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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
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.↗
DOE OSTI2016

Impact of horizontal resolution on simulation of precipitation extremes in an aqua-planet version of Community Atmospheric Model (CAM3)

One key question regarding current climate models is whether the projection of climate extremes converges to a realistic representation as the spatial and temporal resolutions of the model are increased. Ideally the model extreme statistics should approach a fixed distribution once the resolutions are commensurate with the characteristic length and time scales of the processes governing the formation of the extreme phenomena of interest. In this study, a series of AGCM runs with idealized 'aquaplanet-steady-state' boundary conditions have been performed with the Community Atmosphere Model CAM3 to investigate the effect of horizontal resolution on climate extreme simulations. The use of the aquaplanet framework highlights the roles of model physics and dynamics and removes any apparent convergence in extreme statistics due to better resolution of surface boundary conditions and other external inputs. Assessed at a same large spatial scale, the results show that the horizontal resolution and time step have strong effects on the simulations of precipitation extremes. The horizontal resolution has a much stronger impact on precipitation extremes than on mean precipitation. Updrafts are strongly correlated with extreme precipitation at tropics at all the resolutions, while positive low-tropospheric temperature anomalies are associated with extreme precipitation at mid-latitudes.

54 ENVIRONMENTAL SCIENCES↗
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.↗
DOE OSTI2026

Improving thermodynamic nudging in the E3SM Atmosphere Model version 2 (EAMv2): strategy and hindcast skills on weather systems

Nudging techniques are commonly employed to constrain atmospheric simulations toward observed states, facilitating model evaluation and sensitivity studies. However, if applied improperly – particularly to thermodynamic variables such as temperature and humidity – nudging can distort physical processes and introduce spurious biases, undermining the credibility of the simulations. This study presents an improved nudging implementation that applies vertically modulated tendencies to reduce adverse impacts on model physics. The framework is tested in version 2 of the Energy Exascale Earth System Model (EAMv2) using a suite of hindcast simulations nudged toward ERA5 reanalysis. We systematically evaluate the individual and combined effects of nudging wind, temperature, and humidity fields on the model's ability to represent large-scale atmospheric states and high-impact weather systems. Results show that the revised strategy – particularly when nudging temperature and humidity at selected levels – enhances hindcast skill by improving agreement with ERA5 without degrading the hydrological cycle or precipitation processes. Additional improvements in surface temperature, outgoing longwave radiation, and precipitation biases are achieved through targeted nudging of land-surface variables. The proposed approach strengthens the representation of large-scale conditions relevant to tropical cyclones, atmospheric rivers, and extratropical cyclones in the low-resolution EAMv2. These findings demonstrate that carefully designed thermodynamic nudging, especially of temperature and humidity, improves the realism of constrained simulations and broadens the utility of nudged EAMv2 for atmospheric modeling, machine learning, and high-impact weather research.

Atmospheric river↗
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↗
DOE OSTI2016

Temperature and precipitation extremes in century-long gridded observations, reanalyses, and atmospheric model simulations

Knowledge about long-term changes in climate extremes is vital to better understand multidecadal climate variability and long-term changes and to place today's extreme events in a historical context. While global changes in temperature and precipitation extremes since the midtwentieth century are well studied, knowledge about century-scale changes is limited. This paper analyses a range of largely independent observations-based data sets covering 1901–2010 for long-term changes and interannual variability in daily scale temperature and precipitation extremes. We compare across data sets for consistency to ascertain our confidence in century-scale changes in extremes. We find consistent warming trends in temperature extremes globally and in most land areas over the past century. For precipitation extremes we find global tendencies toward more intense rainfall throughout much of the twentieth century; however, local changes are spatially more variable. While global time series of the different data sets agree well after about 1950, they often show different changes during the first half of the twentieth century. In regions with good observational coverage, gridded observations and reanalyses agree well throughout the entire past century. Finally, simulations with an atmospheric model suggest that ocean temperatures and sea ice may explain up to about 50% of interannual variability in the global average of temperature extremes, and about 15% in the global average of moderate precipitation extremes, but local correlations are mostly significant only in low latitudes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysics scheme.This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.

58 GEOSCIENCES↗
DOE OSTI2015

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysics scheme. This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Model computational expense is estimated, and sensitivity to the number of subcolumns is investigated. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in shortwave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Image Collection Simulation Using High-Resolution Atmospheric Modeling

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Learning Physically Interpretable Atmospheric Models From Data With WSINDy

The multiscale and turbulent nature of Earth's atmosphere has historically rendered accurate weather modeling a hard problem. Recently, there has been an explosion of interest surrounding data-driven approaches to weather modeling, which in many cases show improved forecasting accuracy and computational efficiency when compared to traditional methods. However, many of the current data-driven approaches employ highly parameterized neural networks, often resulting in uninterpretable models and limited gains in scientific understanding. In this work, we address the interpretability problem by explicitly discovering partial differential equations governing atmospheric phenomena, identifying symbolic mathematical models with direct physical interpretations. The purpose of this paper is to demonstrate that, in particular, the weak-form sparse identification of nonlinear dynamics (WSINDy) algorithm can learn effective atmospheric models from both simulated and assimilated data. Our approach adapts the standard WSINDy algorithm to work with high-dimensional fluid data of arbitrary spatial dimension.

58 GEOSCIENCES↗
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.↗