Search NASA⌕ Search

SEARCH · Search NASA

Results for “atmospheric processing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

The upper atmosphere research satellite

The Upper Atmosphere Research Satellite (UARS) will provide, for the first time, data on a global basis for the study of the physical processes acting witin and upon the stratosphere, mesosphere, and lower thermosphere. Specifically, the areas of scientifc study to be addressed are energy input and loss, photochemistry, dynamics, and the coupling among processes and between atmospheric regions. The UARS is a single observatory consisting of a multimission modular spacecraft (MMS) and an instrument module containing 10 scientific instruments. The satellite will be Shuttle launched and placed in a 57 deg inclined orbit at 600 km altitude. A Central Data Handling Facility (CDHF) will receive data from the satellite and process these data into atmospheric quantities for use by the science team. The 'processed' data will be stored at the CDHF and will be available via communication lines for analysis by the investigators at their home laboratories using remote computers. Together with other satellite programs, balloons, sounding rockets, and laboratory efforts, UARS will make available the opportunity for extensive coordination of data devoted to solar terrestrial study.

Burr, P. T.↗
NASA NTRS1979

Spacelab science

The Spacelab/Shuttle system will offer a new capability for investigating the earth's environment, solar-terrestrial relationships, and the physics of the solar system and beyond. Many Spacelab science and applications programs have been identified for the 1980s. These include the Solar Optical Telescope, the Chemical Release Module, a variety of materials processing facilities, the Atmospheric Cloud Physics Laboratory, and the Spacelab Infrared Telescope Facility. Experiments carried out by these payloads will range from passive observation of remote astronomical sources to in situ active probing of the earth's atmosphere and magnetosphere to the examination of the processing of materials in space.

Chappell, C. R.↗
NASA NTRS1994

Climate-chemical interactions and greenhouse effects of trace gases

A completely coupled one-dimensional radiative-convective (RC) and photochemical-diffusion (PC) model has been developed recently and used to study the climate-chemical interactions. The importance of radiative-chemical interactions within the troposphere and stratosphere has been examined in some detail. We find that increases of radiatively and/or chemically active trace gases such as CO2, CH4 and N2O have both the direct effects and the indirect effects on climate change by changing the atmospheric O3 profile through their interaction with chemical processes in the atmosphere. It is also found that the climatic effect of ozone depends strongly on its vertical distribution throughout the troposphere and stratosphere, as well on its column amount in the atmosphere.

Shi, Guang-Yu↗
NASA NTRS1999

Remote Sensing of Urban Thermal Landscape Characteristics and Their Affects on Local and Regional Meteorology and Air Quality: An Overview of NASA EOS-IDS Project Atlanta

As an entity, the city is a manifestation of human "management" of the land. The act of city-building, however, drastically alters the biophysical environment, which ultimately, impacts local and regional land-atmosphere energy exchange processes. Because of the complexity of both the urban landscape and the attendant energy fluxes that result from urbanization, remote sensing offers the only real way to synoptically quantify these processes. One of the more important land-atmosphere fluxes that occurs over cities relates to the way that thermal energy is partitioned across the heterogeneous urban landscape. The individual land cover and surface material types that comprise the city, such as pavements and buildings, each have their own thermal energy regimes. As the collective urban landscape, the individual thermal energy responses from specific surfaces come together to form the urban heat island phenomena, which prevails as a dome of elevated air temperatures over cities. Although the urban heat island has been known to exist for well over 150 years, it is not understood how differences in thermal energy responses for land covers across the city interact to produce this phenomenon, or how the variability in thermal energy responses from different surface types drive its development. Additionally, it can be hypothesized that as cities grow in size through time, so do their urban heat islands. The interrelationships between urban sprawl and the respective growth of the urban heat island, however, have not been investigated. Moreover, little is known of the consequential effects of urban growth, land cover change, and the urban heat island as they impact local and regional meteorology and air quality.

