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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Gravitational model improvement at the Goddard Space Flight Center

Major new computations of terrestrial gravitational field models were performed by the Geodynamics Branch of Goddard Space Flight Center (GSFC). This development has incorporated the present state of the art results in satellite geodesy and have relied upon a more consistent set of reference constants than was heretofore utilized in GSFC's GEM models. The solutions are complete in spherical harmonic coefficients out to degree 50 for the gravity field parameters. These models include adjustment for a subset of 66 ocean tidal coefficients for the long wavelength components of 12 major ocean tides. This tidal adjustment was made in the presence of 550 other fixed ocean tidal terms representing 32 major and minor ocean tides and the Wahr frequency dependent solid earth tidal model. In addition 5-day averaged values for Earth rotation and polar motion were derived for the time period of 1980 onward. Two types of models were computed. These are satellite only models relying exclusively on tracking data and combination models which have incorporated satellite altimetry and surface gravity data. The satellite observational data base consists of over 1100 orbital arcs of data on 31 satellites. A large percentage of these observations were provided by third generation laser stations (less than 5 cm). A calibration of the model accuracy of the GEM-T2 satellite only solution indicated that it was a significant improvement over previous models based solely upon tracking data. The rms geoid error for this field is 110 cm to degree and order 36. This is a major advancement over GEM-T1 whose errors were estimated to be 160 cm. An error propagation using the covariances of the GEM-T2 model for the TOPEX radial orbit component indicates that the rms radial errors are expected to be 12 cm. The combination solution, PGS-3337, is a preliminary effort leading to the development of GEM-T3. PGS-3337 has incorporated global sets of surface gravity data and the Seasat altimetry to produce a model complete to (50,50). A solution for the dynamic ocean topography to degree and order 10 was included as part of this adjustment.

Marsh, J. G.↗
DOE OSTI2020

The Coupled Influence of Thermal Physiology and Biotic Interactions on the Distribution and Density of Ant Species along an Elevational Gradient

A fundamental tenet of biogeography is that abiotic and biotic factors interact to shape the distributions of species and the organization of communities, with interactions being more important in benign environments, and environmental filtering more important in stressful environments. This pattern is often inferred using large databases or phylogenetic signal, but physiological mechanisms underlying such patterns are rarely examined. We focused on 18 ant species at 29 sites along an extensive elevational gradient, coupling experimental data on critical thermal limits, null model analyses, and observational data of density and abundance to elucidate factors governing species’ elevational range limits. Thermal tolerance data showed that environmental conditions were likely to be more important in colder, more stressful environments, where physiology was the most important constraint on the distribution and density of ant species. Conversely, the evidence for species interactions was strongest in warmer, more benign conditions, as indicated by our observational data and null model analyses. Our results provide a strong test that biotic interactions drive the distributions and density of species in warm climates, but that environmental filtering predominates at colder, high-elevation sites. Such a pattern suggests that the responses of species to climate change are likely to be context-dependent and more specifically, geographically-dependent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Dissecting galaxy formation models with sensitivity analysis—a new approach to constrain the Milky Way formation history

We present an application of a statistical tool known as sensitivity analysis to characterize the relationship between input parameters and observational predictions of semi-analytic models of galaxy formation coupled to cosmological N-body simulations. We show how a sensitivity analysis can be performed on our chemo-dynamical model, ChemTreeN, to characterize and quantify its relationship between model input parameters and predicted observable properties. The result of this analysis provides the user with information about which parameters are most important and most likely to affect the prediction of a given observable. It can also be used to simplify models by identifying input parameters that have no effect on the outputs (i.e., observational predictions) of interest. Conversely, sensitivity analysis allows us to identify what model parameters can be most efficiently constrained by the given observational data set. We have applied this technique to real observational data sets associated with the Milky Way, such as the luminosity function of the dwarf satellites. The results from the sensitivity analysis are used to train specific model emulators of ChemTreeN, only involving the most relevant input parameters. This allowed us to efficiently explore the input parameter space. A statistical comparison of model outputs and real observables is used to obtain a 'best-fitting' parameter set. We consider different Milky-Way-like dark matter halos to account for the dependence of the best-fitting parameter selection process on the underlying merger history of the models. For all formation histories considered, running ChemTreeN with best-fitting parameters produced luminosity functions that tightly fit their observed counterpart. However, only one of the resulting stellar halo models was able to reproduce the observed stellar halo mass within 40 kpc of the Galactic center. On the basis of this analysis, it is possible to disregard certain models, and their corresponding merger histories, as good representations of the underlying merger history of the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2002

