The present experimental data are combined with prior databases for various flow orientations with respect to Earth gravity and microgravity data collected on parabolic flights. Predictions are made using the Interfacial Lift-off Model for this consolidated subcooled-inlet FBCE-CHF database. A heat utility ratio was included in the model to capture the effects of subcooling and corresponding thermodynamic non-equilibrium. An overall mean absolute error of 19.04% indicates good predictive capability of the model for both heating configurations, different gravity environments, and a wide range of inlet subcooling.

flow boiling↗

NASA NTRS2021

The Role of Fire in Global Forest Loss Dynamics

Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land-use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite-derived data for the 2003–2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire-related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire-related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire-related forest loss, with larger contributions in small clearings in interior tropical forests and human-dominated landscapes. Comparison to higher-resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental-scale estimates of fire-related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire-related and non-fire-related land-use change emissions in forested ecosystems.

Dan van Wees↗

NASA NTRS2024

Thermal Inspection of Low Emissivity Surfaces Using a Pulsed Light Emitting Diodes (PLED) Heat Source

Thermal inspections of a structure typically utilize a flash or quartz lamp heat source located on the same side of an infrared camera. The heat source provides light energy for heating while the infrared camera measures the surface transient temperature response. The inspection can be difficult for low emissivity surfaces for several reasons. First, the high intensity light can reflect off the surface and cause “burn-in” to the camera’s detector. The “burn-in” can take time for the sensors to recover and potentially damage the detector. Secondly, the heat source after pulsing, has a transient cool down component. The cool down component can be reflected and therefore superimposed over the structure’s thermal response which can cause an error (false defect indications) in the inspection. Lastly, the heat source is spectrally broad and therefore while heating, infrared components of the heat source can produce non-uniformity in the measured temperature field. Typically for the inspection of reflective surfaces, paint or other emissivity enhancing coatings are applied before inspection. In this paper, a pulsed light emitting diodes (PLED) heat source is used. The PLED heat source is spectrally narrow, contained within the visible band, and therefore not detectable by the infrared camera. The PLED heat source is configured to reduce any transient cool down components that could produce false defect indications. The PLED thermal inspections are compared to commercially available flash thermography inspections on unpainted aluminum samples with simulated corrosion and additively manufactured Ti-6AL-4V metal specimens.

thermal nondestructive evaluation↗

NASA NTRS2024

Thermal Inspection of Low Emissivity Surfaces Using a Pulsed Light Emitting Diodes (PLED) Heat Source

thermal nondestructive evaluation↗

NASA NTRS2023

Satellite Remote-Sensing Capability to Assess Tropospheric-Column Ratios of Formaldehyde and Nitrogen Dioxide: Case Study During the Long Island Sound Tropospheric Ozone Study 2018 (LISTOS 2018) Field Campaign

