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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Assessment of a Bidirectional Reflectance Distribution Correction of Above-Water and Satellite Water-Leaving Radiance in Coastal Waters

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm.

LISCO(LONG ISLAND SOUND COASTAL OBSERVATORY)↗
NASA NTRS2002

Initial Operation and Checkout of Stratospheric Aerosol Gas Experiment and Meteor-3M Satellite

Under a joint agreement between the National Aeronautics and Space Agency (NASA) and the Russian Aviation and Space Agency (RASA), the Stratospheric Aerosol Gas Experiment III (SAGE III) instrument was launched in low earth orbit on December 10,2001 aboard the Russian Meteor-3M satellite from the Baikonur Cosmodrome. SAGE III is a spectrometer that measures attenuated radiation in the 282 nm to 1550 nm wavelength range to obtain the vertical profiles of ozone, aerosols, and other chemical species that are critical in studying the trends for the global climate change phenomena. This instrument version is more advanced than any of the previous versions and has more spectral bands, elaborate data gathering and storage, and intelligent terrestrial software. There are a number of Russian scientific instruments aboard the Meteor satellite in addition to the SAGE III instrument. These instruments deal with land imaging and biomass changes, hydro-meteorological monitoring, and helio-geophysical research. This mission was under development for over a period of six years and offered a number of unique technical and program management challenges for both Agencies. SAGE III has a long space heritage, and four earlier versions of this instrument have flown in space for nearly two decades now. In fact, SAGE II, the fourth instrument, is still flying in space on NASA s Earth Radiation Budget Satellite (ERBS), and has been providing important atmospheric data over the last 18 years. It has provided vital ozone and aerosol data in the mid latitudes and has contributed vastly in ozone depletion research. Ball Aerospace built the instrument under Langley Research Center s (LaRC) management. This paper presents innovative approaches deployed by the SAGE III and the Meteor teams in performing the initial on-orbit checkout. It further documents a number of early science results obtained by deploying low risk, carefully coordinated procedures in resolving the serious operational issues of this satellite.

Habib, Shahid↗
NASA NTRS2015

Integrated Medical Model Project - Overview and Summary of Historical Application

Introduction: The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project. Methods: Figure 1 [see document] illustrates the IMM modeling system and scenario process. As illustrated, the IMM computational architecture is based on Probabilistic Risk Assessment techniques. Nineteen assumptions and limitations define the IMM application domain. Scenario definitions include crew medical attributes and mission specific details. The IMM forecasts probabilities of loss of crew life (LOCL), evacuation (EVAC), quality time lost during the mission, number of medical resources utilized and the number and type of medical events by combining scenario information with in-flight, analog, and terrestrial medical information stored in the iMED. In addition, the metrics provide the integrated information necessary to estimate optimized in-flight medical kit contents under constraints of mass and volume or acceptable level of mission risk. Results and Conclusions: Historically, IMM simulations support Science and Technology planning, Exploration mission planning, and ISS program operations by supplying simulation support, iMED data information, and subject matter expertise to Crew Health and Safety and the HRP. Upcoming release of IMM version 4.0 seeks to provide enhanced functionality to increase the quality of risk decisions made using the IMM through a more accurate representation of the real world system.

