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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Analysis of Air-Sea Interactions in the NASA MERRA Product

Interactions between the ocean and atmosphere influence the global energy and water balance through the exchange of heat, moisture and momentum. These interactions occur over a wide range of space and time scales and need to be properly represented in climate and reanalysis simulations. This study focuses on the representation of the turbulent latent and sensible heat fluxes in the newly developed NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA). It is shown that MERRA achieves realistic estimates of the turbulent fluxes for many space and time scales although some deficiencies are noted. Comparisons are made at high resolution temporal scales with measurements from several research vessels while long term comparisons are made with moored buoys. These results are contrasted with those from several other currently available reanalysis and satellite based products. The representation of feedbacks between the atmosphere and ocean area also examined through the use of simultaneous and lagged correlation analyses with particular focus on precipitation and sea surface temperature relationships. Together, these results demonstrate the consistency of the NASA MERRA product and its applicability for process studies across wide ranging scales of variability.

Roberts, J. Brent↗
NASA NTRS2012

The Aerosol-Monsoon Climate System of Asia

In Asian monsoon countries such as China and India, human health and safety problems caused by air-pollution are worsening due to the increased loading of atmospheric pollutants stemming from rising energy demand associated with the rapid pace of industrialization and modernization. Meanwhile, uneven distribution of monsoon rain associated with flash flood or prolonged drought, has caused major loss of human lives, and damages in crop and properties with devastating societal impacts on Asian countries. Historically, air-pollution and monsoon research are treated as separate problems. However a growing number of recent studies have suggested that the two problems may be intrinsically intertwined and need to be studied jointly. Because of complexity of the dynamics of the monsoon systems, aerosol impacts on monsoons and vice versa must be studied and understood in the context of aerosol forcing in relationship to changes in fundamental driving forces of the monsoon climate system (e.g. sea surface temperature, land-sea contrast etc.) on time scales from intraseasonal variability (~weeks) to climate change (~ multi-decades). Indeed, because of the large contributions of aerosols to the global and regional energy balance of the atmosphere and earth surface, and possible effects of the microphysics of clouds and precipitation, a better understanding of the response to climate change in Asian monsoon regions requires that aerosols be considered as an integral component of a fully coupled aerosol-monsoon system on all time scales. In this paper, using observations and results from climate modeling, we will discuss the coherent variability of the coupled aerosol-monsoon climate system in South Asia and East Asia, including aerosol distribution and types, with respect to rainfall, moisture, winds, land-sea thermal contrast, heat sources and sink distributions in the atmosphere in seasonal, interannual to climate change time scales. We will show examples of how elevated absorbing aerosols (dust and black carbon) may interact with monsoon dynamics to produce feedback effects on the atmospheric water cycle, leading to in accelerated melting of snowpacks over the Himalayas and Tibetan Plateau, and subsequent changes in evolution of the pre-monsoon and peak monsoon rainfall, moisture and wind distributions in South Asia and East Asia.

Lau, William K. M.↗
NASA NTRS2022

First Observations of Mesospheric OH Emission Profiles from OMPS/LP

The hydroxyl radical (OH) is one of the most reactive trace species and plays several important roles in the photochemical equilibrium and energy balance in the mesosphere. Global observations of OH from satellite instruments have a role to play in the study of OH and water vapor variations. This study describes an advanced algorithm to detect mesospheric OH emission profiles from the Suomi NPP satellite Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP). A triplet technique has been adapted to the OMPS/LP radiance measurements for determining OH emission signatures and OH index (OHI) from the OH A2Σ+-X2Π 0-0 band near the 308.8-nm wavelength. The derived mesospheric profiles provide an overall picture of the vertical distribution of OHI between 55 and 84 km and seasonal and latitudinal variability of the strength and height of the OHI. The observed annual cycle is correlated with the water vapor cycle and anticorrelated with the mesospheric temperature cycle. The data show that the relationships persist during the period of April 2012–December 2020. The seasonal behavior of OHI may be associated with variations in solar illumination or mesospheric water vapor abundance. The influence of solar illumination is dominant in the midlatitudes, while the OHI pattern is dominated by water vapor photolysis and other influences in the tropics.

