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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Exploring an Ensemble-Based Approach to Atmospheric Climate Modeling and Testing at Scale

A strict throughput requirement has placed a cap on the degree to which we can depend on the execution of single, long, fine spatial grid simulations to explore global atmospheric climate behavior. Alternatively, running an ensemble of short simulations is computationally more efficient. We test the null hypothesis that the climate statistics of a full-complexity atmospheric model derived from an ensemble of independent short simulation is equivalent to that from an equilibrated long simulation. The climate of short simulation ensembles is statistically distinguishable from that of a long simulation in terms of the distribution of global annual means, largely due to the presence of low-frequency atmospheric intrinsic variability in the long simulation. We also find that model climate statistics of the simulation ensemble are sensitive to the choice of compiler optimizations. While some answer-changing optimization choices do not effect the climate state in terms of mean, variability and extremes, aggressive optimizations can result in significantly different climate states.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

gdess: A framework for evaluating simulated atmospheric CO 2 in Earth System Models

Atmospheric carbon dioxide (CO 2 ) plays a key role in the global carbon cycle and global warming. Climate-carbon feedbacks are often studied and estimated using Earth System Models (ESMs), which couple together multiple model components—including the atmosphere, ocean, terrestrial biosphere, and cryosphere—to jointly simulate mass and energy exchanges within and between these components. Despite tremendous advances, model intercomparisons and benchmarking are aspects of ESMs that warrant further improvement (Fer et al., 2021; Smith et al., 2014). Such benchmarking is critical because comparing the value of state variables in these simulations against observed values provides evidence for appropriately refining model components; moreover, researchers can learn much about Earth system dynamics in the process (Randall et al., 2019). We introduce `gdess` (a.k.a., Greenhouse gas Diagnostics for Earth System Simulations), which parses observational datasets and ESM simulation output, combines them to be in a consistent structure, computes statistical metrics, and generates diagnostic visualizations. In its current incarnation, `gdess` facilitates evaluating a model's ability to reproduce observed temporal and spatial variations of atmospheric CO 2 . The diagnostics implemented modularly in `gdess` support more rapid assessment and improvement of model-simulated global CO 2 sources and sinks associated with land and ocean ecosystem processes. We intend for this set of automated diagnostics to form an extensible, open source framework for future comparisons of simulated and observed concentrations of various greenhouse gases across Earth system models.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

Model study of atmospheric transport using carbon 14 and strontium 90 as inert tracers

The observed excess carbon 14 in the atmosphere from 1963 to 1970 provides unique, but limited, data up to an altitude of about 35 km for testing the air motions calculated by 11 multidimensional atmospheric models. Strontium 90 measurements in the atmosphere from 1964 to mid-1967 provide data that have more latitude coverage than those of carbon 14 and are useful for testing combined models of air motions and aerosol settling. Model calculations for carbon 14 begin at October 1963, 9 months after the conclusion of the nuclear bomb tests; the initial conditions for the calculations are derived by three methods, each of which agrees fairly well with measured carbon 14 in October 1963 and each of which has widely different values in regions of the stratosphere where there were no carbon 14 measurements. The model results are compared to the stratospheric measurements, not as if the observed data were absolute standards, but in an effort to obtain new insight about the models and about the atmosphere. The measured carbon 14 vertical profiles at 31 deg N are qualitatively different from all of the models; the measured vertical profiles show a maximum mixing ratio in the altitude range of 20 to 25 km from October 1963 through July 1966, but all modeled profiles show mixing ratio maxima that increase in altitude from 20 km in October 1963 to greater than 40 km by April 1966. Both carbon 14 and strontium 90 data indicate that the models differ substantially among themselves with respect to stratosphere-troposphere exchange rate, but the modeled carbon 14 stratospheric residence times indicate that differences among the models are small with respect to transport rate between the middle stratosphere and the lower stratosphere. Strontium 90 data indicate that aerosol settling is important up to at least 35 km altitude. Relative to the measurements, about three quarters of the models transport carbon 14 from the lower stratosphere to the troposphere too rapidly, and all models with all three sets of initial conditions appear to sweep carbon 14 out of the midstratosphere (above 28 km) much more slowly than was observed from 1963 to 1970. Atmospheric dynamicists should seriously consider that the carbon 14 measurements imply with respect to advection in the midstratosphere.

Kinnison, D. E.↗
NASA NTRS2015

Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits

Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Atmospheric Turbulence Modeling↗
NASA NTRS1974

Models of Mars' atmosphere (1974)

Atmospheric models for support of design and mission planning of space vehicles that are to orbit the planet Mars, enter its atmosphere, or land on the surface are presented. Quantitative data for the Martian atmosphere were obtained from Earth-base observations and from spacecraft that have orbited Mars or passed within several planetary radii. These data were used in conjunction with existing theories of planetary atmospheres to predict other characteristics of the Martian atmosphere. Earth-based observations provided information on the composition, temperature, and optical properties of Mars with rather coarse spatial resolution, whereas spacecraft measurements yielded data on composition, temperature, pressure, density, and atmospheric structure with moderately good spatial resolution. The models provide the temperature, pressure, and density profiles required to perform basic aerodynamic analyses. The profiles are supplemented by computed values of viscosity, specific heat, and speed of sound.

