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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Global Reference Atmospheric Model - 1990

GRAM-90, improvement on original model, provides values of atmospheric parameters, either automatically at positions along linear path or along any set of connected positions specified by user. Parameters produced include monthly total and mean values of pressure, density, temperature, and wind, as well as perturbation values and magnitudes. Also provides thermal wind shear for monthly mean winds, percent deviation from standard atmosphere, mean vertical wind, and perturbation data for each position. Perturbation data consist of values of quasi-biennial and random perturbations. Written in FORTRAN 77.

Justus, C. G.↗
NASA NTRS1974

Titan atmosphere models, 1973

The composition and structure of the atmosphere of Titan, based on theory and on spectroscopic and infrared data, is reviewed for the development of numerical engineering models. Light, nominal, and heavy atmospheres are described and tabulated, and their profiles of radius, temperature, pressure, and density are illustrated. Corresponding descriptions of atmospheric dynamics, condensates and surfaces are outlined.

Divine, N.↗
NASA NTRS1985

The MSFC/J70 orbital atmosphere model and the data bases for the MSFC solar activity prediction technique

The MSFC/J70 Orbital Atmospheric Density Model, a modified version of the Smithsonian Astrophysical Observatory Jacchia 1970 model is explained. The algorithms describing the MSFC/J70 model are included as well as listing of the computer program. The 13-month smoothed values of solar flux (F sub 10.7) and geomagnetic index (S sub p), which are required as inputs for the MSFC/J70 model, are also included and discussed.

Johnson, D. L.↗
NASA NTRS1989

Model atmospheres with periodic shocks

The pulsation of a long-period variable star generates shock waves which dramatically affect the structure of the star's atmosphere and produce conditions that lead to rapid mass loss. Numerical modeling of atmospheres with periodic shocks is being pursued to study the processes involved and the evolutionary consequences for the stars. It is characteristic of these complex dynamical systems that most effects result from the interaction of various time-dependent processes.

Bowen, G. H.↗
NASA NTRS2020

Residual Study: Testing Jupiter Atmosphere Models Against Juno MWR Observations

The Juno spacecraft provides unique close-up views of Jupiter underneath the synchrotron radiation belts while circling Jupiter in its 53-day orbits. The microwave radiometer (MWR) onboard measures Jupiter thermal radiation at wavelengths between 1.37 and 50 cm, penetrating the atmosphere to a pressure of a few hundred bars and greater. The mission provides the first measurements of Jupiter's deep atmosphere, down to ~250 bars in pressure, constraining the vertical distributions of its kinetic temperature and constituents. As a result, vertical structure models of Jupiter's atmosphere may now be tested by comparison with MWR data. Taking into account the MWR beam patterns and observation geometries, we test several published Jupiter atmospheric models against MWR data. Our residual analysis confirms Li et al.'s (2017, https://doi.org/10.1002/2017GL073159) result that ammonia depletion persists down to 50–60 bars where ground-based Very Large Array was not able to observe. We also present an extension of the study that iteratively improves the input model and generates Jupiter brightness temperature maps which best match the MWR data. A feature of Juno's north-to-south scanning approach is that latitudinal structure is more easily obtained than longitudinal, and the creation of optimum two-dimensional maps is addressed in this approach.

Zhimeng Zhang↗
NASA NTRS1980

Effect of molecular anisotropy on the intensity and degree of polarization of light scattered from model atmospheres

Computations of the properties of sunlight scattered from models of the earth-atmosphere system are presented to show the effect of molecular anisotropy on the intensity, flux, and degree of polarization of the scattered light. The values of these parameters change significantly when the anisotropy factor is neglected in the molecular optical thickness and scattering phase matrix. However, if the Rayleigh scattering optical thickness is kept constant and the molecular anisotropy factor is included only in the Rayleigh phase matrix, the flux does not change, the intensity changes by a small amount, but the changes in the degree of polarization are still significant.

Bahethi, O. P.↗
NASA NTRS2004

Atmospheric Models for Aerocapture Systems Studies

Aerocapture uses atmospheric drag to decelerate into captured orbit from interplanetary transfer orbit. This includes capture into Earth orbit from, for example, Lunar-return or Mars-return orbit. Eight Solar System destinations have sufficient atmosphere for aerocapture to be applicable - three of the rocky planets (Venus, Earth, and Mars), four gas giants (Jupiter, Saturn, Uranus, and Neptune), and Saturn's moon Titan. These destinations fall into two groups: (1) The rocky planets, which have warm surface temperatures (approx. 200 to 750 K) and rapid decrease of density with altitude, and (2) the gas giants and Titan, which have cold temperatures (approx. 70 to 170 K) at the surface or 1-bar pressure level, and slow rate of decrease of density with altitude. The height variation of average density with altitude above 1-bar pressure level for the gas giant planets is shown. The periapsis density required for aerocapture of spacecraft having typical values of ballistic coefficient (a measure of mass per unit cross-sectional area) is also shown. The aerocapture altitudes at the gas giants would typically range from approx. 150 to 300 km. Density profiles are compared for the rocky planets with those for Titan and Neptune. Aerocapture at the rocky planets would occur at heights of approx. 50 to 100 km. For comparison, typical density and altitudes for aerobraking operations (circularizing a highly elliptical capture orbit, using multiple atmospheric passes) are also indicated.

