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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

A count probability cookbok: Spurious effects and the scaling model

We study the errors brought by finite volume effects and dilution effects on the practical determination of the count probability distribution function P(sub N)(n,l), which is the probability of having N objects in a cell of volume l cubed for a set of average number density n. Dilution effects are particularly revelant to the so-called sparse sampling strategy. This work is mainly done in the framework of the Bailan & Schaeffer scaling model, which assumes that the Q-body correlation functions obey the scaling relation Xi(sub Q)(lambda r(sub l),....lambda r(sub Q) = lambda(exp -(Q-1)gamma) Xi(sub Q)(r(sub 1),....r(sub Q)). We use three synthetic samples as references to perform our analysis: a fractal generated by a Rayleigh-Levy random walk with approximately 3 x 10(exp 4) objects, a sample dominated by a spherical power-law cluster with approximately 3 x 10(exp 4) objects and a cold dark matter (CDM) universe involving approximately 3 x 10(exp 5) matter particles.

Colombi, S.↗
NASA NTRS1998

Radio Occultation Studies of Venus' Atmosphere with Magellan

We have been conducting a systematic study of the middle and lower atmosphere of Venus through analysis of 20 radio occultation experiments conducted with the Magellan spacecraft between October, 1991, and August, 1994. These studies have revealed a rich but sparsely sampled trove of information regarding the structure, composition and dynamics of the Venus atmosphere. The five sets of experiments sampled a variety of latitudes. Basic results include vertical profiles of: (1) electron density in the ionosphere, (2) pressure, temperature, density, and static stability in the neutral atmosphere (from 33 km to 98 km), and (3) sulfuric acid vapor (H2SO4) abundance below the main cloud deck. Further analysis of the temperature profiles led to the discovery of small vertical-scale gravity waves in the neutral atmosphere. The retrieved profiles show intriguing zonal variations that might be due to planetary- scale waves. During the performance period of this grant, we have concentrated on reanalyzing the 15 experiments conducted in 1994 using improved trajectory files for Magellan provided by JPL, obtaining more reliable results, and on conducting an error analysis of the derived profiles. In addition, we have begun an analysis of microwave emission maps of Venus obtained at the Very Large Array (VLA) in April, 1996. This report is organized as follows: A summary of results is presented, giving representative examples of the various physical profiles retrieved from all the Magellan radio occultation studies, emphasizing latitudinal variations evident in the data. Next, a preliminary analysis of the VLA maps is given. A summary of activities follows the scientific results, detailing papers published and presented at various conferences. This report concludes with a "Conclusions and Suggestions for Future Work" section.

Jenkins, Jon M.↗
NASA NTRS2000

Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by the light and heavy rain rates. This is useful in estimating the fraction of rainfall contributed by the rain rates that go undetected by the radar. The results at high rain rates provide a cross-check on the usual attenuation correction methods that are applied at the highest resolution of the instrument.

Meneghini, R.↗
NASA NTRS2001

Multiwavelength Monitoring of Active Galactic Nuclei

By intensive monitoring of AGN variability over a large range in wavelength, we can probe the structure and physics of active galactic nuclei on microarcsecond angular scales. For example, multi-wavelength variability data allow us (a) to establish causal relationships between variations in different wavebands, and thus determine which physical processes are primary and which spectral changes are induced by variations at other wavelengths, and (b) through reverberation mapping of the UV/optical emission lines, to determine the structure and kinematics of the line-emitting region, and thus accurately determine the central masses in AGNs. Multiwavelength monitoring is resource-intensive, and is difficult to implement with general-purpose facilities. As a result, virtually all programs undertaken to date have been either sparsely sampled, or short in duration, or both. The potentially high return on this type of investigation, however, argues for dedicated facilities for multiwavelength monitoring programs.

Peterson, Bradley M.↗
NASA NTRS2007

Status of the L2 and Lunar Charged Particle Environment Models

The L2 Charged Particle Environment (L2-CPE) model is an engineering tool which provides free field charged particle environments for distant magnetotail, magnetosheath, and solar wind environments. L2-CPE is intended for use in assessing contributions from low energy radiation environments (4.1 keV to few MeV) to radiation dose in thin materials used in construction of spacecraft to be placed in orbit about the Sun-Earth L2 point. This paper describes the status of the current version of the L2-CPE model including structure of the model used to organize plasma environments into solar wind, magnetosheath, and magnetotail environments, the algorithms used to estimate radiation fluence in sparsely sampled environments, the updated graphical user interface, and output options for flux and fluence environments. In addition, we describe the status and plans for updating the model to include environments relevant to lunar programs.

