Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Earth Science Data Systems”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Field-warmed soil carbon changes imply high 21st-century modeling uncertainty

Abstract. The feedback between planetary warming and soil carbon loss has been the focus of considerable scientific attention in recent decades, due to its potential to accelerate anthropogenic climate change. The soil carbon temperature sensitivity is traditionally estimated from short-term respiration measurements – either from laboratory incubations that are artificially manipulated or from field measurements that cannot distinguish between plant and microbial respiration. To address these limitations of previous approaches, we developed a new method to estimate soil temperature sensitivity (Q10) of soil carbon directly from warming-induced changes in soil carbon stocks measured in 36 field experiments across the world. Variations in warming magnitude and control organic carbon percentage explained much of field-warmed organic carbon percentage (R2 = 0.96), revealing Q10 across sites of 2.2 [1.6, 2.7] 95 % confidence interval (CI). When these field-derived Q10 values were extrapolated over the 21st century using a post hoc correction of 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) Earth system model outputs, the multi-model mean soil carbon stock changes shifted from the previous value of 88 ± 153 Pg carbon (weighted mean ± 1 SD) to 19 ± 155 Pg carbon with a Q10-driven 95 % CI of 248 ± 191 to −95 ± 209 Pg carbon. On average, incorporating the field-derived Q10 values into Earth system model simulations led to reductions in the projected amount of carbon sequestered in the soil over the 21st century. However, the considerable parameter uncertainty led to extremely high variability in soil carbon stock projections within each model; intra-model uncertainty driven by the field-derived Q10 was as great as that between model variation. This study demonstrates that data integration should capture the variation of the system, as well as mean trends.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Arctic Soil Patterns Analogous to Fluid Instabilities: Supporting Data

This dataset characterizes solifluction lobe morphology and spatial patterns using pre-existing LiDAR-derived digital elevation models of 25 sites across Norway with accompanying long term climate data for each site. Data were collected as part of an effort to better understand controls on the formation of solifluction patterns and to test the idea that they are analogous to fluid instabilities. We also provide soil velocity profiles and estimates of effective viscosity from across the world, drawn from literature. They were collected to improve our understanding of the rheology of soliflucting soil. See this article for more information on the theoretical motivation behind this dataset see "Arctic soil patterns analogous to fluid instabilities" (Glade et al., 2021). Data files arranged in a hierarchy and include image files *.tif and *.png, GIS shapefiles and geopackages (*.gpkg), *.csv (with same file as *.xlsx), and *.py (Python scripts readable with a text editor). Files also bundled into *.zip files. Note (2021-10-20): unit corrections made on two files: RR.csv and snowfall.csv. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

NASA GEOS Composition Forecast System, GEOS-CF

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution analysis and forecasts for weather, aerosols, and air quality. Since 2019, the NASA Global Earth Observing System (GEOS) model provides global near-real-time historical estimates and daily 5-day forecasts of atmospheric composition to the public at unprecedented horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). The GEOS-CF is a tool for scientists and the public health community. This presentation will cover 1) an overview of the GEOS-CF modeling framework and data/visualization access, 2) examples of current and future applications to support NASA missions (e.g., a priori for trace gas retrievals by TEMPO, ground-based instrument teams and field campaigns), and 3) research and development activities as the GEOS-CF system continues to evolve to include multi-constituent data assimilation, near-real time emission adjustment estimates, down-scaling methods to urban-scale, and data access on Google Earth Engine, Amazon Web Services, and other platforms to integrate our state-of-the-science air quality information onto platforms used by stakeholders, air quality managers, and the public.

K. Emma Knowland↗
DOE OSTI2021

Integrating Applied Energy and BER Smart Data Capabilities to Develop a DOE Data Fabric for Energy-Water R&D

