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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites

The Community Land Model (CLM) is an advanced process-based land surface model that simulates carbon, nitrogen, water vapor and energy exchanges between terrestrial ecosystems and the atmosphere at various spatial and temporal scales. We use observed carbon and water fluxes from five representative Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX) eddy covariance tower sites to systematically evaluate the new version CLM4.5 and old version CLM4.0, and to generate insights that may inform future model developments. CLM4.5 underestimates the annual carbon sink at three forest sites and one alpine grassland site but overestimates the carbon sink of a semi-arid grassland site. The annual carbon sink underestimation for the deciduous-dominated forest site results from underestimated daytime carbon sequestration during summer and overestimated nighttime carbon emission during spring and autumn. Compared to CLM4.0, the bias of annual gross primary production (GPP) is reduced by 24% and 28% in CLM4.5 at two subtropical forest sites. However, CLM4.5 still presents a large positive bias in annual GPP. The improvement in net ecosystem exchange (NEE) is limited, although soil respiration bias decreases by 16%–43% at three forest sites. CLM4.5 simulates lower soil water content in the dry season than CLM4.0 at two grassland sites. Drier soils produce a significant drop in the leaf area index and in GPP and an increase in respiration for CLM4.5. The new fire parameterization approach in CLM4.5 causes excessive burning at the Changbaishan forest site, resulting in an unexpected underestimation of NEE, vegetation carbon, and soil organic carbon by 46%, 95%, and 87%, respectively. Altogether, our study reveals significant improvements achieved by CLM4.5 compared to CLM4.0, and suggests further developments on the parameterization of seasonal GPP and respiration, which will require a more effective representation of seasonal water conditions and the partitioning of net radiation between sensible and heat fluxes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Increases in Future AR Count and Size: Overview of 2 the ARTMIP Tier 2 CMIP5/6 Experiment

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi-model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA-2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design. Plain Language Summary: Atmospheric rivers (ARs) are a type of weather pattern known to be important for moving water vapor from the warm, moist tropics to the cool, dry polar regions; when they reach midlatitudes in the winter time, they are commonly associated with heavy precipitation. Recent studies that assess the impacts of global climate change on ARs tend to agree that there will be more ARs in a warmer climate, and that ARs will tend to be more extreme. However, it has been increasingly recognized by the AR research community that these results may depend on the method used to identify ARs and the choice of climate model. This study reports results from a controlled experiment, involving an international research community, that aims to show how different AR identification methods and climate models might impact our scientific understanding of ARs in the future. This experiment shows that there will likely be more ARs in the future, and that ARs will generally have a larger spatial footprint. This experiment also shows that uncertainty in these results are large, with the uncertainty from AR identification methods outweighing that of climate models. Future efforts to better understand the physics of ARs may help us reduce this uncertainty.

T A OBrien↗
NASA NTRSDate not supplied

Status of Venus Global Reference Atmospheric Model (Venus-GRAM) Upgrades

Venus-GRAM Overview - Engineering-oriented atmospheric model that estimates mean values and statistical variations of Venus atmospheric properties - Outputs include atmospheric density, temperature, pressure, chemical composition, and wind components along a user-defined path - Widely used by the engineering community because of its ability to create realistic atmospheric dispersions - Can be integrated into high fidelity flight dynamic simulations of launch, entry, descent and landing (EDL), aerobraking and aerocapture - Has been used in multiple studies and proposals including NASA Engineering and Safety Center (NESC) Autonomous Aerobraking Study and various Discovery proposals - Optional trajectory input file consisting of time, height, latitude, and longitude can be used to provide the Venus-GRAM trajectory path - Optional auxiliary profile consisting of height, latitude, longitude, temperature, pressure, density, eastward wind, and northward wind may be used to replace model data in Venus-GRAM - Not a forecast model - GRAMs are also available for Earth, Mars, Titan, Neptune, Uranus, and Jupiter - Available through the NASA Software Catalog https://software.nasa.gov/software/MFS-33888-1

atmospheric models↗
DOE OSTI2025

New Particle Formation and Growth in the Houston Atmosphere During TRACER (Final Report)