Kinetics of Fast Atoms in the Terrestrial Atmosphere

This report summarizes our investigations performed under NASA Grant NAG5-8058. The three-year research supported by the Geospace Sciences SR&T program (Ionospheric, Thermospheric, and Mesospheric Physics) has been designed to investigate fluxes of energetic oxygen and nitrogen atoms in the terrestrial thermosphere. Fast atoms are produced due to absorption of the solar radiation and due to coupling between the ionosphere and the neutral thermospheric gas. We have investigated the impact of hot oxygen and nitrogen atoms on the thermal balance, chemistry and radiation properties of the terrestrial thermosphere. Our calculations have been focused on the accurate quantitative description of the thermalization of O and N energetic atoms in collisions with atom and molecules of the ambient neutral gas. Upward fluxes of oxygen and nitrogen atoms, the rate of atmospheric heating by hot oxygen atoms, and the energy input into translational and rotational-vibrational degrees of atmospheric molecules have been evaluated. Altitude profiles of hot oxygen and nitrogen atoms have been analyzed and compared with available observational data. Energetic oxygen atoms in the terrestrial atmosphere have been investigated for decades, but insufficient information on the kinetics of fast atmospheric atoms has been a main obstacle for the interpretation of observational data and modeling of the hot geocorona. The recent development of accurate computational methods of the collisional kinetics is seen as an important step in the quantitative description of hot atoms in the thermosphere. Modeling of relaxation processes in the terrestrial atmosphere has incorporated data of recent observations, and theoretical predictions have been tested by new laboratory measurements.

Kharchenko, Vasili A.↗
NASA NTRS1977

Proportionality between Doppler noise and integrated signal path electron density validated by differenced S-X range

Observations of Viking differenced S-band/X-band (S-X) range are shown to correlate strongly with Viking Doppler noise. A ratio of proportionality between downlink S-band plasma-induced range error and two-way Doppler noise is calculated. A new parameter (similar to the parameter epsilon which defines the ratio of local electron density fluctuations to mean electron density) is defined as a function of observed data sample interval (Tau) where the time-scale of the observations is 15 Tau. This parameter is interpreted to yield the ratio of net observed phase (or electron density) fluctuations to integrated electron density (in RMS meters/meter). Using this parameter and the thin phase-changing screen approximation, a value for the scale size L is calculated. To be consistent with Doppler noise observations, it is seen necessary for L to be proportional to closest approach distance a, and a strong function of the observed data sample interval, and hence the time-scale of the observations.

Berman, A. L.↗
NASA NTRS2020

Evaluation of adjoint-based observation impacts as a function of forecast length using an Observing System Simulation Experiment

Adjoints of numerical weather prediction models may be employed for Forecast Sensitivity to Observation (FSO) in order to monitor the contribution of ingested observation data on short-term forecast skill. However, the calculation of short-term forecast error is difficult due to the lack of a truly independent dataset for verification. In an Observing System Simulation Experiment framework, the Nature Run is able to provide a true and complete verification dataset and allows accurate evaluation of short term forecast errors. In this work, an OSSE developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office is used to explore the impact of observational data on forecasts in the 6 to 48 hour range. An adjoint of the Global Earth Observing System model is employed to compare the observation impacts estimated using both self-analysis verification and the true Nature Run verification. Self-analysis verification is found to inflate the estimated forecast error growth during the early forecast period, resulting in overestimations of observation impacts, particularly in the 6-12 hour forecast range. By 48 hours, the self-analysis verification estimates of forecast error and observation impacts more closely match the true values. The fraction of beneficial observations is also overinflated at short forecast times when self-analysis verification is used. The progression of impacts of an individual observation or data type depends on the character of the growth of the initial condition error that each observation affects.

numerical weather prediction↗
DOE OSTI2021

A data-driven global soil heterotrophic respiration dataset and the drivers of its inter-annual variability

