Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “geophysical data”

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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

A-Train Datalist - A New GES DISC Service to Allow One-Stop Shopping for A-Train Data

The currently available services at the Goddard Earth Sciences Data Information Services Center (GES DISC) only allow users to select variables from a single data set at a time. Because entire variables from a data set are often displayed, user selection of variables of interest can be overwhelming. At the American Geophysical Union (AGU) 2016 Fall Meeting, GES DISC unveiled a new service called Datalist: a collection of predefined or user-defined data variables from one or more archived data sets. Our science support team has been curating Datalists and providing added value to the user community.Originally known as Afternoon Constellation, A-Train includes six currently on polar-orbiting Earth observation satellites: OCO-2, GCOM-W1, Aqua, CALIPSO, CloudSat, and Aura, which travel a few minutes apart from each other. This constellation arrangement has enabled coordinated science observations further forming comprehensive pictures of Earth weather and climate that are readily for use in crucial studies such as climate change.GES DISC Datalists are based on the software architecture of the new GES DISC website (also unveiled at the AGU 2016 Fall Meeting). The GES DISC science support team has created a Datalist to support the A-Train Data Depot (ATDD). Using pre-defined Datalist should hopefully save users significant effort in their data searches.

A-Train data ordering↗
NASA NTRS2001

Towards a Future ICRF Realization

The data and analysis for the ICRF were completed in 1995 to define a frame to which the Hipparcos optical catalog could be fixed. Additional observations on most of the 608 sources in the overall ICRF catalog have been acquired using a small portion of geodetic observing time as well as astrometric sessions concentrating on the southern hemisphere. Positions of new sources have been determined, including approx.1200 from a VLBA phase calibrator survey. A future ICRF realization will require improved geophysical modeling, sophisticated treatment of position variations and/or source structure, optimized data selection and weighting, and reidentification of defining sources. The motivation for the next realization could be significant improvement in accuracy and density or preparation for optical extragalactic catalogs with microarcsecond precision.

Ma, Chopo↗
DOE OSTI2020

Utah FORGE: Phase 3 Microgravity Data

A 4D microgravity survey began in early 2019 in order to benchmark surface and subsurface elevations prior to Phase 3 drilling and stimulation campaigns. Microgravity stations are collocated with GPS deformation benchmarks and use the same location survey data. Surveys are undertaken on a quarterly basis. The focus of current activities is comparative analysis of GPS survey results and InSAR analysis (see GDR Submission 1251) to check seasonal variance and to evaluate possible changes in the groundwater elevation. The attached zip file contains a text file and an Excel spreadsheet containing Utah FORGE Phase 3 processed "final" microgravity data through time. The data are identical in both files. The spreadsheet is only supplied for convenience. There is also a ReadMe.txt file that describes the field headings.

15 GEOTHERMAL ENERGY↗
NASA NTRS2002

Towards a Future ICRF Realization

The data and analysis for the ICRF were completed in 1995 to define a frame to which the Hipparcos optical catalog could be fixed. Additional observations on most of the 608 sources in the overall ICRF catalog have been acquired using a small portion of geodetic observing time as well as astrometric sessions concentrating on the Southern Hemisphere. Positions of new sources have been determined, including approximately 1200 from a VLBA phase calibrator survey. A future ICRF realization will require improved geophysical modeling, sophisticated treatment of position variations and/or source structure, optimized data selection and weighting, and re-identification of defining sources. The motivation for the next realization could be significant improvement in accuracy and density or preparation for optical extragalactic catalogs with microarcsecond precision.

