SEARCH · Search NASA
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.
Infrasound data and radiosonde profiles. These data were collected during the AtmoSense campaign.
TROPOMI, the Tropospheric Monitoring Instrument aboard the Sentinel-5 Precursor satellite, provides high spatiotemporal resolution atmospheric measurements. It is essential for monitoring air quality, greenhouse gases, and other trace gases. Integrating TROPOMI Level 2 data into an ArcGIS Image Service marks a significant advancement in the accessibility and utility of satellite-derived environmental information for GIS applications. This paper details the methodology for building an ArcGIS Image Service tailored to handle TROPOMI Level 2 data, with a focus on preprocessing, transformation, and cloud-based publication. The workflow utilizes Python and ArcPy for data reformatting, reprojection, and updating, ensuring efficient processing and cloud-based notifications. By establishing a robust pipeline, the ArcGIS Image Service provides real-time access to TROPOMI Level 2 data, enabling users to visualize, analyze, and interpret atmospheric phenomena effectively.
We present an ultraviolet to infrared search for the electromagnetic (EM) counterpart to GW190425, the second ever binary neutron star merger discovered by the LIGO-Virgo-KAGRA Collaboration. GW190425 was more distant and had a larger localization area than GW170817, so we use a new tool, Teglon, to redistribute the GW190425 localization probability in the context of galaxy catalogs within the final localization volume. We derive a 90th percentile area of 6688 deg 2 , a ∼1.5× improvement relative to the LIGO/Virgo map, and show how Teglon provides an order-of-magnitude boost to the search efficiency of small (≤1 deg 2 ) field-of-view instruments. We combine our data with a large, publicly reported imaging data set, covering 9078.59 deg 2 of unique area and 48.13% of the LIGO/Virgo-assigned localization probability, to calculate the most comprehensive kilonova (KN), short gamma-ray burst (sGRB) afterglow, and model-independent constraints on the EM emission from a hypothetical counterpart to GW190425 to date under the assumption that no counterpart was found in these data. If the counterpart were similar to AT 2017gfo, there would be a 28.4% chance of it being detected in the combined data set. We are relatively insensitive to an on-axis sGRB, and rule out a generic transient with a similar peak luminosity and decline rate as AT 2017gfo to 30% confidence. Finally, across our new imaging and publicly reported data, we find 28 candidate optical counterparts that we cannot rule out as being associated with GW190425, finding that four such counterparts discovered within the localization volume and within 5 days of merger exhibit luminosities consistent with a KN.
Resilience activities are an emerging area within regulatory utility policy. As resilience frameworks develop, many Public Utility Commissions (PUCs) are looking to initiate resilience activities and have identified enhancing grid reliability as a practical starting point. Reliability describes the grid’s ability to deliver electricity steadily and without interruptions under normal or “blue sky” conditions. Reliability is measured using industry standard metrics such as outage frequency (SAIFI) and outage duration (SAIDI). Resilience is broader, reflecting the grid’s ability to both withstand and recover from disruptions, particularly those caused by extreme events such as severe storms. A reliable grid minimizes routine disruptions; a resilient grid ensures the system can recover quickly when disruptions occur, preventing them from escalating into widespread or prolonged crises.
This project involved observations of far-infrared (FIR) fine-structure lines of [S III] (19,33 microns), [O III] (52,99 microns), and [N III] (57 microns) in the outer Galaxy (galactocentric radius R = 11-18 kpc), in order to study the variation of metal abundances with radius in the Galaxy. The metal abundance gradient is a fundamental input into models of galaxy evolution, and greatly constrains theories of galaxy evolution, stellar structure and evolution, and star formation. In addition, we observed the [C III (158 microns) and [O I] (63 microns) lines in these same regions to study molecular cloud structure in the low metallicity outer Galaxy. These observations were carried out over two weeks in August 1995 aboard the Kuiper Airborne Observatory, which was stationed at Hickam AFB at the time. Two Harvey Mudd students worked with me planning the observations and accompanied me on the flights. These students, and two other Harvey Mudd students, worked with me during the remaining time of the grant period analyzing these data and preparing them for publication These data have formed the basis for two journal articles in a professional astronomical journal. The first off these articles has been published (Rudolph et al. 1997, "Far-Infrared Abundance Measurements in the Outer Galaxy", The Astrophysical Journal, 489, 94-101). The second article is in preparation (Rudolph et al. 1999, "The Abundance Gradient in the Galaxy", in preparation for The Astrophysical Journal).