Quattrochi, Dale A.↗
DOE OSTI2024

Reduced‐Order Modeling for Linearized Representations of Microphysical Process Rates

Abstract Representing cloud microphysical processes in large scale atmospheric models is challenging because many processes depend on the details of the droplet size distribution (DSD, the spectrum of droplets with different sizes in a cloud). While full or partial statistical moments of droplet size distributions are the typical variables used in bulk models, prognostic moments are limited in their ability to represent microphysical processes across the range of conditions experienced in the atmosphere. Microphysical parameterizations employing prognostic moments are known to suffer from structural uncertainty in their representations of inherently higher dimensional cloud processes, which limit model fidelity and lead to forecasting errors. Here we investigate how data‐driven reduced‐order modeling can be used to learn predictors for microphysical process rates in bulk microphysics schemes in an unsupervised manner from higher dimensional bin distributions. Using simulations characteristic of marine stratiform clouds, we simultaneously learn lower dimensional representations of droplet size distributions and predict the evolution of the microphysical state of the system. Droplet collision‐coalescence, the main process for generating warm rain, is estimated to have an intrinsic dimension of three. This intrinsic dimension provides a lower limit on the number of degrees of freedom needed to accurately represent collision‐coalescence in models. We demonstrate how deep learning based reduced‐order modeling can be used to discover intrinsic coordinates describing the microphysical state of the system, where process rates such as collision‐coalescence are globally linearized. These implicitly learned representations of the DSD retain more information about the DSD than typical moment‐based representations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

CRITICAL REVIEW OF N, N{sup +}, N{sup +} {sub 2}, N{sup ++}, And N{sup ++} {sub 2} MAIN PRODUCTION PROCESSES AND REACTIONS OF RELEVANCE TO TITAN'S ATMOSPHERE

This paper is a detailed critical review of the production processes and reactions of N, N{sup +}, N{sup +} {sub 2}, N{sup ++}, and N{sup ++} {sub 2} of relevance to Titan's atmosphere. The review includes neutral, ion-molecule, and recombination reactions. The review covers all possible active nitrogen species under Titan's atmospheric conditions, specifically N{sub 2} (A {sup 3}{Sigma}{sup +} {sub u}), N ({sup 4} S), N ({sup 2} D), N ({sup 2} P), N{sup +} {sub 2}, N{sup +} ({sup 3} P), N{sup +} ({sup 1} D), N{sup ++} {sub 2}, and N{sup ++} species, and includes a critical survey of the reactions of N, N{sup +}, N{sup +} {sub 2}, N{sup ++}, and N{sup ++} {sub 2} with N{sub 2}, H{sub 2}, D{sub 2}, CH{sub 4}, C{sub 2}H{sub 2}, C{sub 2}H{sub 4}, C{sub 2}H{sub 6}, C{sub 3}H{sub 8} and the deuterated hydrocarbon analogs, as well as the recombination reactions of N{sup +} {sub 2}, N{sup +}, N{sup ++} {sub 2}, and N{sup ++}. Production processes, lifetimes, and quenching by collisions with N{sub 2} of all reactant species are reviewed. The N ({sup 4} S) state is reactive with radicals and its reactions with CH{sub 2}, CH{sub 3}, C{sub 2}H{sub 3}, and C{sub 2}H{sub 5} are reviewed. Metastable states N{sub 2} (A {sup 3}{Sigma}{sup +} {sub u}), N ({sup 2} D), and N ({sup 2} P) are either reactive or quenched by collisions with the target molecules reviewed. The reactions of N{sup +} ({sup 1} D) have similar rate constants as N{sup +} ({sup 3} P), but the product branching ratios differ significantly. Temperature effects and the role of the kinetic energy content of reactants are investigated. In all cases, experimental uncertainties of laboratory data are reported or estimated. Recommended values with uncertainties, or estimated values when no data are available, are given for rate constants and product branching ratios at 300 K and at the atmospheric temperature range of Titan (150-200 K for neutral reactions and 150 K for ion reactions).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Thermal radiation effects in the atmosphere initiated by pre-earthquake processes

The science community is still looking for pre-earthquake indicators of major seismic events in order to minimize the loss of human life. Recent advances in satellite technology have helped to increase the scientific understanding of the nature of pre-earthquake phenomena in the atmosphere and their relationship with transitional thermal anomalies. It was realized that the thermal heat fluxes over areas of earthquake preparation are a result of air ionization by Rn222, its isotopes and progenies and consequent water vapor condensation on newly formed ions. Latent heat (LH) is released as a result of this process and leads to the formation of local thermal radiation anomalies (TRA) known as outgoing longwave radiation (OLR). We recorded data from the most recent major earthquakes in California (2014) Nepal (2015) that allowed us to summaries TRA's main morphological features. It was also established that the TRA is part of a more complex chain of the short‐term earthquake precursors, which are explained within the framework of a Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model.