Ma, Chopo↗
DOE OSTI2024

Data Format and Descriptions for the Alabama Carbon Storage: Data Sharing and Engagement Project

The Alabama Carbon Storage: Data Sharing and Engagement (ACS-DSE) project seeks to develop publicly accessible geologic carbon storage models and data across the southern Gulf Coastal Plain of Alabama. The public online platform developed for this project will include geologic, geophysical, infrastructure, and other relevant datasets and geologic models of the study area. Datasets, model surfaces (e.g. structural contour maps, isolith maps, porosity maps), and infrastructure data (e.g. offshore pipelines, field boundaries) will be downloadable in commonly used file formats. The anticipated primary geologic datasets are well headers, formation tops, average reservoir properties, and core analyses; these will be available as commaseparated values (CSV) text files and MS Excel workbooks. Geophysical logs will be available in Log ASCII Standard (LAS) file format. Modeled surfaces, such as structure contour maps, will be available in ArcGIS formats and text files. Infrastructure data will be available as ArcGIS shapefiles. This document provides information on the data sources and attributes of the datasets.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1994

Vertical ocean loading amplitudes from VLBI measurements

Vertical ocean loading amplitudes are determined by analysis of IRIS geodetic Very Long Baseline Interferometry (VLBI) data. The 4 nearly diurnal (K(sub 1), P(sub 1), O(sub 1), Q(sub 1)) and 4 nearly semidiurnal (K(sub 2), S(sub 2), M(sub 2), and N(sub 2)) component amplitudes can be inferred from the data with accuracies of 1-2 mm. Uncertainties of total displacements can approach 1 cm. Empirically determined total displacements are considerably larger than the values calculated from two geophysical models. The Scherneck model is found to give a better representation of VLBI delay data than the model of Pagiatakis by about 3 mm in residuals at 6 sites. Empirical estimation of the ocean loading amplitudes reduces Chi squared by 3067 for the 96 additional degrees of freedom in a fit to 273,000 IRIS VLBI observations, and reduces the RMS residuals by 3 mm relative to a fit using the fixed Scherneck model. Vertical ocean loading amplitudes can thus be inferred from VLBI data at a level which improves the overall model, but detailed assessment of individual tidal components is presently obscured by incomplete modeling at the tidal frequencies.

Sovers, O. J.↗
NASA NTRS2014

Status of Terra MODIS Operation, Calibration, and Performance

Since launch in December 1999, Terra MODIS has successfully operated for nearly 15 years, making continuous observations. Data products derived from MODIS observations have significantly contributed to a wide range of studies of key geophysical parameters of the earth's eco-system of land, ocean, and atmosphere, and their changes over time. The quality of MODIS data products relies on the dedicated effort to monitor and sustain instrument health and operation, to calibrate and update sensor parameters and properties, and to improve calibration algorithms. MODIS observations are made in 36 spectral bands, covering wavelengths from visible to long-wave infrared. The reflective solar bands (1-19 and 26) are primarily calibrated by a solar diffuser (SD) panel and regularly scheduled lunar observations. The thermal emissive bands (20-25 and 27- 36) calibration is referenced to an on-board blackbody (BB) source. On-orbit changes in the sensor spectral and spatial characteristics are monitored by a spectroradiometric calibration assembly (SRCA). This paper provides an overview of Terra MODIS on-orbit operation and calibration activities and implementation strategies. It presents and summarizes sensor on-orbit performance using nearly 15 years of data from its telemetry, on-board calibrators, and lunar observations. Also discussed in this paper are changes in sensor characteristics, corrections applied to maintain MODIS level 1B (L1B) data quality, and efforts for future improvements.

Terra↗
NASA NTRS2000

Deep Internal Structure of Mars and the Geophysical Package of Netlander

Our present understanding of the interior structure of Mars is mostly based on the interpretation of gravity and rotation data, the chemistry of the SNC (shergottites, nakhlites, chassignites) meteoroids, and a comparison with the much better-known interior structure of the Earth. However geophysical information from previous missions have been insufficient to determine the deep internal structure of the planet. Therefore the state and size of the core and the depth and type of mantle discontinuities are unknown. Most previous seismic experiments have indeed failed, either due to a launch failure (as for the Optimism seismometer onboard the small surface stations of Mars 96) or after failure on Mars (as for the Viking 1 seismometer). The remaining Viking 2 seismometer did not produce a convincing marsquake detection, basically due to too strong wind sensitivity and too low resolution in the teleseismic frequency band. After almost a decade of continuous activity and proposals, the first network mission to Mars, NetLander (NL), is expected to be launched between 2005 and 2007. One of the main scientific objectives of this four-lander network mission will be the determination of the internal structure of the planet using a geophysical package. This package will have a seismometer, a magnetometer, and a geodetic experiment, allowing a complementary approach that will yield many new constraints on the mineralogy and temperature of the mantle and core of the planet.

