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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Greenhouse models of the atmosphere of Titan.

The greenhouse effect is calculated for a series of Titanian atmosphere models with different proportions of methane, hydrogen, helium, and ammonia. A computer program is used in temperature-structure calculations based on radiative-convective thermal transfer considerations. A brightness temperature spectrum is derived for Titan and is compared with available observational data. It is concluded that the greenhouse effect on Titan is generated by pressure-induced transitions of methane and hydrogen. The helium-to-hydrogen ratio is found to have a maximum of about 1.5. The surface pressure is estimated to be at least 0.4 atm, with a daytime temperature of about 155 K at the surface. The presence of methane clouds in the upper troposphere is indicated. The clouds have a significant optical depth in the visible, but not in the thermal, infrared.

Pollack, J. B.↗
NASA NTRS1984

The response of a nonlinear, time-dependent, baroclinic model of the atmosphere to tropical thermal forcing

A multi-level, sigma coordinate, primitive equation atmospheric model has been utilized to study both the tropical and extratropical response to an isolated region of steady thermal forcing in the tropics. The nonlinear response during the first 28 days of the simulation is described. The response can be generally characterized by two distinct components. The first component is a quasi-stationary disturbance which extends eastward and poleward away from the source region along a 'great circle' path. The structure of this disturbance is essentially barotropic away from the source region. The second component is a growing baroclinic wave propagating zonally at mid-latitudes. Significantly, this disturbance is apparently the result of baroclinic instability induced by the quasi-stationary wavetrain. The discussion is predominantly heuristic in form and relies heavily on graphical presentation and quasi-geostrophic theory to interpret the response and individual components of the thermodynamic energy and momentum equations.

Grose, W. L.↗
NASA NTRS1998

Status of and Outlook for Largescale Modeling of Atmosphere-Ice-Ocean Interactions in the Arctic

Arctic air masses have direct impacts on the weather and climatic extremes of midlatitude areas such as central North America. Arctic physical processes pose special and very important problems for global atmospheric models used for climate simulation and numerical weather prediction. At present, the observational database is inadequate to support research aimed at overcoming these problems. Three interdependent Arctic field programs now being planned will help to remedy this situation: SHEBA, which will operate an ice camp in the Arctic for a year-, ARM, which will supply instruments for use at the SHEBA ice camp and which will also conduct longer-term measurements near Barrow, Alaska; and FIRE, which will conduct one or more aircraft campaigns, in conjunction with remote-sensing investigations focused on the SHEBA ice camp. This paper provides an introductory overview of the physics of the Arctic from the perspective of large-scale modelers, outlines some of the modeling problems that arise in attempting to simulate these processes, and explains how the data to be provided by the three field programs can be used to test and improve large-scale models.

Randall, David↗
NASA NTRS2019

Atmospheric Chemistry Modeling Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model. We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry. This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗
NASA NTRS1997

Extension of a Kolmogorov Atmospheric Turbulence Model for Time-Based Simulation Implementation

The development of any super/hypersonic aircraft requires the interaction of a wide variety of technical disciplines to maximize vehicle performance. For flight and engine control system design and development on this class of vehicle, realistic mathematical simulation models of atmospheric turbulence, including winds and the varying thermodynamic properties of the atmosphere, are needed. A model which has been tentatively selected by a government/industry group of flight and engine/inlet controls representatives working on the High Speed Civil Transport is one based on the Kolmogorov spectrum function. This report compares the Dryden and Kolmogorov turbulence forms, and describes enhancements that add functionality to the selected Kolmogorov model. These added features are: an altitude variation of the eddy dissipation rate based on Dryden data, the mapping of the eddy dissipation rate database onto a regular latitude and longitude grid, a method to account for flight at large vehicle attitude angles, and a procedure for transitioning smoothly across turbulence segments.