Minow, Joseph I.↗
NASA NTRS2006

Airborne Observations of the Spatial and Temporal Variability of Tropospheric Carbon Dioxide during the INTEX-B Campaign

The Intercontinental Chemical Transport Experiment-North America (INTEX-NA) is an international field campaign envisioned to investigate the transport and transformation of gases and aerosols on transcontinental/intercontinental scales and assess their impact on air quality and climate. Phase B (INTEX-B) of the mission was conducted during a 10- week period from March 1 to May 15, 2006 and focused initially on pollution outflow from the Mexico City Metropolitan Area, later addressing the transport of pollution from Asia to North America during springtime meteorological conditions. During the deployment, fast-response (1-s resolution) CO2 measurements were recorded aboard the NASA DC-8 providing valuable regional-scale information on carbon sources and sinks over sparsely sampled areas of North America and adjacent ocean basins. When coupled with the enormously sophisticated chemistry payload on the DC-8, these measurements collectively afford extremely powerful multi-tracer constraints for carbon source/sink attribution. Preliminary examination of the two data sets from the INTEX-B campaign, acquired one month apart, reveals not only the influence of the CO2 seasonal cycle, but also the preponderance of human population and industrial activity in the northern hemisphere. In this presentation, a synergy of the ensemble of airborne and surface observations, bottomup emission inventories, as well as transport history are invoked in a GIS framework to elucidate the source/sink processes reflected in the observations. The airborne CO2 data, along with simultaneous surface measurements (e.g. NOAA ESRL), are examined to establish the vertical distribution and variability of CO2 as a function of location. The role of localized sources, long-range transport, the biosphere, stratospheric exchange, and dynamical processes on the CO2 spatial variability observed throughout the tropospheric column will be discussed.

Vay, Stephanie A.↗
NASA NTRS2008

Enhanced Reporting of Mars Exploration Rover Telemetry

Mars Exploration Rover Enhanced Telemetry Extraction and Reporting System (METERS) is software that generates a human-readable representation of the state of the mobility and arm-related systems of the Mars Exploration Rover (MER) vehicles on each Martian solar day (sol). Data are received from the MER spacecraft in multiple streams having various formats including text messages, sparsely-sampled engineering quantities, images, and individual motor-command histories.

Maimone, Mark W.↗
NASA NTRS2014

Reevaluation of Stratospheric Ozone Trends From SAGE II Data Using a Simultaneous Temporal and Spatial Analysis

This paper details a new method of regression for sparsely sampled data sets for use with time-series analysis, in particular the Stratospheric Aerosol and Gas Experiment (SAGE) II ozone data set. Non-uniform spatial, temporal, and diurnal sampling present in the data set result in biased values for the long-term trend if not accounted for. This new method is performed close to the native resolution of measurements and is a simultaneous temporal and spatial analysis that accounts for potential diurnal ozone variation. Results show biases, introduced by the way data is prepared for use with traditional methods, can be as high as 10%. Derived long-term changes show declines in ozone similar to other studies but very different trends in the presumed recovery period, with differences up to 2% per decade. The regression model allows for a variable turnaround time and reveals a hemispheric asymmetry in derived trends in the middle to upper stratosphere. Similar methodology is also applied to SAGE II aerosol optical depth data to create a new volcanic proxy that covers the SAGE II mission period. Ultimately this technique may be extensible towards the inclusion of multiple data sets without the need for homogenization.

