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At least 613 records · Page 34

SeaWiFS Postlaunch Technical Report Series: The SeaBOARR-98 Field Campaign - Volume 3

This report documents the scientific activities during the first Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-Optical Algorithm Round-Robin (SeaBOARR-98) experiment, which took place from 5-17 July 1998, at the Acqua Alta Oceanographic Tower (AAOT) in the northern Adriatic Sea off the coast of Italy. The ultimate objective of the SeaBOARR activity is to evaluate the effect of different measurement protocols on bio-optical algorithms using data from a variety of field campaigns. The SeaBOARR-98 field campaign was concerned with collecting a high quality data set of simultaneous in-water and above-water radiometric measurements. The deployment goals documented in this report were to: a) use four different surface glint correction methods to compute water-leaving radiances, L W (lambda), from above-water data; b) use two different in-water profiling systems and three different methods to compute L W (lambda) from in-water data (one making measurements at a fixed distance from the tower, 7.5 m, and the other at variable distances up to 29 m away); c) use instruments with a common calibration history to minimize intercalibration uncertainties; d) monitor the calibration drift of the instruments in the field with a second generation SeaWiFS Quality Monitor (SQM-II), to separate differences in methods from changes in instrument performance; and e) compare the L W (lambda) values estimated from the above-water and in-water measurements. In addition to describing the instruments deployed and the data collected, a preliminary analysis of the data is presented, and the kind of follow-on work that is needed to completely assess the estimation of L W (lambda) from above-water and in-water measurements is discussed.

Zibordi, Giuseppe↗

Advanced Exploration Systems (AES) Logistics Reduction and Repurposing Project: Advanced Clothing Ground Study Final Report

All human space missions require significant logistical mass and volume that will become an excessive burden for long duration missions beyond low Earth orbit. The goal of the Advanced Exploration Systems (AES) Logistics Reduction & Repurposing (LRR) project is to bring new ideas and technologies that will enable human presence in farther regions of space. The LRR project has five tasks: 1) Advanced Clothing System (ACS) to reduce clothing mass and volume, 2) Logistics to Living (L2L) to repurpose existing cargo, 3) Heat Melt Compactor (HMC) to reprocess materials in space, 4) Trash to Gas (TTG) to extract useful gases from trash, and 5) Systems Engineering and Integration (SE&I) to integrate these logistical components. The current International Space Station (ISS) crew wardrobe has already evolved not only to reduce some of the logistical burden but also to address crew preference. The ACS task is to find ways to further reduce this logistical burden while examining human response to different types of clothes. The ACS task has been broken into a series of studies on length of wear of various garments: 1) three small studies conducted through other NASA projects (MMSEV, DSH, HI-SEAS) focusing on length of wear of garments treated with an antimicrobial finish; 2) a ground study, which is the subject of this report, addressing both length of wear and subject perception of various types of garments worn during aerobic exercise; and 3) an ISS study replicating the ground study, and including every day clothing to collect information on perception in reduced gravity in which humans experience physiological changes. The goal of the ground study is first to measure how long people can wear the same exercise garment, depending on the type of fabric and the presence of antimicrobial treatment, and second to learn why. Human factors considerations included in the study consist of the Institutional Review Board approval, test protocol and participants' training, and a web-based data collection questionnaire. Cardiovascular exercise was chosen as the activity in this experiment for its profuse sweating effect and because it is considered a more severe treatment applied to the clothes than every-day usage. Study garments were exercise T-shirts and shorts purchased from various vendors. Fabric construction, fabric composition, and finishing treatment were defined as the key variables. The study was divided into three balanced experiments: a cotton-polyester-wool (CPW) T-shirts study with 61 participants, a polyester-modacrylic-polyester/cocona (PMC) T-shirts study with 40 participants, and a shorts study with 70 participants. In the CPW study, the T-shirts were made of 100% cotton, or of 100% polyester or of 100% wool, and categorized into open and tight knit constructions. In the PMC study, the T-shirts were made of 100% polyester, or of 82% modacrylic, or of 95% polyester with 5% cocona fiber, without construction distinction. The shorts were made either of 100% cotton or of 100% polyester, and were knitted or woven. Some garments were treated with Bio-Protect 500 antimicrobial finish according to the experimental design. The data collected from the questionnaire included garment identification, level of exertion, duration of exercise session, number of exercise sessions, an ordinal preference scale for nine sensory elements, and reason for retiring a used garment. From the analysis of the combined CPW and PMC shirt studies, there are statistically significant differences among the mean lifetimes of various types of shirts. The exercise shirts with the longest mean lifetimes are untreated wool (600 minutes), treated cotton (526 minutes), and untreated modacrylic (515 minutes). From the combined CPW and PMC shirt studies, the most preferred material was untreated open-knit wool, which is one of the two materials that jointly were worn the longest, untreated wool, both open-knit and tight-knit. For the CP shorts study, there were no statistically significant differences in mean lifetimes of the exercise shorts at the 5% significance level due to the treatment combinations. There was therefore no justification to examine differences among levels of main effects or interactions. The preference for shorts was in this order: untreated woven polyester, untreated knitted polyester, untreated woven cotton, and treated knitted cotton. The nine preference scales were tabulated to determine the preference responses at the end of those exercise periods which were prior to the period when a garment was retired and a new garment was started. The assumption is that an unfavorable assessment of a garment leads to its retirement. The scent scale response was predominantly unfavorable at the end of the exercise period immediately prior to the exercise period when a new garment was started.