Dimitar Ouzounov↗
NASA NTRS1985

Interactive information processing for NASA's mesoscale analysis and space sensor program

The Atmospheric Sciences Division (ASD) of the Systems Dynamics Laboratory at NASA's Marshall Space Flight Center (MSFC) is currently involved in interactive information processing for the Mesoscale Analysis and Space Sensor (MASS) program. Specifically, the ASD is engaged in the development and implementation of new space-borne remote sensing technology to observe and measure mesoscale atmospheric processes. These space measurements and conventional observational data are being processed together to gain an improved understanding of the mesoscale structure and the dynamical evolution of the atmosphere relative to cloud development and precipitation processes. To satisfy its vast data processing requirements, the ASD has developed a Researcher Computer System consiting of three primary computer systems which provides over 20 scientists with a wide range of capabilities for processing and displaying a large volumes of remote sensing data. Each of the computers performs a specific function according to its unique capabilities.

Parker, K. G.↗
DOE OSTI2024

The MOSAiC Distributed Network: Observing the coupled Arctic system with multidisciplinary, coordinated platforms

Central Arctic properties and processes are important to the regional and global coupled climate system. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) Distributed Network (DN) of autonomous ice-tethered systems aimed to bridge gaps in our understanding of temporal and spatial scales, in particular with respect to the resolution of Earth system models. By characterizing variability around local measurements made at a Central Observatory, the DN covers both the coupled system interactions involving the ocean-ice-atmosphere interfaces as well as three-dimensional processes in the ocean, sea ice, and atmosphere. The more than 200 autonomous instruments (“buoys”) were of varying complexity and set up at different sites mostly within 50 km of the Central Observatory. During an exemplary midwinter month, the DN observations captured the spatial variability of atmospheric processes on sub-monthly time scales, but less so for monthly means. They show significant variability in snow depth and ice thickness, and provide a temporally and spatially resolved characterization of ice motion and deformation, showing coherency at the DN scale but less at smaller spatial scales. Ocean data show the background gradient across the DN as well as spatially dependent time variability due to local mixed layer sub-mesoscale and mesoscale processes, influenced by a variable ice cover. The second case (May–June 2020) illustrates the utility of the DN during the absence of manually obtained data by providing continuity of physical and biological observations during this key transitional period. We show examples of synergies between the extensive MOSAiC remote sensing observations and numerical modeling, such as estimating the skill of ice drift forecasts and evaluating coupled system modeling. The MOSAiC DN has been proven to enable analysis of local to mesoscale processes in the coupled atmosphere-ice-ocean system and has the potential to improve model parameterizations of important, unresolved processes in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Fall Speed Variability of Similarly Sized Ice Particle Aggregates

The terminal velocity ( V t ) of ice hydrometeors is of high importance to atmospheric modeling. V t is governed by the physical characteristics of a hydrometeor, including mass and projected area, as well as environmental conditions. When liquid hydrometeors coalesce to form larger hydrometeors, the resulting hydrometeor can readily be characterized by its spherical or near-spherical shape. For ice hydrometeors, it is more complicated because of the variability of ice shapes possible in the atmosphere as well as the inherent randomness in the aggregation process, which leads to highly variable characteristics. The abundance of atmospheric processes affecting ice particle dimensional characteristics creates potential for highly variable V t for ice particles that are predicted or measured to be of the “same size.” In this article we explore the variability of ice hydrometeor V t both theoretically and through the use of experimental observations. Theoretically, the variability in V t is investigated by analyzing the microphysical characteristics of randomly aggregated hexagonal shapes. The modeled dimensional characteristics are then compared to aircraft probe measurements to constrain the variability in atmospheric ice hydrometeor V t . Results show that the spread in V t can be represented with Gaussian distributions relative to a mean. Variability expressed as the full width at half maximum of the normalized Gaussian probability distribution function is around 20%, with somewhat higher values associated with larger particle sizes and warmer temperatures. Field campaigns where mostly convective clouds were sampled displayed low variability, while Arctic and midlatitude winter campaigns showed broader V t spectra.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impacts of Topography-Based Subgrid Scheme and Downscaling of Atmospheric Forcing on Modeling Land Surface Processes in the Conterminous US