Satellite retrievals of tropospheric-column formaldehyde (HCHO) and nitrogen dioxide (NO 2 ) are frequently used to investigate the sensitivity of ozone (O 3 ) production to emissions of nitrogen oxides and volatile organic carbon compounds. This study inter-compared the systematic biases and uncertainties in retrievals of NO 2 and HCHO, as well as resulting HCHO–NO 2 ratios (FNRs), from two commonly applied satellite sensors to investigate O 3 production sensitivities (Ozone Monitoring Instrument, OMI, and TROPOspheric Monitoring Instrument, TROPOMI) using airborne remote-sensing data taken during the Long Island Sound Tropospheric Ozone Study 2018 between 25 June and 6 September 2018. Compared to aircraft-based HCHO and NO 2 observations, the accuracy of OMI and TROPOMI were magnitude-dependent with high biases in clean environments and a tendency towards more accurate comparisons to even low biases in moderately polluted to polluted regions. OMI and TROPOMI NO 2 systematic biases were similar in magnitude (normalized median bias, NMB = 5 %–6 %; linear regression slope ≈ 0.5–0.6), with OMI having a high median bias and TROPOMI resulting in small low biases. Campaign-averaged uncertainties in the three satellite retrievals (NASA OMI; Quality Assurance for Essential Climate Variables, QA4ECV OMI; and TROPOMI) of NO 2 were generally similar, with TROPOMI retrievals having slightly less spread in the data compared to OMI. The three satellite products differed more when evaluating HCHO retrievals. Campaign-averaged tropospheric HCHO retrievals all had linear regression slopes ∼0.5 and NMBs of 39 %, 17 %, 13 %, and 23 % for NASA OMI, QA4ECV OMI, and TROPOMI at finer (0.05° x 0.05°) and coarser (0.15° x 0.15°) spatial resolution, respectively. Campaign-averaged uncertainty values (root mean square error, RMSE) in NASA and QA4ECV OMI HCHO retrievals were ~9.0 x 10 15 molecules cm –2 (∼ 50 %–55 % of mean column abundance), and the higher-spatial-resolution retrievals from TROPOMI resulted in RMSE values ∼30 % lower. Spatially averaging TROPOMI tropospheric-column HCHO, along with NO 2 and FNRs, to resolutions similar to the OMI reduced the uncertainty in these retrievals. Systematic biases in OMI and TROPOMI NO 2 and HCHO retrievals tended to cancel out, resulting in all three satellite products comparing well to observed FNRs. However, while satellite-derived FNRs had minimal campaign-averaged median biases, unresolved errors in the indicator species did not cancel out in FNR calculations, resulting in large RMSE values compared to observations. Uncertainties in HCHO retrievals were determined to drive the unresolved biases in FNR retrievals.

Matthew S. Johnson↗

NASA NTRS1980

Proton upsets in LSI memories in space

Two types of large scale integrated dynamic random access memory devices were tested and found to be subject to soft errors when exposed to protons incident at energies between 18 and 130 MeV. These errors are shown to differ significantly from those induced in the same devices by alphas from an Am-241 source. There is considerable variation among devices in their sensitivity to proton-induced soft errors, even among devices of the same type. For protons incident at 130 MeV, the soft error cross sections measured in these experiments varied from 10 to the -8th to 10 to the -6th sq cm/proton. For individual devices, however, the soft error cross section consistently increased with beam energy from 18-130 MeV. Analysis indicates that the soft errors induced by energetic protons result from spallation interactions between the incident protons and the nuclei of the atoms comprising the device. Because energetic protons are the most numerous of both the galactic and solar cosmic rays and form the inner radiation belt, proton-induced soft errors have potentially serious implications for many electronic systems flown in space.

Mcnulty, P. J.↗

NASA NTRS1992

Crew decision making under stress

Flight crews must make decisions and take action when systems fail or emergencies arise during flight. These situations may involve high stress. Full-missiion flight simulation studies have shown that crews differ in how effectively they cope in these circumstances, judged by operational errors and crew coordination. The present study analyzed the problem solving and decision making strategies used by crews led by captains fitting three different personality profiles. Our goal was to identify more and less effective strategies that could serve as the basis for crew selection or training. Methods: Twelve 3-member B-727 crews flew a 5-leg mission simulated flight over 1 1/2 days. Two legs included 4 abnormal events that required decisions during high workload periods. Transcripts of videotapes were analyzed to describe decision making strategies. Crew performance (errors and coordination) was judged on-line and from videotapes by check airmen. Results: Based on a median split of crew performance errors, analyses to date indicate a difference in general strategy between crews who make more or less errors. Higher performance crews showed greater situational awareness - they responded quickly to cues and interpreted them appropriately. They requested more decision relevant information and took into account more constraints. Lower performing crews showed poorer situational awareness, planning, constraint sensitivity, and coordination. The major difference between higher and lower performing crews was that poorer crews made quick decisions and then collected information to confirm their decision. Conclusion: Differences in overall crew performance were associated with differences in situational awareness, information management, and decision strategy. Captain personality profiles were associated with these differences, a finding with implications for crew selection and training.

