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At least 127 records · Page 7

Second generation spectrograph for the Hubble Space Telescope

The preliminary design for the Space Telescope Imaging Spectrograph (STIS), which has been selected by NASA for definition study for future flight as a second-generation instrument on the Hubble Space Telescope (HST), is presented. STIS is a two-dimensional spectrograph that will operate from 1050 A to 11,000 A at the limiting HST resolution of 0.05 arcsec FWHM, with spectral resolutions of 100, 1200, 20,000, and 100,000 and a maximum field-of-view of 50 x 50 arcsec. Its basic operating modes include echelle model, long slit mode, slitless spectrograph mode, coronographic spectroscopy, photon time-tagging, and direct imaging. Research objectives are active galactic nuclei, the intergalactic medium, global properties of galaxies, the origin of stellar systems, stelalr spectral variability, and spectrographic mapping of solar system processes.

Woodgate, B. E.↗

Seasat - Results of the mission

The scientific results of the Seasat mission are reviewed, including altimeter, scatterometer, microwave radiometer, and imaging radar studies. The analyses of Seasat data showed that global calibrations of satellite observations are much more accurate than measurements made at points on the ocean. It is found that the accuracy of satellite measurements of a particular variable are improved if the variable is measured by different instruments on the same satellite. The results suggest that important oceanographic variables can be mapped from space with accuracies required by climatological and scientific studies.

Stewart, Robert H.↗

Pictorial communication in virtual and real environments

Papers about the communication between human users and machines in real and synthetic environments are presented. Individual topics addressed include: pictorial communication, distortions in memory for visual displays, cartography and map displays, efficiency of graphical perception, volumetric visualization of 3D data, spatial displays to increase pilot situational awareness, teleoperation of land vehicles, computer graphics system for visualizing spacecraft in orbit, visual display aid for orbital maneuvering, multiaxis control in telemanipulation and vehicle guidance, visual enhancements in pick-and-place tasks, target axis effects under transformed visual-motor mappings, adapting to variable prismatic displacement. Also discussed are: spatial vision within egocentric and exocentric frames of reference, sensory conflict in motion sickness, interactions of form and orientation, perception of geometrical structure from congruence, prediction of three-dimensionality across continuous surfaces, effects of viewpoint in the virtual space of pictures, visual slant underestimation, spatial constraints of stereopsis in video displays, stereoscopic stance perception, paradoxical monocular stereopsis and perspective vergence. (No individual items are abstracted in this volume)

Ellis, Stephen R.↗

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

VandeVen, C.↗

A Vertically Lagrangian Finite-Volume Dynamical Core for Global Models

A finite-volume dynamical core with a terrain-following Lagrangian control-volume discretization is described. The vertically Lagrangian discretization reduces the dimensionality of the physical problem from three to two with the resulting dynamical system closely resembling that of the shallow water dynamical system. The 2D horizontal-to-Lagrangian-surface transport and dynamical processes are then discretized using the genuinely conservative flux-form semi-Lagrangian algorithm. Time marching is split- explicit, with large-time-step for scalar transport, and small fractional time step for the Lagrangian dynamics, which permits the accurate propagation of fast waves. A mass, momentum, and total energy conserving algorithm is developed for mapping the state variables periodically from the floating Lagrangian control-volume to an Eulerian terrain-following coordinate for dealing with physical parameterizations and to prevent severe distortion of the Lagrangian surfaces. Deterministic baroclinic wave growth tests and long-term integrations using the Held-Suarez forcing are presented. Impact of the monotonicity constraint is discussed.