The effects of small-scale topography-induced land surface heterogeneity are not well represented in current Earth System Models (ESMs). In this study, a new topography-based subgrid structure referred to as topographic units (TGU) designed to better capture subgrid topographic effects, and methods to downscale atmospheric forcing to the land TGUs have been implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). Effects of the subgrid scheme and downscaling methods on ELM simulated land surface processes are evaluated over the conterminous United States (CONUS). For this purpose, ELM simulations are performed using two configurations without (NoD ELM) and with (D ELM) downscaling, both using TGUs derived for the 0.5-degree grids and the same land surface parameters. Simulations using the two ELM configurations are compared over the CONUS domain, regional levels, and at observational sites (e.g., SNOTEL). The CONUS-level results suggest that D ELM simulates more snowfall and snow water equivalent (SWE), higher runoff, and less ET during spring and summer. Regional-level results suggest more pronounced impacts of downscaling over regions dominated by higher elevation TGUs and regions with maximum precipitation occurring during cool seasons. Results at the SNOTEL sites suggest that D ELM has superior capability of reproducing the observed SWE at 83% of the sites, with more pronounced performance over topographically heterogeneous TGUs with their maximum precipitation occurring during cool seasons. The results highlight the importance of improving representation of small-scale surface heterogeneity in ESMs and motivate future research to understand their effects on land-atmosphere interactions, streamflow, and water resources management over mountainous regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Production and Distribution of NASA MODIS Remote Sensing Products

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the MODIS Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original MODIS science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to MODIS, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.

Wolfe, Robert↗
NASA NTRS2001

An Overview of Modeling Middle Atmospheric Odd Nitrogen

Odd nitrogen (N, NO, NO2, NO3, N2O5, HNO3, HO2NO2, ClONO2, and BrONO2) constituents are important components in the control of middle atmospheric ozone. Several processes lead to the production of odd nitrogen (NO(sub y)) in the middle atmosphere (stratosphere and mesosphere) including the oxidation of nitrous oxide (N2O), lightning, downflux from the thermosphere, and energetic charged particles (e.g., galactic cosmic rays, solar proton events, and energetic electron precipitation). The dominant production mechanism of NO(sub y) in the stratosphere is N2O oxidation, although other processes contribute. Mesospheric NO(sub y) is influenced by N2O oxidation, downflux from the thermosphere, and energetic charged particles. NO(sub y) is destroyed in the middle atmosphere primarily via two processes: 1) dissociation of NO to form N and O followed by N + NO yielding N2 + O to reform even nitrogen; and 2) transport to the troposphere where HNO3 can be rapidly scavenged in water droplets and rained out of the atmosphere. There are fairly significant differences among global models that predict NO(sub y). NO(sub y) has a fairly long lifetime in the stratosphere (months to years), thus disparate transport in the models probably contributes to many of these differences. Satellite and aircraft measurement provide modeling tests of the various components of NO(sub y). Although some recent reaction rate measurements have led to improvements in model/measurement agreement, significant differences do remain. This presentation will provide an overview of several proposed sources and sinks of NO(sub y) and their regions of importance. Multi-dimensional modeling results for NO(sub y) and its components with comparisons to observations will also be presented.

Jackman, Charles H.↗
NASA NTRS2003

Laboratory Studies of Homogeneous and Heterogeneous Chemical Processes of Importance in the Upper Atmosphere

The objective of this study was to conduct measurements of chemical kinetics parameters for reactions of importance in the stratosphere and upper troposphere, and to study the interaction of trace gases with ice surfaces in order to elucidate the mechanism of heterogeneous chlorine activation processes, using both a theoretical and an experimental approach. The measurements were carried out under temperature and pressure conditions covering those applicable to the stratosphere and upper troposphere. The main experimental technique employed was turbulent flow-chemical ionization mass spectrometry, which is particularly well suited for investigations of radical-radical reactions.

Molina, Mario J.↗
NASA NTRS1981

Superrotation planetary atmospheres: Mechanical analogy, angular momentum budget and simulation of the spin up process

Superrotation rates observed in planetary atmospheres are analyzed based on the concept of a thermally driven zonally symmetric circulation. Specifically, how this superrotation is produced and maintained against the tendency for friction to oppose differential motions between the atmosphere and the underlying planet is addressed. The time evolution of a fluid leading from corotation under uniform heating to superrotation under globally nonuniform heating is simulated using a three dimensional zonally symmetric spectral model and Laplace transformation. The increased tendency toward geostrophy combined with the increase of surface pressure toward the poles (due to meridional mass transport), induces the atmosphere to subrotate temporarily at lower altitudes. The resulting viscous shear near the surface thus permits angular momentum to flow from the planet into the atmosphere where it propagates upwards and, combined with the change in moment of inertia, produces large superrotation rates at higher viscosities.

