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NASA NTRS2014

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

aerosols↗

NASA NTRS2016

Application of Compressive Sensing to Gravitational Microlensing Data and Implications for Miniaturized Space Observatories

Compressive Sensing is a technique for simultaneous acquisition and compression of data that is sparse or can be made sparse in some domain. It is currently under intense development and has been profitably employed for industrial and medical applications. We here describe the use of this technique for the processing of astronomical data. We outline the procedure as applied to exoplanet gravitational microlensing and analyze measurement results and uncertainty values. We describe implications for on-spacecraft data processing for space observatories. Our findings suggest that application of these techniques may yield significant, enabling benefits especially for power and volume-limited space applications such as miniaturized or micro-constellation satellites.

Gravitational Microlensing↗

NASA NTRS2016

Application of Compressive Sensing to Gravitational Microlensing Data and Implications for Miniaturized Space Observatories

Compressive Sensing↗

NASA NTRS1988

Using data tagging to improve the performance of Kanerva's sparse distributed memory

The standard formulation of Kanerva's sparse distributed memory (SDM) involves the selection of a large number of data storage locations, followed by averaging the data contained in those locations to reconstruct the stored data. A variant of this model is discussed, in which the predominant pattern is the focus of reconstruction. First, one architecture is proposed which returns the predominant pattern rather than the average pattern. However, this model will require too much storage for most uses. Next, a hybrid model is proposed, called tagged SDM, which approximates the results of the predominant pattern machine, but is nearly as efficient as Kanerva's original formulation. Finally, some experimental results are shown which confirm that significant improvements in the recall capability of SDM can be achieved using the tagged architecture.

Rogers, David↗

NASA NTRS2021

Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data

Forest structure and composition regulate a range of ecosystem services, including biodiversity, water and nutrient cycling, and wood volume for resource extraction. Forest type is an important metric measured in the US Forest Service Forest Inventory and Analysis (FIA) program, the national forest inventory of the USA. Forest type information can be used to quantify carbon and other forest resources within specific domains to support ecological analysis and forest management decisions, such as managing for disease and pests. In this study, we developed a methodology that uses a combination of airborne hyperspectral and lidar data to map FIA-defined forest type between sparsely sampled FIA plot data collected in interior Alaska. To determine the best classification algorithm and remote sensing data for this task, five classification algorithms were tested with six different combinations of raw hyperspectral data, hyperspectral vegetation indices, and lidar-derived canopy and topography metrics. Models were trained using forest type information from 632 FIA subplots collected in interior Alaska. Of the thirty model and input combinations tested, the random forest classification algorithm with hyperspectral vegetation indices and lidar-derived topography and canopy height metrics had the highest accuracy (78% overall accuracy). This study supports random forest as a powerful classifier for natural resource data. It also demonstrates the benefits from combining both structural (lidar) and spectral (imagery) data for forest type classification.

random forest↗

NASA NTRS1995

Reduction and analysis of seasons 15 and 16 (1991 - 1992) Pioneer Venus radio occulation data and correlative studies with observations of the near infrared emission of Venus

In this study, we sought to characterize variations in the abundance and distribution of subcloud H2SO4(g) in the Venus atmosphere by using a number of 13cm radio occultation measurements conducted with the Pioneer Venus Orbiter near the inferior conjunction of 1991. A total of ten data sets were examined and analyzed, producing vertical profiles of temperature and pressure in the neutral atmosphere, and sulfuric acid vapor abundance below the main cloud layer. Two of the vertical profiles of the abundance of H2SO4(g) were correlated with NIR images of the night side of Venus made during the same period of time by Boris Ragent (under a separate PVO Guest Investigator Grant). Initially, we had hoped that the combination of these two different types of data would make it possible to constrain or identify the composition of the large particles causing the features observed in the NIR images. However, the sparseness of the radio occultation data set, combined with the sparseness of the NIR data set (one image per day over an 8 day period) made it impossible to draw strong conclusions. Considered on their own, however, the parameters retrieved from the radio occultation experiments are valuable science products.

Jenkins, Jon M.↗

NASA NTRS2015

The Parameterization of Top-Hat Particle Sensors with Microchannel-Plate-Based Detection Systems and its Application to the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration resources.