Byrne, Vicky↗

Large-amplitude photometric variations of Nereid

Photometric UVBRI and astrometric data on Nereid were collected in June, 1987 using the 0.9-m telescope and CCD camera at the Cerro Tololo Inter-American Observatory. Four astrometric positions and UVBRI reflectances spanning eight days were obtained. From these data, an unusual reflectance spectrum for Nereid was determined. Variability of Nereid was observed in all bandpasses, with an amplitude greater than 1.5 mag and a probable period of between 8 and 24 hr.

Schaefer, Martha W.↗

Empirical models of the latitudinal variations of Te and Ne in the ionosphere at solar maximum

A global spectral model of electron temperature and density is developed in which only the latitudinal variations observed in narrow altitude and local time bands are used. The measurements for this purpose are obtained during intervals that are short as compared to a season. By suppressing all variables except latitude the model can use 17th-order polynomials and generates a latitudinal structure that is similar to that described by the observational data. The treatment is designed to correct for the eccentricity and slow evolution of the data-collection satellite orbit so that small-scale features can be resolved. By comparing the results of a global model and the present latitudinal model to observational measurements of electron temperature and density it is shown that auroral-zone and midlatitude trough structures are not resolved in latitudinal models. The observational data can be used to study the response of electron density and temperature to solar EUV flux variations and geomagnetic activity.

Brace, L. H.↗

Radar Ocean Wave Spectrometer (ROWS) preprocessing program (PREROWS2.EXE). User's manual and program description

This Technical Memorandum is a user's manual with additional program documentation for the computer program PREROWS2.EXE. PREROWS2 works with data collected by an ocean wave spectrometer that uses radar (ROWS) as an active remote sensor. The original ROWS data acquisition subsystem was replaced with a PC in 1990. PREROWS2.EXE is a compiled QuickBasic 4.5 program that unpacks the recorded data, displays various variables, and provides for copying blocks of data from the original 8mm tape to a PC file.

