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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 271 records · Page 15
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NASA NTRS1990

Finite-element schemes for extended integrations of atmospheric models

Of the two finite-element models presently used to investigate the effect of the conservation of integral invariants, by means of finite-element discretization schemes of the shallow-water equations, in order to serve as a paradigm of long-term atmospheric-model integrations, the first employs rectangular elements and conserves total energy, while the second uses triangular elements and a high-accuracy two-stage Numerov-Galerkin method. Attention is given to critical times for numerical nonlinear instability, as well as to the determination of the critical degree of dissipation entailed by the achievement of stable long-term integrations. Relative computational efficiency and accuracy comparisons are presented for the two finite-element schemes.

Steppeler, J.↗
NASA NTRS2018

Atmospheric Chemistry Modeling Using a Regression Forest Model

Atmospheric chemistry is central to many environmental issues such as air pollution, climate change, and stratospheric ozone loss. Chemistry Transport Models (CTM) are a central tool for understanding these issues, whether for research or for forecasting. 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 CTM. We have investigated a machine learning approach to solving the differential equations instead of solving them numerically. From an annual 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, centennial scale climate simulations etc. We discuss our approches' speed and accuracy, and highlight some potential future directions for improving this approach.

Keller, Christoph A.↗
NASA NTRS1973

Atmospheric model for correction of spacecraft data.

Description of a radiative transfer model which has been used to correct Apollo photographic imagery for degradation arising from atmospheric scattering. The model was tested using aircraft scanner data, and an extrapolation was then made to spacecraft altitudes. Using standard meteorological data for the region of interest, it is possible to determine transmittance, path radiance, and total radiance from calculations made with the multiple scattering atmospheric model. Simple algorithms are presented which allow potential users of spacecraft sensor data to correct imagery for the deleterious effects due to the scattering of radiation under clear or hazy atmospheric conditions.

Turner, R. E.↗
NASA NTRS1990

A one-dimensional interactive soil-atmosphere model for testing formulations of surface hydrology

A model representing a soil-atmosphere column in a GCM is developed for off-line testing of GCM soil hydrology parameterizations. Repeating three representative GCM sensitivity experiments with this one-dimensional model demonstrates that, to first order, the model reproduces a GCM's sensitivity to imposed changes in parameterization and therefore captures the essential physics of the GCM. The experiments also show that by allowing feedback between the soil and atmosphere, the model improves on off-line tests that rely on prescribed precipitation, radiation, and other surface forcing.

Koster, Randal D.↗
NASA NTRS1980

High-resolution Martian atmosphere modeling

A multilayer radiative transfer, high-spectral-resolution infrared model of the lower atmosphere of Mars has been constructed to assess the effect of scattering on line profiles. The model takes into accout aerosol scattering and absorption and includes a line-by-line treatment of scattering and absorption by CO2 and H2O. The aerosol complex indices of refraction used were those measured on montmorillonite and basalt chosen on the basis of Mars ir data from the NASA Lear Airborne Observatory. The particle sizes and distribution were estimated using Viking data. The molecular line treatment employs the AFGL line parameters and Voigt profiles. The modeling results indicate that the line profiles are only slightly affected by normal aerosol scattering and absorption, but the effect could be appreciable for heavy loading. The technique described permits a quantitative approach to assessing and correcting for the effect of aerosols on lineshapes in planetary atmospheres.

Egan, W. G.↗
NASA NTRS2012

Solar-Storm/Lunar Atmosphere Model (SSLAM): An Overview of the Effort and Description of the Driving Storm Environment

On 29 April 1998, a coronal mass ejection (CME) was emitted from the Sun that had a significant impact on bodies located at 1 AU. The terrestrial magnetosphere did indeed become more electrically active during the storm passage but an obvious question is the effect of such a storm on an exposed rocky body like our Moon. The solar-storm/lunar atmosphere modeling effort (SSLAM) brings together surface interactions, exosphere, plasma, and surface charging models all run with a common driver - the solar storm and CME passage occurring from 1-4 May 1998. We present herein an expanded discussion on the solar driver during the 1-4 May 1998 period that included the passage of an intense coronal mass ejection (CME) that had> 10 times the solar wind density and had a compositional component of He++ that exceeded 20%. We also provide a very brief overview oflhe SSLAM system layout and overarching results. One primary result is that the CME driver plasma can greatly increase the exospheric content via sputtering, with total mass loss rates that approach 1 kg/s during the 2-day CME passage. By analogy, we suggest that CME-related sputtering increases might also be expected during a CME passage by a near-earth asteroid or at the Mars exobase, resulting in an enhanced loss of material.