Lognonne, P.↗
NASA NTRS2017

The Value of Data and Metadata Standardization for Interoperability in Giovanni Or: Why Your Product's Metadata Causes Us Headaches!

Giovanni is a data exploration and visualization tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC). It has been around in one form or another for more than 15 years. Giovanni calculates simple statistics and produces 22 different visualizations for more than 1600 geophysical parameters from more than 90 satellite and model products. Giovanni relies on external data format standards to ensure interoperability, including the NetCDF CF Metadata Conventions. Unfortunately, these standards were insufficient to make Giovanni's internal data representation truly simple to use. Finding and working with dimensions can be convoluted with the CF Conventions. Furthermore, the CF Conventions are silent on machine-friendly descriptive metadata such as the parameter's source product and product version. In order to simplify analyzing disparate earth science data parameters in a unified way, we developed Giovanni's internal standard. First, the format standardizes parameter dimensions and variables so they can be easily found. Second, the format adds all the machine-friendly metadata Giovanni needs to present our parameters to users in a consistent and clear manner. At a glance, users can grasp all the pertinent information about parameters both during parameter selection and after visualization.

interoperability↗
DOE OSTI2024

Underground hydrogen storage leakage detection and characterization based on machine learning of sparse seismic data

Underground hydrogen storage (UHS) is considered as a scalable approach for massive storage and seasonal extraction of hydrogen (H 2 ). Although conventional leakage detection and characterization methods based on time-lapse seismic imaging and inversion generally apply to H 2 leakage detection problem, a high-fidelity yet cost effective geophysics approach is still missing to reliably inform leakage location and properties based on very sparse data. In response, we develop a novel supervised machine learning method to detect and characterize H 2 leakage from UHS. The input to our neural network are sparse time-lapse seismic waveforms, while the output from the neural network includes the spatial location and physical properties of a H 2 leakage. Here, we generate high-quality time-lapse waveforms using the elastic-wave equations to train the neural network. We train and validate our machine learning model and find that it attains high accuracy in using extremely sparse time-lapse seismic data to detect and characterize H 2 leakage. Our investigation is the first systematic study that focuses on applying machine learning to subsurface H 2 leakage detection and characterization and could potentially serve as a cost-effective geophysical tool for underground hydrogen leakage detection and characterization with high fidelity.

08 HYDROGEN↗
NASA NTRS2000

Automatic Weather Station (AWS) Lidar

An autonomous, low-power atmospheric lidar instrument is being developed at NASA Goddard Space Flight Center. This compact, portable lidar will operate continuously in a temperature controlled enclosure, charge its own batteries through a combination of a small rugged wind generator and solar panels, and transmit its data from remote locations to ground stations via satellite. A network of these instruments will be established by co-locating them at remote Automatic Weather Station (AWS) sites in Antarctica under the auspices of the National Science Foundation (NSF). The NSF Office of Polar Programs provides support to place the weather stations in remote areas of Antarctica in support of meteorological research and operations. The AWS meteorological data will directly benefit the analysis of the lidar data while a network of ground based atmospheric lidar will provide knowledge regarding the temporal evolution and spatial extent of Type la polar stratospheric clouds (PSC). These clouds play a crucial role in the annual austral springtime destruction of stratospheric ozone over Antarctica, i.e. the ozone hole. In addition, the lidar will monitor and record the general atmospheric conditions (transmission and backscatter) of the overlying atmosphere which will benefit the Geoscience Laser Altimeter System (GLAS). Prototype lidar instruments have been deployed to the Amundsen-Scott South Pole Station (1995-96, 2000) and to an Automated Geophysical Observatory site (AGO 1) in January 1999. We report on data acquired with these instruments, instrument performance, and anticipated performance of the AWS Lidar.

