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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 613 records · Page 34

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NASA NTRS1985

Non-contacting electromagnetic de-spin system for Earth orbiting satellites

A study of electromagnetic satellite de-spin system for orbiting satellites was conducted. Exact closed form solutions for the interacting magnetic flux have been formulated both for the case of the current loop and the bar magnet. The magnet system has been extended to the case of a U shaped magnet. Magnet design details are outlined. Computer simulation of the interacting flux density profile has been attempted. Data for the de-spin times has been extended to higher rpms.

Kadaba, P. K.↗

NASA NTRSDate not supplied

The Impact of Assimilating Large Volumes of GNSS Radio Occultation Observations from Spire’s Commercial Constellation into NASA’s Global Earth Observing System

The upcoming retrospective analysis for the 21st century (R21C) reanalysis product from NASA will include the full dataset of GNSS Radio Occultation (RO) observations collected by Spire with their constellation of smallsats. The Spire RO dataset, which was purchased by NASA for its Commercial Smallsat Data Acquisition (CSDA) archive, has global coverage and includes approximately 6 thousand RO profiles per day during 2019 increasing to nearly 20 thousand in 2022-2023. This more than doubles the volume of RO profiles from all other routinely assimilated RO missions combined during 2023. The increase in the number of RO profiles available is particularly important in the extratropics as the next largest RO constellation, the state-of-the-science Formosa Satellite Mission 7 (FORMOSAT-7)/Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC-2) mission (hereafter COSMIC-2), is focused on the Tropics and only provides approximately 4 thousand RO profiles per day. The large number of observations in the Spire RO dataset have great potential to improve analyses and forecasts of the Earth’s atmosphere produced by numerical weather prediction systems. Their impact is assessed through numerical experiments using NASA’s Global Earth Observing System (GEOS) Atmospheric Data Assimilation System (ADAS) with and without the observations from the COSMIC-2 mission. The ability of the Spire RO observations to make up for the omission of the RO observations from COSMIC-2 is directly assessed over the tropics and the impact of Spire over the extratropics is compared to that of the available RO missions that sample over this region. Finally, the quality of the Spire RO observations is compared to that of the routinely assimilated RO missions using Forecast Sensitivity-based Observation Impact (FSOI).

Michael J. Murphy, Jr.↗

NASA NTRS2008

An Overview of the EOS Data Dissemination Systems

The Earth Observing System Data and Information System (EOSDIS) is the primary data system serving the broad-scope of NASA s Earth Observing System (EOS) program and a significant portion of the "heritage" Earth science data. EOSDIS was designed to support the Earth sciences within NASA s Science Mission Directorate (previously the Earth Science Enterprise (ESE) and Mission to Planet Earth). The EOS Program was NASA s contribution to the United States Global Change Research Program (USGCRP) enacted by Congress in 1990 as part of the Global Change Act. ESE s objective was to launch a series of missions to help answer fundamental global change questions such as "How is Earth changing?" and "What are the consequences for life on Earth?" resulting support of this objective, EOSDIS distributes a wide variety of data to a diverse community.

Ramapriyan, H.K.↗

NASA NTRSDate not supplied

Interannual to Decadal Variability in Subarctic Atlantic Ocean Primary Productivity Historical Variability, Dynamics, and Response to Warming

Phytoplankton primary productivity in the Subarctic Atlantic Ocean sustains valuable fisheries and exports anthropogenic atmospheric carbon dioxide, but multiple Earth system models show that this productivity declines substantially in 21st century global warming scenarios. Prior studies have investigated the spatial and temporal dynamics of the seasonal cycle of the phytoplankton, which exhibit a prominent but spatially variable spring bloom that is caused by the closely related seasonal cycles in solar radiation and vertical mixing that modulate both phytoplankton growth and loss rates. However, recent work indicates that multi-decade declines in this spring bloom with global warming in multiple Earth system models are driven by reductions in circulation of nutrients from the subtropical and tropical thermocline, rather than local changes in vertical mixing or shortwave radiation in the Subarctic. It is unclear if current models of how phytoplankton productivity varies seasonally or over a century in global warming can be interpolated to explain the interannual to decadal variability. In this poster, I will quantify the interannual to decadal variability of phytoplankton chlorophyll using historical satellite ocean color observations and model simulations with the Community Earth System Model. I will then use the observations and model simulations to elucidate the mechanisms of interannual to decadal variability and how that variability is restructured in 21st century global warming scenarios.