Damadeo, R. P.↗
NASA NTRS2015

Predicting the Mineral Composition of Dust Aerosols: Model Evaluation and Identification of Key Processes with Observations - Part 2

A global compilation of nearly sixty measurement studies is used to evaluate two methods of simulating the mineral composition of dust aerosols in an Earth system model. Both methods are based upon a Mean Mineralogical Table (MMT) that relates the soil mineral fractions to a global atlas of arid soil type. The Soil Mineral Fraction (SMF) method assumes that the aerosol mineral fractions match the fractions of the soil. The MMT is based upon soil measurements after wet sieving, a process that destroys aggregates of soil particles that would have been emitted from the original, undisturbed soil. The second method approximately reconstructs the emitted aggregates. This model is referred to as the Aerosol Mineral Fraction (AMF) method because the mineral fractions of the aerosols differ from those of the wet-sieved parent soil, partly due to reaggregation. The AMF method remedies some of the deficiencies of the SMF method in comparison to observations. Only the AMF method exhibits phyllosilicate mass at silt sizes, where they are abundant according to observations. In addition, the AMF quartz fraction of silt particles is in better agreement with measured values, in contrast to the overestimated SMF fraction. Measurements at distinct clay and silt particle sizes are shown to be more useful for evaluation of the models, in contrast to the sum over all particles sizes that is susceptible to compensating errors, as illustrated by the SMF experiment. Model errors suggest that allocation of the emitted silt fraction of each mineral into the corresponding transported size categories is an important remaining source of uncertainty. Evaluation of both models and the MMT is hindered by the limited number of size-resolved measurements of mineral content that sparsely sample aerosols from the major dust sources. The importance of climate processes dependent upon aerosol mineral composition shows the need for global and routine mineral measurements.

aerosols↗
NASA NTRS2016

Spitzer Space Telescope Mid-IR Light Curves of Neptune

We have used the Spitzer Space Telescope in 2016 February to obtain high cadence, high signal-to-noise, 17 hr duration light curves of Neptune at 3.6 and 4.5 microns. The light curve duration was chosen to correspond to the rotation period of Neptune. Both light curves are slowly varying with time, with full amplitudes of 1.1 mag at 3.6 microns and 0.6 mag at 4.5 microns. We have also extracted sparsely sampled 18 hr light curves of Neptune at W1 (3.4 microns) and W2 (4.6 microns) from the Wide-field Infrared Survey Explorer (WISE)/NEOWISE archive at six epochs in 2010-2015. These light curves all show similar shapes and amplitudes compared to the Spitzer light curves but with considerable variation from epoch to epoch. These amplitudes are much larger than those observed with Kepler/K2 in the visible (amplitude approximately 0.02 mag) or at 845 nm with the Hubble Space Telescope (HST) in 2015 and at 763 nm in 2016 (amplitude approximately 0.2 mag). We interpret the Spitzer and WISE light curves as arising entirely from reflected solar photons, from higher levels in Neptune's atmosphere than for K2. Methane gas is the dominant opacity source in Neptune's atmosphere, and methane absorption bands are present in the HST 763 and 845 nm, WISE W1, and Spitzer 3.6 micron filters.

Individual (Neptune)↗
NASA NTRS2017

The First Twenty Years (1994 2014) of Ozone Soundings from Rapa Nui (27 deg S, 109 deg W, 51 m a.s.l.)

Ozone (O3) soundings have been performed on Easter Island or Rapa Nui (27 8S, 109 8W, 51 m a.s.l.) since 1994 as part of the Global Atmospheric Watch Programme of the World Meteorological Organization. In this work, we analyze 260 soundings compiled over the period 19942014, and make the data available for the international community. We characterize O3 profiles over this remote area of the Pacific by means of statistical analyses that consider, on the one hand, a traditional climatology that describes the data in terms of seasonal cycles based on monthly averages and, on the other hand, a process-oriented analysis based on self-organizing maps. Our analyses show the influence of both tropical and subtropical/mid-latitude air masses at Rapa Nui. The former occurs in summer and fall when convective conditions prevail, and the latter in late winter and spring when subsiding conditions are recurrent. The occurrence of stratospheric intrusions in late winter and spring in connection with deep troughs and the presence of the subtropical jet stream is also apparent in the data set. The tropospheric ozone column is in good agreement with the corresponding data derived from satellites but with a systematic overestimate of summer and fall values. There is evidence of an upward trend in ozone near the surface, which suggests the impact of local pollution. We look forward to an enhancement of the Rapa Nui observing site, given its location that offers a privileged position to observe climate change over the sparsely sampled and vast South Pacific Ocean.

