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At least 649 records · Page 36

Rayleigh lidar observations of gravity wave activity in the upper stratosphere at Urbana, Ill.

During 13 nights of Rayleigh lidar measurements at Urbana, Ill. in 1984 to 1986, thirty-six quasi-monochromatic gravity waves were observed in the 35 to 50 km altitude region of the stratosphere. The characteristics of the waves are compared with other lidar and radar measurements of gravity waves and the theoretical models of wave saturation and dissipation phenomena. The measured vertical wavelengths ranged from 2 to 11.5 km and the measured vertical phase velocities ranged from 10 to 85 cm/s. The vertical wavelengths and vertical phase velocities were used to infer observed wave periods which ranged from 100 to 1000 min and horizontal wavelengths which ranged from 70 to 2000 km. Dominant wave activity was found at vertical wavelengths between 2 to 4 km and 7 to 10 km. No significant seasonal variations were evident in the observed parameters. Vertical and horizontal wavelengths showed a clear tendency to increase with wave periods, which is consistent with recent sodium lidar studies of quasi-monochromatic waves near the mesopause. An average amplitude growth length of 20.9 km for the rms wind perturbations was estimated from the data. Kinetic energy density associated with the waves decreased with height, suggesting that waves in this altitude region were subject to dissipation or saturation effects.

Gardner, C. S.↗

The solar coronal density irregularity n squared bar/(n bar) squared derived from simultaneous measurements of the EUV and K-coronal brightness

Results are reported from a study of the low corona based on cospatial and cotemporal measurements of the K-coronal polarized brightness pB, and the intensity of the strong resonance line Mg x 625A as a function of height between 1.05 and 1.24 solar radius. Taken together, these measurements yield an estimate of the solar coronal density irregularity. This quantity, is found to be much greater than 1. On the basis of a simple two-component model, it is found that the well-studied resolved structures of the inner corona as presently understood are not capable of explaining the observed irregularity. It is conjectured that subresolution density fluctations associated with coronal dissipation and heating may be the source of the excess irregularity.

Orrall, F. Q.↗

Theory and design of interferometric synthetic aperture radars

A derivation of the signal statistics, an optimal estimator of the interferometric phase, and the expression necessary to calculate the height-error budget are presented. These expressions are used to derive methods of optimizing the parameters of the interferometric synthetic aperture radar system (InSAR), and are then employed in a specific design example for a system to perform high-resolution global topographic mapping with a one-year mission lifetime, subject to current technological constraints. A Monte Carlo simulation of this InSAR system is performed to evaluate its performance for realistic topography. The results indicate that this system has the potential to satisfy the stringent accuracy and resolution requirements for geophysical use of global topographic data.

Rodriguez, E.↗

Conceptual design of a spaceborne radar for rain and cloud sensing

A conceptual design for a mid-latitude orbiting precipitation and cloud mapping radar is discussed. In this conceptual design the radar utilizes a narrow, dual-frequency beam, electronically scanned antenna to achieve 4-km spatial resolution and 300-km cross-track swath. Vertical resolution of 500 m is achieved by short-pulse transmission. It is expected that such system can measure rain rates up to 100 mm/hr for precipitation at the cloud base, surface precipitation up to 20 mm/hr, and cloud reflectivities as low as -39 dBz. By averaging over 100 independent samples, signal reflectivities can be estimated to better than 20 percent. Other rain and cloud characteristics, such as height, thickness, and cell size, can also be extracted from the data.

Im, Eastwood↗

Projectile-target mixing in melted ejecta formed during a hypervelocity impact cratering event

Tektites contain little to no projectile contamination while, in contrast, some distal ejecta deposits can be relatively projectile-rich (e.g. the Cretaceous-Tertiary (K-T) boundary clay). This compositional difference motivated an experimental study of hypervelocity target-projectile mixing processes. We hope to scale up the results from these experiments and apply them to terrestrial impact structures like the Chicxulub Crater, Yucutan, Mexico, the leading contender as the site for the impact that caused the mass extinction that marks the K-T boundary. Shock decomposition of the approximately 500m thickness of anhydrite, or greater thickness of limestone, in the target rocks at Chicxulub may have been a critical mechanism for either global cooling via SO3, and subsequently H2SO4, formation, or possibly, global warming via increased CO2 formation. Understanding target-projectile mixing processes during hypervelocity impact may permit more accurate estimates of the amount of potentially toxic, target-derived material reaching stratospheric heights.