Focal Area(s): 1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: DOE R&D, including DOE’s Basic Energy Research (BER)’s Environmental Systems Science Division (EESSD) program and DOE’s applied energy research (AER) programs (EERE, FE, and NE) are producers and consumers of Earth systems datasets. This white paper focuses on the first topic area from the call in relation to how crosscutting resources and innovations from DOE’s EESSD and AER can be brought to bear to mutual benefit and more efficient energy-water, Earth system data resources through improved. The overarching challenge posed by this call focuses on how DOE can directly leverage artificial intelligence (AI) to engineer a substantial (paradigm-changing) improvement in Earth System Predictability? While stemming from DOE BER’s EESSD program, this is a challenge that is faced and also being addressed by DOE’s AER programs. Over the past decade plus, FE, EERE, and NE programs have made important strides towards addressing this need. These strides are in many ways highly complementary to EESSD’s MODEX efforts. Energy water systems spanning metocean to groundwater to surface water systems all are data driven whether for basic energy or applied energy. These are remote, multi-variate, complex natural, and in many cases engineered, systems. Key needs and challenges of both EESSD and AER include developing data-focused tools to enhance data search and discovery to fill in knowledge gaps (address sparse data challenge), and rapidly transform datasets, including disparate and multi-source data. Leveraging DOE on-premise computing (HPC, exascale) infrastructure supports the computing-intensive algorithms required to execute these data acquisition and transformation processes to derive enriched knowledge and data, driving AI/ML and big data analytics for these systems. The opportunity lies in combining BER and AER efforts to provide a more robust, advanced, efficient and complete computing data fabric to address energy-water data acquisition and assimilation needs which currently pose significant impediments to AI/ML predictions and research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterization of Extremes and Compound Impacts: Applications of Machine Learning and Interpretable Neural Networks

Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

The Stratospheric Aerosol and Gas Experiment IV

Atmospheric composition continues to be a key Earth science focus for international space agencies and research organizations. The target constituent varies depending upon the topic area of interest such as monitoring the ozone layer and the efficacy of the Montreal Protocol, assessing the influence of volcanic eruptions and large wildfires on the atmosphere, improving our knowledge of transport processes, or evaluating the impacts of greenhouse gases on climate. Additionally, there is a growing need for measurement continuity of many trace gases both from an inability to properly assess long-term trends without it as well as the reliance of reanalyses and chemistry climate models on observational input. To this end, proper continuity requires continuous and overlapping multi-instrument data records of which spaceborne measurements are a critical component. However, most current satellite systems are well beyond their expected lifetimes, and so we look toward the future to develop the Stratospheric Aerosol and Gas Experiment (SAGE) IV as a future mission concept. Enabled by the NASA Earth Science Technology Office’s (ESTO) Instrument Incubator Program, the SAGE IV Pathfinder project has developed and validated a prototype demonstration that paves the way for a future SAGE IV spaceflight mission. Utilizing solar occultation imaging, SAGE IV will be capable of measuring key species in the stratosphere and upper troposphere with the same quality as previous SAGE instruments but with greatly improved pointing knowledge and extensibility to new science targets. Furthermore, current technological advancements allow SAGE IV to fit within a CubeSat framework and make use of commercial hardware, significantly reducing the size and cost when compared with traditional missions and enabling sustainability of future measurements.

Robert Damadeo↗
NASA NTRSDate not supplied

The Stratospheric Aerosol and Gas Experiment (SAGE) IV

Atmospheric composition continues to be a key Earth science focus for international space agencies and research organizations. The target constituent varies depending upon the topic area of interest such as monitoring the ozone layer and the efficacy of the Montreal Protocol, assessing the influence of volcanic eruptions and large wildfires on the atmosphere, improving our knowledge of transport processes, or evaluating the impacts of greenhouse gases on climate. Additionally, there is a growing need for measurement continuity of many trace gases both from an inability to properly assess long-term trends without it as well as the reliance of reanalyses and chemistry climate models on observational input. To this end, proper continuity requires continuous and overlapping multi-instrument data records of which spaceborne measurements are a critical component. However, most current satellite systems are well beyond their expected lifetimes, and so we look toward the future to develop the Stratospheric Aerosol and Gas Experiment (SAGE) IV as a future mission concept. Enabled by the NASA Earth Science Technology Office’s (ESTO) Instrument Incubator Program, the SAGE IV Pathfinder project developed and validated a prototype demonstration that paves the way for a future SAGE IV spaceflight mission. Utilizing solar occultation imaging, SAGE IV will be capable of measuring key species in the stratosphere and upper troposphere with the same quality as previous SAGE instruments but with greatly improved pointing knowledge and extensibility to new science targets. The precision and stability of a well-designed occultation instrument can act as a calibration reference standard for other spaceborne instruments, ensuring proper continuity of the desired science targets. Furthermore, current technological advancements allow SAGE IV to fit within a CubeSat framework and make use of commercial hardware, significantly reducing the size and cost when compared with traditional missions and enabling sustainability of future measurements.