Observations of Mesospheric OH Emission↗
NASA NTRS1994

The effect of gravity waves on the global mean temperature and composition structure of the upper atmosphere

Formulas are presented that parameterize the heating rate and coefficient of turbulent heat conduction produced by saturated internal gravity waves (IGW) in the upper atmosphere. Estimates of these values are made using observational data. The parameterization of IGW influences are introduced into a one-dimensional model of global mean thermal and composition balances of the upper atmosphere. Computations are performed for different values of IGW energy fluxes entering into the upper atmosphere from below. It is shown that realistic vertical profiles of the global mean temperature can be obtained using different values of IGW energy flux into the upper atmosphere. Increasing the IGW intensity leads not only to an increase of the heating rate due to wave enery dissipation, but also to an increase of the heating rate due to wave energy dissipation, but also to an increase in the coefficient of turbulent heat conduction and cooling rate produced by turbulence generated by the wave. So, near an altitude of 100 km the main part of solar heating is compensated by infrared cooling on one hand, and the main part of wave dissipation heating is compensated by turbulent cooling on the other hand. These quasi-balances generally hold for different values of IGW intensity.

Gavrilov, Nikolai M.↗
NASA NTRS2012

An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to the phenology, solar-view geometry, and atmospheric condition etc. factors but not actual landcover difference. Finally, we will compare the classification results from screened and unscreened training samples to assess the improvement achieved by cleaning up the training samples. Keywords:

Tan, Bin↗
NASA NTRS1998

PLUM: Parallel Load Balancing for Adaptive Unstructured Meshes

Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. We present a novel method called PLUM to dynamically balance the processor workloads with a global view. This paper presents the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. A data redistribution model is also presented that predicts the remapping cost on the SP2. This model is required to determine whether the gain from a balanced workload distribution offsets the cost of data movement. Results presented in this paper demonstrate that PLUM is an effective dynamic load balancing strategy which remains viable on a large number of processors.

Oliker, Leonid↗
DOE OSTI2022

Pressure–Strain Interaction as the Energy Dissipation Estimate in Collisionless Plasma

The dissipative mechanism in weakly collisional plasma is a topic that pervades decades of studies without a consensus solution. We compare several energy dissipation estimates based on energy transfer processes in plasma turbulence and provide justification for the pressure–strain interaction as a direct estimate of the energy dissipation rate. The global and scale-by-scale energy balances are examined in 2.5D and 3D kinetic simulations. We show that the global internal energy increase and the temperature enhancement of each species are directly tracked by the pressure–strain interaction. The incompressive part of the pressure–strain interaction dominates over its compressive part in all simulations considered. The scale-by-scale energy balance is quantified by scale filtered Vlasov–Maxwell equations, a kinetic plasma approach, and the lag dependent von Kármán–Howarth equation, an approach based on fluid models. We find that the energy balance is exactly satisfied across all scales, but the lack of a well-defined inertial range influences the distribution of the energy budget among different terms in the inertial range. Therefore, the widespread use of the Yaglom relation in estimating the dissipation rate is questionable in some cases, especially when the scale separation in the system is not clearly defined. In contrast, the pressure–strain interaction balances exactly the dissipation rate at kinetic scales regardless of the scale separation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2016