Evans, Noreen Joyce↗

Geographical representation of radial orbit perturbations due to ocean tides: Implications for satellite altimetry

In analogy to the geographical representation of the zeroth-order radial orbit perturbations due to the static geopotential, similar relationships have been derived for radial orbit perturbations due to the ocean tides. At each location these perturbations are seen to be coherent with the tide height variations. The study of this singularity is of obvious importance to the estimation of ocean tides from satellite altimeter data. We derive analytical expressions for the sensitivity of altimeter derived ocean tide models to the ocean tide force model induced errors in the orbits of the altimeter satellite. In particular, we focus on characterizing and quantifying the nonresonant tidal orbit perturbations, which cannot be adjusted into the empirical accelerations or radial perturbation adjustments commonly used during orbit determination and in altimeter data processing. As an illustration of the utility of this technique, we study the differences between a TOPEX/POSEIDON-derived ocean tide model and the Cartwright and Ray 1991 Geosat model. This analysis shows that nearly 60% of the variance of this difference for M(sub 2) can be explained by the Geosat radial orbit eror due to the omission of coefficients from the GEM-T2 background ocean tide model. For O(sub 1), K(sub 1), S(sub 2), and K(sub 2) the orbital effects account for approximately 10 to 40% of the variances of these differences. The utility of this technique to assessment of the ocean tide induced errors in the TOPEX/POSEIDON-derived tide models is also discussed.

Bettadpur, Srinivas V.↗

Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

Kimes, Daniel S.↗

Determination of Top-of-Atmosphere Longwave Radiative Fluxes: A Comparison Between Two Approaches Using ScaRaB Data

Two conceptually different approaches (broadband-based ERBE and narrowband-based ISCCP approaches), used to derive the TOA longwave radiative fluxes, are compared using the ScaRaB simultaneous narrowband and broadband measurements. This study directly shows that the ERBE MLE-derived cloud covers implicitly contain some information on the cloud optical properties. A spurious view-zenith-angle dependence of the MLE scene identification scheme is confirmed by this study. Except for very thin cirrus clouds, differences between the ERBE and ISCCP approaches are in general < 10 W/sq m for the TOA LW radiative fluxes. For clear pixels, the model calculated (ISCCP approach) TOA LW radiances are systematically smaller than the observations. Though the bias is found to be correlated on the column precipitable water amount, the exact source of this discrepancy remains undetermined and merits further study. Compared with the radiative transfer model used in this study, the ERBE LW ADMs are too weakly limb-darkened for optically thin clouds, but too strongly limb-darkened for optically thick clouds, indicating that more accurate instantaneous TOA LW flux estimations from the ERBE approach would require additional cloud classes based on cloud height and optical thickness.