Robert Damadeo↗
DOE OSTI2021

Integrating continuous atmospheric boundary layer and tower-based flux measurements to advance understanding of land-atmosphere interactions

The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Envisioning U.S. Climate Predictions and Projections to Meet New Challenges

In the face of a changing climate, the understanding, predictions, and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long-term adaptation strategies, and guide mitigation approaches. Increasingly complex socio-economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high-resolution modeling of global-to-local Earth system processes across timescales, reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science-to-service pathways, and co-production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally-funded U.S. modeling groups outline here perspectives on a six-pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support next generation climate services.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps

Abstract Underlying policy efforts to address global climate change is the scientific need to develop the methods to accurately measure and model carbon stocks and fluxes across the wide range of spatial and temporal scales in the Earth system. Initiated in 2010, the NASA Carbon Monitoring System is one of the most ambitious relevant science initiatives to date, exploiting the satellite remote sensing resources, computational capabilities, scientific knowledge, airborne science capabilities, and end-to-end system expertise that are major strengths of the NASA Earth Science program. Here we provide a synthesis of ‘Phase 2’ activities (2011–2019), encompassing 79 projects, 482 publications, and 136 data products. Our synthesis addresses four key questions: What has been attempted? What major results have been obtained? What major gaps and uncertainties remain? and What are the recommended next steps? Through this review, we take stock of what has been accomplished and identify future priorities toward meeting the nation’s needs for carbon monitoring reporting and verification.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Summary of flight performance of the Skylab Earth Resources Experiment Package /EREP/

A group of six remote sensor systems (sensing visible, infrared, and microwave radiation) known as the Earth Resources Experiment Package (EREP) was flown on the NASA Skylab spacecraft to furnish data to numerous investigators in the earth sciences and in technology assessment. Inflight sensor performance in three categories (functional, geometric, and radiometric) was evaluated using: (1) ground measurements of surface, atmospheric, and illumination parameters; (2) ground deployment and operation of microwave receivers and transponders to monitor and excite the active EREP sensors; (3) measurement of surface and atmospheric parameters by instrumented aircraft on underflights of Skylab passes; and (4) analysis of the actual flight data. This resulted in identification and correction of anomalous sensor operation, quantization of geometric distortions or aberrations, improvement or confirmation of calibrations, and determination of sensitivity, accuracy, and stability of the sensors.

Potter, A. E.↗
NASA NTRS1983

Space station architectural concepts and functional capability

Space program goals that NASA can best achieve by the construction of a space station in keeping with the 1958 directive to maintain U.S. pre-eminence in space technology are discussed. Science goals that can be satisfied by a suitable equipped space station include a deeper understanding of the earth/sun system and the earth as a planet, the acquisition of new data on the evolution of the solar system, of life, and of the universe, and the extended study of the laws governing the state of matter and energy. Application goals that can be pursued with a space station include assaying all renewable and nonrenewable earth resources, predicting environment, weather, and climatic changes, studying ocean dynamics, using space to develop new processes and materials, and using space for information transmission on a global basis. The space station can serve as a waypoint for voyages by manned or unmanned spacecraft, as a laboratory, observation platform, and technology proving station, and as a base for deployment and repair of other spacecraft.

Herman, D. H.↗
NASA NTRS1985

EOS - The earth observing system of the 1990s

Attention is given to the deliberations of NASA's Earth Observing System (EOS) Science and Mission Requirements Working Group, which has addressed the requirements and prospects for low earth orbit sensor platforms in the 1990s. The proposed EOS network would link data users with mission data repositories. Three EOS instrument packages have been chosen on the basis of synergistic instrument groupings for making simultaneous observations of selected phenomena over a variety of wavelengths.