Capturing Complete Spatial Context in Satellite Observations of Greenhouse Gases

Scientific consensus from a 2015 pre-Decadal Survey workshop highlighted the essential need for a wide-swath (mapping) low earth orbit (LEO) instrument delivering carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) measurements with global coverage. OCO-2 pioneered space-based CO2 remote sensing, but lacks the CH4, CO and mapping capabilities required for an improved understanding of the global carbon cycle. The Carbon Balance Observatory (CARBO) advances key technologies to enable high-performance, cost-effective solutions for a space-based carbon-climate observing system. CARBO is a compact, modular, 15-30° field of view spectrometer that delivers high-precision CO2, CH4, CO and solar induced chlorophyll fluorescence (SIF) data with weekly global coverage from LEO. CARBO employs innovative immersion grating technologies to achieve diffraction-limited performance with OCO-like spatial (2 x 2 sq.km) and spectral (λ/Δλ≈ 20,000) resolution in a package that is >50% smaller, lighter and more cost-effective. CARBO delivers a 25- to 50-fold increase in spatial coverage compared to OCO-2 with no loss of detection sensitivity. Individual CARBO modules weigh < 20 kg, opening diverse new space-based platform opportunities.

Miller, Charles E.↗
NASA NTRS2020

Advancing Precipitation Estimation, Prediction, and Impact Studies

Precipitation exhibits a large variability over a wide range of space and time scales: from seconds to years and decades in time; from the millimeter scale of microphysical processes to regional and global scales in space. It also exhibits a large variability in magnitude and frequency, from low extremes resulting in prolonged droughts to high extremes resulting in devastating floods. Improving precipitation estimation and prediction has great societal impact for decision support in water resources management, infrastructure protection and design under accelerating climate extremes, quantifying water and energy balances at the regional to global scales, and predicting hurricanes, tornadoes, floods and droughts that affect the economy and security around the world (e.g., Blunden and Arndt, 2019). Yet, despite significant advances in observations and physical understanding, precipitation still remains one of the most challenging variables to model and predict at local, regional and global scales with significant implications for our ability to quantify water and energy cycle dynamics, inform decision making, and predict hydro-geomorphic hazards in response to precipitation extremes (e.g. Maggioni and Massari, 2019).

Efi Foufoula-Georgiou↗
NASA NTRS1984

An energy balance climate model with cloud feedbacks

The present two-level global climate model, which is based on the atmosphere-surface energy balance, includes physically based parameterizations for the exchange of heat and moisture across latitude belts and between the surface and the atmosphere, precipitation and cloud formation, and solar and IR radiation. The model field predictions obtained encompass surface and atmospheric temperature, precipitation, relative humidity, and cloudiness. In the model integrations presented, it is noted that cloudiness is generally constant with changing temperature at low latitudes. High altitude cloudiness increases with temperature, although the cloud feedback effect on the radiation field remains small because of compensating effects on thermal and solar radiation. The net global feedback by the cloud field is negative, but small.

Roads, J. O.↗
NASA NTRS1980

The effect of clouds on the earth's solar and infrared radiation budgets

The effect of global cloudiness on the solar and infrared components of the earth's radiation balance is studied in general circulation model experiments. A wintertime simulation is conducted in which the cloud radiative transfer calculations use realistic cloud optical properties and are fully interactive with model-generated cloudiness. This simulation is compared to others in which the clouds are alternatively non-interactive with respect to the solar or thermal radiation calculations. Other cloud processes (formation, latent heat release, precipitation, vertical mixing) were accurately simulated in these experiments. It is concluded that on a global basis clouds increase the global radiation balance by 40 W/sq m by absorbing longwave radiation, but decrease it by 56 W/sq m by reflecting solar radiation to space. The net cloud effect is therefore a reduction of the radiation balance by 16 W/sq m, and is dominated by the cloud albedo effect. Changes in cloud frequency and distribution and in atmospheric and land temperatures are also reported for the control and for the non-interactive simulations. In general, removal of the clouds' infrared absorption cools the atmosphere and causes additional cloudiness to occur, while removal of the clouds' solar radiative properties warms the atmosphere and causes fewer clouds to form. It is suggested that layered clouds and convective clouds over water enter the climate system as positive feedback components, while convective clouds over land enter as negative components.