Myers, J.↗
NASA NTRS1999

Interdisciplinary Research Scenario Testing of EOSDIS

During the reporting period, the Principle Investigator (PI) has continued to serve on numerous review panels, task forces and committees with the goal of providing input and guidance for the Earth Observing System Data and Information System (EOSDIS) program at NASA Headquarters and NASA GSFC. In addition, the PI has worked together with personnel at the University of Virginia and the subcontractor (Simpson Weather Associates (SWA)) to continue to evaluate the latest releases of various versions of the user interfaces to the EOSDIS. Finally, as part of the subcontract, SWA has created an on-line Hierarchial Data Format (HDF) tutorial for non-HDF experts, particularly those that will be using EOSDIS and future EOS data products. A summary of these three activities is provided. The topics include: 1) Participation on EODIS Panels and Committees; 2) Evaluation and Tire Kicking of EODIS User Interfaces; and 3) An On-line HDF Tutorial. The report also includes attachments A, B, and C. Attachment A: Report From the May 1999 Science Data Panel. The topics include: 1) Summary of Data Panel Meeting; and 2) Panel's Comments/Recommendations. Attachment B: Survey Requesting Integrated Design Systems (IDS) Teams Input on the Descoping and Rescoping of the EODIS; and Attachment C: An HDF Tutorial for Beginners: EODIS Users and Small Data Providers (HTML Version). The topics include: 1) Tutorial Overview; 2) An introduction to HDF; 3) The HDF Library: Software and Hardware; 4) Methods of Working with HDF Files; 5) Scientific Data API; 6) Attributes and Metadata; 7) Writing a SDS to an HDF file; 8) Obtaining Information on Existing HDF Files; 9) Reading a Scientific Data Set from an HDF file: 10) Example Programs; 11) Browsing and Visualizing HDF Data; and 12) Laboratory (Question and Answer).

Emmitt, G. D.↗
NASA NTRS2016

Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

AIRS AMSU↗
NASA NTRS2019

CHIANTI-An Atomic Database for Emission Lines. XV. Version 9, Improvements for the X-Ray Satellite Lines

CHIANTI contains a large quantity of atomic data for the analysis of astrophysical spectra. Programs are available in IDL and Python to perform calculation of the expected emergent spectrum from these sources. The database includes atomic energy levels, wavelengths, radiative transition probabilities, rate coefficients for collisional excitation, ionization, and recombination, as well as data to calculate free–free, free–bound, and two-photon continuum emission. In Version 9, we improve the modeling of the satellite lines at X-ray wavelengths by explicitly including autoionization and dielectronic recombination processes in the calculation of level populations for select members of the lithium isoelectronic sequence and Fe XVIII–XXIII. In addition, existing data sets are updated, new ions are added, and new total recombination rates for several Fe ions are included. All data and IDL programs are freely available at http://www.chiantidatabase.org or through SolarSoft, and the Python code ChiantiPy is also freely available at https://github.com/chianti-atomic/ChiantiPy.

X-rays (general)↗
NASA NTRS2009

The International Space Station Urine Monitoring System (UMS)

A device capable of making in-flight volume measurements of single void urine samples, the Urine Monitoring System (UMS), was developed and flown on seven U.S. Space Shuttle missions. This device provided volume data for each urine void from multiple crewmembers and allowed samples of each to be taken and returned to Earth for post-flight analysis. There were a number of design flaws in the original instrument including the presence of liquid carry-over producing invalid "actual" micturition volumes and cross-contamination between successive users from residual urine in "dead" spots". Additionally, high or low volume voids could not be accurately measured, the on-orbit calibration and nominal use sequence was time intensive, and the unit had to be returned and disassembled to retrieve the volume data. These problems have been resolved in a new version, the International Space Station (ISS) UMS, that has been designed to provide real-time in-flight volume data with accuracy and precision equivalent to measurements made on Earth and the ability to provide urine samples that are unadulterated by the device. Originally conceived to be interfaced with a U.S.-built Waste Collection System (WCS), the unit now has been modified to interface with the Russian-supplied Sanitary Hygiene Device (ASY). The ISS UMS provides significant advantages over the current method of collecting urine samples into Urine Collection Devices (UCDs), from which samples are removed and returned to Earth for analyses. A significant future advantage of the UMS is that it can provide an interface to analytical instrumentation that will allow real-time measurement of urine bioanalytes allowing monitoring of crewmember health status during flight and the ability to provide medical interventions based on the results of these measurements. Currently, the ISS UMS is scheduled to launch along with Node-3 on STS-130 (20A) in December 2009. UMS will be installed and scientific/functional verification completed prior to placing the instrument into operation. Samples collected during the verification sequence will be returned for analyses on STS-131 (19A) currently scheduled for launch in March 2010. The presence of a UMS on ISS will provide the capability to conduct additional collaborative human life science investigations among the ISS International Partners.