Chen, Ting↗

Thin-Filament Pyrometry Developed for Measuring Temperatures in Flames

Many valuable advances in combustion science have come from observations of microgravity flames. This research is contributing to the improved efficiency and reduced emissions of practical combustors and is benefiting terrestrial and spacecraft fire safety. Unfortunately, difficulties associated with microgravity have prevented many types of measurements in microgravity flames. In particular, temperature measurements in flames are extremely important but have been limited in microgravity. A novel method of measuring temperatures in microgravity flames is being developed in-house at the National Center for Microgravity Research and the NASA Glenn Research Center and is described here. Called thin-filament pyrometry, it involves using a camera to determine the local gas temperature from the intensity of inserted fibers glowing in a flame. It is demonstrated here to provide accurate measurements of gas temperatures in a flame simultaneously at many locations. The experiment is shown. The flame is a laminar gas jet diffusion flame fueled by methane (CH4) flowing from a 14-mm round burner at a pressure of 1 atm. A coflowing stream of air is used to prevent flame flicker. Nine glowing fibers are visible. These fibers are made of silicon carbide (SiC) and have a diameter of 15 m (for comparison, the average human hair is 75 m in diameter). Because the fibers are so thin, they do little to disturb the flame and their temperature remains close to that of the local gas. The flame and glowing filaments were imaged with a digital black-and-white video camera. This camera has an imaging area of 1000 by 1000 pixels and a wide dynamic range of 12 bits. The resolution of the camera and optics was 0.1 mm. Optical filters were placed in front of the camera to limit incoming light to 750, 850, 950, and 1050 nm. Temperatures were measured in the same flame in the absence of fibers using 50-m Btype thermocouples. These thermocouples provide very accurate temperatures, but they generally are not useful in microgravity tests because they measure temperature at only one location at a time. Thermocouple measurements at a height of 11 mm above the burner were used to calibrate the thin-filament pyrometry system at all four wavelengths. This calibration was used to perform thin-filament pyrometry at other heights above the burner. One such profile is shown in this graph; this is for a height of 21 mm. The agreement between the pyrometry measurements and thermocouple results at this height is excellent in the range of 1000 to 2000 K, with an estimated uncertainty of 50 K and an estimated upper limit of 2500 K. Neither the thermocouple nor the thin-filament pyrometry temperatures have been corrected for radiation, but the correction is expected to be nearly the same for both methods. We anticipate that thin-filament pyrometry similar to that developed here will become an important diagnostic for studies of microgravity flames owing to its accuracy and its ability to simultaneously measure finely spaced temperatures.

Sunderland, Peter B.↗

Hartman Testing of X-Ray Telescopes

Hartmann testing of x-ray telescopes is a simple test method to retrieve and analyze alignment errors and low-order circumferential errors of x-ray telescopes and their components. A narrow slit is scanned along the circumference of the telescope in front of the mirror and the centroids of the images are calculated. From the centroid data, alignment errors, radius variation errors, and cone-angle variation errors can be calculated. Mean cone angle, mean radial height (average radius), and the focal length of the telescope can also be estimated if the centroid data is measured at multiple focal plane locations. In this paper we present the basic equations that are used in the analysis process. These equations can be applied to full circumference or segmented x-ray telescopes. We use the Optical Surface Analysis Code (OSAC) to model a segmented x-ray telescope and show that the derived equations and accompanying analysis retrieves the alignment errors and low order circumferential errors accurately.

Saha, Timo T.↗

Principal Component and Machine Learning Approach to Gap Fill Hyperspectral Ocean Color Satellite Retrievals

Retrievals of ocean color properties from space are important for monitoring the health of the ocean ecosystem but such retrievals can be limited spatially due to conditions such as clouds, aerosols, and sun glint. Gap filling of ocean color retrievals is typically performed by combining retrievals from multiple satellites or temporally averaging multiple days of retrievals. Despite these techniques large gaps still exist posing challenges for near real time monitoring of events like harmful algae blooms. To address these limitations, we developed a spatial gap filling approach applying machine learning approach to hyperspectral instruments to learn how to perform an atmospheric correction under challenging retrieval conditions. In this approach a principal component analysis is used to decompose the hyperspectral measurements into spectral components that describe the scattering and absorption of the atmosphere mixed with the surface spectral signatures. The coefficients of the principal components are used to train a neural network to predict ocean color properties derived from a standard MODIS ocean color algorithm. We apply the approach to two hyperspectral UV/VIS sensors, the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can be used to estimate ocean color properties such as chlorophyll, remote sensing reflectance, and fluorescence line height. This method could be used as a gap-filling technique for the future Ocean Color Instrument (OCI) onboard upcoming NASA's Plankton, Aerosol Cloud, ocean Ecosystem (PACE) satellite to provide additional information for monitoring the health of our global oceans. Additionally, it could be applied to the first NASA and Smithsonian geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO) spectrometer to better understand diurnal variability in inland and coastal ocean ecology.

