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A detailed description of the machine-readable catalog as it is currently being distributed from the Astronomical Data Center is given. The catalog contains a main data file of 2970 sources and a supplemental file of 3176 sources measured at wavelengths of 4.2, 11, 20 and 27 microns.
The merging of data from various catalogs and their incorporation into existing databases such as SIMBAD is a demanding task, mainly because of the diverse and inconsistent astronomical nomenclature that has developed over the years. Although the cross identification of objects by computer is in principle an extremely simple procedure, numerous pitfalls have been encountered in practice because of errors and mutually exclusive identifications in existing catalogs. The incorporation of classical and new data into SIMBAD is clearly simplified if machine versions of catalogs are prepared with a view toward this problem. New versions of a number of important catalogs have been prepared and fully documented at the Astronomical Data Center, NASA Goddard Space Flight Center with consideration of both independent use and data integration. Recently completed catalogs and current projects will be reviewed in this presentation.
The background and goals of Indian Ocean thermal sampling are discussed from the perspective of a national project which has research goals relevant to variation of climate in Australia. The critical areas of SST variation are identified. The first goal of thermal sampling at this stage is to develop a climatology of thermal structure in the areas and a description of the annual variation of major currents. The sampling strategy is reviewed. Dense XBT sampling is required to achieve accurate, monthly maps of isotherm-depth because of the high level of noise in the measurements caused by aliasing of small scale variation. In the Indian Ocean ship routes dictate where adequate sampling can be achieved. An efficient sampling rate on available routes is determined based on objective analysis. The statistical structure required for objective analysis is described and compared at 95 locations in the tropical Pacific and 107 in the tropical Indian Oceans. XBT data management and quality control methods at CSIRO are reviewed. Results on the mean and annual variation of temperature and baroclinic structure in the South Equatorial Current and Pacific/Indian Ocean Throughflow are presented for the region between northwest Australia and Java-Timor. The mean relative geostrophic transport (0/400 db) of Throughflow is approximately 5 x 106 m3/sec. A nearly equal volume transport is associated with the reference velocity at 400 db. The Throughflow feeds the South Equatorial Current, which has maximum westward flow in August/September, at the end of the southeasterly Monsoon season. A strong semiannual oscillation in the South Java Current is documented. The results are in good agreement with the Semtner and Chervin (1988) ocean general circulation model. The talk concludes with comments on data inadequacies (insufficient coverage, timeliness) particular to the Indian Ocean and suggestions on the future role that can be played by Data Centers, particularly with regard to quality control of data as research bodies are replaced by operational bodies in the Global Ocean Observing System.
The importance of an accurate knowledge of the time bias corrections to predicted orbits to a satellite laser ranging (SLR) observer, especially for low satellites, is highlighted. Sources of time bias values and the optimum strategy for extrapolation are discussed from the viewpoint of the observer wishing to maximize the chances of getting returns from the next pass. What is said may be seen as a commercial encouraging wider and speedier use of existing data centers for mutually beneficial exchange of time bias data.
The historical archives of in situ (National Oceanographic Data Center) and satellite (Coastal Zone Color Scanner) chlorophyll data were combined using the blended analysis method of Reynolds [1988] in an attempt to construct an improved climatological seasonal representation of global chlorophyll distributions. The results of the blended analysis differed dramatically from the CZCS representation: global chlorophyll estimates increased 8-35% in the blended analysis depending upon season. Regional differences were even larger, up to 140% in the equatorial Indian Ocean in summer (during the southwest monsoon). Tropical Pacific chlorophyll values increased 25-41%. The results suggested that the CZCS generally underestimates chlorophyll. Regional and seasonal differences in the blended analysis were sufficiently large as to produce a different representation of global chlorophyll distributions than otherwise inferred from CZCS data alone. Analyses of primary production and biogeochemical cycles may be substantially impacted by these results.
This NOAA/NASA Pathfinder effort was established to locate, acquire, and process Advanced Very High Resolution Radiometer (AVHRR) imagery into geo-located and calibrated radiances, cloud masks, surface clear-sky broadband albedo, clear-sky skin temperatures, satellite viewing times, and viewing and solar geometry for the, high-latitude portions of the northern and southern hemispheres (all area north of 48N and south of 53S). AVHRR GAC data for August 1981 - July 1998 were acquired, with some gaps remaining, and processed into twice-daily 5-km grids, with some products also provided at 25-km resolution. AVHRR LAC data for 3.5 years of coverage in the northern hemisphere and 2.75 years of coverage in the southern hemisphere were processed into 1.25-km grids for the same suite of products. The resulting data sets are presently being transferred to the National Snow and Ice Data Center (NSIDC) for archiving and distribution. Using these data, researchers now have at their disposal an extensive AVHRR data set for investigations of high-latitude processes. In addition, the data lend themselves to development and testing of algorithms. The products are particularly relevant for climate research and algorithm development as applied to relatively long time periods and large areas.
