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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Global Precipitation Experiment—A New World Climate Research Programme Lighthouse Activity

The future state of the global water cycle and the prediction of freshwater availability for humans around the world remain among the challenges of climate research and are relevant to several United Nations Sustainable Development Goals. The Global Precipitation Experiment (GPEX) takes on the challenge of improving the prediction of precipitation quantity, phase, timing, and intensity, characteristics that are products of a complex integrated system. It will achieve this by leveraging existing World Climate Research Programme (WCRP) activities and community capabilities in satellite, surface-based, and airborne observations, modeling, and experimental research and by conducting new and focused activities. It was launched in October 2023 as a WCRP Lighthouse Activity. Here, we present an overview of the GPEX Science Plan that articulates the primary science questions related to precipitation measurements, process understanding, model performance and improvements, and plans for capacity development. The central phase of GPEX is the WCRP Years of Precipitation for 2–3 years with coordinated global field campaigns focusing on different storm types (atmospheric rivers, mesoscale convective systems, monsoons, and tropical cyclones, among others) over different regions and seasons. Activities are planned over the three phases (before, during, and after the Years of Precipitation) spanning a decade. These include gridded data evaluation and development, advanced modeling, enhanced understanding of processes critical to precipitation, multiscale prediction of precipitation events across scales, and capacity development. These activities will be further developed as part of the GPEX Implementation Plan.

Climate change↗
NASA NTRS1999

Unstable Air-Sea Interaction in the Extratropical North Atlantic

The possibility of coupled modes in the extratropical North Atlantic has fascinated the climate community since 1960's. A significant aspect of such modes is an unstable air-sea interaction, also called positive feedback, where disturbances between the atmosphere and ocean grow unbound. If a delayed response exists before the negative feedback takes effect, an oscillatory behaviour will develop. Here we explore the relationship between heat flux (positive upward) and sea surface temperature (SST). Positive feedback is characterized by a cross-correlation between the two where correlation maintains a negative sign whether SST or heat flux leads. We use model results and observations to argue that in the North Atlantic there exist regions with positive feedback. The two main locations coincide with the well-known north-south SST dipole where anomalies of opposite sign occupy areas east of Florida and north-east of Newfoundland. We show that oceanic dynamics, wave propagation and advection, give rise to oceanic anomalies in these regions. Subsequently these anomalies are amplified by atmosphere- ocean interaction: thus a positive feedback.

Hakkinen, Sirpa↗
NASA NTRS2005

Using a Web Browser for Environmental and Climate Change Studies

A new web browser for viewing and manipulating meteorological data sets is located on a web server at NASA, Langley Research Center. The browser uses a live access server (LAS) developed by the Thermal Modeling and Analysis Project at NOAA's Pacific Marine Environmental Laboratory. LAS allows researchers to interact directly with the data to view, select, and subset the data in terms of location (latitude, longitude) and time such as day, month, or year. In addition, LAS can compare two data sets and can perform averages and variances, LAS is used here to show how it functions as an internet/web browser for use by the scientific and educational community. In particular its versatility in displaying and manipulating data sets of atmospheric measurements in the earth's radiation budget (ERB) or energy balance, which includes measurements of absorbed solar radiation, reflected shortwave radiation (RSW), thermal outgoing longwave radiation (OLR), and net radiation is demonstrated. These measurements are from the Clouds and the Earth's Radiant Energy System (CERES) experiment and the surface radiation budget (SRB) experiment.

Bess, T. Dale↗
NASA NTRS2002

Using a Web Browser for Environmental and Climate Change Studies

A new web browser for viewing and manipulating meteorological data sets is located on a web server at NASA, Langley Research Center. The browser uses a live access server (LAS) developed by the Thermal Modeling and Analysis Project at NOAA's Pacific Marine Environmental Laboratory. LAS allows researchers to interact directly with the data to view, select, and subset the data in terms of location (latitude, longitude) and time such as day, month, or year. In addition, LAS can compare two data sets and can perform averages and variances, LAS is used here to show how it functions as an internet/web browser for use by the scientific and educational community. In particular its versatility in displaying and manipulating data sets of atmospheric measurements in the earth s radiation budget (ERB) or energy balance, which includes measurements of absorbed solar radiation, reflected shortwave radiation (RSW), thermal outgoing longwave radiation (OLR), and net radiation is demonstrated. These measurements are from the Clouds and the Earth s Radiant Energy System (CERES) experiment and the surface radiation budget (SRB) experiment.