Contents of the papers include: Visualization techniques- The next generation, Small-machine visualizing very big data sets, Public display of Lunar Prospector data, Steering molecules via Feel, High-dimensional data browser, Multi-source visualization, Interactive surface flow visualization, and the Virtual Windtunnel.
The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions, with applications extending from process-based studies to multi-scale model intercomparison and improvement as well as to remote-sensing algorithm assessments and advancements. ACTIVATE used two NASA Langley Research Center aircraft, a HU-25 Falcon and King Air, to conduct systematic and spatially coordinated flights over the northwest Atlantic Ocean, resulting in 162 joint flights and 17 other single-aircraft flights between 2020 and 2022 across all seasons. Data cover 574 and 592 cumulative flights hours for the HU-25 Falcon and King Air, respectively. The HU-25 Falcon conducted profiling at different level legs below, in, and just above boundary layer clouds (< 3 km) and obtained in situ measurements of trace gases, aerosol particles, clouds, and atmospheric state parameters. Under cloud-free conditions, the HU-25 Falcon similarly conducted profiling at different level legs within and immediately above the boundary layer. The King Air (the high-flying aircraft) flew at approximately ∼ 9 km and conducted remote sensing with a lidar and polarimeter while also launching dropsondes (785 in total). Collectively, simultaneous data from both aircraft help to characterize the same vertical column of the atmosphere. In addition to individual instrument files, data from the HU-25 Falcon aircraft are combined into “merge files” on the publicly available data archive that are created at different time resolutions of interest (e.g., 1, 5, 10, 15, 30, 60 s, or matching an individual data product's start and stop times). This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes. The data are publicly accessible through https://doi.org/10.5067/SUBORBITAL/ACTIVATE/DATA001 (ACTIVATE Science Team, 2020).
Infrasound data and balloon trajectories. These data were collected during the OSIRIS-REx sample return capsule re-entry.
Upcoming cosmological surveys have the potential to reach groundbreaking discoveries on multiple fronts, including the neutrino mass, dark energy, and inflation. Most of the key science goals require the joint analysis of datasets from multiple surveys to break parameter degeneracies and calibrate systematics. To realize such analyses, a large set of mock simulations that realistically model correlated observables is required. In this paper we present the N-body component of the HalfDome cosmological simulations, designed for the joint analysis of Stage-IV cosmological surveys, such as Rubin LSST, Euclid, SPHEREx, Roman, DESI, PFS, Simons Observatory, CMB-S4, and LiteBIRD. Our 300TB initial data release includes full-sky lightcones and halo catalogs between z = 0–4 for 11 fixed cosmology realizations, as well as an additional run with local primordial non-Gaussianity (f NL = 20). The simulations evolve 61443 particles in a 3.75 h -1 Gpc box, reaching a minimum halo mass of ∼6 × 1012 h -1 M ⊙ and maximum scale of k ∼ h Mpc-1. Our data is publicly available: instructions to access the data and plans for future data releases can be found at https://halfdomesims.github.io.
Real-time data filtering and selection—or trigger—systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider must process extremely high-rate data streams under stringent bandwidth, latency, and storage constraints. Yet these systems are typically designed as static, hand-tuned menus of selection criteria grounded in prior knowledge and simulation. In this work, we further explore the concept of a self-driving trigger, an autonomous data-filtering framework that reallocates resources and adjusts thresholds dynamically in real-time to optimize signal efficiency, rate stability, and computational cost as instrumentation and environmental conditions evolve. We introduce a benchmark ecosystem to emulate realistic collider scenarios and demonstrate real-time optimization of a menu including canonical energy sum triggers as well as modern anomaly-detection algorithms that target non-standard event topologies using machine learning. Using simulated data streams and publicly available collision data from the Compact Muon Solenoid experiment, we demonstrate the capability to dynamically and automatically optimize trigger performance under specific cost objectives without manual retuning. Our adaptive strategy shifts trigger design from static menus with heuristic tuning to intelligent, automated, data-driven control, unlocking greater flexibility and discovery potential in future high-energy physics analyses.