Zachary Fasnacht↗

A Principal Component and Machine Learning Approach to Spatially Gap Fill Hyperspectral Ocean Color Satellite Retrievals

Retrievals of ocean color properties from space are important for monitoring the health of the ocean ecosystem but such retrievals tend to be limited in spatial coverage due to conditions such as clouds, aerosols, and sun glint. Gap filling of ocean color retrievals is typically performed by combining retrievals from multiple satellites or temporally averaging multiple days of retrievals but despite these techniques large gaps still exist posing challenges for near real time monitoring of events like harmful algae blooms. To address these limitations, we propose a spatial gap filling approach using machine learning to learn how to perform an atmospheric correction under challenging retrieval conditions. In this approach a principal component analysis is used to decompose the hyperspectral measurements into spectral features that describe the scattering and absorption of the atmosphere as well as the underlying surface. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from a standard ocean color algorithm such as the MODIS atmospheric correction algorithm. This machine learning approach is independent of a priori information and does not rely on any radiative transfer modeling. We apply the approach to two hyperspectral UV/VIS instruments, the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can be used to estimate ocean color properties such as chlorophyll, remote sensing reflectance, and fluorescence line height. This method could be used as a gap-filling technique for the future Ocean Color Instrument (OCI) which will be onboard NASA's Plankton, Aerosol Cloud, ocean Ecosystem (PACE) ocean color satellite to provide additional information for monitoring the health of our global oceans. Additionally, it could be applied to the geostationary satellite Tropospheric Emissions: Monitoring of Pollution (TEMPO) to better understand diurnal variability in ocean ecology.

MODIS atmospheric correction algorithm↗

Survival of Juvenile Florida Scrub-Jays is Habitat Specific, Positively Correlated With Month and Negatively Correlated With Male Breeder Death

Juvenile survival in birds is difficult to estimate but this vital rate can be an important consideration for management decisions. We estimated juvenile survival of cooperatively breeding Florida Scrub-Jays (Aphelocoma coerulescens) in a landscape degraded by fire suppression and fragmentation using data from marked (n = 325) and unmarked juveniles (n = 1,306) with an integrated hierarchical Bayesian model. To assess the combined analyses, we also analyzed these datasets separately, with a Cormack-Jolly-Seber (CJS) model (marked) and young model (unmarked). Our data consisted of monthly censuses of territorial family groups from Florida Scrub-Jay populations in East Central Florida collected over a 22-yr period. Juvenile survival was estimated from July when young Florida Scrub-Jays begin developing independence to March when they become first year individuals and grouped according to the habitat quality class of their natal territory that were based on shrub height (with intermediate shrub heights being optimal and short and tall shrub heights being suboptimal) and the presence of sandy openings (the preferred open having many sandy openings; closed not having enough). Parameter estimates in the combined analysis were intermediate to the separate analyses. Notable differences among the separate analyses were that suboptimal habitat survival was lower in the unmarked analysis, the unmarked analysis showed a linear effect of time not seen in the marked analysis, and there was an effect of male breeder death in the marked but not unmarked analysis. The combined data analysis provided more inference than did either data set analyzed separately including juveniles in optimal-closed territories unexpectedly had higher survival than those in optimal-open, survival increased through time, and male breeder death had a negative effect on survival. This study suggests that optimal-closed habitat may play an important role in juvenile Florida Scrub-Jay survival perhaps by providing better cover from predators and warrants further investigation for management implications.