Lin, Shian-Jiann↗

Role of the Russell-McPherron Effect in the Acceleration of Relativistic Electrons

While it is well known that high fluxes of relativistic electrons in the Earth's radiation belts are associated with high-speed solar wind and its heightened geoeffectiveness,less known is the fact that the Russell McPherron(R M) effect strongly controls whether or not a given high-speed stream is geoffective. To test whether it then follows that the R M effect also strongly controls fluxes of relativistic electrons, we perform a superposed epoch analysis across corotating interaction regions (CIR) keyed on the interfaces between slow and fast wind. A total of 394 stream interfaces were identified in the years 1994-2006. Equinoctial interfaces were separated into four classes based on the R-M effect,that is, whether the solar wind on either side of the interface was either(geo)effective (E) or ineffective (I) depending on season and the polarity of the interplanetary magnetic field (IMF). Four classes of interface identified as II, IE, EI,and EE are possible. The classes IE and EI correspond to CIRs with polarity changes indicating passage through the heliospheric current sheet. To characterize the behavior of solar wind and magnetospheric variables, we produced maps of dynamic cumulative probability distribution functions (cdfs) as a function of time over 10-day intervals centered on the interfaces. These reveal that effective high-speed streams have geomagnetic activity nearly twice as strong as ineffective streams and electron fluxes a factor of 12 higher. In addition they show that an effective low-speed stream increases the flux of relativistic electrons before the interface so that an effective to ineffective transition results in lower fluxes after the interface.We conclude that the R-M effect plays a major role in organizing and sustaining a sequence of physical processes responsible for the acceleration of relativistic electrons.

McPherron, R. L.↗

Deep Ocean Warming Assessed from Altimeters, GRACE, 3 In-situ Measurements, and a Non-Boussinesq OGCM

Observational surveys have shown significant oceanic bottom water warming, but they are too spatially and temporally sporadic to quantify the deep ocean contribution to the present-day sea level rise (SLR). In this study, altimetry sea surface height (SSH), Gravity Recovery and Climate Experiment (GRACE) ocean mass, and in situ upper ocean (0-700 m) steric height have been assessed for their seasonal variability and trend maps. It is shown that neither the global mean nor the regional trends of altimetry SLR can be explained by the upper ocean steric height plus the GRACE ocean mass. A non-Boussinesq ocean general circulation model (OGCM), allowing the sea level to rise as a direct response to the heat added into the ocean, is then used to diagnose the deep ocean steric height. Constrained by sea surface temperature data and the top of atmosphere (TOA) radiation measurements, the model reproduces the observed upper ocean heat content well. Combining the modeled deep ocean steric height with observational upper ocean data gives the full depth steric height. Adding a GRACE-estimated mass trend, the data-model combination explains not only the altimetry global mean SLR but also its regional trends fairly well. The deep ocean warming is mostly prevalent in the Atlantic and Indian oceans, and along the Antarctic Circumpolar Current, suggesting a strong relation to the oceanic circulation and dynamics. Its comparison with available bottom water measurements shows reasonably good agreement, indicating that deep ocean warming below 700 m might have contributed 1.1 mm/yr to the global mean SLR or one-third of the altimeter-observed rate of 3.11 +/- 0.6 mm/yr over 1993-2008.

sea level↗

The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situ Rrs as input to the models, the performance of eleven semianalytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

Phytoplankton↗

Unique Spectroscopy and Imaging of Mars with the James Webb Space Telescope

In this paper, we summarize the main capabilities of the James Webb Space Telescope (JWST) for performing observations of Mars. The distinctive vantage point of JWST at the Sun-Earth Lagrange point (L2) will allow sampling the full observable disk, permitting the study of short-term phenomena, diurnal processes (across the east-west axis), and latitudinal processes between the hemispheres (including seasonal effects) with excellent spatial resolutions (0.''07 at 2 micron). Spectroscopic observations will be achievable in the 0.7-5 micron spectral region with NIRSpec at a maximum resolving power of 2700 and with 8000 in the 1-1.25 micron range. Imaging will be attainable with the Near-Infrared Camera at 4.3 micrometers and with two narrow filters near 2 micron, while the nightside will be accessible with several filters in 0.5 to 2 micron. Such a powerful suite of instruments will be a major asset for the exploration and characterization of Mars. Some science cases include the mapping of the water D/H ratio, investigations of the Martian mesosphere via the characterization of the non-local thermodynamic equilibrium CO2 emission at 4.3 micron, studies of chemical transport via observations of the O2 nightglow at 1.27 micron, high-cadence mapping of the variability dust and water-ice clouds, and sensitive searches for trace species and hydrated features on the Martian surface. In-flight characterization of the instruments may allow for additional science opportunities.