Arvidson, R. E.↗
NASA NTRS1992

The preservation of LANDSAT data by the National Land Remote Sensing Archive

Digital data, acquired by the National Landsat Remote Sensing Program, document nearly two decades of global agricultural, environmental, and sociological change. The data were widely applied and continue to be essential to a variety of geologic, hydrologic, agronomic, and strategic programs and studies by governmental, academic, and commercial researchers. Landsat data were acquired by five observatories that use primarily two digital sensor systems. The Multispectral Scanner (MSS) was onboard all five Landsats, which have orbited over 19 years; the higher resolution Thematic Mapper (TM) sensor acquired data for the last 9 years on Landsats 4 and 5 only. The National Land Remote Sensing Archive preserves the 800,000 scenes, which total more than 60 terabytes of data, on master tapes that are steadily deteriorating. Data are stored at two terabytes of data, on master tapes that are steadily deteriorating. Data are stored at two locations (Sioux Falls, South Dakota and Landover, Maryland), in three archive formats. The U.S. Geological Survey's EROS Data Center has initiated a project to consolidate and convert, over the next 4 years, two of the archive formats from antiquated instrumentation tape to rotary-recorded cassette magnetic tape. The third archive format, consisting of 300,000 scenes of MSS data acquired from 1972 through 1978, will not be converted because of budgetary constraints. This data preservation project augments EDC's experience in data archiving and information management, expertise that is critical to EDC's role as a Distributed Active Archive Center for the Earth Observing System, a new and much larger national earth science program.

Boyd, John E.↗
NASA NTRS1994

Scientific and Technical Publishing at Goddard Space Flight Center in Fiscal Year 1994

This publication is a compilation of scientific and technical material that was researched, written, prepared, and disseminated by the Center's scientists and engineers during FY94. It is presented in numerical order of the GSFC author's sponsoring technical directorate; i.e., Code 300 is the Office of Flight Assurance, Code 400 is the Flight Projects Directorate, Code 500 is the Mission Operations and Data Systems Directorate, Code 600 is the Space Sciences Directorate, Code 700 is the Engineering Directorate, Code 800 is the Suborbital Projects and Operations Directorate, and Code 900 is the Earth Sciences Directorate. The publication database contains publication or presentation title, author(s), document type, sponsor, and organizational code. This is the second annual compilation for the Center.

Source record↗
NASA NTRS2003

An Automated Approach for Acquiring Onboard Rover Science

Rover traverse distances are increasing at a faster rate than downlink capacity is increasing. As this trend continues, the quantity of data that can be returned to Earth per meter traversed is reduced. The capacity of the rover to collect data, however, remains high. This circumstance leads to an opportunity to increase mission science return by carefully selecting the data with the highest science interest for downlink. We have developed an onboard science analysis technology for increasing science return from missions. Our technology evaluates the geologic data gathered by the rover. This analysis is used to prioritize the data for transmission, so that the data with the highest science value is transmitted to Earth. In addition, the onboard analysis results are used to identify additional science gathering opportunities. A planning and scheduling component of the system enables the rover to take advantage of the identified science opportunity.

Anderson, R. C.↗
NASA NTRSDate not supplied

CERES ERBE-like Instantaneous TOA Estimates (ES-8) in HDF (CER_ES8_Aqua-FM3_Edition2)

The ES-8 archival data product contains a 24-hour, single-satellite, instantaneous view of scanner fluxes at the top-of-atmosphere (TOA) reduced from spacecraft altitude unfiltered radiances using Earth Radiation Budget Experiment (ERBE) scanner Inversion algorithms and the ERBE shortwave (SW) and longwave (LW) Angular Distribution Models (ADMs). The ES-8 also includes the total (TOT), SW, LW, and window (WN) channel radiometric data; SW, LW, and WN unfiltered radiance values; and the ERBE scene identification for each measurement. These data are organized according to the CERES 3.3-second scan into 6.6-second records. As long as there is one valid scanner measurement within a record, the ES-8 record will be generated. The following CERES ES8 data sets are currently available: CER_ES8_TRMM-PFM_Edition1 CER_ES8_TRMM-PFM_Edition2 CER_ES8_TRMM-PFM_Transient-Ops2 CER_ES8_Terra-FM1_Edition1 CER_ES8_Terra-FM2_Edition1 CER_ES8_Terra-FM1_Edition2 CER_ES8_Terra-FM2_Edition2 CER_ES8_Aqua-FM3_Edition1 CER_ES8_Aqua-FM4_Edition1 CER_ES8_Aqua-FM3_Edition2 CER_ES8_Aqua-FM4_Edition2 CER_ES8_Aqua-FM3_Edition1-CV CER_ES8_Aqua-FM4_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

LONGWAVE FLUX↗