The EOS Data Products Handbook provides brief descriptions of the data products that will be produced from a range of missions of the Earth Observing System (EOS) and associated projects. Volume 1, originally published in 1997, covers the Tropical Rainfall Measuring Mission (TRMM), the Terra mission (formerly named EOS AM-1), and the Data Assimilation System, while this volume, Volume 2, covers the Active Cavity Radiometer Irradiance Monitor Satellite (ACRIMSAT), Aqua, Jason-1, Landsat 7, Meteor 3M/Stratospheric Aerosol and Gas Experiment III (SAGE III). the Quick Scatterometer (QuikScat), the Quick Total Ozone Mapping Spectrometer (Quik-TOMS), and the Vegetation Canopy Lidar (VCL) missions. Volume 2 follows closely the format of Volume 1, providing a list of products and an introduction and overview descriptions of the instruments and data processing, all introductory to the core of the book, which presents the individual data product descriptions, organized into 11 topical chapters. The product descriptions are followed by five appendices, which provide contact information for the EOS data centers that will be archiving and distributing the data sets, contact information for the science points of contact for the data products, references, acronyms and abbreviations, and a data products index.
The high volume of Earth Observing System data has proven to be challenging to manage for data centers and users alike. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), about 1 TB of new data are archived each day. Distribution to users is also about 1 TB/day. A substantial portion of this distribution is MODIS calibrated radiance data, which has a wide variety of uses. However, much of the data is not useful for a particular user's needs: for example, ocean color users typically need oceanic pixels that are free of cloud and sun-glint. The GES DAAC is using a simple Bayesian classification scheme to rapidly classify each pixel in the scene in order to support several experimental content-based data services for near-real-time MODIS calibrated radiance products (from Direct Readout stations). Content-based subsetting would allow distribution of, say, only clear pixels to the user if desired. Content-based subscriptions would distribute data to users only when they fit the user's usability criteria in their area of interest within the scene. Content-based cache management would retain more useful data on disk for easy online access. The classification may even be exploited in an automated quality assessment of the geolocation product. Though initially to be demonstrated at the GES DAAC, these techniques have applicability in other resource-limited environments, such as spaceborne data systems.
Assessment of National Airspace System performance, which is usually measured in terms of delays resulting from the application of traffic flow management initiatives in response to weather conditions, volume, equipment outages and runway conditions, is needed both for guiding flow control decisions during the day of operations and for post operations analysis. Comparison of the actual delay, resulting from the traffic flow management initiatives, with the expected delay, based on traffic demand and other conditions, provides the assessment of the National Airspace System performance. This paper provides a method for estimating delay using the expected traffic demand and weather. In order to identify the cause of delays, 517 days of National Airspace System delay data reported by the Federal Aviation Administration s Operations Network were analyzed. This analysis shows that weather is the most important causal factor for delays followed by equipment and runway delays. Guided by these results, the concept of weather weighted traffic counts as a measure of system delay is described. Examples are given to show the variation of these counts as a function of time of the day. The various datasets, consisting of aircraft position data, enroute severe weather data, surface wind speed and visibility data, reported delay data and number of aircraft handled by the Centers data, and their sources are described. The procedure for selecting reference days on which traffic was minimally impacted by weather is described. Different traffic demand on each reference day of the week, determined by analysis of 42 days of traffic and delay data, was used as the expected traffic demand for each day of the week. Next, the method for computing the weather weighted traffic counts using the expected traffic demand, derived from reference days, and the expanded regions around severe weather cells is discussed. It is shown via a numerical example that this approach improves the dynamic range of the weather weighted traffic counts considerably. Time histories of these new weather weighted traffic counts are used for synthesizing two statistical features, six histogram features and six time domain features. In addition to these enroute weather features, two surface weather features of number of major airports in the United States with high mean winds and low mean visibility are also described. A least squares procedure for establishing a functional relation between the features, using combinations of these features, and system delays is explored using 36 days of data. Best correlations between the estimated delays using the functional relation and the actual delays provided by the Operations Network are obtained with two different combinations of features: 1) six time domain features of weather weighted traffic counts plus two surface weather features, and 2) six histogram features and mean of weather weighted traffic counts along with the two surface weather features. Correlation coefficient values of 0.73 and 0.83 were found in these two instances.