Orasanu, J.↗

NASA NTRS1984

Simulation of time-control procedures for the advanced air traffic control system

The problem of mixing four-dimensional (4D) equipped aircraft - aircraft equipped with on-board guidance systems that can predict and control the touchdown time of an aircraft to an accuracy of a few seconds throughout the descent - with unequipped aircraft in the terminal area has been investigated via a real-time air traffic control simulation study. The objective of this study was to examine the effect of time errors (at 120 n. mi. from touchdown) on touchdown time scheduling, and to develop efficient algorithms and procedures to null the initial time errors prior to reaching the final control sector (30 n. mi. from touchdown). Results indicate that initial random errors of up to + or - 2 min can be handled via a single speed advisory issued in the arrival control sector, and thus the time schedule is not disrupted.

Tobias, L.↗

NASA NTRS2006

Geolocation and Pointing Accuracy Analysis for the WindSat Sensor

Geolocation and pointing accuracy analyses of the WindSat flight data are presented. The two topics were intertwined in the flight data analysis and will be addressed together. WindSat has no unusual geolocation requirements relative to other sensors, but its beam pointing knowledge accuracy is especially critical to support accurate polarimetric radiometry. Pointing accuracy was improved and verified using geolocation analysis in conjunction with scan bias analysis. nvo methods were needed to properly identify and differentiate between data time tagging and pointing knowledge errors. Matchups comparing coastlines indicated in imagery data with their known geographic locations were used to identify geolocation errors. These coastline matchups showed possible pointing errors with ambiguities as to the true source of the errors. Scan bias analysis of U, the third Stokes parameter, and of vertical and horizontal polarizations provided measurement of pointing offsets resolving ambiguities in the coastline matchup analysis. Several geolocation and pointing bias sources were incfementally eliminated resulting in pointing knowledge and geolocation accuracy that met all design requirements.

Meissner, Thomas↗

NASA NTRS2017

Information Theoretic Evaluation of Satellite Soil Moisture Retrievals

Microwave radiometry has a long legacy of providing estimates of remotely sensed near surfacesoil moisture measurements over continental and global scales. A consistent assessment of theerrors and uncertainties associated with these retrievals is important for their effective utilization in modeling, data assimilation and end-use application environments. This article presents an evaluationof soil moisture retrieval products from AMSR-E, ASCAT, SMOS, AMSR2 and SMAPinstruments using information theory-based metrics. These metrics rely on time series analysis ofsoil moisture retrievals for estimating the measurement error, level of randomness (entropy) andregularity (complexity) of the data. The results of the study indicate that the measurement errors inthe remote sensing retrievals are significantly larger than that of the ground soil moisture measurements.The SMAP retrievals, on the other hand, were found to have reduced errors (comparable to Preprint submitted to Remote Sensing of Environment October 1, 2017those of in-situ datasets), particularly over areas with moderate vegetation. The SMAP retrievals also demonstrate high information content relative to other retrieval products, with higher levelsof complexity and reduced entropy. Finally, a joint evaluation of the entropy and complexity ofremotely sensed soil moisture products indicates that the information content of the AMSR-E, ASCAT,SMOS and AMSR2 retrievals is low, whereas SMAP retrievals show better performance. The use of information theoretic assessments is effective in quantifying the required levels of improvements needed in the remote sensing soil moisture retrievals to enhance their utility and information content.

Information theory↗

NASA NTRS1981

Ultimate limits to error probabilities for ionospheric models based on solar geophysical indices and how these compare with the state of the art

An ideal model based on a given set of geophysical indices is defined as a model that provides a least squares fit to the data set as a function of the indices considered. Satellite measurements of electron content for three stations at different magnetic latitudes were used to provide such data sets which were each fitted to the geophysical indices. The magnitude of the difference between the measured value and the derived equation for the data set was used to estimate the probability of making an error greater than a given magnitude for such an ideal model. Atmospheric Explorer C data is used to examine the causes of the fluctuations and suggestions are made about how real improvements can be made in ionospheric forecasting ability. Joule heating inputs in the auroral electrojets are related to the AL and AU magnetic indices. Magnetic indices based on the time integral of the energy deposited in the electrojets are proposed for modeling processes affected by auroral zone heating.

Nisbet, J. S.↗