Vaughn, Charles R.↗

Sensitive Procedures for Determining the Permeation Resistance of Chlorinated Polyethylene Against Liquid Propellants

The permeation resistance of chlorinated polyethylene (CPE) used in totally encapsulating chemical protective suits against the aerospace fuels hydrazine, monomethylhydrazine, and uns-dimethylhydrazine was determined by measuring the breakthrough time (BT) and time-averaged vapor transmission rate (VTR) using procedures consistent with ASTM F 739 and ASTM F 1383. Two exposure scenarios were simulated: a 2 hour (h) fuel vapor exposure, and a liquid fuel "splash" followed by a 2 h vapor exposure. To simulate internal suit pressure during operation, a positive differential pressure of 0.3 in. water (75 Pa) on the collection side of the permeation apparatus was used. Using the available data, a model was developed to estimate propellant concentrations inside an air-line fed, totally encapsulating chemical protective suit. Concentrations were calculated under simulated conditions of fixed vapor transmission rate, variable breathing air flow rate, and variable splash exposure area. Calculations showed that the maximum allowable permeation rates of hydrazine fuels through CPE were of the order of 0.05 to 0.08 ng/sq cm min for encapsulating suits with low breathing air flow rates (of the order of 5 scfm or 140 L min-1). Above these permeation rates, the 10 parts-per-billion (ppb) threshold limit value time-weighted average could be exceeded. To evaluate suit performance at 10 ppb threshold-limiting value/time-weighted average level concentrations, use of a sensitive analytical method such as cation exchange high performance liquid chromatography with amperometric detection was found to be essential. The analytical detection limit determines the lowest measurable VTR, which in turn governed the lowest per meant concentration that could be calculated inside the totally encapsulating chemical protective suit.

Waller, Jess M.↗

Twist Model Development and Results From the Active Aeroelastic Wing F/A-18 Aircraft

Understanding the wing twist of the active aeroelastic wing F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption and by using neural networks. These techniques produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.

Lizotte, Andrew↗

Twist Model Development and Results from the Active Aeroelastic Wing F/A-18 Aircraft

Understanding the wing twist of the active aeroelastic wing (AAW) F/A-18 aircraft is a fundamental research objective for the program and offers numerous benefits. In order to clearly understand the wing flexibility characteristics, a model was created to predict real-time wing twist. A reliable twist model allows the prediction of twist for flight simulation, provides insight into aircraft performance uncertainties, and assists with computational fluid dynamic and aeroelastic issues. The left wing of the aircraft was heavily instrumented during the first phase of the active aeroelastic wing program allowing deflection data collection. Traditional data processing steps were taken to reduce flight data, and twist predictions were made using linear regression techniques. The model predictions determined a consistent linear relationship between the measured twist and aircraft parameters, such as surface positions and aircraft state variables. Error in the original model was reduced in some cases by using a dynamic pressure-based assumption. This technique produced excellent predictions for flight between the standard test points and accounted for nonlinearities in the data. This report discusses data processing techniques and twist prediction validation, and provides illustrative and quantitative results.

Lizotte, Andrew M.↗

Evaluation of Different MODIS AOD Retrieval Algorithms for PM (sub 2.5) Estimation in the Western, Midwestern and Southeastern United States with Implications for Public Health

This study was part of the research activities of the Center for Applied Atmospheric Research and Education (CAARE) funded by the NASA MUREP (Minority University Research and Education Project) Institutional Research Opportunity (MIRO) Program. Satellite measurements of Aerosol Optical Depth (AOD) have been shown to be correlated with ground measurements of fine particulate matter less than 2.5 microns PM (sub 2.5), which in turn has been linked to respiratory and heart diseases. The strength of the correlation between AOD and PM (sub 2.5) varies for different AOD retrieval algorithms and geographic regions. We evaluated several Moderate Resolution Imaging Spectrometer (MODIS) AOD products from different satellites (Aqua vs. Terra), retrieval algorithms (Dark Target versus Deep Blue), Collections (5.1 versus 6) and spatial resolutions (10-kilometers versus 3-kilometers) for cities in the Western, Midwestern and Southeastern U.S. We developed and validated PM (sub 2.5) prediction models using remotely-sensed AOD data, which were improved by incorporating meteorological variables (temperature, relative humidity, precipitation, wind speed, and wind direction) from the North American Land Data Assimilation System Phase 2 (NLDAS-2). Adding these meteorological data significantly improved the predictive power of all the PM (sub 2.5) models, especially in the Western U.S. Temperature, relative humidity and wind speed were the most significant meteorological variables throughout the year in the Western U.S. Wind speed was the most significant meteorological variable for the cold season while temperature was the most significant variable for the warm season in the Midwestern and Southeastern U.S. Our study re-establishes the connection between PM (sub 2.5) and public health concerns including respiratory and cardiovascular diseases (asthma, high blood pressure, coronary heart disease, heart attack, and stroke). Using PM (sub 2.5) data and health data from the Centers for Disease Control and Prevention (CDC)'s Behavioral Risk Factor Surveillance System (BRFSS), our statistical analysis showed that heart attack and stroke occurrences had the strongest correlations with PM (sub 2.5).

