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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
NASA NTRS2018

OMI/TROPOMI Data Support from GES DISC

The NASA GES DISC has been the official archive center for data from the Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission since 2004. In recent years, the GES DISC has been evolving and improving its data management and services in order to promote its data to be easily discovered and accessed, as well as to facilitate data "interoperability". This presentation will summarize metrics collected of OMI data usage and GES DISC data services. In order to support the recently released Sentinel-5P/TROPOMI data from ESA at the NASA GES DISC, a new End User License Agreement (EULA) has been implemented for users accessing these data from the GES DISC.

Johnson, J.↗
NASA NTRS2007

Validation of the Aura Microwave Limb Sounder middle atmosphere water vapor and nitrous oxide measurements

The quality of the version 2.2 (v2.2) middle atmosphere water vapor and nitrous oxide measurements from the Microwave Limb Sounder (MLS) on the Earth Observing System (EOS) Aura satellite is assessed. The impacts of the various sources of systematic error are estimated by a comprehensive set of retrieval simulations. Comparisons with correlative data sets from ground-based, balloon and satellite platforms operating in the UV/visible, infrared and microwave regions of the spectrum are performed. Precision estimates are also validated, and recommendations are given on the data usage. The v2.2 H2O data have been improved over v1.5 by providing higher vertical resolution in the lower stratosphere and better precision above the stratopause. The single-profile precision is ~0.2–0.3 ppmv (4–9%), and the vertical resolution is ~3–4 km in the stratosphere. The precision and vertical resolution become worse with increasing height above the stratopause. Over the pressure range 0.1–0.01 hPa the precision degrades from 0.4 to 1.1 ppmv (6–34%), and the vertical resolution degrades to ~12–16 km. The accuracy is estimated to be 0.2–0.5 ppmv (4–11%) for the pressure range 68–0.01 hPa. The scientifically useful range of the H2O data is from 316 to 0.002 hPa, although only the 82–0.002 hPa pressure range is validated here. Substantial improvement has been achieved in the v2.2 N2O data over v1.5 by reducing a significant low bias in the stratosphere and eliminating unrealistically high biased mixing ratios in the polar regions. The single-profile precision is ~13–25 ppbv (7–38%), the vertical resolution is ~4–6 km and the accuracy is estimated to be 3–70 ppbv (9–25%) for the pressure range 100–4.6 hPa. The scientifically useful range of the N2O data is from 100 to 1 hPa.

Atlas, E.↗
NASA NTRSDate not supplied

Observation impacts in the lower troposphere and challenges of Planetary Boundary Layer data assimilation

The Goddard Earth Observing System (GEOS) developed by the NASA Global Modeling and Assimilation Office assimilates a wide range of observations to support various NASA Earth Science missions. To set the stage for follow-on Planetary Boundary Layer (PBL) science and prepare for future observing systems of the next decade, we have assessed the effectiveness of the use of existing observing systems in the lower troposphere in GEOS, and analyzed model responses to the incremental analysis update (IAU) forcing. With a better understanding of the GEOS data assimilation algorithms in the PBL, we have developed strategies for improved PBL data assimilation in GEOS. The strategies to enhance data usages in both the data assimilation system and forecast model will be presented, and the utilization of PBL height data from multiple observing systems will be discussed as well.

Yanqiu Zhu↗
NASA NTRS2003

The Use of Sage Water Vapor Data for Investigating Climate Change Issues

SAGE water vapor data has proven valuable for addressing several of the important issues in climate change research. It has been used to investigate how the upper troposphere water vapor responds to warming and convection, a key question in understanding the water vapor feedback to anthropogenic global warming. In the case of summer versus winter differences, SAGE results showed that the upper tropospheric relative humidity remained approximately constant; this result was in general agreement with how a GCM handled the seasonal difference, and gave credence to the argument that the GCM was not overestimating the water vapor feedback associated with convection. In addition, the convection-water vapor relationship was investigated further using SAGE water vapor and ISCCP cloud data. The results showed that upper tropospheric drying did appear to occur simultaneously with deep convective events in the tropics, only to be replaced by moistening a few hours later, associated (most likely) with the reevaporation of moisture from anvil clouds. The total effect was, again, a moistening of the upper troposphere associated with convection. Calculation of the actual trends in upper tropospheric moisture is a potential goal for SAGE data usage; trends calculated with radiosonde data, or instruments calibrated with radiosonde data have the problem of the effect of changing radiosonde instruments. SAGE data have in effect been used to compare different radiosondes through comparisons, and could continue to do so. SAGE 3 should also help clarify the absolute accuracy of SAGE retrievals in the troposphere. and its consequences. Model results show that water vapor increases can help explain the observations of stratospheric cooling, along with increasing C02 and ozone reduction. SAGE has been shown to provide trends similar to those of some other satellite and in situ retrievals, with increasing water vapor over time. However, SAGE is impacted by aerosol contamination which must be removed from the data; approaches used in the past will be reviewed. The SAGE water vapor errors, if taken literally, would make it hard to justify using SAGE data for such trends, and the error bars must be investigated. Stratospheric water vapor increases, like tropospheric increases, would lead to noticeable warming at the surface, and their changes must be quantified.