nterannual↗

NASA NTRSDate not supplied

Introduction to our COSPAR-Sponsored Session: Space-Observation Contributions Supporting Climate Action

• The challenge for us at COSPAR in putting this program together was that we are primarily a scientifically oriented organization. “Climate Action,” as it is often expressed publicly, tends to be the domain of “activists.” As scientists, on the other hand, to retain our credibility – and for the contributions we make to continue carrying the weight of scientific truth – it is critical that we remain even-handed in our analysis and our reporting of results. • COSPAR is the Committee on Space Research, and fortunately, much of what we observe from space bears objectively on the attributes of the Earth System and how it is evolving. We can measure from space changes in the cryosphere, in the oceans, the land surface and the atmosphere, frequently, on a global scale, to a degree that is generally not possible any other way. And we have been making such observations, in increasing detail, scope, and precision, for about 60 years. • These data help us characterize the current state and identify patterns of change in the Earth System that allow us to infer processes and to improve climate models. With modeling we can test and refine our inferences, and make some predictions. The results can then inform policy and decision-makers, the public in general, as well as those taking direct action. • So, for today’s session we have invited 7 15-minute presentations spanning a broad range of climate-related topics, covering observations from space that can inform climate-related decision-making – from sea-ice extent and sea-level rise, to land surface properties and land-based water resources, to interactions between land or water surfaces and the atmosphere, to severe events in the atmosphere itself. • We begin with an overview of the observations contributed by one of the premier space agencies, given by NASA Chief Scientist and Senior Climate Advisor Dr. Kate Calvin, which will be followed by talks on what we are learning about specific attributes of the Earth System from space-based measurements that can inform climate-related policy and action.

Ralph Kahn↗

NASA NTRS2021

Harmonized Emissions Component (HEMCO) 3.0 as a Versatile Emissions Component for Atmospheric Models: Application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS Models

Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to re-grid, combine, overwrite, subset, and scale emissions from different inventories through a configuration file and with no change to the model source code. The configuration file also maps emissions to model species with appropriate units. HEMCO can operate in offline stand-alone mode, but more importantly it provides an online facility for models to compute emissions at runtime. HEMCO complies with the Earth System Modeling Framework (ESMF) for portability across models. We present a new version here, HEMCO 3.0, that features an improved three-layer architecture to facilitate implementation into any atmospheric model and improved capability for calculating emissions at any model resolution including multiscale and unstructured grids. The three-layer architecture of HEMCO 3.0 includes (1) the Data Input Layer that reads the configuration file and accesses the HEMCO library of emission inventories and other environmental data, (2) the HEMCO Core that computes emissions on the user-selected HEMCO grid, and (3) the Model Interface Layer that re-grids (if needed) and serves the data to the atmospheric model and also serves model data to the HEMCO Core for computing emissions dependent on model state (such as from dust or vegetation). The HEMCO Core is common to the implementation in all models, while the Data Input Layer and the Model Interface Layer are adaptable to the model environment. Default versions of the Data Input Layer and Model Interface Layer enable straightforward implementation of HEMCO in any simple model architecture, and options are available to disable features such as re-gridding that may be done by independent couplers in more complex architectures. The HEMCO library of emission inventories and algorithms is continuously enriched through user contributions so that new inventories can be immediately shared across models. HEMCO can also serve as a general data broker for models to process input data not only for emissions but for any gridded environmental datasets. We describe existing implementations of HEMCO 3.0 in (1) the GEOS-Chem “Classic” chemical transport model with shared-memory infrastructure, (2) the high-performance GEOS-Chem (GCHP) model with distributed-memory architecture, (3) the NASA GEOS Earth System Model (GEOS ESM), (4) the Weather Research and Forecasting model with GEOS-Chem (WRF-GC), (5) the Community Earth System Model Version 2 (CESM2), and (6) the NOAA Global Ensemble Forecast System – Aerosols (GEFS-Aerosols), as well as the planned implementation in the NOAA Unified Forecast System (UFS). Implementation of HEMCO in CESM2 contributes to the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) by providing a common emissions infrastructure to support different simulations of atmospheric chemistry across scales.