Florida Scrub-Jay↗

Modeling Tetragonal Lysozyme Crystal Growth Rates

Tetragonal lysozyme 110 face crystal growth rates, measured over 5 orders of magnitude in range, can be described using a model where growth occurs by 2D nucleation on the crystal surface for solution supersaturations of c/c(sub eq) less than or equal to 7 +/- 2. Based upon the model, the step energy per unit length, beta was estimated to be approx. 5.3 +/- 0.4 x 10(exp -7) erg/mol-cm, which for a step height of 56 A corresponds to barrier of approx. 7 +/- 1 k(sub B)T at 300 K. For supersaturations of c/c(sub eq) > 8, the model emphasizing crystal growth by 2D nucleation not only could not predict, but also consistently overestimated, the highest observable crystal growth rates. Kinetic roughening is hypothesized to occur at a cross-over supersaturation of c/c(sub eq) > 8, where crystal growth is postulated to occur by a different process such as adsorption. Under this assumption, all growth rate data indicated that a kinetic roughening transition and subsequent crystal growth by adsorption for all solution conditions, varying in buffer pH, temperature and precipitant concentration, occurs for c/c(sub eq)(T, pH, NaCl) in the range between 5 and 10, with an energy barrier for adsorption estimated to be approx. 20 k(sub B)T at 300 K. Based upon these and other estimates, we determined the size of the critical surface nucleate, at the crossover supersaturation and higher concentrations, to range from 4 to 10 molecules.

Gorti, Sridhar↗

Dose Calibration of the ISS-RAD Fast Neutron Detector

The ISS-RAD instrument has been fabricated by Southwest Research Institute and delivered to NASA for flight to the ISS in late 2015 or early 2016. ISS-RAD is essentially two instruments that share a common interface to ISS. The two instruments are the Charged Particle Detector (CPD), which is very similar to the MSL-RAD detector on Mars, and the Fast Neutron Detector (FND), which is a boron-loaded plastic scintillator with readout optimized for the 0.5 to 10 MeV energy range. As the FND is completely new, it has been necessary to develop methodology to allow it to be used to measure the neutron dose and dose equivalent. This talk will focus on the methods developed and their implementation using calibration data obtained in quasi-monoenergetic (QMN) neutron fields at the PTB facility in Braunschweig, Germany. The QMN data allow us to determine an approximate response function, from which we estimate dose and dose equivalent contributions per detected neutron as a function of the pulse height. We refer to these as the "pSv per count" curves for dose equivalent and the "pGy per count" curves for dose. The FND is required to provide a dose equivalent measurement with an accuracy of 10% of the known value in a calibrated AmBe field. Four variants of the analysis method were developed, corresponding to two different approximations of the pSv per count curve, and two different implementations, one for real-time analysis onboard ISS and one for ground analysis. We will show that the preferred method, when applied in either real-time or ground analysis, yields good accuracy for the AmBe field. We find that the real-time algorithm is more susceptible to chance-coincidence background than is the algorithm used in ground analysis, so that the best estimates will come from the latter.

Zeitlin, C.↗

BOLT II Forebody Surface Measurement Analysis

Surface impression molds of the nosetip/forebody interface, discrete tripping elements, and other surface imperfections were formed on the BOLT II flight vehicle prior to its launch in March 2022. The silicon-rubber molds cast on the interface between the nickel nosetip and the stainless steel forebody were measured using a 3D optical measurement system and a stylus profilometer and were evaluated for step direction and height. The step around the nosetip/forebody interface was found to vary in both magnitude and direction, but values were generally modest with most samples below 60 μm across the span and only two samples, both cast in the gutter, with step values larger than 100 μm. Impressions of the secondary-side tripping elements were strictly scanned with the optical device and similar methods were used to calculate trip height as step height. The measured centerline trip height was 2623 ±12 μm, while the leading-edge, quadrant 2 and 3, trip heights were 897 ±5 μm and 891 ±18 μm, respectively. Surface imperfections on the nose and forebody were also evaluated. Surface roughness values and spectra were estimated, and profiles were extracted across the imperfections to quantify the magnitude of those features.