Rind, D.↗
NASA NTRS2019

Reusability in NASA's Earth Observation System Data and Information System (EOSDIS)

NASA's Earth Observation System Data and Information System (EOSDIS) has been operational since 1994. The term FAIR is relatively recent compared to the operational life of EOSDIS. However, given the evolutionary nature of EOSDIS in response to both the state of the art and community expectations, it is useful to assess where EOSDIS stands relative to the FAIR data management. In this presentation we evaluate EOSDIS against the Reusability principle, which calls for a clear and accessible data usage license, rich description of data, detailed provenance, and compliance with domain-relevant community standards.Achieving consistent compliance for datasets is particularly challenging with the diverse community of missions and scientists providing data to EOSDIS. To address this, EOSDIS's constituent Distributed Active Archive Centers work with data producers to utilize the applicable standards and conventions. In addition, a guidebook is under development to provide comprehensive and understandable guidance on how to construct compliant, and thus more reusable, data products.

Hampapuram (Rama) Ramapriyan↗
DOE OSTI2025

Shared and Ownership Mobility Technologies in the US: Data Availability and Usage Trends

This report supports the vision for a more sustainable transportation future by summarizing and analyzing the latest data on new mobility technologies, including ridesharing, shared and privately owned bikes, e-bikes, and scooters that have emerged over the past two decades. Having access to accurate and current data that is representative of new mobility systems and individual usage of these systems across different parts of the country is critical for researchers, city and regional planning professionals, and current and potential industry technology developers to better understand and forecast usage trends both nationwide as well as across different existing and potential future markets across the country. Building on the previous study published in 2022, this report incorporates the latest available market and usage data on new mobility technologies and compares usage by Chicago and New York City demographic characteristics. Moreover, this report includes recent developments and insights on privately owned micromobility technologies. Our analysis found that more downtown areas in Chicago show high per capita usage for all three modes than in the previous study, likely due to the full launch of shared e-scooter systems citywide in 2022. Notably, the majority of high shared mobility usage is concentrated in high-income, densely populated downtown areas in Chicago, which also have good public transit access. In contrast, TNC and bikeshare usage hotspots in central Manhattan are more widely distributed, though also appear to be shaped by the geography of the public transit system. Analysis of privately owned micromobility shows that the greatest energy savings occurred when e-bikes replaced single-occupancy vehicle (SOV) trips (i.e., gasoline-powered cars driven alone). Based on the literature review and analysis results, we also make recommendations for supporting the development of both shared and privately owned micromobility programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2000

STS-99 / Endeavour SRTM Science Briefing and Applications from JSC

The primary objective of the STS-99 mission was to complete high resolution mapping of large sections of the Earth's surface using the Shuttle Radar Topography Mission (SRTM), a specially modified radar system. This radar system produced unrivaled 3-D images of the Earth's Surface. This videotape shows a science press briefing. The panel members are Michael Kobrick, the SRTM Project Scientist at JPL; Thomas Henning, SRTM Program Manager at the National Imagery and Mapping Agency; Diane Evans, the Director of the Earth Sciences Program at NASA; and Marian Werner, XSAR Project Manager for the DLR, Deutschen Zentrum fur Luft- und Raumfahrt, Germany's National Aerospace Research Center. Michael Kobrick explained the mechanics of interferometric measurements of the Earth. He explained and demonstrated with a scale model the deployable mast's use. He also explained the importance of the attitude and orbit determination avionics. A brief animated video showing how four beams would give a 225 km wide swath of the Earth topography was viewed. Thomas Henning discussed some of the usage of the digital terrain elevation data for flood relief planning, cell phone station placement, military planning for command and control centers, and flight simulation. He explained that public access to the most precise data would be limited. Diane Evans described data usage in flood prediction, earthquake fault identification and archeology. Marian Werner described the German and Italian input to the project. The questions from the press concerned the time to process this data, and the reasons for the limited access to the more precise data.