From 2020-2025, researchers from UC Irvine, UC Riverside, and Colorado State University collaborated on a Department of Energy-funded project to understand how airborne particles form and grow in urban atmospheres, conducting an intensive field campaign in Houston, Texas during summer 2022. Using advanced instruments to measure gas-phase chemicals, particle composition, and a specialized chamber to study particle growth, the team discovered that sulfur-containing compounds from industrial and power plant emissions are the dominant driver of new particle formation in Houston, with particles typically forming locally in the city and growing as air moves away in the urban plume. The research revealed an important methodological insight: measurements from fixed ground stations can be misleading when interpreting how particles actually evolve as air masses move, which has significant implications for how scientists worldwide interpret atmospheric observations. These findings improve understanding of urban air quality and help reduce uncertainties in climate models, since these particles play critical roles in cloud formation and Earth's radiation balance, while also providing detailed information about ultrafine particle composition relevant to public health. The project trained three doctoral students, developed enhanced computer models for urban particle formation, and made all data publicly available through the DOE Atmospheric Radiation Measurement data archive for use by the broader scientific community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Metabolic tradeoffs and heterogeneity in microbial responses to temperature determine the fate of litter carbon in simulations of a warmer world

Abstract. Climate change has the potential to destabilize the Earth's massive terrestrial carbon (C) stocks, but the degree to which models project this destabilization to occur depends on the kinds and complexities of microbial processes they simulate. Of particular note is carbon use efficiency (CUE), which determines the fraction of C processed by microbes that is anabolized into microbial biomass rather than lost to the atmosphere and soil as carbon dioxide and extracellular products. The temperature sensitivity of CUE is often modeled as an intrinsically fixed (homogeneous) property of the community, which contrasts with empirical data and has unknown impacts on projected changes to the soil C cycle under global warming. We used the Decomposition Model of Enzymatic Traits (DEMENT) – which simulates taxon-level litter decomposition dynamics – to explore the effects of introducing organism-level heterogeneity into the CUE response to temperature for decomposition of leaf litter under 5 ∘C of warming. We found that allowing the CUE temperature response to differ between taxa facilitated increased loss of litter C, unless fungal taxa were specifically restricted to decreasing CUE with temperature. Litter C loss was exacerbated by variable and elevated CUE at higher temperature, which effectively lowered costs for extracellular enzyme production. Together these results implicate a role for diversity of taxon-level CUE responses in driving the fate of litter C in a warmer world within DEMENT, which should be explored within the framework of additional model structures and validated with empirical studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Near-earth orbital guidance and remote sensing

The curriculum of a short course in remote sensing and parameter optimization is presented. The subjects discussed are: (1) basics of remote sensing and the user community, (2) multivariant spectral analysis, (3) advanced mathematics and physics of remote sensing, (4) the atmospheric environment, (5) imaging sensing, and (6)nonimaging sensing. Mathematical models of optimization techniques are developed.

Powers, W. F.↗
NASA NTRS1977

SESAME/Environmental Research Laboratories

The Environmental Research Laboratories (ERL) have been designated as the basic research group of the National Oceanic and Atmospheric Administration (NOAA). ERL performs an integrated program of research and research services directed toward understanding the geophysical environment, protecting the environment, and improving the forecasting ability of NOAA. Twenty-four laboratories located throughout the United States comprise ERL. The Project SESAME (Severe Environmental Storms and Mesoscale Experiment) Planning Office is a project office within ERL. SESAME is conceived as a joint effort involving NOAA, NASA, NSF, and the atmospheric science community to lay the foundation for improved prediction of severe convective storms. The scientific plan for SESAME includes a phased buildup of analysis, modeling, instrumentation development and procurement, and limited-scale observational activities.

Source record↗
NASA NTRS1995

Mississippi State University Center for Air Sea Technology FY95 Research Program

The Mississippi State University (MSU) Center for Air Sea Technology (CAST) evolved from the Institute for Naval Oceanography's (INO) Experimental Center for Mesoscale Ocean Prediction (ECMOP) which was started in 1989. MSU CAST subsequently began operation on 1 October 1992 under an Office of Naval Research (ONR) two-year grant which ended on 30 September 1994. In FY95 MSU CAST was successful in obtaining five additional research grants from ONR, as well as several other research contracts from the Naval Oceanographic Office via NASA, the Naval Research Laboratory, the Army Corps of Engineers, and private industry. In the past, MSU CAST technical research and development has produced tools, systems, techniques, and procedures that improve efficiency and overcome deficiency for both the operational and research communities residing with the Department of Defense, private industry, and university ocean modeling community. We continued this effort with the following thrust areas: to develop advanced methodologies and tools for model evaluation, validation and visualization, both oceanographic and atmospheric; to develop a system-level capability for conducting temporally and ; spatially scaled ocean simulations driven by or are responsive to ocean models, and take into consideration coupling to atmospheric models; to continue the existing oceanographic/atmospheric data management task with emphasis on distributed databases in a network environment, with database optimization and standardization, including use of Mosaic and World Wide Web (WWW) access; and to implement a high performance parallel computing technology for CAST ocean models