Bess, T. Dale↗
NASA NTRS2009

Combined MODIS/AMSR-E SST Composites for Regional Weather Applications

Recent applications of a high resolution MODlS composite SST product have clearly shown the importance of developing high-resolution SST data sets for coastal applications and modeling. In general, coupling between the oceans and atmospheres has been closely linked to SST gradients and fronts, indicating a need for high resolution SSTs, specifically in the areas of large gradients associated with coastal regions. Thus an accurate determination of SST gradients has become critical for determining the appropriate air-sea coupling and the influence on ocean modeling. Recent research is focused on improving the accuracy and spatial coverage of the current operational MODIS SST composite product provided by the Short-term Prediction Research and Transition (SPORT) project and distributed to the community. GHRSST-PP MODlS data and microwave AMSR-E data are being combined to produce composite data sets for both the West Coast and East Coast of the United States, including the Gulf of Mexico. The use of 1 km MODIS data has explicit advantages over other SST products including its global coverage and high resolution. The AMSR-E data will reduce the latency of the composites. A strategy for utilizing the error characteristics contained in the GHRSST data has been developed. This strategy will include using the error characteristics directly to calculate weights in the SST composites, uncertainty maps based on the composite biases and RMS errors, and latency products calculated in the compositing process. Recent accomplishments include the development of an enhanced compositing approach based on the error-weighted combination of recent clear MODIS SST values, where the error contributions come from measurement error, potential cloud contamination, and data latency sources. Future plans call for the inclusion of AMSR-E SST values with appropriate weights based upon measurement accuracy, MODIS-AMSR-E SST bias, and latency.

Jedlovec, Gary↗
NASA NTRSDate not supplied

TPSAS-NF1676L-33601-DND

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 18 years of an accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. CERES provides the climate community the following parameters: coincident instantaneous 1? gridded CERES observed TOA fluxes, computed profile and surface fluxes, as well as MODIS cloud and aerosol retrievals. Clouds and radiation interaction one key factor that dominates climate feedbacks and is also the most difficult problem with large uncertainty. To further advance our understanding of the cloud-radiation interaction, the climate community need data with accurate fluxes and their associated cloud properties for both observational and modelling study. The new CERES FluxByCldTyp data product is produced for this purpose. The flux product combines for the first time CERES measured TOA fluxes along with the associated MODIS cloud properties, which links radiative flux directly to a specific cloud type. This was achieved by computing sub-footprint fluxes for the clear-sky and cloudy portions of the CERES footprint. The spatially distributed cloud properties within the CERES footprint were retrieved from 2-km MODIS pixels, that were stratified by cloud type. The sub-footprint fluxes were estimated from MODIS radiances based on empirically derived narrowband to broadband coefficients. The combined sub-footprint fluxes can then be validated with the observed footprint flux. This presentation will focus on the algorithm development of the flux-by-cloud-type product and its validation.

Moguo Sun↗
NASA NTRSDate not supplied

TPSAS-NF1676L-33753-DND

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 18 years of an accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. CERES provides the climate community the following parameters: coincident instantaneous 1 gridded CERES observed TOA fluxes, computed profile and surface fluxes, as well as MODIS cloud and aerosol retrievals. Clouds and radiation interaction one key factor that dominates climate feedbacks and is also the most difficult problem with large uncertainty. To further advance our understanding of the cloud-radiation interaction, the climate community need data with accurate fluxes and their associated cloud properties for both observational and modelling study. The new CERES FluxByCldTyp data product is produced for this purpose. The flux product combines for the first time CERES measured TOA fluxes along with the associated MODIS cloud properties, which links radiative flux directly to a specific cloud type. This was achieved by computing sub-footprint fluxes for the clear-sky and cloudy portions of the CERES footprint. The spatially distributed cloud properties within the CERES footprint were retrieved from 2-km MODIS pixels, that were stratified by cloud type. The sub-footprint fluxes were estimated from MODIS radiances based on empirically derived narrowband to broadband coefficients. The combined sub-footprint fluxes can then be validated with the observed footprint flux. This presentation will focus on the algorithm development of the flux-by-cloud-type product and its validation. The paper will also discuss CERES FlxbyCldTyp simulator and its application.