Instrument-model↗

NASA NTRS2006

Temperature-dependent Absolute Refractive Index Measurements of Synthetic Fused Silica

Using the Cryogenic, High-Accuracy Refraction Measuring System (CHARMS) at NASA's Goddard Space Flight Center, we have measured the absolute refractive index of five specimens taken from a very large boule of Corning 7980 fused silica from temperatures ranging from 30 to 310 K at wavelengths from 0.4 to 2.6 microns with an absolute uncertainty of plus or minus 1 x 10 (exp -5). Statistical variations in derived values of the thermo-optic coefficient (dn/dT) are at the plus or minus 2 x 10 (exp -8)/K level. Graphical and tabulated data for absolute refractive index, dispersion, and thermo-optic coefficient are presented for selected wavelengths and temperatures along with estimates of uncertainty in index. Coefficients for temperature-dependent Sellmeier fits of measured refractive index are also presented to allow accurate interpolation of index to other wavelengths and temperatures. We compare our results to those from an independent investigation (which used an interferometric technique for measuring index changes as a function of temperature) whose samples were prepared from the same slugs of material from which our prisms were prepared in support of the Kepler mission. We also compare our results with sparse cryogenic index data from measurements of this material from the literature.

Leviton, Douglas B.↗

NASA NTRS1987

Monitoring global vegetation using Nimbus-7 37 GHz data - Some empirical relations

The difference of the vertically and horizontally polarized brightness temperatures observed by the 37 GHz channel of the SMMR on board the Nimbus-7 satellite are correlated temporally with three indicators of vegetation density, namely the temporal variation of the atmospheric CO2 concentration at Mauna Loa (Hawaii), rainfall over the Sahel and the normalized difference vegetation index derived from the AVHRR on board the NOAA-7 satellite. SMMR 37 GHz and AVHRR provide complementary data sets for monitoring global vegetation, the 37 GHz data being more suitable for arid and semiarid regions as these data are more sensitive to changes in sparse vegetation. The 37-GHz data might be useful for understanding desertification and indexing Co2 exchange between the biosphere and the atmosphere.

Choudhury, B. J.↗

NASA NTRS2019

Online Visualization and Analysis of NASA Satellite-Based Global and Regional Precipitation Products Through Giovanni

Observational data are essential for Earth science research and applications. Traditional ground-based observations suffer from many limitations (e.g. costly deployment). As a result, data are often sparse and inconsistent, especially over vast oceans that cover nearly 71% of the Earth's surface, and for remote continents. Precipitation is one of the important physical parameters in the global hydrological cycle and other disciplines. Each year, severe floods and droughts happen in different parts of the world and cause significant damage to the economy, as well as human casualties (e.g. Hurricane Katrina, the Dust Bowl). Accurate and timely precipitation observations and predictions are important for research and applications. However, ground-based precipitation observations are quite limited, especially in remote and mountainous regions. Since the satellite era began, satellite-based precipitation products have gained popularity in Earth science research, applications, and education. Accessing satellite products can be a daunting task to many users, especially those who do not have prior experience or knowledge with satellite data. Recognizing this obstacle, the NASA Goddard Earth Sciences and Data and Information Services Center (GES DISC), home to data archives for the NASA-JAXA Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM), has developed data services including an online visualization and analysis tool, Giovanni (the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure), enabling users at different levels to access, explore, and evaluate NASA satellite-based data products without downloading either data and software, or requiring coding. Currently, global and regional precipitation products from different satellite missions (TRMM, GPM) and projects (e.g. the Modern Era Retrospective-analysis for Research and Applications Version 2 (MERRA-2), and the North American Land Data Assimilation System (NLDAS)), ranging from half-hourly to monthly temporal resolution, are available in Giovanni. There are over 1900 variables in Giovanni, covering measurements in precipitation, hydrology, atmospheric dynamics, atmospheric chemistry, etc. In this poster presentation, we will provide a live demonstration of Giovanni and its latest development, including precipitation-related variables, and new basic features such as polar projections. The session will also provide a Q&A opportunity for attendees.