tropical and subtropical/mid-latitude air masses↗
NASA NTRS2016

Deep HST/STIS Visible-Light Imaging of Debris Systems Around Solar Analog Hosts

We present new Hubble Space Telescope observations of three a priori known starlight-scattering circumstellar debris systems (CDSs) viewed at intermediate inclinations around nearby close-solar analog stars: HD 207129, HD202628, and HD 202917. Each of these CDSs possesses ring-like components that are more massive analogs of our solar systems Edgeworth Kuiper Belt. These systems were chosen for follow-up observations to provide imaging with higher fidelity and better sensitivity for the sparse sample of solar-analog CDSs that range over two decades in systemic ages, with HD 202628 and HD 207129 (both approx. 2.3 Gyr) currently the oldest CDSs imaged in visible or near-IR light. These deep (10-14 ks) observations, made with six-roll point-spread-function template visible-light coronagraphy using the Space Telescope Imaging Spectrograph, were designed to better reveal their angularly large debris rings of diffuse low surface brightness, and for all targets probe their exo-ring environments for starlight-scattering materials that present observational challenges for current ground-based facilities and instruments. Contemporaneously also observing with a narrower occulter position, these observations additionally probe the CDS endo-ring environments that are seen to be relatively devoid of scatterers. We discuss the morphological, geometrical, and photometric properties of these CDSs also in the context of other CDSs hosted by FGK stars that we have previously imaged as a homogeneously observed ensemble. From this combined sample we report a general decay in quiescent-disk F disk /F star optical brightness approx. t( exp.-0.8), similar to what is seen at thermal IR wavelengths, and CDSs with a significant diversity in scattering phase asymmetries, and spatial distributions of their starlight-scattering grains.

starlight-scattering circumstellar debris systems ↗
NASA NTRS2017

OGLE-2013-BLG-1761Lb: A Massive Planet around an MK Dwarf

We report the discovery and the analysis of the planetary microlensing event, OGLE-2013-BLG-1761. There are some degenerate solutions in this event because the planetary anomaly is only sparsely sampled. However, the detailed light curve analysis ruled out all stellar binary models and shows the lens to be a planetary system. There is the so-called close wide degeneracy in the solutions with the planet host mass ratio of q approx.(7.0+/-2.0) x 10(exp -3) and q approx.(8.1+/-2.6) x 10(exp -3) with the projected separation in Einstein radius units of s = 0.95 (close) and s = 1.18(wide), respectively. The microlens parallax effect is not detected, but the finite source effect is detected. Our Bayesian analysis indicates that the lens system is located -D(sub L) = 6.9(+ 1.0 -1.2)kpc away from us and the host star is an M/K dwarf with amass of M(sub L) = 0.33(+ 0.32- 1.9)Stellar Mass orbited by a super-Jupiter mass planet with a mass of m(sub p) = 2.7(+ 2.5 - 1.5) M(sub Jup) at the projected separation of a(sub l) = 1.8(+ 0.5 -0.5)au. The preference of the large lens distance in the Bayesian analysis is due to the relatively large observed source star radius. The distance and other physical parameters may be constrained by the future high-resolution imaging by large ground telescopes or HST. If the estimated lens distance is correct, then this planet provides another sample for testing the claimed deficit of planets in the Galactic bulge.

Hirao, Y.↗
NASA NTRS2018

Artificial Neural Networks for Determining Magnetospheric Conditions

This chapter presents a neural-network-based technique that allows for the reconstruction of the global, time-varying distribution of some physical quantity Q, that has been sparsely sampled at various locations within the magnetosphere, and at different times. We begin with a general introduction to the problem of prediction and specification, and why it is important and difficult to achieve with existing methods. We then provide a basic introduction to neural networks, and describe our technique using the specific example of reconstructing the electron plasma density in the Earth's inner magnetosphere on the equatorial plane. We then show more advanced uses of the technique, including 3D reconstruction of the plasma density, specification of chorus and hiss waves, and energetic particle fluxes. We summarize and conclude with a general discussion of how machine learning techniques might be used to advance the state-of-the-art in space weather prediction, and insight discovery.