Rall, Jonathan A.R.↗
NASA NTRS1976

Terrestrial bodies orbiter, LUNAR - A system for detailed global measurements of a planet's properties

The NASA Lunar Polar Orbiter, to be launched by a Delta vehicle in 1980, is designed to perform a global exploration of such moon properties as the gravity field, figure, and surface composition, as well as a lunar resource survey. The paper reviews the mission, spacecraft, and data system concepts in terms of baseline mission sequence, choice of orbits, spacecraft configuration requirements, mission sequence requirements and data system and operations. Scientific experiments planned for the Orbiter mission include geophysical altimetry and gravity experiments, heat flow experiment, magnetic field experiments, measurements of the moon's natural gamma-ray spectrum, X-ray fluorescence of lunar surface materials, sunlight reflectance spectroscopy, and spectro-stereo imaging. Characteristics of instruments designed for use in these investigations are examined. Through the use of advanced sensors and data-system techniques, coupled with well-developed spacecraft systems, the mission promises to return a very large quantity and variety of lunar data at a cost comparable with that of simpler missions in the past.

Burke, J. D.↗
NASA NTRS2008

Evolution of the Earth Observing System (EOS) Data and Information System (EOSDIS)

One of the strategic goals of the U.S. National Aeronautics and Space Administration (NASA) is to "Develop a balanced overall program of science, exploration, and aeronautics consistent with the redirection of the human spaceflight program to focus on exploration". An important sub-goal of this goal is to "Study Earth from space to advance scientific understanding and meet societal needs." NASA meets this subgoal in partnership with other U.S. agencies and international organizations through its Earth science program. A major component of NASA s Earth science program is the Earth Observing System (EOS). The EOS program was started in 1990 with the primary purpose of modeling global climate change. This program consists of a set of space-borne instruments, science teams, and a data system. The instruments are designed to obtain highly accurate, frequent and global measurements of geophysical properties of land, oceans and atmosphere. The science teams are responsible for designing the instruments as well as scientific algorithms to derive information from the instrument measurements. The data system, called the EOS Data and Information System (EOSDIS), produces data products using those algorithms as well as archives and distributes such products. The first of the EOS instruments were launched in November 1997 on the Japanese satellite called the Tropical Rainfall Measuring Mission (TRMM) and the last, on the U.S. satellite Aura, were launched in July 2004. The instrument science teams have been active since the inception of the program in 1990 and have participation from Brazil, Canada, France, Japan, Netherlands, United Kingdom and U.S. The development of EOSDIS was initiated in 1990, and this data system has been serving the user community since 1994. The purpose of this chapter is to discuss the history and evolution of EOSDIS since its beginnings to the present and indicate how it continues to evolve into the future. this chapter is organized as follows. Sect. 7.2 provides a discussion of EOSDIS, its elements and their functions. Sect. 7.3 provides details regarding the move towards more distributed systems for supporting both the core and community needs to be served by NASA Earth science data systems. Sect. 7.4 discusses the use of standards and interfaces and their importance in EOSDIS. Sect. 7.5 provides details about the EOSDIS Evolution Study. Sect. 7.6 presents the implementation of the EOSDIS Evolution plan. Sect. 7.7 briefly outlines the progress that the implementation has made towards the 2015 Vision, followed by a summary in Sect. 7.8.

Ramapriyan, Hampapuram K.↗
NASA NTRS2000

Application of Radar Data to Remote Sensing and Geographical Information Systems

The field of synthetic aperture radar changed dramatically over the past decade with the operational introduction of advance radar techniques such as polarimetry and interferometry. Radar polarimetry became an operational research tool with the introduction of the NASA/JPL AIRSAR system in the early 1980's, and reached a climax with the two SIR-C/X-SAR flights on board the space shuttle Endeavour in April and October 1994. Radar interferometry received a tremendous boost when the airborne TOPSAR system was introduced in 1991 by NASA/JPL, and further when data from the European Space Agency ERS-1 radar satellite became routinely available in 1991. Several airborne interferometric SAR systems are either currently operational, or are about to be introduced. Radar interferometry is a technique that allows one to map the topography of an area automatically under all weather conditions, day or night. The real power of radar interferometry is that the images and digital elevation models are automatically geometrically resampled, and could be imported into GIS systems directly after suitable reformatting. When combined with polarimetry, a technique that uses polarization diversity to gather more information about the geophysical properties of the terrain, a very rich multi-layer data set is available to the remote sensing scientist. This talk will discuss the principles of radar interferometry and polarimetry with specific application to the automatic categorization of land cover. Examples will include images acquired with the NASA/JPL AIRSAR/TOPSAR system in Australia and elsewhere.