The Offshore Geologic Carbon Storage Data Collection Web Application is an interactive data collection which aggregates and disseminates publicly available data to support offshore geologic carbon storage (GCS) in the United States. This data collection can be leveraged by stakeholders to understand where GCS may be viable offshore, create GCS project analogs, and address challenges to GCS in offshore environments. Use of this tool is solely at the discretion of the user. See full Federal Disclaimer for further information (https://netl.doe.gov/home/disclaimer).
The purpose of this data services request was to demonstrate integration of the Atmospheric Radiation Measurement (ARM) User Facility’s “met” datastreams with time series data from other earth science data sources using the BASIN-3D data synthesis software tool. BASIN-3D is an open-source Python library that enables researchers to integrate data across configured public and private data sources. It provides a common query language for researchers to request measurement locations and time series data based on specified locations, variables, time period, statistics, aggregation, and data quality. BASIN-3D acquires the data that match the query from each configured data source and translates the results into harmonized vocabularies, thus reducing researchers' data-wrangling effort. In addition, because the queries are executed on demand, researchers can easily regenerate their synthesized data sets as new data and/or data updates become available, eliminating one-off data products. BASIN-3D can output data using a variety of different data structures for end-user applications including Python pandas data frames and hdf5 output formats.
Ocean phytoplankton, detrital material, and water absorb and scatter light spectrally. The Ocean- Atmosphere Spectral Irradiance Model (OASIM) is intended to provide surface irradiance over the oceans with sufficient spectral resolution to support ocean ecology, biogeochemistry, and heat exchange investigations, and of sufficient duration to support inter-annual and decadal investigations. OASIM total surface irradiance (integrated 200 nm to 4 microns) was compared to in situ data and three publicly available global data products at monthly 1-degree resolution. OASIM spectrally-integrated surface irradiance had root mean square (RMS) difference= 20.1 W/sq m (about 11%), bias=1.6 W/sq m (about 0.8%), regression slope= 1.01 and correlation coefficient= 0.89, when compared to 2322 in situ observations. OASIM had the lowest bias of any of the global data products evaluated (ISCCP-FD, NCEP, and ISLSCP 11), and the best slope (nearest to unity). It had the second best RMS, and the third best correlation coefficient. OASIM total surface irradiance compared well with ISCCP-FD (RMS= 20.7 W/sq m; bias=-11.4 W/sq m, r=0.98) and ISLSCP II (RMS =25.2 W/sq m; bias= -13.8 W/sq m; r=0.97), but less well with NCEP (RMS =43.0 W/sq m ;bias=-22.6 W/sq m; x=0.91). Comparisons of OASIM photosynthetically available radiation (PAR) with PAR derived from SeaWiFS showed low bias (-1.8 mol photons /sq m/d, or about 5%), RMS (4.25 mol photons /sq m/d ' or about 12%), near unity slope (1.03) and high correlation coefficient (0.97). Coupled with previous estimates of clear sky spectral irradiance in OASIM (6.6% RMS at 1 nm resolution), these results suggest that OASIM provides reasonable estimates of surface broadband and spectral irradiance in the oceans, and can support studies on ocean ecosystems, carbon cycling, and heat exchange.
Both the Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellites are returning rich data for the study of the solid earth, the oceans, and the climate. Current software analysis tools do not provide researchers with the ease and flexibility required to make full use of this data. We evaluate the capabilities and shortcomings of existing software tools including Mathematica, the GOCE User Toolbox, the ICGEM's (International Center for Global Earth Models) web server, and Tesseroids. Using existing tools as necessary, we design and implement software with the capability to produce gridded data and publication quality renderings from raw gravity data. The straight forward software interface marks an improvement over previously existing tools and makes new space gravity data more useful to researchers. Using the software we calculate Bouguer anomalies of the gravity tensor's vertical component in the Gulf of Mexico, Antarctica, and the 2010 Maule earthquake region. These maps identify promising areas of future research.
In this paper we describe measurements of the bidirectional reflectance-distribution function (BRDF) acquired over a 30-year period (1984-2014) by the National Aeronautics and Space Administration's (NASA's) Cloud Absorption Radiometer (CAR). Our BRDF database encompasses various natural surfaces that are representative of many land cover or ecosystem types found throughout the world. CAR's unique measurement geometry allows a comparison of measurements acquired from different satellite instruments with various geometrical configurations, none of which are capable of obtaining such a complete and nearly instantaneous BRDF. This database is therefore of great value in validating many satellite sensors and assessing corrections of reflectances for angular effects. These data can also be used to evaluate the ability of analytical models to reproduce the observed directional signatures, to develop BRDF models that are suitable for sub-kilometer-scale satellite observations over both homogeneous and heterogeneous landscape types, and to test future spaceborne sensors. All of these BRDF data are publicly available and accessible in hierarchical data format (http:car.gsfc.nasa.gov/).
