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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Near-Nadiral Normalized Radar Cross Section of the SEA Surface at Ku, Ka, and W-Bands: Comparison of Measurements and Models

Understanding the relationship between wind speed and direction and the near-nadiral normalized radar cross section (NRCS) of the sea surface is important in many oceanographic and atmospheric remote sensing applications: (1) wind speed retrievals in traditional altimeter systems (2) assistance in calibration and path integrated attenuation processing for atmospheric profiling radars The desired wind speed (and direction in some cases) retrieval requires a clear understanding of the relationship between the relevant geophysical quantities and the observed NRCS Such understanding is available from existing electromagnetic models, but the presence of many such models, as well as implicit descriptions of the sea surface, motivates continued evaluation of model performance.

CloudSat↗
DOE OSTI2022

Overview of the MOSAiC expedition—Atmosphere

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A Functional Response Metric for the Temperature Sensitivity of Tropical Ecosystems

Abstract Earth system models (ESMs) simulate a large spread in carbon cycle feedbacks to climate change, particularly in their prediction of cumulative changes in terrestrial carbon storage. Evaluating the performance of ESMs against observations and assessing the likelihood of long-term climate predictions are crucial for model development. Here, we assessed the use of atmospheric growth rate variations to evaluate the sensitivity of tropical ecosystem carbon fluxes to interannual temperature variations. We found that the temperature sensitivity of the observed growth rate depended on the time scales over which atmospheric observations were averaged. The temperature sensitivity of the growth rate during Northern Hemisphere winter is most directly related to the tropical carbon flux sensitivity since winter variations in Northern Hemisphere carbon fluxes are relatively small. This metric can be used to test the fidelity of interactions between the physical climate system and terrestrial ecosystems within ESMs, which is especially important since the short-term relationship between ecosystem fluxes and temperature stress may be related to the long-term feedbacks between ecosystems and climate. If the interannual temperature sensitivity is used to constrain long-term temperature responses, the inferred sensitivity may be biased by 20%, unless the seasonality of the relationship between the observed growth rate and tropical fluxes is taken into account. These results suggest that atmospheric data can be used directly to evaluate regional land fluxes from ESMs, but underscore that the interaction between the time scales for land surface processes and those for atmospheric processes must be considered.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Lithium and Lithium Isotopes in Earth’s Surface Cycles

Lithium and its isotopes can provide information on continental silicate weathering, which is the primary natural drawdown process of atmospheric CO 2 and a major control on climate. Lithium isotopes themselves can aid our understanding of weathering, via globally important processes such as clay formation and cation retention. Both these processes occur as part of weathering in modern surface environments, such as rivers, soil pore waters, and groundwaters, but Li isotopes can also be used to track weathering changes across major climate-change events. Lithium isotope evidence from several past climatic warming and cooling episodes shows that weathering processes respond rapidly to changes in temperature, meaning that weathering is capable of bringing climate back under control within a few tens of thousands of years.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Emerson, Charles W.↗
NASA NTRS1990

Status of the Delco Systems Operations forward looking windshear detection program

Delco Systems Operations, a division of General Motors Hughes Electronics Corporation, is developing a Forward Looking Windshear Detection System based on the integration of infrared remote sensing and accelerometer reactive sensing technologies. The infrared sensor is a multi-spectral, scanning radiometer operating in the 8 to 14 micron region. A 2 x 5 detector array with parallel-serial scanning produces 60 degrees horizontal and 10 degrees vertical-fields of view. Using multiple wavelength signals, azimuth temperature gradients are analyzed for characteristic signatures of thermally induced windshear phenomena. Elevation temperature gradients are processed through an atmosphere model to continuously compute a stability index for arming microburst detection criteria. The atmosphere model and proprietary computer processing algorithms combine to generate coarse estimates of disturbance ranges based on multiple wavelength radiance data with different extinction coefficients. Computer outputs of atmospheric stability, disturbance intensity, and azimuth and range information provide a situation display capability. A ground operated, experimental radiometer has been developed and is being used to verify the detection and discrimination concepts at an atmospheric and simulated rain test facility in Milwaukee. A prototype airborne radiometer is being developed for flight test evaluation during the summer of 1989.

Gallagher, Brian J.↗
DOE OSTI2023

Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ~ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ~ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Modeling Dust Mineralogical Composition: Sensitivity to Soil Mineralogy Atlases and Their Expected Climate Impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ∼ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ∼ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

Soil dust↗
DOE OSTI2021

A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

Abstract. We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden–Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Niño–Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model's climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Studies of planetary boundary layer by infrared thermal imagery

The IR camera is a relatively novel device for remote sensing of atmospheric thermal processes from the Planetary Boundary Layer (PBL) based on measurements of the infrared radiation. Infrared radiation is energy radiated by the motion of atoms and molecules on the surface of aerosols, when their temperature is more than absolute zero. The IR camera measures directly the intensity of radiation emitted by aerosols which is converted by an imaging sensor into an electric signal, resulting a thermal image. Every image pixel that corresponds to a specific radiance is pre-processed to identify the brightness temperature. The thermal infrared imaging radiometer used in this study, NicAir, is a precision radiometer developed by Prata et al. The device was calibrated for the temperature range of 270–320 K and using a calibration table along with image processing software, important information about variations in temperature can be extracted from acquired IR images. The PBL is the lowest layer of the troposphere where the atmosphere interacts with the ground surfaces. The importance of PBL lies in the fact that it provides a finite but varying volume in which pollutants can disperse. The aim of this paper is to analyze the PBL altitude and thickness variations over Iasi region using the IR imaging camera as well as its behavior from day to night and thermal processes occurring in PBL.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1982