Justus, C. G.↗
NASA NTRS1991

Predictability of a coupled ocean-atmosphere model

A study is presented to determine the limits on the predictability of the coupled ocean-atmosphere system. Following the classical methods developed for atmospheric predictability studies, the model used is one of the simplest that realistically reproduces many of the important features of the observed interannual variability of sea surface temperature in the tropical Pacific Ocean when forced by observed wind stresses. As no reasonable analysis is available for all the fields, initial conditions for these prediction experiments were taken from a model control run in which the ocean model was forced by the observed surface winds. The atmospheric component of the coupled model is not capable of accurately simulating the large-scale components of the observed wind stress.

Goswami, B. N.↗
NASA NTRS1999

Modeling the Atmospheric Structure and Dynamics of the Martian Atmosphere

Models of the general circulation and climate system of Mars have reached a high level of maturity, but observations to validate them have lacked the kind of global and temporal coverage required. However, we are now on the verge of a new era in Mars exploration as Mars Global Surveyor, and the now enroute Mars Climate Orbiter, will provide daily global coverage of the atmosphere for two Mars years. In the coming years, data from these missions will test the predictions of general circulation models (GCM's) whose results have perhaps become too accepted as truth. This talk will review what GCM's tell us about Mars, what their weaknesses are, and what the latest results imply for their future. Additional information is contained in the original extended abstract.

Haberle, R. M.↗
NASA NTRS1977

Atmospheric model development in support of SEASAT. Volume 1: Summary of findings

Atmospheric analysis and prediction models of varying (grid) resolution were developed. The models were tested using real observational data for the purpose of assessing the impact of grid resolution on short range numerical weather prediction. The discretionary model procedures were examined so that the computational viability of SEASAT data might be enhanced during the conduct of (future) sensitivity tests. The analysis effort covers: (1) examining the procedures for allowing data to influence the analysis; (2) examining the effects of varying the weights in the analysis procedure; (3) testing and implementing procedures for solving the minimization equation in an optimal way; (4) describing the impact of grid resolution on analysis; and (5) devising and implementing numerous practical solutions to analysis problems, generally.

Kesel, P. G.↗
NASA NTRS1987

Solar proton events as tests for the fidelity of middle atmosphere models

Ozone depletions associated with solar proton events have now been observed in nine events: November 1969, January and September 1971, August 1972, June and August 1979, October 1981, and July and December 1982. Since the proton fluxes during these events are fairly well known from satellite observations, modelers have been able to compare model predictions with observations of ozone behavior during these events to test the validity of atmospheric photochemical models. Ozone decreases initially follow approximately their theoretically predicted behavior below about 45 km (where NOx is thought to cause the ozone decrease), but after about two weeks the observed decrease appears to be larger than the computed decrease. Above 45 km, where HOx is thought to cause the ozone decrease, the picture of model validity is not as clear. The observed ozone decreases between about 45 and 60 km are substantially more than that predicted by present photochemical models while between about 60 and 85 km the observed ozone decrease is approximately equal to that predicted.

Jackman, Charles H.↗
NASA NTRS2018

Machine Learning Application to Atmospheric Chemistry Modeling

Atmospheric chemistry is a high-dimensionality, large-data problem and thus may be suited to machine-learning algorithms. We show here the potential of a random forest regression algorithm to replace the gas-phase chemistry solver in the GEOS-Chem chemistry model. In this proof-of-concept study, we used one month of model output to train random forest regression models to predict the concentrations of each long-lived chemical species after integration based upon the physical and chemical conditions before the chemical integration. The choice of prediction type has a strong impact on the skill of the regression model. We find best results from predicting the change in concentration for very long-lived species and the absolute concentration for shorter lived species. The skill of the machine learning algorithm is further improved by using a family approach for NO and NO2 rather than treating them independently.By replacing the numerical integrator with the random forest algorithm and running this model for one month, we find that the model is able to reproduce many of the features of the reference chemistry simulation. Replacing the integration methodology with a machine learning algorithm has the potential to be substantially faster. There are a wide range of applications for such an approach, e.g. to generate boundary conditions, for use in air quality forecasts or chemical data assimilation systems, etc.

Keller, Christoph A.↗