Soil heterotrophic respiration (SHR), one of the primary carbon fluxes from terrestrial ecosystems to the atmosphere, is important for carbon-climate feedbacks because of its sensitivity to available litter and soil carbon, climatic conditions, and nutrient availability. However, until recently limited SHR data were available, and most published global SHR estimates have either a short time span, coarse spatial resolution, or reply on overly-simple model formulations. To better understand and quantify the global distribution of SHR and its sensitivity to climate variability, we produced a new global SHR dataset using Random Forest algorithms, up-scaling 455 point data from the Global Soil Respiration Database (SRDB 4.0) with gridded fields of climatic, edaphic and productivity as explanatory variables. We estimated a global total SHR of 46.8 Pg C yr-1 over 1985-2013 (95% confidence interval: 38.6-56.3 Pg C yr-1), with a significant increasing trend of 0.03 Pg C yr-2 during this period. We found that the choice of soil moisture datasets contributes more to the difference among these data-driven SHR members rather than that of productivity, temperature and precipitation data sources. We also analyzed the influence of climatic variables on the inter-annual variability (IAV) of our SHR product. Water availability was the dominant driver of IAV at global scales, although the inferred sensitivity depends on the choice of the soil moisture gridded dataset. At the ecosystem scale, temperature strongly controls the IAV of SHR in tropical forests, while water availability dominates in extra-tropical forest and semi-arid regions. Our machine-learning gridded SHR dataset and outputs from process-based land surface models (TRENDYv6) show agreement for a strong association between water variability and SHR IAV at the global scale, but the two approaches lead to different temporal trend globally and different controlling variables for IAV at the ecosystem scale. Our study provides evidence for the pervasive and important role of water availability in driving SHR, indicating both a direct effect limiting decomposition rates and an indirect effect through the amount of fresh organic matter made available to SHR from productivity. In consideration of potential limitations and uncertainties remaining in our data-driven SHR datasets, we call for a more scientifically designed observation network for SHR, more observation data compilation, and increased use of deep learning methods making maximum use of observation data in hand. This will benefit process-based models, and improve our understanding of SHR response to future anomalous environmental conditions.

Yao, Yitong↗
NASA NTRS2006

Validation of CALIPSO Lidar Observations Using Data From the NASA Langley Airborne High Spectral Resolution Lidar

This poster focuses on preliminary comparisons of data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spacecraft with data acquired by the NASA Langley Airborne High Spectral Resolution Lidar (HSRL). A series of 20 aircraft validation flights was conducted from 14 June through 27 September 2006, under both day and night lighting conditions and a variety of aerosol and cloud conditions. This poster presents comparisons of CALIOP measurements of attenuated backscatter at 532 and 1064 nm and depolarization at 532 nm with near coincident measurements from the Airborne HSRL as a preliminary assessment of CALIOP calibration accuracy. Note that the CALIOP data presented here are the pre-release version. These data have known artifacts in calibration which have been corrected in the December 8 CALIPSO data release which was not available at the time the comparisons were conducted for this poster. The HSRL data are also preliminary. No artifacts are known to exist; however, refinements in calibration and algorithms are likely to be implemented before validation comparisons are made final.

Hostetler, Chris↗
DOE OSTI2020

Interactions Between the Amazonian Rainforest and Cumuli Clouds: A Large‐Eddy Simulation, High‐Resolution ECMWF, and Observational Intercomparison Study

Abstract The explicit coupling at meter and second scales of vegetation's responses to the atmospheric‐boundary layer dynamics drives a dynamic heterogeneity that influences canopy‐top fluxes and cloud formation. Focusing on a representative day during the Amazonian dry season, we investigate the diurnal cycle of energy, moisture and carbon dioxide at the canopy top, and the transition from clear to cloudy conditions. To this end, we compare results from a large‐eddy simulation technique, a high‐resolution global weather model, and a complete observational data set collected during the GoAmazon14/15 campaign. The overall model‐observation comparisons of radiation and canopy‐top fluxes, turbulence, and cloud dynamics are very satisfactory, with all the modeled variables lying within the standard deviation of the monthly aggregated observations. Our analysis indicates that the timing of the change in the daylight carbon exchange, from a sink to a source, remains uncertain and is probably related to the stomata closure caused by the increase in vapor pressure deficit during the afternoon. We demonstrate quantitatively that heat and moisture transport from the subcloud layer into the cloud layer are misrepresented by the global model, yielding low values of specific humidity and thermal instability above the cloud base. Finally, the numerical simulations and observational data are adequate settings for benchmarking more comprehensive studies of plant responses, microphysics, and radiation.