Haipeng Lin↗

NASA NTRS2013

Numerical Prediction of Dust

Covers the whole breadth of mineral dust research, from a scientific perspective Presents interdisciplinary work including results from field campaigns, satellite observations, laboratory studies, computer modelling and theoretical studies Explores the role of dust as a player and recorder of environmental change This volume presents state-of-the-art research about mineral dust, including results from field campaigns, satellite observations, laboratory studies, computer modelling and theoretical studies. Dust research is a new, dynamic and fast-growing area of science and due to its multiple roles in the Earth system, dust has become a fascinating topic for many scientific disciplines. Aspects of dust research covered in this book reach from timescales of minutes (as with dust devils, cloud processes, and radiation) to millennia (as with loess formation and oceanic sediments), making dust both a player and recorder of environmental change. The book is structured in four main parts that explore characteristics of dust, the global dust cycle, impacts of dust on the Earth system, and dust as a climate indicator. The chapters in these parts provide a comprehensive, detailed overview of this highly interdisciplinary subject. The contributions presented here cover dust from source to sink and describe all the processes dust particles undergo while travelling through the atmosphere. Chapters explore how dust is lifted and transported, how it affects radiation, clouds, regional circulations, precipitation and chemical processes in the atmosphere, and how it deteriorates air quality. The book explores how dust is removed from the atmosphere by gravitational settling, turbulence or precipitation, how iron contained in dust fertilizes terrestrial and marine ecosystems, and about the role that dust plays in human health. We learn how dust is observed, simulated using computer models and forecast. The book also details the role of dust deposits for climate reconstructions. Scientific observations and results are presented, along with numerous illustrations. This work has an interdisciplinary appeal and will engage scholars in geology, geography, chemistry, meteorology and physics, amongst others with an interest in the Earth system and environmental change.

dust↗

NASA NTRS1990

Laser Atmospheric Wind Sounder (LAWS) phase 1. Volume 1: Executive summary

The laser atmospheric wind sounder (LAWS) will provide a new space based capability for the direct measurement of atmospheric winds in the troposphere. LAWS will make a major contribution toward advancing the understanding and prediction of the total Earth system and NASA's Earth Observing System (EOS) Program. LAWS is designed to measure a fundamental atmospheric parameter required to advance weather forecasting accuracies and investigate global climatic change. LAWS has a potential added benefit of providing (global) concentration profiles of large aerosols including visible and subvisible cirrus clouds, volcanic dust, smoke, and other pollutants. The objective of this Phase One study was to develop a LAWS concept and configuration. The instrument design is outlined in this first volume of three.

Source record↗

NASA NTRS1999

Advanced Geosynchronous Imager

For improved understanding of chaotic processes and the diurnal cycle, an advanced GOES imager must also have the multi-spectral spectral bands used by low earth orbit (LEO) imagers, with on-orbit calibration for all bands. A synergy between GEO and LEO radiometry would enable earth system scientists to fuse the remote sensing data from all the spaceborne platforms. These additional radiometric capabilities are designed to observe important physical processes that vary rapidly and unpredicably: smoke, fires, precipitation, ozone, volcanic ash, cloud phase and height, and surface temperature. We believe the technology now exists to develop an imaging system that can meet future weather reporting and earth system science needs. To meet this need, we propose a design for a comprehensive geosynchronous atmospheric imager. This imager is envisioned to fly on a GOES-N class spacecraft, within the volume, weight and power constraints of a platform similar to GOES-N while delivering 100 times more data and radiometric quality than the GOES-N imager. The higher data rate probably requires its own ground station, which could serve as a systems prototype for NOAA's next generation of operational satellites. For operational compatibility, our proposed advanced GOES imaging system contains the GOES-R requirements as a subset, and the GOES-N imager capabilities (and the sounder's imaging channels) as a further subset.

Chesters, Dennis↗

NASA NTRSDate not supplied

High Latitude Atmospheric Rivers: Teleconnections and Impacts

Atmospheric rivers (ARs) are long, narrow synoptic scale features that act as moisture transport vehicles by moving water vapor poleward. They are typically found in storm tracks and often have profound implications for regional hydroclimate. For high latitude locales such as Antarctica and the Arctic, ARs are fewer in number but often have an outsized impact by either producing significant snow accumulation events, or, depending on their thermal characteristics, initiating melt events on ice sheets, ice shelves, and sea ice. In this study, we apply both reanalysis and climate model data to evaluate high latitude ARs for both the Arctic and Antarctic in the context of teleconnections and modes of variability. Specifically, we fold in both MERRA-2 and ERA5 reanalysis as well as historical and climate change simulations from the CESM2 (Community Earth System Model, Version 2) and E3SMv2 (Energy Exascale Earth System Model, v2) with multiple ensemble members to better understand natural variability versus climate change signals. An overview of AR climatology and impacts will be presented, including a baseline uncertainty quantification analysis using data from ARTMIP (the Atmospheric River Tracking Method Intercomparison Project). AR impacts during specific modes of variability will be characterized by diagnosing precipitation and boundary layer temperature associated with Ars influencing the cryosphere. Modes of variability investigated include the SAM (Southern Annular Mode), PDO (Pacific Decadal Oscillation), PSA2 (Pacific South American Mode 2), the IOD (Indian Ocean Dipole), and the AO (Arctic Oscillation).