Moguo Sun↗
DOE OSTI2014

An evaluation of experimental decadal predictions using CCSM4

This study assesses retrospective decadal prediction skill of sea surface temperature (SST) variability in initialized climate prediction experiments with the Community Climate System Model version 4 (CCSM4). Ensemble forecasts initialized with two different historical ocean and sea-ice states are evaluated and compared to an ensemble of uninitialized coupled simulations. Both experiments are subject to identical twentieth century historical radiative forcings. Each forecast consists of a 10-member ensemble integrated over a 10-year period. One set of historical ocean and sea-ice conditions used for initialization comes from a forced ocean-ice simulation driven by the Coordinated Ocean-ice Reference Experiments interannually varying atmospheric dataset. Following the Coordinated Model Intercomparison Project version 5 (CMIP5) protocol, these forecasts are initialized every 5 years from 1961 to 1996, and every year from 2000 to 2006. A second set of initial conditions comes from historical ocean state estimates obtained through the assimilation of in-situ temperature and salinity data into the CCSM4 ocean model. These forecasts are only available over a limited subset of the CMIP5 recommended start dates. Both methods result in retrospective SST prediction skill over broad regions of the Indian Ocean, western Pacific Ocean and North Atlantic Ocean that are significantly better than reference skill levels from a spatio-temporal auto-regressive statistical model of SST. However the subpolar gyre region of the North Atlantic stands out as the only region where the CCSM4 initialized predictions outperform uninitialized simulations. Some features of the ocean state estimates used for initialization and their impact on the forecasts are discussed.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Distinct Assembly Processes and Microbial Communities Constrain Soil Organic Carbon Formation

Soil stores more carbon (C) than all vegetation and the atmosphere combined. Soil C stocks are broadly shaped by temperature, moisture, soil physical characteristics, vegetation, and microbial-mediated metabolic processes. The efficiency with which microorganisms use soil C regulates the balance between C storage in soil and the atmosphere. In this review, we discuss how microbial physiology and community assembly processes determine microbial growth rate and efficiency and, in turn, soil organic C cycling through the lens of community ecology. We introduce a conceptual framework cataloging life history (i.e., growth rate, resource acquisition, and stress tolerance) and assembly traits (i.e., competition, facilitation, and dispersal) that correspond with different growth efficiencies. We also compare how dominant mycorrhizal fungal type affects growth efficiency. We propose that further development and inclusion of specific community parameters in microbial-explicit Earth system models are needed for accurately predicting soil organic C responses to global change.

carbon sequestration↗
DOE OSTI2018

Documenting the function of non-cultivated microorganisms in terrestrial ecosystems

The terrestrial biosphere contains a large fraction of global carbon and nearly 70% of the organic carbon in these systems is found in soils. Global changes in atmospheric CO 2 , temperature, precipitation, and ecosystem N inputs, are expected to impact primary production and carbon inputs to soils, but it remains difficult to predict the response of soil processes to anthropogenic change. Models that predict soil C-cycling as a function of ecosystem properties do not explain well variation in soil processes. Our difficulty in predicting the response of soil processes to environmental change suggests a need for a greater understanding of the biotic mechanisms that govern the soil C-cycle. Changes in microbial community structure and function have been proposed to impact soil C-cycling. However, our ability to predict the impacts of these changes on terrestrial ecosystems is constrained by our limited understanding of mechanisms that drive microbial processes in soil systems. We have applied a newly developed approach of Microbial Food Web Mapping to chart the carbon assimilation dynamics of microbial taxa in soils. This method made it possible to track different classes of 13C-labeled substrates into the DNA of nearly every member of the soil community simultaneously over time. Microbial Food Web Mapping was used to identify and characterize microbial taxa that fill key roles in the soil carbon cycle. We mapped the assimilation of carbon into thousands of discrete soil microorganisms as a function of soil carbon content and pH. In so doing we characterized assimilatory carbon metabolism, an essential component of soil C-cycling, for a vast array of uncultivated soil microorganisms. Further, we characterized the spatial and temporal dynamics of these microorganisms across a series of sites representing variation in soil characteristics. This project revealed fundamental aspects of soil C-cycling and provided ecological and metabolic insights on diverse uncultivated soil organisms that are widespread and play major roles in the global C-cycle. The genetic capacity of microbial communities can be studied through ‘omic approaches but it remains difficult to make direct links between the genetic capacity of microorganisms and their function in the soil C-cycle. Microbial Food Web Mapping makes it possible to link gene sequences to soil C-cycle processes as they occur in soil. This approach allows us to characterize the activity of non-cultivated microorganisms in a range of terrestrial systems. This data will be used to build a base of information about the role of non-cultivated organisms in critical C-cycle processes in terrestrial ecosystems and will provide insight on the manner in which soil communities metabolize soil organic matter. The results generated by this project will improve our ability to examine the impacts of management decisions, soil history, and environmental change on the behavior of microbial communities in terrestrial ecosystems, revealing the ecological mechanisms by which microbes regulate both C mineralization and carbon retention in soils, and improving our ability to predict changes in terrestrial ecosystem processes in the face of accelerating global change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Dispersion Validation for Flow Involving a Large Structure Revisited: 45 Degree Rotation