Villanueva, Geronimo L.↗

A functional global sensitivity measure and efficient reliability sensitivity analysis with respect to statistical parameters

Sensitivity analysis and reliability assessment are two important aspects of structural and system safety. Epistemic uncertainty with respect to probabilistic model of input parameters due to lack of knowledge is present in many scarce-data applications and complicates the characterization of uncertainty in model response. In this article, we present two importance measures to evaluate the impact of distribution parameters on the probability distribution function (PDF) of the output and the failure probability. The epistemic uncertainty associated with the distribution parameters is modeled as random variables. Additionally, a modified extended polynomial chaos expansion (MEPCE) approach is introduced in which aleatory and epistemic random variables are modeled and propagated simultaneously while allowing the separate assessment for any single epistemic variable. A MEPCE-based kernel density estimation (KDE) construction provides a composite map from each epistemic variable to the response PDF. The functional global sensitivity index of the PDF with respect to the distribution parameters is thus derived, as a function of output, which is both more informative and more efficient than standard scalar sensitivity measures. Reliability sensitivity indices can be readily evaluated by integrating the global sensitivity index function over the failure zone. Three illustrative examples are used to demonstrate the proposed methodology.

42 ENGINEERING↗

Building Maps for Terrain Relative Navigation Using Blender: An Open-Source Approach

A persistent challenge for vision-based navigation systems that compare imagery to a reference map is generating high quality maps with similar lighting conditions. Image rendering software can be used to apply variable lighting to reference maps or to generate synthetic imagery for test trajectories. While many image rendering software packages are available, with several developed specifically for spaceflight applications, there are often limitations due to cost, image fidelity, or flexibility. In this paper, we demonstrate the use of an open-source image rendering software, Blender, for use in Terrain Relative Navigation (TRN) applications. A scene in Blender was generated based on elevation data and satellite imagery of the region of West Texas used by Blue Origin for the operation of their New Shepard suborbital rocket. The Blender scene was validated by reproducing imagery collected during a flight of New Shepard in October 2020 and was further used to generate reference maps for use by a TRN algorithm on a subsequent New Shepard flight in August 2021. The work was performed under the NASA Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project, which is focused on technology advancement for precision landing and hazard avoidance. This work aims to lower the cost of entry and generally promote the adoption and advancement of vision-based navigation technologies.

Kyle W Smith↗

Neurocomputing strategies in decomposition based structural design

The present paper explores the applicability of neurocomputing strategies in decomposition based structural optimization problems. It is shown that the modeling capability of a backpropagation neural network can be used to detect weak couplings in a system, and to effectively decompose it into smaller, more tractable, subsystems. When such partitioning of a design space is possible, parallel optimization can be performed in each subsystem, with a penalty term added to its objective function to account for constraint violations in all other subsystems. Dependencies among subsystems are represented in terms of global design variables, and a neural network is used to map the relations between these variables and all subsystem constraints. A vector quantization technique, referred to as a z-Network, can effectively be used for this purpose. The approach is illustrated with applications to minimum weight sizing of truss structures with multiple design constraints.

Szewczyk, Z.↗

Global-scale sea surface variability from combined altimetric and tide gauge measurements

By correcting Geosat altimetric data for a set of line frequencies, and then doing a heavy average in space and time, a set of global maps of sea surface variability is produced over time intervals ranging from three months to two years. These maps are demonstrated to be consistent with the global network of tide gauges and sets of maps incorporating those data into the altimetric estimates are also produced. Tide gauge records too fragmentary for computation of a two-year mean are employed by time-differencing them. An estimate of the global difference of sea level change over one year, on very large space scales, shows the effects of the 1987 El Nino. The spherical harmonic coefficients employed in the computations are then used to estimate the full three-dimensional frequency/wavenumber spectrum of surface circulation variability.