McMinn, John D.↗
NASA NTRS2019

Optical Communication Link Atmospheric Attenuation Model

The Space Communications and Navigation (SCaN) Center for Networking, Integration, and Communications (SCENIC) user interface, which provides web accessible space mission simulation and communication system analysis capabilities using verified and validated analysis algorithms, can execute analyses including, but not limited to, line-of-sight, orbit propagation, and dynamic link budget calculations between sets of missions and/or assets. SCENIC's purpose is to provide NASA civil servants and contractors a user-friendly tool, integrated with model data, that can simulate and analyze a range of space mission architectures without the need for repeated and redundant modeling. Given the abundance and further future development of free space optical (FSO) communication channels within modern space infrastructure, the availability of a reliable optical link analysis capability is crucial for SCENIC users. The efforts outlined in this paper aim to provide a model for atmospheric attenuation of FSO communication links, both due to absorption/scattering and turbulence, to increase the accuracy of SCENIC's optical link assessment capabilities. A previous model existed for optical absorption/scattering within the SCaN Link Budget Tool, but it was not location specific for the Earth ground-based nodes, nor was the model optimized for run-time. The new model utilizes years of National Oceanic and Atmospheric Administration (NOAA) visibility data from ground station locations around the world. Visibility, along with the wavelength of the optical signal, are input parameters to calculate the optical specific attenuation, which is a parameter in the calculation of the slant-path attenuation. A final FSO atmospheric attenuation value is comprised of the absorption/scattering attenuation and the turbulence attenuation. A run-time efficient algorithm for the model was then developed and programmed in MATLAB ® . Due to the simple model and vectorization possible in MATLAB, the algorithm has an average run-time of less than one fourth of the run-time of the previous implementation.

Jack L Green↗
NASA NTRS1986

Models for aurora and airglow emissions from other planetary atmospheres

Models for aurora and airglow emissions from planetary atmospheres other than the earth are surveyed, with emphasis on accomplishments of the last seven years. The goals of modeling the terrestrial planets and modeling the outer planets are very different. Because less is known about the atmospheres of the outer planets, models of their luminosity seek to provide information about the basic structure of the atmospheres and to identify the major production mechanisms. Models of the terrestrial planets have recently begun to address more complex questions about the abundances of trace and minor constituents, about transport phenomena, and about spatial and temporal variations in the atmosphere and in the processes that produce the emissions. In addition, there are a few instances in which models have been used to elucidate atomic and molecular processes that are difficult to study either in the terrestrial atmosphere or in the laboratory.

Fox, J. L.↗
NASA NTRS1998

Correcting Satellite Image Derived Surface Model for Atmospheric Effects

This project was a continuation of the project entitled "Resolution Earth Surface Features from Repeat Moderate Resolution Satellite Imagery". In the previous study, a Bayesian Maximum Posterior Estimate (BMPE) algorithm was used to obtain a composite series of repeat imagery from the Advanced Very High Resolution Radiometer (AVHRR). The spatial resolution of the resulting composite was significantly greater than the 1 km resolution of the individual AVHRR images. The BMPE algorithm utilized a simple, no-atmosphere geometrical model for the short-wave radiation budget at the Earth's surface. A necessary assumption of the algorithm is that all non geometrical parameters remain static over the compositing period. This assumption is of course violated by temporal variations in both the surface albedo and the atmospheric medium. The effect of the albedo variations is expected to be minimal since the variations are on a fairly long time scale compared to the compositing period, however, the atmospheric variability occurs on a relatively short time scale and can be expected to cause significant errors in the surface reconstruction. The current project proposed to incorporate an atmospheric correction into the BMPE algorithm for the purpose of investigating the effects of a variable atmosphere on the surface reconstructions. Once the atmospheric effects were determined, the investigation could be extended to include corrections various cloud effects, including short wave radiation through thin cirrus clouds. The original proposal was written for a three year project, funded one year at a time. The first year of the project focused on developing an understanding of atmospheric corrections and choosing an appropriate correction model. Several models were considered and the list was narrowed to the two best suited. These were the 5S and 6S shortwave radiation models developed at NASA/GODDARD and tested extensively with data from the AVHRR instrument. Although the 6S model was a successor to the 5S and slightly more advanced, the 5S was selected because outputs from the individual components comprising the short-wave radiation budget were more easily separated. The separation was necessary since both the 5S and 6S did not include geometrical corrections for terrain, a fundamental constituent of the BMPE algorithm. The 5S correction code was incorporated into the BMPE algorithm and many sensitivity studies were performed.