The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been actively involved in many aspects of ensuring the long-term preservation of NASA earth science data and knowledge. This involves both the recovery and preservation of early NASA meteorological and other earth observation data, as well as preserving the more recent Earth Observation System (EOS) mission data sets which continue or have reached their end of lifetime. The GES DISC adds value to these preserved data by adding metadata and making the data available online to future researchers. The early NASA meteorological and earth observation data sets from the 1960s and 70s were originally archived on magnetic tapes, and visualizations of these data were preserved on 70-mm film. As these media have aged, their contents have been at risk of permanent loss. NASA has given the task of preserving these early data sets to the GES DISC and making these data sets easily available to the public. The data from these early missions are potentially useful to climate researchers as these are some of the only global measurements made at their time. These old data on magnetic tapes and film strips do not contain easily readable metadata, and so to add value the GES DISC has added digital metadata to them so that the data are searchable and findable. The GES DISC is also involved in preserving the data and knowledge from the EOS era missions. The GES DISC follows the guidelines developed for the preservation of data as specified in the NASA EOS Data and Information System (EOSDIS) Earth Science Data Preservation Content Specification (423-SPEC-001) document. To date, the GES DISC has consulted with the data science teams from the following missions: UARS, Earth Probe TOMS, Aura HIRDLS, and SORCE, in order to properly preserve their data and accompanying documentation. The GES DISC is also currently working with the EOS science teams from TRMM, AIRS, MLS, OMI and additional missions to ensure that the relevant documents and data sets are properly archived for future researchers. A standardized procedure for mission data preservation following 423-SPEC-001 makes preservation among the many NASA EOSDIS data centers uniform, so that these could be transitioned easily to a common EOSDIS preservation repository. This presentation will give an overview of the preservation and recovery of the old NASA historical data sets archived at the GES DISC, as well as the data and documentation preservation efforts of the EOS era missions.
NASA produces a large volume and variety of data products that are used every day to support research, decision making, and education. The widespread use of NASA’s Earth Science data is enabled by NASA’s Earth Science Data System (ESDS) program, which oversees the archiving and distribution of these data and invests in the development of new data systems and tools. However, NASA’s current approach to Earth Science data distribution — based on distributed institutional archives with individual on-premises high-performance computing capabilities — faces some significant challenges, including massive increases in data volume from upcoming missions, a greater need for transdisciplinary science that synthesizes many different kinds of observations, and a push to make science more open, inclusive, and accessible. To address these challenges, NASA is aggressively migrating its Earth Science data and related tools and services into the commercial cloud. Migration of data into the commercial cloud can significantly improve NASA’s existing data system capabilities by (1) providing more flexible options for storage and compute (including rapid, as-needed access to state-of-the-art capabilities); (2) by centralizing and standardizing data access, which gives all of NASA’s institutional data centers access to all of each other’s datasets; and (3) by facilitating “analysis-in-place”, whereby users can bring their own computational workflows and tools to the data rather than having to maintain their own copies of NASA datasets. However, migration to the commercial cloud also poses some significant challenges, including (1) managing costs under a “pay-as-you-go” model; (2) incompatibility with existing tools and data formats with object-based storage and network access; (3) vendor lock-in; (4) challenges with data access for workflows that mix on-premise and cloud computing; and (5) standardization for highly diverse data as is present in NASA’s data archive. I conclude with two examples of recent NASA activities showcasing capabilities enabled by the commercial cloud: An interactive analysis and development platform for analyzing airborne imaging spectroscopy data, and a new collection of tools and services for data discovery, analysis, publication, and data-driven storytelling (Visualization, Exploration, and Data Analysis, VEDA).
This dataset contains the publicly available data for the publication "Stability analysis of WEST L-mode discharges with improved confinement from boron powder injection" by Bodner et al. The data is stored as both matlab save files (.mat) and text files (.txt). Instructions on how to the reproduce the figures are detailed in the included README.txt file.