Giovanni↗

NASA NTRSDate not supplied

Why Developing A Full-Sun UV Spectrograph Sounding Rocket Is Difficult but Necessary

For a conference focused on a 20-year perspective of where we have been and where we are going, this talk will highlight specifically why we need a sounding rocket to lead the way in obtaining high-resolution UV spectroscopy of our sun-as-a-star. The currently available data is either sparse or at a much lower resolution when compared with Hubble (HST) spectra of other stars. Because of this, we cannot say with certainty if our Sun’s variability is typical. This limitation is hindering our quest to place our Sun in it’s rightful place on our star-charts. Ultraviolet light is a key component in determining this. Elements such as Hydrogen and Iron have strong emission lines here, and from them we can determine many things about the star from which they originate. The width of these spectral features can tell us about the relative plasma activity on the surface of the star, the abundance of those elements, and of course the temperatures. This has of course been done with many instruments that have very narrow field of views and/or narrow bandwidths. The only way to directly compare our Sun’s UV ”fingerprint” with other stars is to take an image of it in the same manner by which HST does: as a point source object. Our team’s aim has been to develop a sounding rocket capable of doing just that. Along the way, the many challenges we face are producing many solutions. A unique take on the traditional Rowland circle spectrograph will allow us to cover a large range of UV spectra with minimal moving parts. A novel in-situ gain calibration technique will be used in order to maintain the high level of radiometric accuracy desired. Naturally, complications arise when one takes UV measurements as you are flying out of earth’s atmosphere and back into it. Though it may be minor, the absorbed UV spectra from the atmosphere will have to be accounted for. In preparing for this, we have stumbled across a way in which those ”telluric” absorption lines may prove useful for spectral calibration purposes. In addition, raw data from previous sounding rocket missions may have hidden within them useful information for the atmospheric-physics community. In this talk, we will highlight the unique calibration problems and solutions we have faced, and how those are of greater importance to the greater heliophysics and atmospheric communities. With these amazing developments at hand, the future of heliophysics instrumentation is looking bright. This material is based upon work supported by the NSF EPSCoR RII-Track-1.2a (Non-invasive plasma diagnostics for LTP) Cooperative Agreement OIA-1655280. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

NASA, UAH, MSU, Sounding Rocket, Aeronomy, Instrum↗

NASA NTRS1979

Thickness of western mare basalts

An isopach map of the basalt thickness in the western mare basins is constructed from measurements of the exposed external rim height of partially buried craters. The data, although numerically sparse, is sufficiently distributed to yield gross thickness variations. The average basalt thickness in Oceanus Procellarum and adjacent regions is 400 m with local lenses in excess of 1500 m in the circular maria. The total volume of basalt in the western maria is estimated to be in the range of 1.5 x 10 to the 6th power cu km. The chief distinction between the eastern and western maria appears to be one of basalt volumes erupted to the surface. Maximum volumes of basalt are deposited west of the central highlands and flood subjacent terrain to a greater extent than on the east. The surface structures of the western maria reflect the probability of a greater degree of isostatic response to a larger surface loading by the greater accumulation of mare basalt.

Dehon, R. A.↗

NASA NTRS1986

Regional-scale estimates of surface moisture availability and thermal inertia using remote thermal measurements

A review is presented of numerical models which were developed to interpret thermal IR data and to identify the governing parameters and surface energy fluxes recorded in the images. Analytic, predictive, diagnostic and empirical models are described. The limitations of each type of modeling approach are explored in terms of the error sources and inherent constraints due to theoretical or measurement limitations. Sample results of regional-scale soil moisture or evaporation patterns derived from the Heat Capacity Mapping Mission and GOES satellite data through application of the predictive model devised by Carlson (1981) are discussed. The analysis indicates that pattern recognition will probably be highest when data are collected over flat, arid, sparsely vegetated terrain. The soil moisture data then obtained may be accurate to within 10-20 percent.

Carlson, T. N.↗

NASA NTRS1988

Plasma acceleration, injection, and loss - Observational aspects

A history of the understanding of the sudden accelerations of charged particles noted in plasmas, and the accompanying intrusions of energized plasma into adjacent regions of space, is presented. It is pointed out that studies of the earth's magnetosphere are hampered by the lack of adequate sampling in space and time. Although the feature matching technique of building magnetic and electric field models can help compensate for the sparseness of experimental data, future studies will nonetheless require large numbers of spacecraft placed in carefully coordinated orbits. The notion that the ignition of portions of the auroral shell in association with earth flares results in the heating of ionospheric particles that are then convected inward to form the ring current is considered.