Emery, William↗
NASA NTRS2012

Constraints on the Profiles of Total Water PDF in AGCMs from AIRS and a High-Resolution Model

Atmospheric general circulation model (AGCM) cloud parameterizations generally include an assumption about the subgrid-scale probability distribution function (PDF) of total water and its vertical profile. In the present study, the Atmospheric Infrared Sounder (AIRS) monthly-mean cloud amount and relative humidity fields are used to compute a proxy for the second moment of an AGCM total water PDF called the RH01 diagnostic, which is the AIRS mean relative humidity for cloud fractions of 0.1 or less. The dependence of the second moment on horizontal grid resolution is analyzed using results from a high-resolution global model simulation.The AIRS-derived RH01 diagnostic is generally larger near the surface than aloft, indicating a narrower PDF near the surface, and varies with the type of underlying surface. High-resolution model results show that the vertical structure of profiles of the AGCM PDF second moment is unchanged as the grid resolution changes from 200 to 100 to 50 km, and that the second-moment profiles shift toward higher values with decreasing grid spacing.Several Goddard Earth Observing System, version 5 (GEOS-5), AGCM simulations were performed with several choices for the profile of the PDF second moment. The resulting cloud and relative humidity fields were shown to be quite sensitive to the prescribed profile, and the use of a profile based on the AIRS-derived proxy results in improvements relative to observational estimates. The AIRS-guided total water PDF profiles, including their dependence on underlying surface type and on horizontal resolution, have been implemented in the version of the GEOS-5 AGCM used for publicly released simulations.

Molod, Andrea↗
DOE OSTI2018

The use of atmospheric prediction models to invert infrasound for linear-equivalent time domain moment tensors: Source Physics Experiment, Phase 1

We invert far field infrasound data for the equivalent seismo-acoustic time domain moment tensor to assess the effects of variable atmospheric models as well as to quantify the relative contributions of two presumed source phenomena. The infrasound data was produced by a series of underground chemical explosions that were conducted during the Source Physics Experiment, (SPE) which was originally designed to study explosion-generated seismo-acoustic signal phenomena. The goal of the work presented herein is two-fold: the first goal is to investigate the sensitivity of the estimated time domain moment tensors to variability of the estimated atmospheric model. The second goal is to determine the relative contribution of two possible source mechanisms to the observed infrasonic wave field. Rather than using actual atmospheric observations to estimate the necessary atmospheric Green's functions, we build a series of atmospheric models that rely on publicly available, regional atmospheric observations and the assumption that the acoustic energy results from a linear combination of an underground isotropic explosion and surface spall. The atmospheric observations are summarized and interpolated onto a 3D grid to produce a model of sound speed at the time of the experiment. For each of four SPE acoustic datasets that we invert, we produced a suite of three atmospheric models, based on ten years of regional meteorological observations: an average model, which averages the atmospheric conditions for ten years prior to each SPE event, as well as two extrema models. We find that the inversion yields relatively repeatable results for the estimated spall source. Conversely, the estimated isotropic explosion source is highly variable. This suggests that the majority of the observed acoustic energy is produced by the spall source and/or our modeling of the elastic energy propagation, and it's subsequent conversion to acoustic energy via linear elastic-to-acoustic coupling at the free surface, is too simplistic.

58 GEOSCIENCES↗