Environmental Public Health↗

Search for Transient Gravitational Waves in Coincidence with Short-Duration Radio Transients During 2007-2013

We present an archival search for transient gravitational-wave bursts in coincidence with 27 single-pulse triggers from Green Bank Telescope pulsar surveys, using the LIGO (Laser Interferometer Gravitational Wave Observatory), Virgo (Variability of Solar Irradiance and Gravity Oscillations) and GEO (German-UK Interferometric Detector) interferometer network. We also discuss a check for gravitational-wave signals in coincidence with Parkes fast radio bursts using similar methods. Data analyzed in these searches were collected between 2007 and 2013. Possible sources of emission of both short-duration radio signals and transient gravitational-wave emission include star quakes on neutron stars, binary coalescence of neutron stars, and cosmic string cusps. While no evidence for gravitational-wave emission in coincidence with these radio transients was found, the current analysis serves as a prototype for similar future searches using more sensitive second-generation interferometers.

Abbott, B. P.↗

Development of Increasingly Autonomous Traffic Data Manager Using Pilot Relevancy and Ranking Data

NASA's Safe Autonomous Systems Operations (SASO) project goal is to define and safely enable all future airspace operations by justifiable and optimal autonomy for advanced air, ground, and connected capabilities. This work showcases how Increasingly Autonomous Systems (IAS) could create operational transformations beneficial to the enhancement of civil aviation safety and efficiency. One such IAS under development is the Traffic Data Manager (TDM). This concept is a prototype 'intelligent party-line' system that would declutter and parse out non-relevant air traffic, displaying only relevant air traffic to the aircrew in a digital data communications (Data Comm) environment. As an initial step, over 22,000 data points were gathered from 31 Airline Transport Pilots to train the machine learning algorithms designed to mimic human experts and expertise. The test collection used an analog of the Navigation Display. Pilots were asked to rate the relevancy of the displayed traffic using an interactive tablet application. Pilots were also asked to rank the order of importance of the information given, to better weight the variables within the algorithm. They were also asked if the information given was enough data, and more importantly the "right" data to best inform the algorithm. The paper will describe the findings and their impact to the further development of the algorithm for TDM and, in general, address the issue of how can we train supervised machine learning algorithms, critical to increasingly autonomous systems, with the knowledge and expertise of expert human pilots.

Le Vie, Lisa R.↗

Evaluation of GEOS-Simulated L-Band Microwave Brightness Temperature using Aquarius Observations over Non-Frozen Land across North America

L-band brightness temperature (T(sub b)) is one of the key remotely-sensed variables that provides information regarding surface soil moisture conditions. In order to harness the information in T(sub b) observations, a radiative transfer model (RTM) is investigated for eventual inclusion into a data assimilation framework. In this study, T(sub b) estimates from the RTM implemented in the NASA Goddard Earth Observing System (GEOS) were evaluated against the nearly four-year record of daily T(sub b) observations collected by L-band radiometers onboard the Aquarius satellite. Statistics between the modeled and observed T(sub b) were computed over North America as a function of soil hydraulic properties and vegetation types. Overall, statistics showed good agreement between the modeled and observed T(sub b) with a relatively low, domain-average bias (0.79 K (ascending) and -2.79 K (descending)), root mean squared error (11.0 K (ascending) and 11.7 K (descending)), and unbiased root mean squared error (8.14 K (ascending) and 8.28 K (descending)). In terms of soil hydraulic parameters, large porosity and large wilting point both lead to high uncertainty in modeled T(sub b) due to the large variability in dielectric constant and surface roughness used by the RTM. The performance of the RTM as a function of vegetation type suggests better agreement in regions with broadleaf deciduous and needleleaf forests while grassland regions exhibited the worst accuracy amongst the five different vegetation types.