Mcilwain, C. E.↗

NASA NTRS1995

A search for evolutionary changes in planetary nuclei: A continuation

This report summarizes the final results of an IUE investigation to search for signs of evolutionary changes in high-mass central stars of planetary nuclei, as evidenced by UV-optical fading over the lifetime of the satellite. The program is a continuation of an earlier investigation, expanding the target list to include more types of hot central stars and to obtain more spectra of previously observed stars. In order to compare the IUE fluxes of a central star obtained over a more-than-ten-year timespan, several steps were necessary, including reprocessing of very early spectra and correction for the sensitivity degradation of the SWP camera over time. The results indicate that while a few stars appear to have diminished UV fluxes compared to earlier IUE observations, the evidence for this is less than overwhelming due to the sparseness of the data. Those stars which emerge from this study as viable candidates for having faded are the cooler Of-type stars (O6f-O7f), i.e., those for which the change in spectral energy with increasing temperature is greatest. The report describes the data analysis steps and discusses the uncertainties in both the data and in the resulting fading rates. Estimates of stellar mass based on theoretical evolutionary rates are also provided.

Altner, Bruce↗

NASA NTRS2004

Climatic Analysis of Oceanic Water Vapor Transports Based on Satellite E-P Datasets

Understanding the climatically varying properties of water vapor transports from a robust observational perspective is an essential step in calibrating climate models. This is tantamount to measuring year-to-year changes of monthly- or seasonally-averaged, divergent water vapor transport distributions. This cannot be done effectively with conventional radiosonde data over ocean regions where sounding data are generally sparse. This talk describes how a methodology designed to derive atmospheric water vapor transports over the world oceans from satellite-retrieved precipitation (P) and evaporation (E) datasets circumvents the problem of inadequate sampling. Ultimately, the method is intended to take advantage of the relatively complete and consistent coverage, as well as continuity in sampling, associated with E and P datasets obtained from satellite measurements. Independent P and E retrievals from Special Sensor Microwave Imager (SSM/I) measurements, along with P retrievals from Tropical Rainfall Measuring Mission (TRMM) measurements, are used to obtain transports by solving a potential function for the divergence of water vapor transport as balanced by large scale E - P conditions.

Smith, Eric A.↗

NASA NTRS2003

Adjoint-Based Methods for Estimating CO2 Sources and Sinks from Atmospheric Concentration Data

Work to develop adjoint-based methods for estimating CO2 sources and sinks from atmospheric concentration data was initiated in preparation for last year's summer institute on Carbon Data Assimilation (CDAS) at the National Center for Atmospheric Research in Boulder, CO. The workshop exercises used the GSFC Parameterized Chemistry and Transport Model and its adjoint. Since the workshop, a number of simulations have been run to evaluate the performance of the model adjoint. Results from these simulations will be presented, along with an outline of challenges associated with incorporating a variety of disparate data sources, from sparse, but highly precise, surface in situ observations to less accurate, global future satellite observations.

Andrews, Arlyn E.↗

NASA NTRS1997

Rhenium Rocket Manufacturing Technology

The NASA Lewis Research Center's On-Board Propulsion Branch has a research and technology program to develop high-temperature (2200 C), iridium-coated rhenium rocket chamber materials for radiation-cooled rockets in satellite propulsion systems. Although successful material demonstrations have gained much industry interest, acceptance of the technology has been hindered by a lack of demonstrated joining technologies and a sparse materials property data base. To alleviate these concerns, we fabricated rhenium to C-103 alloy joints by three methods: explosive bonding, diffusion bonding, and brazing. The joints were tested by simulating their incorporation into a structure by welding and by simulating high-temperature operation. Test results show that the shear strength of the joints degrades with welding and elevated temperature operation but that it is adequate for the application. Rhenium is known to form brittle intermetallics with a number of elements, and this phenomena is suspected to cause the strength degradation. Further bonding tests with a tantalum diffusion barrier between the rhenium and C-103 is planned to prevent the formation of brittle intermetallics.

Source record↗