Source record↗
DOE OSTI2017

1–2.4 μm Near-IR Spectrum of the Giant Planet β Pictoris b Obtained with the Gemini Planet Imager

Using the Gemini Planet Imager located at Gemini South, we measured the near-infrared (1.0–2.4 μm) spectrum of the planetary companion to the nearby, young star β Pictoris. We compare the spectrum obtained with currently published model grids and with known substellar objects and present the best matching models as well as the best matching observed objects. Comparing the empirical measurement of the bolometric luminosity to evolutionary models, we find a mass of 12.9 ± 0.2 M{sub Jup}, an effective temperature of 1724 ± 15 K, a radius of 1.46 ± 0.01 R{sub Jup}, and a surface gravity of logg=4.18±0.01 [dex] (cgs). The stated uncertainties are statistical errors only, and do not incorporate any uncertainty on the evolutionary models. Using atmospheric models, we find an effective temperature of 1700–1800 K and a surface gravity of logg=3.5–4.0 [dex] depending upon the model. These values agree well with other publications and with “hot-start” predictions from planetary evolution models. Further, we find that the spectrum of β Pic b best matches a low surface gravity L2 ± 1 brown dwarf. Finally, comparing the spectrum to field brown dwarfs, we find the the spectrum best matches 2MASS J04062677–381210 and 2MASS J03552337+1133437.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1967

Models of stellar atmospheres

Stellar atmosphere models that assume interior energy sources, thermodynamic and mechanical equilibrium, and absorption of radiant energy only in continuous spectrum

THERMODYNAMIC EQUILIBRIUM↗
NASA NTRS1983

Sensitivity /comparison study between the Jacchia 1970, 1971, and 1977 upper atmospheric density models

The neutral upper atmospheric models for the Earth's thermosphere currently used in NASA-MSFC programs are the Jacchia 1970 (J70), 1971 (J71), and 1977 (J77). The Jacchia 1970 model (modified) is used in all MSFC orbital mechanics analyses. Since total density and its variations are the main environmental parameters of interest in orbital lifetime and attitude control studies, the total neutral density was selected for this analysis. This report presents the results of a parametric study of the total density (at 400 km altitude) as computed with three MSFC/Jacchia models. The sensitivity of each of the density models at the summer solstice to varying solar conditions (flux) and geomagnetic (index) values is discussed.

Johnson, D. L.↗
NASA NTRS2010

Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits

Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Kopasakis, George↗
NASA NTRS1994

Soft X-ray spectral fits of Geminga with model neutron star atmospheres

The spectrum of the soft X-ray pulsar Geminga consists of two components, a softer one which can be interpreted as thermal-like radiation from the surface of the neutron star, and a harder one interpreted as radiation from a polar cap heated by relativistic particles. We have fitted the soft spectrum using a detailed magnetized hydrogen atmosphere model. The fitting parameters are the hydrogen column density, the effective temperature T(sub eff), the gravitational redshift z, and the distance to radius ratio, for different values of the magnetic field B. The best fits for this model are obtained when B less than or approximately 1 x 10(exp 12) G and z lies on the upper boundary of the explored range (z = 0.45). The values of T(sub eff) approximately = (2-3) x 10(exp 5) K are a factor of 2-3 times lower than the value of T(sub eff) obtained for blackbody fits with the same z. The lower T(sub eff) increases the compatibility with some proposed schemes for fast neutrino cooling of neutron stars (NSs) by the direct Urca process or by exotic matter, but conventional cooling cannot be excluded. The hydrogen atmosphere fits also imply a smaller distance to Geminga than that inferred from a blackbody fit. An accurate evaluation of the distance would require a better knowledge of the ROSAT Position Sensitive Proportional Counter (PSPC) response to the low-energy region of the incident spectrum. Our modeling of the soft component with a cooler magnetized atmosphere also implies that the hard-component fit requires a characteristic temperature which is higher (by a factor of approximately 2-3) and a surface area which is smaller (by a factor of 10(exp 3), compared to previous blackbody fits.

Meyer, R. D.↗
NASA NTRS1978

A study of key features of the RAE atmospheric turbulence model

A complex atmospheric turbulence model for use in aircraft simulation is analyzed in terms of its temporal, spectral, and statistical characteristics. First, a direct comparison was made between cases of the RAE model and the more conventional Dryden turbulence model. Next the control parameters of the RAE model were systematically varied and the effects noted. The RAE model was found to possess a high degree of flexibility in its characteristics, but the individual control parameters are cross-coupled in terms of their effect on various measures of intensity, bandwidth, and probability distribution.

Jewell, W. F.↗
DOE OSTI2023

Generalized Aerosol/Chemistry Interface (GIANT): A Community Effort to Advance Collaborative Science across Weather and Climate Models

Atmospheric aerosol and chemistry modules are key elements in Earth system models (ESMs), as they predict air pollutant concentrations and properties that can impact human health, weather, and climate. The current uncertainty in climate projections is partly due to the inaccurate representation of aerosol direct and indirect forcing. Aerosol/chemistry parameterizations used within ESMs and other atmospheric models span large structural and parameter uncertainties that are difficult to assess independently of their host models. Moreover, there is a strong need for a standardized interface between aerosol/chemistry modules and the host model to facilitate portability of aerosol/chemistry parameterizations from one model to another, allowing not only a comparison between different parameterizations within the same modeling framework, but also quantifying the impact of different model frameworks on aerosol/chemistry predictions. To address this need, we have initiated a new community effort to coordinate the construction of a Generalized Aerosol/Chemistry Interface (GIANT) for use across weather and climate models. We aim to organize a series of community workshops and hackathons to design and build GIANT, which will serve as the interface between a range of aerosol/chemistry modules and the physics and dynamics components of atmospheric host models. GIANT will leverage ongoing efforts at the U.S. modeling centers focused on building next-generation ESMs and the international AeroCom initiative to implement this common aerosol/chemistry interface. GIANT will create transformative opportunities for scientists and students to conduct innovative research to better characterize structural and parametric uncertainties in aerosol/chemistry modules, and to develop a common set of aerosol/chemistry parameterizations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.

Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

surface energy↗