L-band radiometry↗

An Assessment of the Ability of Potential Space-Borne Instruments to Resolve Spatial and Temporal Variability of Atmospheric Carbon Dioxide

Mounting concern regarding the possibility that increasing carbon dioxide concentrations will initiate climate change has stimulated interest in the feasibility of measuring CO2 mixing ratios from satellites. Currently, the most comprehensive set of atmospheric CO2 data is from the NOAA CMDL cooperative air sampling network, consisting of more than 40 sites where flasks of air are collected approximately weekly. Sporadic observations in the troposphere and stratosphere from airborne in situ and flask samplers are also available. Although the surface network is extensive, there is a dearth of data in the Southern Hemisphere and most of the stations were intentionally placed in remote areas, far from major sources. Sufficiently precise satellite observations with adequate spatial and temporal resolution would substantially increase our knowledge of the atmospheric CO2 distribution and would undoubtedly lead to improved understanding of the global carbon budget. We use a 3-D chemical transport model to investigate the ability of potential satellite instruments with a variety of orbits, horizontal resolution and vertical weighting functions to capture the variation in the modeled CO2 fields. The model is driven by analyzed winds from the Goddard Data Assimilation Office. Simulated CO2 fields are compared with existing surface and aircraft data, and the effects of the model convection scheme and representation of the planetary boundary layer are considered.

Andrews, Arlyn E.↗

An Assessment of the Ability of Potential Spaceborne Instruments to Resolve Spatial and Temporal Variability of Atmospheric Carbon Dioxide

Mounting concern regarding the possibility that increasing carbon dioxide concentrations will initiate climate change has stimulated interest in the feasibility of measuring CO2 mixing ratios from satellites. Currently, the most comprehensive set of atmospheric CO2 data is from the NOAA CMDL cooperative air sampling network, consisting of more than 40 sites where flasks of air are collected approximately weekly. Sporadic observations in the troposphere and stratosphere from airborne in situ and flask samplers are also available. Although the surface network is extensive, there is a dearth of data in the Southern Hemisphere and most of the stations were intentionally placed in remote areas, far from major sources. Sufficiently precise satellite observations with adequate spatial and temporal resolution would substantially increase our knowledge of the atmospheric CO2 distribution and would undoubtedly lead to improved understanding of the global carbon budget. We use a 3-D chemical transport model to investigate the ability of potential satellite instruments with a variety of orbits, horizontal resolution and vertical weighting functions to capture the variation in the modeled CO2 fields. The model is driven by analyzed winds from the Goddard Data Assimilation Office. Simulated CO2 fields are compared with existing surface and aircraft data, and the effects of the model convection scheme and representation of the planetary boundary layer are considered.

Andrews, Arlyn E.↗

Expanding the Spatiotemporal Range of Soil Moisture Analysis Utilizing NASA Earth Observations and In Situ Measurements