Feeback, Daniel L.↗
NASA NTRS1995

Manual for a workstation-based generic flight simulation program (LaRCsim), version 1.4

LaRCsim is a set of ANSI C routines that implement a full set of equations of motion for a rigid-body aircraft in atmospheric and low-earth orbital flight, suitable for pilot-in-the-loop simulations on a workstation-class computer. All six rigid-body degrees of freedom are modeled. The modules provided include calculations of the typical aircraft rigid-body simulation variables, earth geodesy, gravity and atmospheric models, and support several data recording options. Features/limitations of the current version include English units of measure, a 1962 atmosphere model in cubic spline function lookup form, ranging from sea level to 75,000 feet, rotating oblate spheroidal earth model, with aircraft C.G. coordinates in both geocentric and geodetic axes. Angular integrations are done using quaternion state variables Vehicle X-Z symmetry is assumed.

Jackson, E. Bruce↗
NASA NTRSDate not supplied

Verification of TROPOMI NO2 Product Using OMI NO2 algorithm

We evaluated S5P TROPOspheric Monitoring Instrument (TROPOMI) operational nitrogen dioxide (NO2) product by comparing with the NO2 retrievals from Ozone Monitoring Instrument (OMI) onboard NASA’s Aura satellite. We compared spatially matched NO2 vertical column density (VCD) data from OMI and TROPOMI to identify any discrepancies between the two operational products. We also applied OMI Air-Mass Factor (AMF) algorithm to TROPOMI Slant Column Density (SCD) data (v02.03.01) aiming to create long-term merged NO2 Earth Science Data Record (https://disc.gsfc.nasa.gov/datasets/TROPOMI_MINDS_NO2_1.1/summary ). The algorithm (version 4.0) uses new Geometry-dependent Lambertian Equivalent surface Reflectivity (GLER) product available for each TROPOMI pixel. GLER is pre-calculated using the vector linearized discrete ordinate radiative transfer (VLIDORT) model, which uses as input high-resolution bidirectional reflectance distribution function (BRDF) information from NASA's Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the wind-dependent Cox–Munk wave-facet slope distribution over water, the latter with a contribution from the water-leaving radiance based on MODIS gap-filled in-water chlorophyll-a data. The GLER data, combined with consistently retrieved cloud parameters, provide improved information for the calculation of the scattering weight profiles. Additional AMF improvements result from using high resolution (0.25o latitude x 0.25o longitude) a priori NO2 profile shapes and other auxiliary information from the Global Modeling Initiative (GMI) Replay simulation sampled using S5P orbital simulator. Our TROPOMI_MINDS_NO2 algorithm employs the stratosphere-troposphere separation scheme, de-striping, and surface snow/ice treatment consistently with the latest OMI NO2 re-processing (version 4). We evaluate the TROPOMI_MINDS_NO2 product by comparing with the S5P operational NO2 product as well as with independent NO2 observations from ground-based Pandora and aircraft observations. Our results indicate that the new TROPOMI_MINDS_NO2 retrievals are generally higher than the S5P operational NO2 product over polluted regions and show improved agreement with independent validation data.

TROPOMI↗
NASA NTRS1979

Bounds on the minimum number of data transfers in WFTA and FFT programs

Bounds on the minimum number of data transfers (i.e., loads, stores, copies) required by WFTA and FFT programs are presented. The analysis is applicable to those general-purpose computers with M general processor registers, where M is equal to or greater than 4 but much less than the transform length. It is shown that the 1008-point WFTA requires about 21 percent more data transfers than the 1024-point radix-4 FFT; on the other hand, the 120-point WFTA has about the same number of data transfers as the mixed radix (4 x 4 x 4 x 2) version of the 128-point FFT and 22 percent fewer than the radix-2 version. Finally, comparisons of the 'total' program execution times (multiplications, additions, and data transfers, but not indexing or permutations) are presented.