Wunsch, Carl↗

Variable Side-Look Angle Concept For Radar Mapping

Radar mapping of planets can be accomplished at lower cost and with reduced emphasis on propulsion system capability from spacecraft operating in elliptical orbit than from circular orbit.

Vandenberg, Frank A.↗

Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems

In this work, we present Lift & Learn, a physics-informed method for learning low-dimensional models for large-scale dynamical systems. The method exploits knowledge of a system’s governing equations to identify a coordinate transformation in which the system dynamics have quadratic structure. This transformation is called a lifting map because it often adds auxiliary variables to the system state. The lifting map is applied to data obtained by evaluating a model for the original nonlinear system. This lifted data is projected onto its leading principal components, and low-dimensional linear and quadratic matrix operators are fit to the lifted reduced data using a least-squares operator inference procedure. Analysis of our method shows that the Lift & Learn models are able to capture the system physics in the lifted coordinates at least as accurately as traditional intrusive model reduction approaches. This preservation of system physics makes the Lift & Learn models robust to changes in inputs. Numerical experiments on the FitzHugh–Nagumo neuron activation model and the compressible Euler equations demonstrate the generalizability of our model.

97 MATHEMATICS AND COMPUTING↗

Mapping a Better Vintage

Vineyards such as those located in California's Napa Valley tend to be subdivided into relatively large fields or blocks that often encompass heterogeneous physical conditions. Since growers typically treat the entire block as a single minimum management unit for cultivation and harvest, mapping and monitoring the variability within a block is a concern. Over the last decade, an increasing number of vineyard managers have utilized digital remote sensing and geographic information systems (GIS) to visualize the variability within their blocks. With computer software designed to overlay remotely sensed imagery with environmental and agronomic geographic data on a map, GIS helps growers recognize and explain patterns that might not have been obvious otherwise. GIS can also serve as a valuable archiving mechanism for future reference. To further develop the use of image technology and GIS for vineyard management support, NASA's Earth Science Enterprise partnered with the U.S. wine and commercial remote sensing industries for a project known as the Viticultural Integration of NASA Technologies for Assessment of the Grapevine Environment (VINTAGE). With project investigators from NASA's Ames Research Center, the California State University at Monterey Bay, and the University of Montana, several prototype products have been developed to support agricultural decisions concerning canopy management and irrigation practice. One key VINTAGE aspect involved the evaluation of satellite and airborne multispectral imagery for delineation of sub-block management zones within a vineyard.

Source record↗

Things that go bump in the light - On the optical specification of contact severity

Psychologists are intrigued with the idea that optical variables can specify not only the time until an object impacts an observer but also the severity of the impact. However, the mapping between the optical variables and the kinematic variables has been misstated, erroneously implying that there exist critical values of the optical variables used for locomotion and control. In this commentary, the mathematical relationship between the optical and kinematic variables is reexamined and the erroneous assumptions that have led to the proposal of critical values are shown. Also examined are the empirical data on deceleration to approach to assess whether the proposed optical variables are likely candidates for control strategies. Finally, problems associated with numerical approximations to dynamic systems, particularly when analytic solutions exist, are discussed.

Kaiser, Mary K.↗

Satellite Power System (SPS) mapping of exclusion areas for rectenna sites

The areas of the United States that were not available as potential sites for receiving antennas that are an integral part of the Satellite Power System concept are presented. Thirty-six variables with the potential to exclude the rectenna were mapped and coded in a computer. Some of these variables exclude a rectenna from locating within the area of its spatial influence, and other variables potentially exclude the rectenna. These maps of variables were assembled from existing data and were mapped on a grid system.

Blackburn, J. B., Jr.↗