Farrell, W. M.↗
NASA NTRS1990

Temperature and wind measurements and model atmospheres of the 1989 Airborne Arctic Stratospheric Expedition

The ER-2 Meteorological Measurement System provides accurate in situ measurements of atmospheric state variables. During the Airborne Arctic Stratospheric Expedition (AASE) the ER-2 flew over the polar region on 14 occasions in January and February, 1989. Vertical temperature profiles, during aircraft takeoff at about 60 deg N and during midflight descent and ascent at high latitudes, are presented. Latitudinal variations of the horizontal wind measurement are illustrated and discussed. Based on observation data, model atmospheres at 60 deg and 75 deg N, representative of the environment of the AASE campaign, are developed.

Chan, K. R.↗
NASA NTRS2011

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003.2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS) ]derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top ]down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗
NASA NTRS1974

Model atmospheres for Mercury based on a lunar analogy

Similarities in daytime spectral reflectivities and nighttime infrared emission from Mercury and the moon are shown to imply that the atmosphere of Mercury must be tenuous, like that of the moon. The theory of formation, transport, and loss in the lunar atmosphere is applied to Mercury. Models of the Hermian atmosphere at perihelion and aphelion are presented, based on the solar wind as the dominant source of gases. Only the noncondensable species - hydrogen, helium and neon - are considered. Of these, helium is the most abundant atmospheric gas, with maximum concentration of about 40,000,000 per cu cm at the nighttime surface. The maximum concentration of H2 is 6,000,000 per cu cm, and that of neon is 700,000 per cu cm.

Hodges, R. R., Jr.↗
NASA NTRS2021

Retrieving the global distribution of the threshold of wind erosion from satellite data and implementing it into the Geophysical Fluid Dynamics Laboratory land–atmosphere model (GFDL AM4.0/LM4.0)

Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Many dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and land surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of the wind erosion threshold (V(threshold)) over dry and sparsely vegetated surfaces. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land–atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and the seasonal cycle of DOD are better captured over the “dust belt” (i.e., northern Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean V(threshold), all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycles as well as dust forecasting.

Bing Pu↗
NASA NTRS2013

A Global Atmospheric Model of Meteoric Iron

The first global model of meteoric iron in the atmosphere (WACCM-Fe) has been developed by combining three components: the Whole Atmosphere Community Climate Model (WACCM), a description of the neutral and ion-molecule chemistry of iron in the mesosphere and lower thermosphere (MLT), and a treatment of the injection of meteoric constituents into the atmosphere. The iron chemistry treats seven neutral and four ionized iron containing species with 30 neutral and ion-molecule reactions. The meteoric input function (MIF), which describes the injection of Fe as a function of height, latitude, and day, is precalculated from an astronomical model coupled to a chemical meteoric ablation model (CABMOD). This newly developed WACCM-Fe model has been evaluated against a number of available ground-based lidar observations and performs well in simulating the mesospheric atomic Fe layer. The model reproduces the strong positive correlation of temperature and Fe density around the Fe layer peak and the large anticorrelation around 100 km. The diurnal tide has a significant effect in the middle of the layer, and the model also captures well the observed seasonal variations. However, the model overestimates the peak Fe+ concentration compared with the limited rocket-borne mass spectrometer data available, although good agreement on the ion layer underside can be obtained by adjusting the rate coefficients for dissociative recombination of Fe-molecular ions with electrons. Sensitivity experiments with the same chemistry in a 1-D model are used to highlight significant remaining uncertainties in reaction rate coefficients, and to explore the dependence of the total Fe abundance on the MIF and rate of vertical transport.

meteoric inputfunction↗