Nawab, H.↗
NASA NTRS2016

The SMAP Level 4 Carbon PRODUCT for Monitoring Terrestrial Ecosystem-Atmosphere CO2 Exchange

The NASA Soil Moisture Active Passive (SMAP) mission Level 4 Carbon (L4_C) product provides model estimates of Net Ecosystem CO2 exchange (NEE) incorporating SMAP soil moisture information as a primary driver. The L4_C product provides NEE, computed as total respiration less gross photosynthesis, at a daily time step and approximate 14-day latency posted to a 9-km global grid summarized by plant functional type. The L4_C product includes component carbon fluxes, surface soil organic carbon stocks, underlying environmental constraints, and detailed uncertainty metrics. The L4_C model is driven by the SMAP Level 4 Soil Moisture (L4_SM) data assimilation product, with additional inputs from the Goddard Earth Observing System, Version 5 (GEOS-5) weather analysis and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The L4_C data record extends from March 2015 to present with ongoing production. Initial comparisons against global CO2 eddy flux tower measurements, satellite Solar Induced Canopy Florescence (SIF) and other independent observation benchmarks show favorable L4_C performance and accuracy, capturing the dynamic biosphere response to recent weather anomalies and demonstrating the value of SMAP observations for monitoring of global terrestrial water and carbon cycle linkages.

SMAP↗
NASA NTRS2020

Near 40 Years MERRA-2 Data at NASA GES DISC -Opportunity and Challenge to Support Extremes Study

To the end of 2019, 40 years NASA climate reanalysis data sets from the Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) will be available at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 consists atmosphere, land, and ocean data, which may be used for the studies ranging from the short scale weather events to the large scale decadal vulnerabilities. The hourly products, such as precipitation, soil moisture, temperature, and aerosols etc., have been used widely to study extreme events.In supporting users from broad communities, GES DISC have developed various data access services, including subsetter for downloading only data of interest with preferred format; OPeNDAP - for machine-to-machine data access; and Giovanni- for online visualization and analysis, etc. A big challenge for extreme study is to downloading and processing long-term hourly or daily data. The data downloading performance is not very satisfied by many users with current services and the native archived data structure. Late June 2019, many people in Europe had experienced extreme heat waves. The temperatures in several countries exceeded 40°C (104°F). For example, MERRA-2 shows that the near surface daily maximum temperature of June 28 2019 over Marseille, a city in southern France, reached 41.1 °C (106°F), which is the record breaking temperature in the last 40 years. GES DISC is working together with domain science experts to improve the performance of long time series access, making analysis ready data sets in supporting application researches, such as extreme study. In this presentation, using Europe heat wave as an example, we will show prototype of the in developing service for finding extremes from near 40 years MERRA-2 data at a given location. MERRA-2 data can be accessed from NASA GES DISC(https://disc.gsfc.nasa.gov/ ) by search keyword "MERRA-2".

Shen, Suhung↗
NASA NTRSDate not supplied

GLDAS-2 Land Surface Model Data and Data Services at NASA GES DISC

The goal of the NASA Global Land Data Assimilation System (GLDAS, https://ldas.gsfc.nasa.gov/gldas(https://ldas.gsfc.nasa.gov/gldas)) is to generate optimal fields of land surface states and fluxes by ingesting satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques (Rodell et al., 2004).The GLDAS dataset currently archived at and distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC, https://disc.gsfc.nasa.gov/ (https://disc.gsfc.nasa.gov/)) is GLDAS Version 2 (GLDAS-2). It contains a series of output fields from the upgraded Noah-3.6, Catchment-F2.5, and VIC-4.1.2 Land Surface Models (LSMs) in the Land Information System (LIS-V7, https://lis.gsfc.nasa.gov/ (https://lis.gsfc.nasa.gov/)). GLDAS-2 has three components:GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the upgraded Princeton Meteorological ForcingV2.2 Dataset and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data, with data spanning from 2000 to the present. The GLDAS-2.2 product suite uses data assimilation(DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, varies for different GLDAS-2.2 products. The currently availableGLDAS-2.2 data contain a daily 0.25-degree output from the Catchment-F2.5 LSM in LIS-V7. The data are forced with the meteorological analysis fields from the operational European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) and assimilated with GRACE and GRACE-FO data, ranging from February 1, 2003 to the present. The current GLDAS-2.0 and 2.1 Noah LSM data were reprocessed in November 2019 and January 2020 respectively and their data from Catchment and VIC LSMs are new to the GLDAS-2 collection. This presentation provides a summary of theGLDAS-2 data products, their land surface fields, and their related data services at the GES DISC; and a description of the majorGLDAS-2 climatological characteristics as well as the intercomparison with the data of the previous version.

