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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
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.↗
DOE OSTI2023

Examining the effects of soil entrainment during nuclear cloud rise on fallout predictions using a multiscale atmospheric modeling framework

Current operational models for nuclear cloud rise over land were developed and validated using observations from shallow-buried or surface detonations, where lofted soil quickly mixed with fission products from the detonation. These models poorly predict fallout from elevated detonations near the fallout-free height of burst (FFHOB), where interactions with the ground are limited and the mixing of fission products and lofted soil is incomplete. Fallout-free is a misnomer at this HOB, as fallout was observed in these cases, but was below the levels of concern, especially off-grounds of the nuclear test site. To correctly characterize and model fallout from detonations near the FFHOB, models must be developed which can capture the stratified nature of the particle and activity-size distributions within the cloud. Previously, it was shown that the Weather Research and Forecasting (WRF) model can accurately simulate nuclear cloud rise for airbursts with little to no ground interactions (Arthur et al., 2021). That work is expanded here by (1) using a radiation-hydrodynamics code to improve the fireball initialization in WRF, (2) further developing an aerosol package from WRF-Chem to simulate lofted soil, and (3) combining the WRF cloud rise simulations with the operational models used at the National Atmospheric Release Advisory Center (NARAC) for fallout modeling. Using this combination of codes, the Upshot-Knothole Grable detonation, which was just below the FFHOB, is simulated from seconds after detonation through cloud rise and fallout, and results are compared to historical test data. Here, the results show improved prediction of dose rate and highlight the need to correctly characterize the entrainment of material into the cloud and the subsequent mixing of fission products with entrained material.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Impacts of Aerosol Dry Deposition on Black Carbon Spatial Distributions and Radiative Effects in the Community Atmosphere Model CAM5

Dry deposition is a vital process affecting the lifetime and spatial distributions of atmospheric aerosols. Black carbon (BC) plays an important role in the Earth’s climate. To explore the sensitivity of modeled BC spatial distributions to particle dry deposition treatments, the scheme of Petroff & Zhang (2010) (PZ10) is implemented into the Community Atmospheric Model version 5 (CAM5), and model simulations using PZ10 are compared with the one using the default scheme of Zhang et al. (2001) (Z01). The PZ10 scheme suggests much lower dry deposition velocities than Z01 for fine particles in Aitken, primary carbon, and accumulation modes, resulting in 73.0% lower of global mean BC dry deposition fluxes and 23.2% higher of global mean BC column burdens. CAM5 with PZ10 increases modeled BC concentrations at all altitudes and latitudes compared to Z01, which improves the agreement with observations of BC profiles in the lower troposphere in the Arctic. It also helps the simulation of surface BC concentrations in high-latitudes remote regions and its seasonality in the Arctic. Yet, PZ10 slightly exacerbates the overestimation of modeled BC concentrations in the middle and upper troposphere, which might be due to model uncertainties in other aerosol physical and chemical processes. The global annual mean radiative effects due to aerosol-radiation interactions (REari) and aerosol-cloud interactions (REaci) of BC from the CAM5 experiment using Z01 are 0.61±0.007 and -0.11±0.02 W m -2 , respectively, compared to slightly larger REari (0.75±0.01 W m -2 ) and REaci (-0.14±0.02 W m -2 ) from CAM5 using PZ10.

54 ENVIRONMENTAL SCIENCES↗
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↗
DOE OSTI2025

Stable Simulation of the Community Atmosphere Model Using Machine‐Learning Physical Parameterization Trained With Experience Replay

In recent years, machine learning (ML) models have been used to improve physical parameterizations of general circulation models (GCMs). A significant challenge of integrating ML models into GCMs is the online instability when they are coupled for long‐term simulation. We present a new strategy that demonstrates robust online stability when the physical parameterization package of an atmospheric GCM is replaced by a deep ML model. The method uses experience replay with a multistep training scheme of the ML model in which the model's own output at the previous time step is used in the training. Predicted physics tendencies in the replay buffer with the most recent errors in the training iterations are reused, making the ML model learn from its own errors. The training method reduces the gap between the offline and online environments of the ML model. The method is used to train the ML model as the physical parameterization of the Community Atmosphere Model (CAM5) with training data from the Multi‐scale Modeling Framework high resolution simulations. Three 6‐year online simulations of the CAM5 are carried out by using the ML physics package. The simulated spatial distributions of precipitation, surface temperature and zonally averaged atmospheric fields demonstrate overall better accuracy than that of the standard CAM5 and benchmark model even without the use of additional physical constraints or tuning. This work is the first to demonstrate a solution to address the online instability problem in climate modeling with ML physics by using experience replay.

54 ENVIRONMENTAL SCIENCES↗
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.↗
DOE OSTI2018

Future Community Efforts in Understanding and Modeling Atmospheric Processes

Atmospheric processes are important for weather, climate, and water prediction, as well as climate change projection, but their representation through subgrid parameterizations remains challenging. Understanding and representing these processes are therefore major goals of international research programs. The Global Atmospheric System Studies (GASS) Panel (Zeng and Klocke 2017), as part of the Global Energy and Water Exchanges Project (GEWEX), is dedicated to developing and improving the representation of the atmosphere in weather and climate models by facilitating and supporting the international community to carry out and use observations, process studies, and numerical model experiments.

54 ENVIRONMENTAL SCIENCES↗
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.↗
DOE OSTI2024

Assessment of Current MACCS Capabilities for Modeling Atmospheric Physical and Chemical Transformations

The physical and chemical transformation during atmospheric transport of radionuclides released into the environment has the possibility of impacting consequence modeling results. Accordingly, this report identifies physical and chemical transformations that may occur following release of chemically reactive radioactive species, how those transformations may affect modeling of consequences of release to the atmosphere and identifies current capabilities – in both MACCS and other state-of-practice atmospheric transport and dispersions models– to model those transformations. It was found that the inclusion of physical and chemical transformations is currently very limited in current state-of-practice codes for atmospheric dispersion of radionuclides. State-of-practice atmospheric dispersion codes appear to be typically limited to simulating either physical-chemical transformations or radioactive transformations, but not both. A state-of-practice atmospheric dispersion code capable of performing parallel physical, chemical, and radioactive transformation was not identified. A few atmospheric dispersion codes capable of modeling physical and chemical transport of specific species such as tritium or uranium hexafluoride were identified. Consequently, there is currently no information available that clearly suggests updates to the MACCS code are needed to bring it up to state-of-practice. However, investigations concluded that the MACCS computational framework can currently accommodate multiple physical/chemical forms in one simulation. Additionally, with some major assumptions, the computational framework in MACCS can accommodate parallel physical-chemical and radioactive transformations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
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.↗