Atmospheric Rivers↗

NASA NTRSDate not supplied

Supporting Arctic Research, Engagement, and Policy With GMAO’s Next Generation Reanalysis & Prediction Systems

Modeling efforts at NASA aim to advance scientific understanding of the Earth system and its response to natural and human-induced changes and to improve our ability to predict climate, weather, and natural hazards. These efforts are particularly relevant for communities, scientists and stakeholders working and living in the Arctic. Here, we highlight current and planned Earth system prediction and data assimilation products from the Global Modeling and Assimilation Office (GMAO). We invite feedback and discussion on GMAO’s model and reanalysis development in support of Arctic research, engagement, and policy.

Lauren C Andrews↗

NASA NTRS2021

Southwest Water Resources: Monitoring Surface Water Extents of Remote Stock Ponds in the Southwestern United States Using Earth Observing Systems for Enhanced Water Resources Management

Due to increasingly frequent and severe drought conditions in the southwestern US, land managers and livestock producers need to monitor stock ponds with increasing regularity. The ability to assess stock pond water levels with Earth observing satellite systems would enhance monitoring efforts of partners at the US Forest Service, Arizona Department of Game and Fish, and the Diablo Trust. This study employed Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) to monitor surface water extent for hundreds of critical stock ponds in Arizona. Using methods adapted from previously developed image processing workflows, this project conducted a time-series analysis to capture seasonal and interannual variations in surface water area between 2013 to 2021. In addition, end users can monitor the surface water extent of stock ponds through the developed Google Earth Engine software tool called Surface Water Identification and Forecasting Tool (SWIFT). SWIFT incorporates the Automated Water Extraction Index, Modified Normalized Difference Water Index, and Tasseled Cap-Wetness Index for optical imagery and the incidence angle, VV and VH polarization bands for Sentinel-1 imagery to detect small water bodies in the study area with an overall accuracy range of 88-93%. These tools will empower our partners to monitor the extents of water in their stock ponds remotely, enabling them to develop data-informed and sustainable management solutions for decades to come.

Rainey Aberle↗

NASA NTRS2020

Historical and Future Changes in Air Pollutants from CMIP6 Models

Poor air quality is currently responsible for large impacts on human health across the world. In addition, the air pollutants ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5) are also radiatively active in the atmosphere and can influence Earth's climate. It is important to understand the effect of air quality and climate mitigation measures over the historical period and in different future scenarios to ascertain any impacts from air pollutants on both climate and human health. The Coupled Model Intercomparison Project Phase 6 (CMIP6) presents an opportunity to analyse the change in air pollutants simulated by the current generation of climate and Earth system models that include a representation of chemistry and aerosols (particulate matter). The shared socio-economic pathways (SSPs) used within CMIP6 encompass a wide range of trajectories in precursor emissions and climate change, allowing for an improved analysis of future changes to air pollutants. Firstly, we conduct an evaluation of the available CMIP6 models against surface observations of O3 and PM2.5. CMIP6 models consistently overestimate observed surface O3 concentrations across most regions and in most seasons by up to 16 ppb, with a large diversity in simulated values over Northern Hemisphere continental regions. Conversely, observed surface PM2.5 concentrations are consistently underestimated in CMIP6 models by up to 10 µg m−3, particularly for the Northern Hemisphere winter months, with the largest model diversity near natural emission source regions. The biases in CMIP6 models when compared to observations of O3 and PM2.5 are similar to those found in previous studies. Over the historical period (1850–2014) large increases in both surface O3 and PM2.5 are simulated by the CMIP6 models across all regions, particularly over the mid to late 20th century, when anthropogenic emissions increase markedly. Large regional historical changes are simulated for both pollutants across East and South Asia with an annual mean increase of up to 40 ppb for O3 and 12 µg m−3 for PM2.5. In future scenarios containing strong air quality and climate mitigation measures (ssp126), annual mean concentrations of air pollutants are substantially reduced across all regions by up to 15 ppb for O3 and 12 µg m−3 for PM2.5. However, for scenarios that encompass weak action on mitigating climate and reducing air pollutant emissions (ssp370), annual mean increases in both surface O3 (up 10 ppb) and PM2.5 (up to 8 µg m−3) are simulated across most regions, although, for regions like North America and Europe small reductions in PM2.5 are simulated due to the regional reduction in precursor emissions in this scenario. A comparison of simulated regional changes in both surface O3 and PM2.5 from individual CMIP6 models highlights important regional differences due to the simulated interaction of aerosols, chemistry, climate and natural emission sources within models. The projection of regional air pollutant concentrations from the latest climate and Earth system models used within CMIP6 shows that the particular future trajectory of climate and air quality mitigation measures could have important consequences for regional air quality, human health and near-term climate. Differences between individual models emphasise the importance of understanding how future Earth system feedbacks influence natural emission sources, e.g. response of biogenic emissions under climate change.