The atmospheric dispersion of contaminants in the wake of a large urban structure is a challenging fluid mechanics problem of interest to the scientific and engineering communities. Magnetic Resonance Velocimetry (MRV) and Magnetic Resonance Concentration (MRC) are relatively new techniques that leverage diagnostic equipment used primarily by the medical field to make 3D engineering measurements of flow and contaminant dispersal. SIERRA/Fuego, a computational fluid dynamics (CFD) code at Sandia National Labs is employed to make detailed comparisons to the dataset to evaluate the quantitative and qualitative accuracy of the model. This work is the second in a series of scenarios. In the prior work, a single large building in an array of similar buildings was considered with the wind perpendicular to a building face. In this work, the geometry is rotated by 45 degrees and improved studies are performed for simulation credibility. The comparison exercise shows conditionally good comparisons between the model and experiment. Model uncertainties are assessed through parametric variations. Various methods of quantifying the accuracy between experiments and data are examined Three-dimensional analysis of accuracy is performed. The effort helped identify deficiencies in the techniques used to make these comparisons, and further methods development therefore becomes one of the main recommendations for follow-on work.

42 ENGINEERING↗
NASA NTRS1993

United States Weather Research Program (USWRP)

After more than a decade of development by a broad cross-section of the U.S. atmospheric research community involved in planning for the National STORM Program, the Subcommittee on Atmospheric Research (SAR) of the Committee on Earth and Environmental Science (CEES) led the development of a strategic plan to realize the objectives of STORM so as to improve our nation's capability to provide accurate short-term forecasts of weather. This strategic plan will guide the planning and implementation of what is now called the United States Weather Research Program (USWRP). The USWRP is charged with achieving operational atmospheric prediction based on mesoscale observations and model results and establishing the scientific and technological basis for global atmospheric mesoscale prediction by the year 2000. The key scientific questions that are addressed under USWRP are discussed.

Bhumralkar, Chandrakant↗
NASA NTRS1995

Workshop on Mars Telescopic Observations

The Mars Telescopic Observations Workshop, held August 14-15, 1995, at Cornell University in Ithaca, New York, was organized and planned with two primary goals in mind: The first goal was to facilitate discussions among and between amateur and professional observers and to create a workshop environment fostering collaborations and comparisons within the Mars observing community. The second goal was to explore the role of continuing telescopic observations of Mars in the upcoming era of increased spacecraft exploration. The 24 papers presented at the workshop described the current NASA plans for Mars exploration over the next decade, current and recent Mars research being performed by professional astronomers, and current and past Mars observations being performed by amateur observers and observing associations. The workshop was divided into short topical sessions concentrating on programmatic overviews, groundbased support of upcoming spacecraft experiments, atmospheric observations, surface observations, modeling and numerical studies, and contributions from amateur astronomers.