Mayr, H. G.↗
NASA NTRS2001

Laboratory Studies of Homogeneous and Heterogeneous Chemical Processes of Importance in the Upper Atmosphere

The objective of this study is to conduct measurements of chemical kinetics parameters for reactions of importance in the stratosphere and upper troposphere, and to study the interaction of trace gases such as HCl with ice surfaces in order to elucidate the mechanism of heterogeneous chlorine activation processes, using both a theoretical and an experimental approach. The measurements will be carried out under temperature and pressure conditions covering those applicable to the stratosphere and upper troposphere. The techniques to be employed include turbulent flow - chemical ionization mass spectrometry, and optical ellipsometry. The next section summarizes our research activities during the second year of the project, and the section that follows consists of the statement of work for the third year.

Molina, Mario J.↗
NASA NTRS1976

The chemistry of planetary atmospheres

Present knowledge concerning the chemistry of planetary atmospheres is reviewed along with the theories which attempt to explain observational data. The known gross atmospheric compositions of the terrestrial and giant planets are listed, differences between the atmospheres of earth and Venus are discussed, and the atmospheres of the giant planets are described. The origin and evolution of the atmospheres of earth, Venus, Mars, Jupiter, Saturn, and Uranus are outlined, and chemical processes in the atmospheres are examined, particularly cloud formation. The question of organic synthesis and evolution in the reducing atmospheres of the giant planets is considered. It is noted that laboratory work on the individual chemical processes and reactions involved in the evolution of organic compounds in planetary atmospheres, comets, and interstellar space points to the inevitability of organic-compound synthesis in all these situations and to the pervasiveness of organic chemistry throughout the universe.

Huntress, W. T., Jr.↗
DOE OSTI2026

Subseasonal Forecasting and MJO Teleconnections in Machine Learning Weather Prediction Models

Abstract In recent years, machine‐learning (ML) models trained on reanalysis data have rivaled physics‐based forecast models in terms of performance skill for global weather forecasting. With increased rollout stability, the question of how these models perform for subseasonal to seasonal (S2S, week 3–8) forecasting has emerged. In this study we run a large set of subseasonal hindcasts over 2004–2023 to evaluate two ML weather forecast models at the S2S time scale, SFNO‐HENS (Nvidia, fully ML) and NeuralGCM (Google Research, hybrid). Corresponding hindcasts from the European Centre for Medium‐Range Weather Forecasts (ECMWF) are used as a baseline for comparison to a physics‐based model. Because our focus is on predicting moisture transport over the Western United States between October and March, we evaluate the models' prediction skill for the Madden‐Julian Oscillation (MJO) and its associated teleconnections in the North Pacific. We find that both ML models are competitive with the ECWMF model, with comparable skill in predicting the North Pacific large‐scale circulation and the MJO at week 3 and beyond. Even though overall the mid‐latitude subseasonal prediction skill remains low, the ML models exhibit interesting behavior such as a realistic propagation of the MJO across the Maritime Continent and realistic teleconnections. A SFNO‐HENS sensitivity experiment with altered initial conditions in the tropics demonstrates the stability of the model, and it illustrates the capability of ML models to represent important physical processes of the atmosphere at the S2S time scale. Plain Language Summary Predicting weather patterns and precipitation a few weeks in advance (subseasonal time scale) is of great interest for stakeholders such as water managers in the Southwest United States (US), where arid conditions prevail. Subseasonal forecasts from traditional weather forecast models exhibit low skill in the region, limiting their applicability. Here we examine whether the recent breakthrough in weather forecasting made with machine learning/artificial intelligence models can translate to improved subseasonal forecasts. Recently‐developed machine learning models exhibit comparable skill to a state‐of‐the‐art physics‐based model for predicting weather patterns in the North Pacific/North America region, and associated moisture transport. The same applies to their skill in predicting the tropical pattern, the Madden‐Julian Oscillation, and its important remote perturbations over the midlatitude East Pacific and Southwest US. Additionally, a perturbation experiment carried out with one of the machine learning models illustrates their ability to not only predict the evolution of atmospheric fields, but also to learn and represent physical processes such as tropics‐extratropics Rossby wave propagation. Key Points Two machine learning weather forecast models exhibit state‐of‐the‐art prediction skill at the subseasonal time scale in the Pacific sector The models equal ECWMF in terms of Madden‐Julian oscillation (MJO) prediction skill, and they accurately predict the MJO propagation and associated teleconnections The two machine‐learning models represent key physical processes for subseasonal prediction, despite being trained for weather forecasting

Peings, Yannick↗