Bortnik, Jacob↗
NASA NTRSDate not supplied

TPSAS-NF1676L-17943-DND

SAGE II used the solar occultation technique to measure atmospheric ozone for 21 years between 1984 and 2005 and has continued to play a key role in numerous international assessments. Traditionally, the determination of trends in ozone using SAGE II data has been done via time series analysis of monthly mean data within specific latitude bands. However, given the sparse sampling of SAGE II data, this will introduce temporal and/or spatial biases, particularly in the period after late 2000 when the instrument operated at half-duty cycle. Herein we present a new method for performing time series analysis of unevenly sampled data (in particular SAGE II); namely, we utilize the daily mean data and perform a simultaneous temporal and spatial analysis, making use of a Fourier series to constrain latitudinal variation. This methodology is applied to both the previous (v6.2) and current (v7.0) versions of the SAGE II data. Results are discussed that show the improvements to the data between versions 6.2 and 7.0 that make time series analysis produce reduced residuals as well as the preliminary results of the time series itself, which reveal some of the limitations in currently used proxies for the regression.

Robert P Damadeo↗
NASA NTRSDate not supplied

Remote Sensing of Lineage Functional Types for Modeling and Monitoring Biodiversity

Hyperspectral remote sensing has the potential to continuously scale plant function and plant diversity information from landscape to global extents. Numerous studies have indicated that VSWIR (400-2500 nm) reflectance properties of vegetation capture evolutionarily conserved biochemical, structural, and other functional attributes of plant species. Spectral properties conserved in plants provide the opportunity to both 1) aggregate species into lineages with improved classification accuracy and 2) link those lineages directly to plant traits. Full realization of this goal will enable parameterization of Land Surface Models (LSMs) with remotely sensed information, e.g., canopy nitrogen, and better representations of biodiversity and functional diversity in biogeographic studies. In this study, we use hyperspectral AVIRIS data from the 2013 HyspIRI campaign over the Southern Sierra Nevada, California flight box to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from roughly 1372 surveys and a phylogeny representing 1361 species. We aggregate species into lineages ranging from species level groups down to similar number of Plant Functional Types as often used in LSMs. We assessed the ability of Random Forest and Partial Least Squares Discriminant Analysis to discriminate across these different phylogenetic scales and determine the optimal number of lineages to classify. Although there are some temporal and spatial differences in our training data, our best approaches achieved moderate classification accuracy (Kappa > 0.65). Given an optimal number of lineages, we explored approaches to improve classifications including machine learning and unmixing approaches. This work suggests that lineage-based methods may be a promising way to leverage the huge amounts of data that will come from high resolution and high return interval hyperspectral data planned for the Surface Biology and Geology mission with sparsely sampled existing ground-based ecological data.

Hyperspectral↗
NASA NTRS2021

Assimilation of DAWN Doppler Wind Lidar Data During the 2017 Convective Processes Experiment (CPEX): Impact on Precipitation and Flow Structure

An improved representation of 3-D air motion and precipitation structure through forecast models and assimilation of observations is vital for improvements in weather forecasting capabilities. However, there are few independent data to properly validate a model forecast of precipitation structure when the underlying dynamics are evolving on short convective timescales. Using data from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2 μmDoppler Aerosol Wind (DAWN) lidar collected during the2017 Convective Processes Experiment (CPEX), the NASA Unified Weather Research and Forecasting (WRF) Ensemble Data Assimilation System (EDAS) modeling system was used to quantify the impact of high-resolution sparsely sampled DAWN measurements on the analyzed variables and on the forecast when the DAWN winds were assimilated. Over-all, the assimilation of the DAWN wind profiles had a discernible impact on the wind field as well as the evolution and timing of the 3-D precipitation structure. Analysis of individual variables revealed that the assimilation of the DAWN winds resulted in important and coherent modifications of the environment. It led to an increase in the near-surface convergence, temperature, and water vapor, creating more favorable conditions for the development of convection exactly where it was observed (but not present in the control run). Comparison to APR-2 and observations by the Global Precipitation Measurement (GPM) satellite shows a much-improved forecast after the assimilation of the DAWN winds – development of precipitation where there was none, more organized precipitation where there was some, and a much more intense and organized cold pool, similar to the analysis of the dropsonde data. The onset of the vertical evolution of the precipitation showed similar radar-derived cloud-top heights, but delayed in time. While this investigation was limited to a single CPEX flight date, the investigation design is appropriate for further investigation of the impact of airborne Doppler wind lidar observations upon short-term convective precipitation forecasts

DAWN↗
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↗