Vilà‐Guerau de Arellano, J.↗
DOE OSTI2015

THE PANCHROMATIC STARBURST IRREGULAR DWARF SURVEY (STARBIRDS): OBSERVATIONS AND DATA ARCHIVE

Understanding star formation in resolved low mass systems requires the integration of information obtained from observations at different wavelengths. We have combined new and archival multi-wavelength observations on a set of 20 nearby starburst and post-starburst dwarf galaxies to create a data archive of calibrated, homogeneously reduced images. Named the panchromatic “STARBurst IRregular Dwarf Survey” archive, the data are publicly accessible through the Mikulski Archive for Space Telescopes. This first release of the archive includes images from the Galaxy Evolution Explorer Telescope (GALEX), the Hubble Space Telescope (HST), and the Spitzer Space Telescope (Spitzer) Multiband Imaging Photometer instrument. The data sets include flux calibrated, background subtracted images, that are registered to the same world coordinate system. Additionally, a set of images are available that are all cropped to match the HST field of view. The GALEX and Spitzer images are available with foreground and background contamination masked. Larger GALEX images extending to 4 times the optical extent of the galaxies are also available. Finally, HST images convolved with a 5″ point spread function and rebinned to the larger pixel scale of the GALEX and Spitzer 24 μm images are provided. Future additions are planned that will include data at other wavelengths such as Spitzer IRAC, ground-based Hα, Chandra X-ray, and Green Bank Telescope H i imaging.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Uncovering Where Compensating Errors Could Hide in ENDF/B-VIII.0

Unconstrained physics spaces between two or more nuclear data observables in a library occur when their values can be simultaneously adjusted without violating the uncertainties in either differential information or simulations of relevant integral experiments. Differential data are often too imprecise to fully bound all nuclear data observables of interest for application simulations. Integral data are simulated with combinations of nuclear data so that an error in one observable may be hidden by a counterbalancing error in another. In this manner compensating errors may lurk within nuclear data libraries and these errors have the potential to undermine the predictive power of neutron transport simulations, particularly in situations where there is no conclusive validation experiment that resembles the application of interest. The EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) developed a preliminary workflow to identify these unconstrained physics spaces by bringing together results from a large collection of integral experiments with their simulated counter-parts as well as differential information that have a one-to-one correspondence to nuclear data. This wealth of information is processed by machine learning tools for subsequent refinement by human experts. Here, we show how the EUCLID work-flow is executed by applying it first to 239 Pu and then to 9 Be nuclear data in ENDF/B-VIII.0.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Uncovering Where Compensating Errors Could Hide in ENDF/B-VIII.0

Unconstrained physics spaces between two or more nuclear data observables in a library occur when their values can be simultaneously adjusted without violating the uncertainties in either differential information or simulations of relevant integral experiments. Differential data are often too imprecise to fully bound all nuclear data observables of interest for application simulations. Integral data are simulated with combinations of nuclear data so that an error in one observable may be hidden by a counterbalancing error in another. In this manner compensating errors may lurk within nuclear data libraries and these errors have the potential to undermine the predictive power of neutron transport simulations, particularly in situations where there is no conclusive validation experiment that resembles the application of interest. The EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) developed a preliminary workflow to identify these unconstrained physics spaces by bringing together results from a large collection of integral experiments with their simulated counter-parts as well as differential information that have a one-to-one correspondence to nuclear data. This wealth of information is processed by machine learning tools for subsequent refinement by human experts. Here, we show how the EUCLID work-flow is executed by applying it first to 239 Pu and then to 9 Be nuclear data in ENDF/B-VIII.0.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2015

High-Resolution Mesoscale Model Setup for the Eastern Range and Wallops Flight Facility