Plasmapause transitions, as seen in the H + and He+ density gradients measured by the Orbiting Geophysical Observatory 5 (OGO 5) ion spectrometer [Sharp, IEE Trans. in Geosci. Elect., 1969], have been investigated in an attempt to relate them to their topside ionospheric signatures as seen in the Alouette-1 & 2 and ISIS-1 data. The satellite data were obtained from the National Space Science Data Center (NSSDC). A search of the OGO-5 data revealed 54 sharp plasmapause crossings as evaluated from the H+ density. The ionospheric footprints (at 1400 km altitude) of the magnetic-field lines through the locations of these plasmapause crossings were then used to search for topside ionospheric electron-density profiles from the NSSDC. No profiles corresponding to these projections were identified. A similar search of the topside-sounder 35-mm ionogram-film database, however, identified 17 cases of candidate "conjunctions" involving Alouette l & 2 and ISIS 1. We will present samples of the plasmapause OGO-5 ion transitions and the related topside ionospheric signatures and discuss the observations in relation to the recent similar study based on Explorer-45 and ISIS-2 data [Grebowsky et al., JASTP, 2009].
Recently, it has become easier to access climate data from satellites, ground measurements, and models from various data centers, However, searching. accessing, and prc(essing heterogeneous data from different sources are very tim -consuming tasks. There is lack of a comprehensive visual platform to acquire distributed and heterogeneous scientific data and to render processed images from a single accessing point for climate studies. This paper. documents the design and implementation of a Web-based visual, interoperable, and scalable platform that is able to access climatological fields from models, satellites, and ground stations from a number of data sources using Google Earth (GE) as a common graphical interface. The development is based on the TCP/IP protocol and various data sharing open sources, such as OPeNDAP, GDS, Web Processing Service (WPS), and Web Mapping Service (WMS). The visualization capability of integrating various measurements into cE extends dramatically the awareness and visibility of scientific results. Using embedded geographic information in the GE, the designed system improves our understanding of the relationships of different elements in a four dimensional domain. The system enables easy and convenient synergistic research on a virtual platform for professionals and the general public, gr$tly advancing global data sharing and scientific research collaboration.
A suite of automated scientific instruments (the Apollo Lunar Surface Experiment Package, or ALSEP) was installed at each of the landing sites of Apollo 12, 14, 15, 16, and 17 from 1969 to 1972. They operated from deployment until decommissioning on 30 September 1977. These data were continuously transmitted to Earth and saved on the Range Tapes, which were recorded at the Manned Space Flight Network stations. These data were also broken out by experiment and sent to the experiment Principal Investigators on what were called the P.I. Tapes. Starting in April 1973 the Range Tape data were stored in digital format on 7-track magnetic tapes, the ARCSAV Tapes. In February 1976, the handling of the Range Tapes was transferred to UT Galveston. They produced 9-track tapes referred to as the Work Tapes. Following the Apollo program the Range and ARCSAV tapes, which were never archived, were lost. The Work Tapes were archived at the National Space Science Data Center (NSSDC). Some investigators archived their individual experiment data with NSSDC as well, but much of the data had minimal documentation, were not in digital form, or were stored in difficult to translate formats. Data from many experiments were never delivered to the NSSDC. The Lunar Data Project was started to address the problem of both missing and not readily usable data. Our effort has resulted in recovery of some of the ARCSAV tapes, recovery and digitization of a large volume of Apollo scientific and technical documentation, and restoration of many ALSEP and other Apollo data collections. Restoration involves deciphering formats, assembling necessary ancillary data (metadata), and packaging data in digital format to be archived with the Planetary Data System (PDS). Recovery of the data from the ARCSAV tapes involved having the tapes read on special equipment and extracting the individual experiment data out of the integrated data stream. We will report on the history and status of the various recovery efforts.
We present the discovery from Transiting Exoplanet Survey Satellite (TESS) data of LTT 1445Ab. At a distance of 6.9 pc, it is the second nearest transiting exoplanet system found to date, and the closest one known for which the primary is an M dwarf. The host stellar system consists of three mid-to-late M dwarfs in a hierarchical configuration, which are blended in one TESS pixel. We use MEarth data and results from the Science Processing Operations Center data validation report to determine that the planet transits the primary star in the system. The planet has a radius of {1.38}_{-0.12}^{+0.13} {R}_{\oplus }, an orbital period of {5.35882}_{-0.00031}^{+0.00030} days, and an equilibrium temperature of {433}_{-27}^{+28} K. With radial velocities from the High Accuracy Radial Velocity Planet Searcher, we place a 3σ upper mass limit of 8.4 {M}_{\oplus } on the planet. LTT 1445Ab provides one of the best opportunities to date for the spectroscopic study of the atmosphere of a terrestrial world. We also present a detailed characterization of the host stellar system. We use high-resolution spectroscopy and imaging to rule out the presence of any other close stellar or brown dwarf companions. Nineteen years of photometric monitoring of A and BC indicate a moderate amount of variability, in agreement with that observed in the TESS light-curve data. We derive a preliminary astrometric orbit for the BC pair that reveals an edge-on and eccentric configuration. The presence of a transiting planet in this system hints that the entire system may be co-planar, implying that the system may have formed from the early fragmentation of an individual protostellar core.
NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven dataset discovery, where users seek publications on projects similar to their intended study. For this approach to be effective, users need a clear connection between the underlying data in the publications and the study objectives; this is not often apparent to non-expert users. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. As an illustration of these challenges, in this work we focus on the atmospheric chemistry processes related to Earth environmental impacts such as ozone depletion, aerosols, smog formation, acid rain, and radiative forcing. We further limit our study to publications that use data from the Microwave Limb Sounder (MLS) instrument flown on the Aura Earth Observing System. To create knowledge representations of science carried out in these publications, we use existing ontologies such as the Global Change Master Directory (GCMD) and Semantic Web for Earth and Environmental Terminology (SWEET). These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, action words, among many others. Based on these terms acknowledge graph database was populated with the terms retrieved from scientific publications that study atmospheric chemistry. These databases can be used to further enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. These tools and methods can also be extended to apply to content from other related Earth science domains.
Attribution of datasets that were used to generate research results described in peer-reviewed publications to the original source of these datasets (which are often archived at NASA Earth Science data centers) has been very challenging. Even though the data citation standard of citing datasets as research artifacts and citing them with Digital Object Identifiers (DOIs) was introduced over a decade ago, most authors do not properly reference the data used in their studies and merely mention them in the text. The lack of proper citations of datasets makes the peer-reviewed publication less transparent, imperils reproducibility, and impedes open science. We offer an open-source publication management methodology and a tool that can help to enhance usage-based data discovery, prominence, and provenance of the data; reproducibility of the research results; and potentially increase the return on investment on NASA-funded research.
The worldwide ionospheric data base is scattered over the entire globe. Different data sets are held at different institutions in the U.S., U.S.S.R., Australia, Europe, and Asia. The World Data Centers on the different continents archive and distribute part of the huge data base; the scope and cross section of the individual data holdings depend on the regional and special interest of the center. An attempt is made to pull together all the strings that point toward different ionospheric data holdings. Requesters are provided with the information about what is available and where to get it. An attempt is also made to evaluate the reliability and compatibility of the different data sets based on the consensus in the ionospheric research community. The status and accuracy of the standard ionospheric models are also discussed because they may facilitate first order assessment of ionospheric effects. This is a first step toward an ionospheric data directory within the framework of NSSDC's master directory.
We will present our recovery of Voyager 1 and 2 plasma electron observations during their Jupiter flybys. The analysis is expected to be completed by the time of the Fall AGU 2023 Meeting and stored in Goddard’s Data Center and we will present new results never published before. The original summary data tapes and later data files at first appeared to be permanently lost but eventually located at the Massachusetts Institute of Technology, while data analysis results done at Goddard Space Flight Center, except for that published in journals, were permanently lost such as electron distribution functions, spacecraft trajectory and spacecraft attitude information. In addition to recovering the electron plasma observations (electron intensities and fluid parameters of the thermal and suprathermal electron populations, respectively), we use Spice Kernels for Voyager 1 and 2 trajectory and spacecraft attitude information, fortunately produced by NASA’s Jet Propulsion Laboratory. We will present new results of our work, originally funded under the Planetary Data Archiving, Restoration, and Tools (PDART) program but now being funded by the Internal Scientist Funding Model (ISFM) Exosphere Ionosphere Magnetospheres Modeling (EIMM) program at NASA Goddard Space Flight Center. If time permits, we will also present some of our recovery of the Voyager 2 Uranus plasma electron data and analysis similar to what was done for Jupiter.
We will present our recovery of Voyager 1 and 2 plasma electron observations during their Jupiter flybys. The analysis is expected to be completed by the time of the Fall AGU 2023 Meeting and stored in Goddard’s Data Center and we will present new results never published before. The original summary data tapes and later data files at first appeared to be permanently lost but eventually located at the Massachusetts Institute of Technology, while data analysis results done at Goddard Space Flight Center, except for that published in journals, were permanently lost such as electron distribution functions, spacecraft trajectory and spacecraft attitude information. In addition to recovering the electron plasma observations (electron intensities and fluid parameters of the thermal and suprathermal electron populations, respectively), we use Spice Kernels for Voyager 1 and 2 trajectory and spacecraft attitude information, fortunately produced by NASA’s Jet Propulsion Laboratory. We will present new results of our work, originally funded under the Planetary Data Archiving, Restoration, and Tools (PDART) program but now being funded by the Internal Scientist Funding Model (ISFM) Exosphere Ionosphere Magnetospheres Modeling (EIMM) program at NASA Goddard Space Flight Center. If time permits, we will also present some of our recovery of the Voyager 2 Uranus plasma electron data and analysis similar to what was done for Jupiter.