Source record↗
NASA NTRS1994

Data assimilation and model evaluation experiment datasets

The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

Lai, Chung-Cheng A.↗
NASA NTRS2017

Use of Schema on Read in Earth Science Data Archives

Traditionally, NASA Earth Science data archives have file-based storage using proprietary data file formats, such as HDF and HDF-EOS, which are optimized to support fast and efficient storage of spaceborne and model data as they are generated. The use of file-based storage essentially imposes an indexing strategy based on data dimensions. In most cases, NASA Earth Science data uses time as the primary index, leading to poor performance in accessing data in spatial dimensions. For example, producing a time series for a single spatial grid cell involves accessing a large number of data files. With exponential growth in data volume due to the ever-increasing spatial and temporal resolution of the data, using file-based archives poses significant performance and cost barriers to data discovery and access. Storing and disseminating data in proprietary data formats imposes an additional access barrier for users outside the mainstream research community. At the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), we have evaluated applying the schema-on-read principle to data access and distribution. We used Apache Parquet to store geospatial data, and have exposed data through Amazon Web Services (AWS) Athena, AWS Simple Storage Service (S3), and Apache Spark. Using the schema-on-read approach allows customization of indexing spatially or temporally to suit the data access pattern. The storage of data in open formats such as Apache Parquet has widespread support in popular programming languages. A wide range of solutions for handling big data lowers the access barrier for all users. This presentation will discuss formats used for data storage, frameworks with This presentation will discuss formats used for data storage, frameworks with support for schema-on-read used for data access, and common use cases covering data usage patterns seen in a geospatial data archive.

cloud applications↗
NASA NTRS1982

The reusable Space Shuttle Main Engine prepares for long life

Attention is given to Space Shuttle Main Engine (SSME) life extension and logistical systems that support launch and ground operations. The operations and maintenance tasks involved in this aspect of SSME development include turnaround requirements, ground support equipment, and control documentation. A discussion is presented on the spare parts provisioning system, which emphasizes the source of decision-making data and encompasses the hardware tracking system, usage data from ground testing and launch operations, and current and projected life limits. The life extension test program leads the launch program, offering comfortable life limit margins. Planned overhauls for the extension of useful hardware life beyond the 55-mission requirement, a turnabout improvement program, and a continuous training program contribute to launch cost reductions, reliable operations, and long life.

Klatt, F. P., Jr.↗
NASA NTRS1986

Rdesign: A data dictionary with relational database design capabilities in Ada

Data Dictionary is defined to be the set of all data attributes, which describe data objects in terms of their intrinsic attributes, such as name, type, size, format and definition. It is recognized as the data base for the Information Resource Management, to facilitate understanding and communication about the relationship between systems applications and systems data usage and to help assist in achieving data independence by permitting systems applications to access data knowledge of the location or storage characteristics of the data in the system. A research and development effort to use Ada has produced a data dictionary with data base design capabilities. This project supports data specification and analysis and offers a choice of the relational, network, and hierarchical model for logical data based design. It provides a highly integrated set of analysis and design transformation tools which range from templates for data element definition, spreadsheet for defining functional dependencies, normalization, to logical design generator.

Lekkos, Anthony A.↗
NASA NTRS2016

The EOSDIS Products Usability for Disaster Response

The focus of the study is to categorize both NRT and standard data products based on applicability to the SDR-defined disaster types. This will identify which datasets from current NASA satellite missions instruments are best suited for disaster response. The distribution metrics of the products that have been used for studying various selected disasters that have occurred over last 5 years will be analyzed that include volume, number of files, number of users, user domains, user country, etc. This data usage analysis will provide information to the data centers staff that can help them develop the functionality and allocate the resources needed for enhanced access and timely availability of the data products that are critical for the time-sensitive analyses.