Herman, G. F.↗
NASA NTRS1997

Efficient Load Balancing and Data Remapping for Adaptive Grid Calculations

Mesh adaption is a powerful tool for efficient unstructured- grid computations but causes load imbalance among processors on a parallel machine. We present a novel method to dynamically balance the processor workloads with a global view. This paper presents, for the first time, the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. Previous results indicated that mesh repartitioning and data remapping are potential bottlenecks for performing large-scale scientific calculations. We resolve these issues and demonstrate that our framework remains viable on a large number of processors.

Oliker, Leonid↗
NASA NTRS1985

Aerosol measurement program strategy for global aerosol backscatter model development

The purpose was to propose a balanced program of aerosol backscatter research leading to the development of a global model of aerosol backscatter. Such a model is needed for feasibility studies and systems simulation studies for NASA's prospective satellite-based Doppler lidar wind measurement system. Systems of this kind measure the Doppler shift in the backscatter return from small atmospheric aerosol wind tracers (of order 1 micrometer diameter). The accuracy of the derived local wind estimates and the degree of global wind coverage for such a system are limited by the local availability and by the global scale distribution of natural aerosol particles. The discussions here refer primarily to backscatter model requirements at CO2 wavelengths, which have been selected for most of the Doppler lidar systems studies to date. Model requirements for other potential wavelengths would be similar.

Bowdle, David A.↗
NASA NTRS2008

GEWEX Water and Energy Budget Study

Closing the global water and energy budgets has been an elusive Global Energy and Water-cycle Experiment (GEWEX) goal. It has been difficult to gather many of the needed global water and energy variables and processes, although, because of GEWEX, we now have globally gridded observational estimates for precipitation and radiation and many other relevant variables such as clouds and aerosols. Still, constrained models are required to fill in many of the process and variable gaps. At least there are now several atmospheric reanalyses ranging from the early National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) and NCEP/Department of Energy (DOE) reanalyses to the more recent ERA40 and JRA-25 reanalyses. Atmospheric constraints include requirements that the models state variables remain close to in situ observations or observed satellite radiances. This is usually done by making short-term forecasts from an analyzed initial state; these short-term forecasts provide the next guess, which is corrected by comparison to available observations. While this analysis procedure is likely to result in useful global descriptions of atmospheric temperature, wind and humidity, there is no guarantee that relevant hydroclimate processes like precipitation, which we can observe and evaluate, and evaporation over land, which we cannot, have similar verisimilitude. Alternatively, the Global Land Data Assimilation System (GLDAS), drives uncoupled land surface models with precipitation, surface solar radiation, and surface meteorology (from bias-corrected reanalyses during the study period) to simulate terrestrial states and surface fluxes. Further constraints are made when a tuned water balance model is used to characterize the global runoff observational estimates. We use this disparate mix of observational estimates, reanalyses, GLDAS and calibrated water balance simulations to try to characterize and close global and terrestrial atmospheric and surface water and energy budgets to within 10-20% for long term (1986-1995), large-scale global to regional annual means.

Roads, J.↗
NASA NTRS1982

The mineralogy of global magnetic anomalies

Problems with the Curie balance, which severely hindered the acquisition of data, were rectified. Chemical analytical activities are proceeding satisfactorily. The magnetization characteristics of metamorphic suites were analyzed and susceptibility data for a wide range of metamorphic and igneous rocks. These rock magnetic signatures are discussed as well as the relationships between geology, gravity and MAGSAT anomalies of West Africa.

Haggerty, S. E.↗
DOE OSTI2022

Adaptive Sampling for In Situ Cloud Probe (Final Report)