Study of phenomena related to the sintering process of silicon nitride at atmospheric pressure

A procedure was perfected for the production of components used in engineering applications of silicon nitride. Particles of complex geometry that combine remarkable mechanical properties with a high density are obtained. The process developed, in contrast to the "hot pressing" method, does not use external pressures, and in contrast to the reaction bonding method, final densities close to the theoretical value are obtained.

Bertani, A.↗
NASA NTRS1987

Atmospheric Turbulence Relative to Aviation, Missile, and Space Programs

The purpose of the workshop was to bring together various disciplines of the aviation, missile, and space programs involved in predicting, measuring, modeling, and understanding the processes of atmospheric turbulence. Working committees re-examined the current state of knowledge, identified present and future needs, and documented and prioritized integrated and cooperative research programs.

Camp, Dennis W.↗
NASA NTRS1983

Stronger Carbon Fibers for Reinforced Plastics

Process makes fibers 70 percent stronger at lower carbonization temperature. Stronger carbon fibers result from benzoic acid pretreatment and addition of acetylene to nitrogen carbonizing atmosphere. New process also makes carbon fibers of higher electrical resistance -- an important safety consideration.

Cagliostro, D. E.↗
NASA NTRS1992

The spectroscopy of the atmosphere using far-infrared emission experiment (SAFIRE)

The goal of the SAFIRE experiment is to improve understanding of the middle-atmospher ozone distribution by conducting and analyzing global-scale measurements of important chemical, radiative and dynamical processes, including coupling among these processes and atmospheric regions. This will be accomplished by observing vertical profiles of temperature and key gases in the main chemical families. A detailed listing of SAFIRE measurements, including sepctral ranges, altitude ranges, IFOV, spatial and temporal resolution, latitude coverage and estimated precision is provided. The temperature, O3, CH4, and H2O observations will be useful for deriving and studying dynamical quantities such as geopotential height, potential vorticity, balanced winds and Eliassen-Palm fluxes. The SAFIRE observations will provide important data for study of chemistry, dynamics and transport processes. This experiment was conceived in response to a need for simultaneous measurements of odd hydrogen gases. These include gases such as OH, HO2, and atomic oxygen, which have not been observed by past satellite experiments and which will not be measured by any of teh Upper Atmosophere Reserach Satellite (UARS) experiments to be launched in 1991.

Russell, J. M., III↗
DOE OSTI2022

Rain-Induced Stratification of the Equatorial Indian Ocean and Its Potential Feedback to the Atmosphere

Surface freshening through precipitation can act to stably stratify the upper ocean, forming a rain layer (RL). RLs inhibit subsurface vertical mixing, isolating deeper ocean layers from the atmosphere. This process has been studied using observations and idealized simulations. The present ocean modeling study builds upon this body of work by incorporating spatially resolved and realistic atmospheric forcing. Fine-scale observations of the upper ocean collected during the Dynamics of the Madden-Julian Oscillation field campaign are used to verify the General Ocean Turbulence Model (GOTM). Spatiotemporal characteristics of equatorial Indian Ocean RLs are then investigated by forcing a 2D array of GOTM columns with realistic and well-resolved output from an existing regional atmospheric simulation. RL influence on the ocean-atmosphere system is evaluated through analysis of RL-induced modification to surface fluxes and sea surface temperature (SST). This analysis demonstrates that RLs cool the ocean surface on time scales longer than the associated precipitation event. A second simulation with identical atmospheric forcing to that in the first, but with rainfall set to zero, is performed to investigate the role of rain temperature and salinity stratification in maintaining cold SST anomalies within RLs. Approximately one third, or 0.1°C, of the SST reduction within RLs can be attributed to rain effects, while the remainder is attributed to changes in atmospheric temperature and humidity. The prolonged RL-induced SST anomalies enhance SST gradients that have been shown to favor the initiation of atmospheric convection. These findings encourage continued research of RL feedbacks to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Data evaluation, analysis, and scientific study

Extensive work was performed in data analysis and modeling of solar active phenomena. The work consisted in the study of UV data from the Ultraviolet Spectrometer and Polarimeter (UVSP) instrument on board the Solar Maximum Mission satellite. These data were studied in conjunction with X-rays from the Hard X-ray Imaging Spectrometer (HXIS) instrument, and with H-alpha and magnetographic data from ground-based observatories. The processes we studied are the active phenomena which result from the interaction of the solar magnetic fields with the plasma in the outer regions of the solar atmosphere. These processes include some very dynamic processes such as the prominence eruptions and the 'microflares'. Our research aimed at characterizing the following: the observed phenomena, the possible physical models, and the relevance to the chromospheric and coronal heating.

Wu, S. T.↗