Drought can cause immense agricultural and ecological damage resulting in high mitigation and compensation costs. Climate variability in future decades is expected to cause severe drought conditions and threaten necessary water resources. Stakeholders seek to implement effective drought assessments in preparation for potential economic and environmental damage invoked by drought. Although in-situ measurements are accurate, the current infrastructure is spatially limited and costly to maintain. A framework was created to compare modeled, satellite and in-situ data in drought monitoring. Here we show that the comparison of in-situ and remotely sensed soil moisture (SM) measurements can increase the spatiotemporal range of SM assessments. Data collected between 2003 and 2021 by NASA’s SPoRT Land Information System (SPoRT-LIS) and Soil Moisture Active Passive (SMAP) mission were standardized and compared with in-situ data provided through the Illinois Climate Network (WARM). Statistical analysis results including the Pearson correlation coefficient (r), root mean squared error, mean absolute error and others were calculated to compare the WARM measurements to the SMAP and SPoRT-LIS products. Results indicate that both satellite products demonstrate seasonally variable bias that is not present in the in-situ measurements. Bias was highest in the winter months and lowest in the late summer and early fall months in both satellite datasets. Overall, WARM-SPoRT comparisons resulted in lower seasonal variability. However, on average, the SMAP comparison demonstrated higher correlation values and lower error values. The WARM-SMAP average correlation (r) was 0.61 compared to the WARM-SPoRT average correlation (r) value of 0.54. Average mean absolute error values calculated for the SMAP and SPoRT comparisons were 0.07 and 0.08 percent soil moisture by volume, respectively. These analyses suggest integrating in-situ measurements and those provided by NASA Earth observations can be utilized in a multi-faceted SM evaluation, a valuable contribution to drought monitoring and water resource decision making.

Emma P Myrick↗

High resolution atmospheric and surface variability from combined MAMS and VAS radiances

Measuring of the variation of atmospheric and surface quantities such as moisture and stability at small scales is an important step to monitoring, understanding and forecasting mesoscale processes. For instance, moisture and stability products from the geostationary platform VISSR Atmospheric Sounder (VAS) exhibit interesting detail at the meso B (20-200 km) level (Chesters et al., 1986; Smith et al., 1985). However, variations at the meso C scale (2-20 km) and at the lower end of the meso B scale (20-100 km) suffer from the effects of noise. Noise can be greatly reduced by using a high resolution data collection system. The Multispectral Atmospheric Mapping Sensor (MAMS), with its 100-m resolution over a 36km swath, is well suited to provide high resolution mesoscale information about the atmosphere and surface of the earth. A more complete depiction of the atmospheric state at the smaller scales is possible through the combination of the high horizontal resolution MAMS data with the vertical sounding data of the VAS. This paper demonstrates a procedure for combining MAMS and VAS data in a physical retrieval to produce high resolution derived products of precipitable water (PW), lifted index (LI), and skin temperature (TS). The variability of these products is evaluated in a structure function analysis similar to that of Hillger and Vonder Haar (1979). Results for 19 June 1986 from the Cooperative Hunstville Meteorological Experiment (COHMEX) are presented.

Moeller, Christopher C.↗

Understanding the Biosphere From Space: Strategies to Exploit Remote Sensing Data

The quantitative interpretation of satellite observations requires the use of mathematical tools to extract the desired information on terrestrial environments from the radiation data collected in space. A whole range of approaches can be pursued, from the development of models capable of explaining the nature of the physical signal being measured and of characterizing the state of the system under observation, to the empirical correlations between the variables of interest and the space measurements. The premises and implications of these approaches are outlined, paying special attention to the mathematical and numerical requirements. The role and specific applications of empirical bidirectional reflectance models is also discussed, even though these models do not contribute to the understanding of the theory of radiation transfer or to the assessment of the variables of interest. The advantages and drawbacks of these various approaches and the research priorities for the next few years are discussed in the context of the planned availability of new sensors.

Michel M Verstraete↗

Dry Process for Manufacturing Hybridized Boron Fiber/Carbon Fiber Thermoplastic Composite Materials from a Solution Coated Precursor

An apparatus for producing a hybrid boron reinforced polymer matrix composite from precursor tape and a linear array of boron fibers. The boron fibers are applied onto the precursor tapes and the precursor tape processed within a processing component having an impregnation bar assembly. After passing through variable-dimension forming nip-rollers, the precursor tape with the boron fibers becomes a hybrid boron reinforced polymer matrix composite. A driving mechanism is used to pulled the precursor tape through the method and a take-up spool is used to collect the formed hybrid boron reinforced polymer matrix composite.

Harry L Belvin↗