Yeske, Lanny↗
NASA NTRS1993

Extreme environments and exobiology

Ecological research on extreme environments can be applied to exobiological problems such as the question of life on Mars. If life forms (fossil or extant) are found on Mars, their study will help to solve fundamental questions about the nature of life on Earth. Extreme environments that are beyond the range of adaptability of their inhabitants are defined as "absolute extreme". Such environments can serve as terrestrial models for the last stages of life in the history of Mars, when the surface cooled down and atmosphere and water disappeared. The cryptoendolithic microbial community in porous rocks of the Ross Desert in Antarctica and the microbial mats at the bottom of frozen Antarctic lakes are such examples. The microbial communities of Siberian permafrost show that, in frozen but stable communities, long-term survival is possible. In the context of terraforming Mars, selected microorganisms isolated from absolute extreme environments are considered for use in creation of a biological carbon cycle.

NASA Discipline Exobiology↗
DOE OSTI2020

The Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA)

To explore the various couplings across space, time and between ecosystems in a consistent manner, atmospheric modeling is moving away from the fractured limited-scale modeling strategy of the past towards a unification of the range of scales inherent in the Earth System. This paper describes the forward-looking MUlti-Scale Infrastructure for Chemistry and Aerosols (MUSICA), which is intended to become the next generation community infrastructure for research involving atmospheric chemistry and aerosols. MUSICA will be developed collaboratively by the National Center for Atmospheric Research (NCAR) and university and government researchers, with the goal of serving the international research and applications communities. The capability of unifying various spatio-temporal scales, coupling to other Earth System components and process-level modularization will allow advances in both fundamental and applied research in atmospheric composition, air quality and climate and is also envisioned to become a platform that addresses the needs of policy makers and stakeholders.

Pfister, Gabriele G.↗
NASA NTRS2006

Space Weather Modeling Services at the Community Coordinated Modeling Center

The Community Coordinated Modeling Center (CCMC) is a multi-agency partnership, which aims at the creation of next generation space weather models. The goal of the CCMC is to support the research and developmental work necessary to substantially increase the present-day modeling capability for space weather purposes, and to provide models for transition to the Rapid Prototyping Centers at the space weather forecast centers. This goal requires close collaborations with and substantial involvement of the research community. The physical regions to be addressed by CCMC-related activities range from the solar atmosphere to the Earth's upper atmosphere. The CCMC is an integral part of the National Space Weather Program Implementation Plan, of NASA's Living With a Star (LWS) initiative, and of the Department of Defense Space Weather Transition Plan. CCMC includes a facility at NASA Goddard Space Flight Center. CCMC also provides, to the research community, access to state-of-the-art space research models. In this paper we will provide a description of the current CCMC status, discuss current plans, research and development accomplishments and goals, and describe the model testing and validation process undertaken as part of the CCMC mandate. Special emphasis will be on solar and heliospheric models currently residing at CCMC, and on plans for validation and verification.

Hesse, Michael↗
DOE OSTI2016

Green Ocean Amazon 2014/15 – Scaling Amazon Carbon Water Couplings Field Campaign Report

Forests soak up 25% of the carbon dioxide (CO2) emitted by anthropogenic fossil energy use (10 Gt C y-1), moderating its atmospheric accumulation. How this terrestrial CO2 uptake will evolve with climate change in the 21st Century is largely unknown. Rainforests are the most active ecosystems, with the Amazon basin storing 120 Gt C as biomass and exchanging 18 Gt C y-1 of CO2 via photosynthesis and respiration and fixing carbon at 2-3 kg C m-2 y-1. Furthermore, the intense hydrologic and carbon cycles are tightly coupled in the Amazon where about half of the water is recycled by evapotranspiration and the other half imported from the ocean by Northeasterly trade winds. Climate models predict a drying in the Amazon with reduced carbon uptake while observationally guided assessments indicate sustained uptake. We set out to resolve this huge discrepancy in the size and sign of the future Amazon carbon cycle by performing the first simultaneous regional-scale high-frequency measurements of atmospheric CO2, H2O, HOD, CH4, N2O, and CO at the T3 site in Manacupuru, Brazil, as part of DOE's GoAmazon 2014/15 project. Our data will be used to inform and develop DOE's Community Land Model (CLM) on the tropical carbon-water couplings at the appropriate grid scale (10-50 km). Our measurements will also validate the CO2 data from Japan's Greenhouse gases Observing Satellite (GOSAT) and NASA's Orbiting Carbon Observatory (OCO)-2 satellite (launched in July, 2014). Our data addresses these science questions: 1. How does ecosystem heterogeneity and climate variability influence the rainforest carbon cycle? 2. How well do current tropical ecosystem models simulate the observed regional carbon cycle? 3. Does nitrogen deposition (from the Manaus, Brazil, plume) enhance rainforest carbon uptake?