Clouds play a leading role in the Earth's global energy and solar radiation balance and hydrological cycle. Improving cloud models requires detailed information on the cloud microphysical properties, such as droplet size distribution and number density, liquid water content and cloud composition (droplets, ice particles), which can only be provided by aerial in situ measurements. However, for many atmospheric measurement instruments, the lack of flexibility in selecting the operational mode during operation can lead to uncertainties in sampling and measurement characteristics under continuously varying atmospheric conditions. This SBIR project is developing an advanced, compact optical imaging technology for in situ characterization of cloud hydrometeors. The development involves a deep modification of the existing Mesa Photonics’ Cloud Droplet Measurement System (CDMS) in order to implement real-time automatic adaptive sampling based on the acquired in situ data and environmental parameters. The new system, CDMS-2, implements two measurement modes: side-scatter imaging for smaller hydrometeors and direct bright-field-illumination imaging for larger hydrometeors in a significantly larger sample volume. The system measures the droplet size distribution (DSD) and number density with an added capability of discriminating between liquid water and ice hydrometeors (based on polarization-resolved side-scatter imaging). The instrument will implement automatic switching or alternating between the regular side-scatter imaging mode and sparse/large hydrometeor mode (based on the acquired data). Other adaptive sampling capabilities include variable sample volume and dynamic range (based on the measured DSD). The preferred deployment platforms are uncrewed aircraft systems (UAS) and tethered balloon/kite systems (TBS). The Phase I project achieved (or exceeded) the goals listed in the Work Plan. A CDMS-2 laboratory prototype implementing the polarization-resolved side-scatter imaging mode and direct bright-field-illumination imaging mode was designed and built. Additional capabilities included the variable illumination pulse energy and sample volume. The smallest detectable droplet diameter was improved to 3–4 μm (from the nominal 10 μm value specified for the original CDMS). Discrimination between water droplets and ice particles was experimentally demonstrated. The Phase I prototype was extensively tested and calibrated in the laboratory and also tested in the Pi Cloud Chamber at Michigan Technological University (MTU). The two intensive experimental campaigns at MTU provided unique opportunities of testing the CDMS-2 laboratory prototype under realistic warm and mixed-phase cloud conditions (stable for long periods of time), testing different sampling modes and intercomparing the CDMS-2 prototype to other co-located cloud characterization instruments. The Phase I project successfully demonstrated the feasibility of the proposed technology and identified the engineering challenges of designing a field deployable prototype instrument in Phase II. The Phase I study provides a solid basis for development, characterization and field-testing of the proposed advanced cloud probe with adaptive sampling in Phase II followed by commercialization of the technology in Phase III.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Bringing Inorganic Carbon to Life: Developing Model Metalloenzymes for C1 Conversion Reactions

The global carbon cycle is carefully balanced through the use of specialized enzymes in plants, algae, bacteria, and archaea. A primordial metabolic pathway for the conversion of inorganic carbon into cellular biomass uses a large, nickel-containing enzyme called carbon monoxide dehydrogenase (CODH)/acetyl coenzyme A synthase (ACS). This system fixes carbon dioxide (CO 2 ) into carbon monoxide (CO) at the CODH site. The carbon monoxide is then used to generate acetyl coenzyme A, a biological building block, through a key carbon-carbon bond forming step at the nickel site in ACS. Despite the significance of these processes in the context of energy conversion, the fundamental chemistry underlying these transformations has remained elusive, in part due to the complexity of the natural enzyme. To better understand the principles governing these biological processes, which represent one-carbon (C 1 ) activation reactions, this project will develop functional models of CODH and ACS based on modifications to a small metalloprotein scaffold. Comprehensive characterization of these systems using advanced spectroscopic and biophysical techniques will reveal key elements responsible for conferring high levels of activity to the model systems, with implications for gaining insight into the mechanisms of the natural enzymes. Moreover, the principles learned from this research can be used to guide design of robust catalysts for efficient conversion of CO 2 and CO into liquid fuels.

10 SYNTHETIC FUELS↗
NASA NTRS1982

Workshop on Closed System Ecology

Self maintaining laboratory scale ecological systems completely isolated from exchanges of matter with external systems were demonstrated. These research tools are discussed in terms of their anticipated value in understanding (1) global ecological material and energy balances, (2) the dynamics of stability and instability in ecosystems, (3) the effects of man-made substances and structures on ecosystems, and (4) the precise requirements for dynamic control of controlled ecology life support systems (CELSS).

Source record↗