Mesoscale weather conditions can have an adverse effect on space launch, landing, ground processing, and weather advisories, watches, and warnings at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally-driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. These convective processes often last 60 minutes or less and pose a significant challenge to the local forecasters. Surface winds during the transition seasons (spring and fall) pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned local data assimilation (DA) and forecast model at a high resolution is needed to provide improved capability. To accomplish this, a number of sensitivity tests were performed using the Weather Research and Forecasting (WRF) model in order to determine the best DA/model configuration for operational use at each of the space launch ranges to best predict winds, precipitation, and temperature. A set of Perl scripts to run the Gridpoint Statistical Interpolation (GSI)/WRF in real-time were provided by NASA's Short-term Prediction Research and Transition Center (SPoRT). The GSI can analyze many types of observational data including satellite, radar, and conventional data. The GSI/WRF scripts use a cycled GSI system similar to the operational North American Mesoscale (NAM) model. The scripts run a 12-hour pre-cycle in which data are assimilated from 12 hours prior up to the model initialization time. A number of different model configurations were tested for both the ER and WFF by varying the horizontal resolution on which the data assimilation was done. Three different grid configurations were run for the ER and two configurations were run for WFF for archive cases from 27 Aug 2013 through 10 Nov 2013. To quantify model performance, standard model output will be compared to the Meteorological Assimilation Data Ingest System (MADIS) data. The MADIS observation data will be compared to the WRF forecasts using the Model Evaluation Tools (MET) verification package. In addition, the National Centers for Environmental Prediction's Stage IV precipitation data will be used to validate the WRF precipitation forecasts. The author will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for each space launch range.

Watson, Leela R.↗
NASA NTRSDate not supplied

A Novel Architecture of JupyterHub on Amazon Elastic Kubernetes Service for Open Data Cube Sandbox

The Open Data Cube (ODC) initiative, with support from the Committee on Earth Observation Satellites (CEOS) System Engineering Office (SEO) has developed a state-of-the-art suite of software tools and products to facilitate the analysis of Earth Observation data. This paper presents a short summary of our novel architecture approach in a project related to the Open Data Cube (ODC) community that provides users with their own ODC sandbox environment. Users can have a sandbox environment all to themselves for the purpose of running Jupyter notebooks that leverage the ODC. This novel architecture layout will remove the necessity of hosting multiple users on a single Jupyter notebook server and provides better management tooling for handling resource usage. In this new layout each user will have their own credentials which will give them access to a personal Jupyter notebook server with access to a fully deployed ODC environment enabling exploration of solutions to problems that can be supported by Earth observation data.

Open Data Cube↗
NASA NTRS1974

Post-flight differential correction analysis using Vinti's spheroidal method for the small astronomy satellite orbit

The results of an intensive analysis of a differential orbit improvement method utilizing observational data for a 550-kilometer altitude, near-circular, near-equatorial satellite orbit are presented. Observations of the Small Astronomy Satellite (SAS-1) are in the form of direction cosines as measured at two ground interferometer tracking stations near the Equator during the first 22 orbital revolutions (approximately 37 hours) after launch of the spacecraft. Numerical results, in both tabular and graphical form, are displayed for numerous iterated fittings of various observational arcs by differential correction of the orbital elements. Parameters varied in these comparative cases include the time duration of the observational data block, the number of pairs of direction cosine data and the number of tracking station passes included in the solution, the distribution of such passes between the two available tracking stations, and the acceptance criterion for the observational residuals in the least squares fitting procedure. It was found that three observational pairs of direction cosine data, the minimum number possible for a uniquely determined solution in theory, are sufficient to promote covergence to an accurate solution, if properly selected.

Walden, H.↗
NASA NTRS1991

Interiors and atmospheres of the outer planets

This theoretical/observational project constrains structure of outer planet atmospheres and interiors through observational data. The primary observation tool is through observations of occultations of stars by outer solar system objects, which yield information about atmospheric temperatures and dynamics, and planetary dimensions and oblateness. The theoretical work relates the data to interior structures in a variety of ways.

Hubbard, W. B.↗
NASA NTRS1987

Interannual variability of Mars' south polar cap

Published observational data on the seasonal recession of the south polar cap on Mars (covering the period 1903-1977) are compiled in tables and graphs and analyzed statistically. The basic data set (photographic observations obtained at Lowell Observatory) of Fischbacher et al. (1960) and James and Lumme (1982) and the reduction procedures described by Baum and Martin (1973) are employed, and Viking data from 1977 are used for comparison; the early onset (relative to the mean) of the 1956 recession is characterized in detail. A list of photographically documented large dust storms is provided, and it is suggested that in years with early spring storms, recession may be slower than in years without such storms.

James, Philip B.↗