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Reducing Long‐Standing Surface Ozone Overestimation in Earth System Modeling by High‐Resolution Simulation and Dry Deposition Improvement

The overestimation of surface ozone concentration in low‐resolution global atmospheric chemistry and climate models has been a long‐standing issue. We first update the ozone dry deposition scheme in both high‐ (0.25°) and low‐resolution (1°) Community Earth System Model (CESM) version 1.3 runs, by adding the effects of leaf area index and correcting the sunlit and shaded fractions of stomatal resistances. With this update, 5‐year‐long summer simulations (2015–2019) using the low‐resolution CESM still exhibit substantial ozone overestimation (by 6.0–16.2 ppbv) over the U.S., Europe, eastern China, and ozone pollution hotspots. The ozone dry deposition scheme is further improved by adjusting the leaf cuticle conductance, reducing the mean ozone bias by 19%, and increasing the model resolution further reduces the ozone overestimation by 43%. We elucidate the mechanism by which model grid spacing influences simulated ozone, revealing distinctive pathways in urban versus rural areas. In rural areas, grid spacing mainly affects daytime ozone levels, where additional NO x emissions from nearby urban areas result in an ozone boost and overestimation in low‐resolution simulations. In contrast, over urban areas, daytime ozone overestimation follows a similar mechanism due to the influence of volatile organic compounds from surrounding rural areas. However, nighttime ozone overestimation is closely linked to weakened NO titration owing to the redistribution of urban NO x to rural areas. Additionally, stratosphere‐troposphere exchange may also contribute to reducing ozone bias in high‐resolution simulations, warranting further investigation. This optimized high‐resolution CESM may enhance understanding of ozone formation mechanisms, sources, and changes in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Venus Global Reference Atmospheric Model (Venus-GRAM) Upgrades

Introduction: The Venus Global Reference Atmospheric Model (Venus-GRAM) is one of the most widely used engineering models of Venus’ atmosphere. The Venus-GRAM upgrades are being developed by NASA Marshall Space Flight Center (MSFC) and NASA Langley Research Center (LaRC). This presentation will provide details regarding the upgrades that have been made to Venus-GRAM and the ongoing objectives, tasks, and milestones related to the GRAM upgrades funded by the NASA Science Mission Directorate (SMD). Venus-GRAM: Venus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of the atmospheric properties of Venus. Venus-GRAM provides mean values and variability for any point in the atmosphere as well as seasonal, geographic, and altitude variations. Venus-GRAM outputs include atmospheric density, temperature, pressure, winds, and chemical composition along a user-defined path. It is extensively used by the engineering community because of its ability to create realistic dispersions. GRAMs have been integrated into high fidelity flight dynamic simulations of launch, entry, descent and landing (EDL), aerobraking and aerocapture. GRAMs are currently available for Earth, Mars, Venus, Neptune, Titan, and Uranus. The lower atmosphere model in Venus-GRAM (up to 250 km) is based on the Venus International Reference Atmosphere (VIRA) [1]. The Venus-GRAM thermosphere (250 to 1000 km) is based on a MSFC-developed model [2] which assumes an isothermal temperature profile initialized using VIRA conditions at 250 km [3]. The VIRA version included in Venus-GRAM includes Pioneer Venus Orbiter and Probe data as well as Venera probe data, but it does not include a solid planet model or a high-resolution gravity model [4]. Venus-GRAM Upgrade Status: Code Modernization. Venus-GRAM has been rearchitected from Fortran to a common object-oriented C++ framework called the GRAM Suite. This new architecture creates a common GRAM library of data models and utilities. The first C++ release of the rearchitected Venus-GRAM is a straight conversion from the latest Fortran version. Model Upgrades. The focus of the model upgrade task is to improve the atmosphere models in the existing GRAMs and to establish a foundation for developing GRAMs for additional destinations. The GRAM ephemeris has been upgraded to the NASA Navigation and Ancillary Information Facility (NAIF) SPICE toolkit (version N0066). The calculation of the speed of sound has also been improved in the GRAMs. In FY20, the GRAM project established contracts to improve the model data within Venus-GRAM. Hampton University is developing an empirical global model for Venus. The University of Wisconsin is reanalyzing the Venus Express radio occultation observations and analyzing the Akatsuki thermal imaging data. Upgraded Venus-GRAM Release. GRAM Suite Version 1.3 will be released in September 2021 and will contain the rearchitected Venus-GRAM, including the common GRAM framework and planet–specific code. A User Guide and Programmer’s Manual are released with all GRAMs. Conclusions: GRAMs are frequently used toolsets and vital in assessing effects of atmospheres on interplanetary spacecraft during the program life cycle process. Releases of the GRAM Suite, upgrades of the existing planetary GRAMs, and development of new planetary GRAMs are ongoing. Venus-GRAM atmosphere model upgrades will be included in the next phase of GRAM tasks. References: [1] Kliore, A. J. et al. (1985) ASR, 5, 11, 1-304. [2] Justh, H. L. et al. (2006) AIAA/AAS Astrodynamics Specialist Conference & Exhibit, Abstract AIAA-2006-6394. [3] Guide to Reference and Standard Atmosphere Models, BSR/AIAA G-003-2010. [4] Limaye, S. S. (2012), LPSC VEXAG Townhall Meeting. Acknowledgments: The authors gratefully acknowledge support from the NASA SMD.