Hydrology↗
NASA NTRS2021

The Io GIS Database 1.0: A Proto-Io Planetary Spatial Data Infrastructure

We collected a set of published, higher-order data products of Jupiterʼs volcanic moon Io and assembled them in an ArcGISTM database we are calling the Io GIS Database, version 1.0. The purpose of this database is to collect image, topographic, geologic, and thermal emission data of Io in one geospatially registered location to form the data component of an Io planetary spatial data infrastructure (PSDI). The goals of an Io PSDI are (1) to make higher-order data products more accessible and usable to the broader planetary science community, particularly to new scientists that were not associated with the projects that obtained the data; (2) to enable new scientific studies with the data; and (3) to create a tool to support observation planning for future Io-focused planetary missions. In this paper we describe the motivation behind our project, discuss the data sets acquired for this first version of the database, and demonstrate how they can be used. We conclude with a discussion of how our database relates to other PSDIs, our plans for future updates, and a request for additional Io data sets.

David A Williams↗
NASA NTRS1976

An application of the Multi-Purpose System Simulation /MPSS/ model to the Monitor and Control Display System /MACDS/ at the National Aeronautics and Space Administration /NASA/ Goddard Space Flight Center /GSFC/

The Multi-Purpose System Simulator (MPSS) model was used to investigate the current and projected performance of the Monitor and Control Display System (MACDS) at the Goddard Space Flight Center in processing and displaying launch data adequately. MACDS consists of two interconnected mini-computers with associated terminal input and display output equipment and a disk-stored data base. Three configurations of MACDS were evaluated via MPSS and their performances ascertained. First, the current version of MACDS was found inadequate to handle projected launch data loads because of unacceptable data backlogging. Second, the current MACDS hardware with enhanced software was capable of handling two times the anticipated data loads. Third, an up-graded hardware ensemble combined with the enhanced software was capable of handling four times the anticipated data loads.

Mill, F. W.↗
NASA NTRS1972

Polar orbiting operational weather satellites.

The progress in the development of operational weather satellites is reviewed, covering their chronology from Explorer 7 of 1959 through Meteor 12 of June, 1972. Special attention is given to the development of the TIROS series satellites with the evolution of their operational sensors, data systems and performance requirements. The topics also include the data collection system designs, to Advanced Very High Resolution Radiometer (AVHRR), the sounder radiometer, the Solar Environment Monitor (SEM), the data processor, and TIROS-N operation and orbital characteristics. It is expected that TIROS-N and its forthcoming advanced versions will provide an effective technology for sensing environmental data on a global scale in the latter half of the decade.

Stampfl, R. A.↗
NASA NTRS1990

Directory interchange format manual, version 3.0

The Directory Interchange Format (DIF) is a data structure used to exchange directory level information about data sets among information systems. The format consists of a number of fields that describe the attributes of a directory entry and text blocks that contain a descriptive summary of and references for the directory entry. All fields and the summary are preceded by labels identifying their contents. All values are ASCII character strings. The structure is intended to be flexible, allowing for future changes in the contents of directory entries.

Source record↗
NASA NTRS1991

Directory interchange format manual, version 4.0

The Directory Interchange Format (DIF) is a data structure used to exchange directory-level information about data sets among information systems. In general the format consists of a number of fields that describe the attributes of a directory entry and text blocks that contain a descriptive summary of and references for the directory entry. All fields and the summary are preceded by labels identifying their contents. All values are ASCII character strings. The structure is intended to be flexible, allowing for future changes in the contents of directory entries. The manual is structured as follows: section 1 is a general description of what constitutes a directory entry; section 2 describes the content of the individual fields within the data structure, together with some examples. Also included in the six appendices is a description of the syntax used within the examples; samples of the directory interchange format applied to different data sets; the allowable discipline keywords; a current list of valid location keywords; a list of allowable parameter keywords; a list of acronyns and a glossary of terms used; and a description of the Standard Formatted Data Unit header, which may be added to the front of a DIF file to identify the file as a registered standard format.

Source record↗