LANCE↗
DOE OSTI2026

Data and scripts associated with “Non-random processes impacting organic matter chemistry are maximized in mid-order streams”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Non-random processes impacting organic matter chemistry are maximized in mid-order streams” submitted to Limnology and Oceanography (L&O) by Danczak et al. (in review). This package contains data and scripts used to investigate dissolved organic matter (DOM) molecular chemistry and diversification processes across 47 surface-water sampling sites in the Yakima River Basin, Washington, USA, during an August 2021 sampling campaign. The package contains analyses of ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), geochemical measurements, geospatial attributes, molecular diversity, and meta-metabolome ecological null models needed to reproduce the main manuscript results. The underlying field data were pulled from exising data packages at https://doi.org/10.15485/1892052 (Fulton et al., 2022) and https://doi.org/10.15485/1898914 (Grieger et al., 2022). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. We thank the following organizations for providing access to field locations for sample collection: the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, the Confederated Tribes and Bands of the Yakama Nation, and the Cowiche Canyon Conservatory. Research was conducted under Washington State Parks and Recreation Commission Scientific Research Permit #210901. We are grateful to the Yakama Nation Tribal Council and Yakama Nation Fisheries for their collaboration in facilitating sample collection and ensuring data usage aligns with their values and worldview. This data package contains an R-Markdown file for analyses and five folders: (1) Data, (2) Geospatial Data, (3) Supplemental_Files, (5) Figures_pdf, (4) and src. The Data folder contains tabular inputs and derived files used in the manuscript analysis. The Geospatial Data folder contains climate and water-balance, hydrologic, land-cover, population/regional water-use, stream, topographic, and stream-order attribute CSV files. The src folder contains scripts used to process data, run analyses, and generate figures. The Figures_pdf folder contains manuscript figure outputs. The Supplemental_Files folder contains supplemental analysis products. All files are .csv, .pdf, .html, .png, .R, .Rmd, .svg, or .tre. This data package is associated with the rcfsa-RC2-SPS_Null_Modeling repository found at https://github.com/river-corridors-sfa/rcfsa-RC2-SPS_Null_Modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Goddard Atmospheric Composition Data Center: Aura Data and Services in One Place

The Goddard Atmospheric Composition Data and Information Services Center (AC-DISC) is a portal to the Atmospheric Composition specific, user driven, multi-sensor, on-line, easy access archive and distribution system employing data analysis and visualization, data mining, and other user requested techniques for the better science data usage. It provides convenient access to Atmospheric Composition data and information from various remote-sensing missions, from TOMS, UARS, MODIS, and AIRS, to the most recent data from Aura OMI, MLS, HIRDLS (once these datasets are released to the public), as well as Atmospheric Composition datasets residing at other remote archive site.

Leptoukh, G.↗
DOE OSTI2026

United States Data Center Energy Usage Report: 2025 Update

This report updates the 2024 Data Center Energy Usage Report (2024 Report) and estimates that data centers could account for 11.8% of total U.S. electricity by 2030. The estimate also includes a range of scenarios that indicate the energy use could be between 9.5 and 15.3% of total U.S. electricity use by 2030. In comparison, the 2024 Report estimate range was 6.7% to 12.0% of total U.S. electricity by 2028.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2013

GHRSST-14 DAS-TAG Report

The DAS-TAG provides the informatics and data management expertise in emerging information technologies for the GHRSST community. It provides expertise in data and metadata formats and standards, fosters improvements for GHRSST data curation, experiments with new data processing paradigms, and evaluates services and tools for data usage. It provides a forum for producer and distributor data management issues and coordination.

data processing↗
DOE OSTI2025

Data Readiness for AI: A 360-Degree Survey

Artificial Intelligence (AI) applications critically depend on data. Poor-quality data produces inaccurate and ineffective AI models that may lead to incorrect or unsafe use. Evaluation of data readiness is a crucial step in improving the quality and appropriateness of data usage for AI. R&D efforts have been spent on improving data quality. However, standardized metrics for evaluating data readiness for use in AI training are still evolving. In this study, we perform a comprehensive survey of metrics used to verify data readiness for AI training. This survey examines more than 140 papers published by ACM Digital Library, IEEE Xplore, journals such as Nature, Springer, and Science Direct, and online articles published by prominent AI experts. This survey aims to propose a taxonomy of data readiness for AI (DRAI) metrics for structured and unstructured datasets. We anticipate that this taxonomy will lead to new standards for DRAI metrics that would be used for enhancing the quality, accuracy, and fairness of AI training and inference.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Performability modeling based on real data: A casestudy

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different types of errors.

Hsueh, M. C.↗