atmospheric models↗
DOE OSTI2023

JuliaOceanWaves

SAND2023-05107O JuliaOceanWaves is a collection of packages and functions for modeling wave energy converters. The open-source software is designed to be used by the wave energy community to model new concepts, perform design optimization, and more. Capabilities include: • A representation of ocean wave spectra and input/output (e.g. read from National Oceanic and Atmospheric Administration buoys) and post-processing functionalities; • A solver for the linear potential flow radiation and diffraction equations for wave forcing on floating structures. • Solving the floating body linear dynamics in the frequency domain. Future additions to the software will include solving non-linear floating body dynamics in the time-domain through time-marching Ordinary Differential Equation solvers and the pseudo-spectral optimization method. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Michelen Strofer, Carlos↗
DOE OSTI2017

Advanced Atmospheric Ensemble Modeling Techniques

Ensemble modeling (EM), the creation of multiple atmospheric simulations for a given time period, has become an essential tool for characterizing uncertainties in model predictions. We explore two novel ensemble modeling techniques: (1) perturbation of model parameters (Adaptive Programming, AP), and (2) data assimilation (Ensemble Kalman Filter, EnKF). The current research is an extension to work from last year and examines transport on a small spatial scale (<100 km) in complex terrain, for more rigorous testing of the ensemble technique. Two different release cases were studied, a coastal release (SF6) and an inland release (Freon) which consisted of two release times. Observations of tracer concentration and meteorology are used to judge the ensemble results. In addition, adaptive grid techniques have been developed to reduce required computing resources for transport calculations. Using a 20- member ensemble, the standard approach generated downwind transport that was quantitatively good for both releases; however, the EnKF method produced additional improvement for the coastal release where the spatial and temporal differences due to interior valley heating lead to the inland movement of the plume. The AP technique showed improvements for both release cases, with more improvement shown in the inland release. This research demonstrated that transport accuracy can be improved when models are adapted to a particular location/time or when important local data is assimilated into the simulation and enhances SRNL’s capability in atmospheric transport modeling in support of its current customer base and local site missions, as well as our ability to attract new customers within the intelligence community.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Monitoring, analyzing, and modeling global climate

Diabatic heating rate estimates as residuals of the dry thermodynamic equation were generated for May 1, 1985 to December 1989 in pentad resolution. Published results show moderate correlations (approx. .6) between heating rate and outgoing long wave radiation for periods under 90 days in the tropics and many extratropical locations. Nine years of simulation with the Community Climate Model 1 (CCM1) using R15 and observed sea surface temperatures shows that the model retains significantly more heat at the surface and in the free atmosphere than does the actual earth system. A post-processor for the CCM1, with capabilities to produce simulated microwave sounding unit (MSU) brightness temperatures was written. Techniques were refined considerably and validation studies were carried out to verify the globally distributed free atmosphere temperature anomalies derived from MSU data. The precision is such that detailed, long-term climate monitoring is well within the capability of these data.

Christy, John R.↗
NASA NTRS2023

Tutorial: Models and Tools at the CCMC for Space Weather Research and Education

Community Coordinated Modeling Center (CCMC) is hosting an expanding collection of space weather models covering the entire domain from the solar corona to the Earth’s lower atmosphere. The tutorial will present examples of CCMC models utilization in different research projects and demonstrate how CCMC tools and systems can be utilized in research and education. The presentation will also include highlights of International Space Weather Action Teams Initiatives and discuss opportunities for early career scientists. The presentation will be followed by hands-on demo of CCMC tools and systems.

Maria Kuznetsova↗