Air pollutants↗

NASA NTRS1992

Advanced technologies to support earth orbiting systems

Within NASA, the Office of Aeronautics and Space Technology (OAST) is conducting a major, ongoing engineering research and technology program directed toward the support of future programs, with a major focus on technology for future space science missions. OAST is conducting a substantial effort to identify the technologies required to support the evolution of Mission to Planet Earth. The effort consists of studies, workshops, and technology research programs to explore: (1) new concepts for multisatellite, earth-observing instrumentation and sensor sets; (2) information system advances for continuous and reliable processing of terabit per day data streams; and (3) infrastructure development, including spacecraft bus technology and operations for substantial performance, cost, and reliabiltiy gains. This paper discusses the technological needs of future earth science systems, reviews current and planned activities, and highlights significant achievements in the research and technology program.

Rosen, Robert↗

NASA NTRSDate not supplied

Reanalysis Activities at the NASA Global Modeling and Assimilation Office

This talk presents an overview of recent reanalysis activities at the NASA Global Modeling and Assimilation Office (GMAO) as part of a multi-faceted strategy towards an Integrated Earth System retrospective analysis, coupling components of the atmosphere, ocean, chemistry, land, and ice. While elements of the atmosphere-ocean coupled Goddard Earth Observing System (GEOS) model and data assimilation are being actively developed, a suite of reanalysis products is designed to provide further understanding of key aspects of Earth system coupling in a reanalysis context: The baseline atmospheric reanalysis, the GEOS Retrospective analysis for the early 21st Century (GEOS-R21C), features recent advances in the GEOS model and data assimilation, and targets the NASA’s Earth Observing System EOS and post-EOS satellite observations; GEOS-IT, a user-tailored low-resolution atmospheric reanalysis, serves as a second baseline to the NASA Instrument Teams for validation and calibration and drives a one-way coupled ocean reanalysis, GEOSIT-Ocean; PolarMERRA, a high-resolution downscaled product for the polar regions, focuses on improving the representation of polar atmospheric processes with an assessment of current cryospheric biases, and targeted improvements to surface sea ice and glacier conditions; Finally, R21C-Chem, an off-line atmospheric chemistry and composition reanalysis, includes both tropospheric and stratospheric trace gases. The diversity of these reanalysis activities presents unique opportunities for collaborations cross-teams/institutions, with new commercial data partners, and with end-user groups. This talk will discuss these opportunities and explore leveraging the lessons learned along the way on key drivers in Earth system interactions as we converge towards the next generation of the Modern-Era Retrospective analysis for Research and Applications (MERRA) suite.

Amal El Akkraoui↗

NASA NTRS2002

Earth observing system microwave limb sounder (EOS MLS) science data processing

Explore the source record for details and available documents.

microwave limb sounder MLS EOS Earth observing sys↗

NASA NTRS1996

Discover Earth

Discover Earth is a NASA-funded project for teachers of grades 5-12 who want to expand their knowledge of the Earth system, and prepare to become master teachers who promote Earth system science in their own schools, counties, and throughout their state. Participants from the following states are invited to apply: Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Washington, DC. Teachers selected for the project participate in a two-week summer workshop conducted at the University of Maryland, College Park; develop classroom-ready materials during the workshop for broad dissemination; conduct a minimum of two peer training activities during the coming school year; and participate in other enrichment/education opportunities as available and desired. Discover Earth is a team effort that utilizes expertise from a range of contributors, and balances science content with hands-on classroom applications.

Steele, Colleen↗

NASA NTRS1997

Discover Earth

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