Bell, J. F., III↗
NASA NTRS2003

Methane Production by Microbial Mats Under Low Sulfate Concentrations

Cyanobacterial mats collected in hypersaline salterns were incubated in a greenhouse under low sulfate concentrations ([SO4]) and examined for their primary productivity and emissions of methane and other major carbon species. Atmospheric greenhouse warming by gases such as carbon dioxide and methane must have been greater during the Archean than today in order to account for a record of moderate to warm paleoclemates, despite a less luminous early sun. It has been suggested that decreased levels of oxygen and sulfate in Archean oceans could have significantly stimulated microbial methanogenesis relative to present marine rates, with a resultant increase in the relative importance of methane in maintaining the early greenhouse. We maintained modern microbial mats, models of ancient coastal marine communities, in artificial brine mixtures containing both modern [SO4=] (ca. 70 mM) and "Archean" [SO4] (less than 0.2 mM). At low [SO4], primary production in the mats was essentially unaffected, while rates of sulfate reduction decreased by a factor of three, and methane fluxes increased by up to ten-fold. However, remineralization by methanogenesis still amounted to less than 0.4 % of the total carbon released by the mats. The relatively low efficiency of conversion of photosynthate to methane is suggested to reflect the particular geometry and chemical microenvironment of hypersaline cyanobacterial mats. Therefore, such mats w-ere probably relatively weak net sources of methane throughout their 3.5 Ga history, even during periods of low- environmental levels oxygen and sulfate.

Bebout, Brad M.↗
DOE OSTI2013

Tracking Pulses of the Madden-Julian Oscillation

An international field campaign aiming at atmospheric and oceanic processes associated with the Madden-Julian Oscillation (MJO) was conducted in and around the tropical Indian Ocean (IO) during October 2011 - March 2012. The objective of the field campaign was to collect observations urgently needed to expedite the progress of understanding the key processes of the MJO, focusing on its initiation but also including propagation and maturation, and ultimately to improve skills of numerical simulation and prediction of the MJO. Primary targets of the field campaign include interaction of atmospheric deep convection with its environmental moisture, evolution of cloud populations, and air-sea interaction. Several MJO events were captured by ground-based, airborne, and oceanic instruments with advanced observing technology. Numerical simulations and real-time forecasts were integrated components of the field campaign in its design and operation. Observations collected during the campaign provide unprecedented opportunities to reveal detailed processes of the MJO and to assist evaluation, improvement and development of weather and climate models. The data policy of the campaign encourages the broad research community to use the field observations to advance the MJO study.

madden-julian↗
DOE OSTI2015

RACORO continental boundary layer cloud investigations. Part I: Case study development and ensemble large-scale forcings

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60-hour case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in-situ measurements from the RACORO field campaign and remote-sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be ~0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing datasets are derived from the ARM variational analysis, ECMWF forecasts, and a multi-scale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in 'trial' large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Source Term Analysis of Xenon (STAX): An effort focused on differentiating man-made isotope production from nuclear explosions via stack monitoring

An overview of the hardware and software developed for the Source Term Analysis of Xenon (STAX) project is presented which includes the data collection from two stack monitoring systems installed at medical isotope production facilities, infrastructure to transfer data to a central repository, and methods for sharing data from the repository with users. STAX is an experiment to collect radioxenon emission data from industrial nuclear facilities with the goal of developing a better understanding of the global radioxenon background and the effect industrial radioxenon releases have on nuclear explosion monitoring. The final goal of this work is to utilize collected data along with atmospheric transport modeling to calculate the contribution of a peak or set of peaks detected by the International Monitoring System (IMS) to provide desired discriminating information to the International Data Centre (IDC) and National Data Centers (NDCs). Types of data received from the STAX equipment are shown and collected data was used for a case study to predict radioxenon concentrations at two IMS stations closest to the Institute for RadioElements (IRE) in Belgium. The initial evaluation of results indicate that the data is very valuable to the nuclear explosion monitoring community.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Spatial Interpolation of Air Pollutant and Meteorological Variables in Central Amazonia

The Amazon Rainforest is highlighted by the global community both for its extensive vegetation cover that constantly suffers the effects of anthropic action and for its substantial biodiversity. This dataset presents data of meteorological variables from the Amazon Rainforest region with a spatial resolution of 0.001° in latitude and longitude, resulting from an interpolation process. The original data were obtained from the GoAmazon 2014/5 project, in the Atmospheric Radiation Measurement (ARM) repository, and then processed through mathematical and statistical methods. The dataset presented here can be used in experiments in the field of Data Science, such as training models for predicting climate variables or modeling the distribution of species.

54 ENVIRONMENTAL SCIENCES↗