vanZyl, Jakob J.↗
NASA NTRS1998

Atmospheric Aerosol Chemical Composition Measurements for the Subsonic Aircraft: Contrail and Cloud Effects Special Study (SUCCESS)

We received funding to provide measurements of the chemical composition of aerosols aboard the NASA Ames DC-8 research aircraft during the SUCCESS mission. These measurements were successfully completed and the final data resides in the Cloud I computer archive at NASA Ames Research Center. The interpretation of the data obtained on this mission over the central United States has been published in special issues of Geophysical Research Letters. The papers with the University of New Hampshire as first author constitute this report and summarize the salient features of our data. The paper by Talbot et al. discusses the impact of vertical transport on free tropospheric chemistry over the the central USA in springtime. This transport was a dominant feature of the aerosol chemistry during SUCCESS. The paper by Dibb et al. discusses aerosol chemistry specifically as it related to free tropospheric sulfate related to jet exhaust and surface sources. Somewhat surprisingly, we found that surface sources appeared to dominant the distribution of aerosol sulfate in the free troposphere. In addition to these first authored papers, researchers from the University of New Hampshire were co-authors on numerous other companion papers in the special issues.

Talbot, Robert W.↗
NASA NTRS2001

Meteorological Data for Geodynamics Use: IERS Special Bureau for the Atmosphere

During the life of this contract, the PI set up and operated a data center known as the "Special Bureau for the Atmosphere" of the International Earth Rotation Service (IERS) at Atmospheric and Environmental Research, Inc., and in conjunction with the U.S. National Oceanic and Atmospheric Administration. The role of the center is to calculate, archive, analyze, and distribute atmospheric data related to Earth rotation, polar motion and other motions of the Earth. We have produced data from 4 different operational meteorological centers. We have also produced data from atmospheric reanalyzes, spanning back about a half a century. The center is one of several centers under the Global Geophysical Fluids Center (GGFC) of the IERS; the GGFC is centered at NASA's Goddard Space Flight Center. Our data center has made data available to a large variety of scientists worldwide.

Salstein, David A.↗
DOE OSTI2021

WHOLESCALE: Seismic Survey Metadata from San Emidio Nevada 2021

This is a collection of metadata from the 2021 seismic survey at the San Emidio geothermal field in Nevada. In April and May 2021, 37 tri-axial short period seismographs were deployed in a 1.8km diameter cluster centered on 40.367278 deg N, 119.409019 deg W. The first data record started at 2021-04-06T07:09:10Z UTC and the last record ended 2021-05-11T02:58:52Z UTC. The 37 stations included 29 SmartSolo IGU-16HR 3C all-in-one 5 Hz seismographs and 8 DataCube seismographs with 4.5 Hz HGS HG-6(B coil) tri-axial geophones. The raw format (level 0) data includes 353 GB of 500 sps SmartSolo data in native DLD format, 113 GB of 400 sps DataCube data in native DataCube format, and 3.4 GB of GPS data collected during the RTK GPS survey. The SAC data (level 1) files include 564 GB of hourly SAC files. The experiment was designed to monitor seismic activity before, during, and after the planned three-day plant maintenance shutdown April 19-21, 2021. The pumping stopped at 2021/04/19 12:51:45 UTC and resumed about 2021/04/21 21:00:00 UTC. The raw and processed data are in an associated GDR submission, linked below. The metadata here includes files containing experiment details, station locations, seismic data logger specifications, instrumentation specifications, and descriptions of data. Also included are data and metadata from a 2016 seismic survey at the same site.

15 GEOTHERMAL ENERGY↗