Trip height↗

Exploring the effects of molecular beam epitaxy growth characteristics on the temperature performance of state-of-the-art terahertz quantum cascade lasers

This study conducts a comparative analysis, using non-equilibrium Green’s functions (NEGF), of two state-of-the-art two-well (TW) Terahertz Quantum Cascade Lasers (THz QCLs) supporting clean 3-level systems. The devices have nearly identical parameters and the NEGF calculations with an abrupt-interface roughness height of 0.12 nm predict a maximum operating temperature (T max ) of ~ 250 K for both devices. However, experimentally, one device reaches a T max of ~ 250 K and the other a T max of only ~ 134 K. Both devices were fabricated and measured under identical conditions in the same laboratory, with high quality processes as verified by reference devices. The main difference between the two devices is that they were grown in different MBE reactors. Our NEGF-based analysis considered all parameters related to MBE growth, including the maximum estimated variation in aluminum content, growth rate, doping density, background doping, and abrupt-interface roughness height. From our NEGF calculations it is evident that the sole parameter to which a drastic drop in T max could be attributed is the abrupt-interface roughness height. We can also learn from the simulations that both devices exhibit high-quality interfaces, with one having an abrupt-interface roughness height of approximately an atomic layer and the other approximately a monolayer. However, these small differences in interface sharpness are the cause of the large performance discrepancy. This underscores the sensitivity of device performance to interface roughness and emphasizes its strategic role in achieving higher operating temperatures for THz QCLs. We suggest Atom Probe Tomography (APT) as a path to analyze and measure the (graded)-interfaces roughness (IFR) parameters for THz QCLs, and subsequently as a design tool for higher performance THz QCLs, as was done for mid-IR QCLs. Our study not only addresses challenges faced by other groups in reproducing the record T max of ~ 250 K and ~ 261 K but also proposes a systematic pathway for further improving the temperature performance of THz QCLs beyond the state-of-the-art.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Earth GRAM-99 and Trace Constituents

Global Reference Atmospheric Model (GRAM-99) is an engineering-level model of Earth's atmosphere. It provides both mean values and perturbations for density, temperature, pressure, and winds, as well as monthly- and geographically-varying trace constituent concentrations. From 0-27 km, GRAM thermodynamics and winds are based on National Oceanic and Atmospheric Administration Global Upper Air Climatic Atlas (GUACA) climatology. Above 120 km, GRAM is based on the NASA Marshall Engineering Thermosphere (MET) model. In the intervening altitude region, GRAM is based on Middle Atmosphere Program (MAP) climatology that also forms the basis of the 1986 COSPAR International Reference Atmosphere (CIRA). Atmospheric composition is represented in GRAM by concentrations of both major and minor species. Above 120 km, MET provides concentration values for N2, O2, Ar, O, He, and H. Below 120 km, species represented also include H2O, O3, N2O, CO, CH4, and CO2. At COSPAR 2002 a comparison was made between GRAM constituents below 120 km and those provided by Naval Research Laboratory (NRL) climatology. No current need to update GRAM constituent climatology in that height range was identified. This report examines GRAM (MET) constituents between 100 and 1000 km altitudes. Discrepancies are noted between GRAM (MET) constituent number densities and mass density or molecular weight. Near 110 km altitude, there is up to about 25% discrepancy between MET number density and mass density (with mass density being valid and number densities requiring adjustment). Near 700 km altitude there is also up to about 25% discrepancy between MET number density and mean molecular weight (with molecular weight requiring adjustment). In neither case are MET mass density estimates invalidated. These discrepancies have been traced to MET subroutines SLV (which affects 90-170 km height range) and SLVH (which affects helium above 440 km altitude). With these discrepancies corrected, results are presented to illustrate GRAM (MET) constituent mole fractions in terms of height-latitude cross sections from 100 to 1000 km altitude, and latitude-longitude 'maps' at 450 km (approximate height of International Space Station). Plans are discussed for an update of MET (and GRAM) to correct these constituent inconsistencies and to incorporate several new thermospheric model features.

Justus, C. G.↗