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Found 6 result(s)
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The Data Center for Aurora in NIPR is responsible for data archiving and dissemination of all-sky camera observations, visual observations, other optical observations (such as TV and photometric observations), auroral image and particle observations from satellites, geomagnetic observations, and observations of upper atmosphere phenomena associated with aurora such as ULF, VLF and CNA activities. This Data Catalogue summarizes the collection of data sets, data books, related publications and facilities available in the WDC for Aurora as of December 2003. The WDC for Aurora changed its name as "Data Center for Aurora in NIPR" in 2008 due to the disappearance of the WDC panel in ICSU.
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AVISO stands for "Archiving, Validation and Interpretation of Satellite Oceanographic data". Here, you will find data, articles, news and tools to help you discover or improve your skills in the altimetry domain through four key themes: ocean, coast, hydrology and ice. Altimetry is a technique for measuring height. Satellite altimetry measures the time taken by a radar pulse to travel from the satellite antenna to the surface and back to the satellite receiver. Combined with precise satellite location data, altimetry measurements yield sea-surface heights.
The SAR Data Center has a large data archive of Synthetic Aperture Radar (SAR) from a variety of sensors available at no cost. Much of the SAR data in the ASF SDC archive is limited in distribution to the scientific research community and U.S. Government Agencies. In accordance with the Memoranda of Understanding (MOU) between the relevant flight agencies (CSA, ESA, JAXA) and the U.S. State Department, the ASF SDC does not distribute SAR data for commercial use. The research community can access the data (ERS-1, ERS-2, JERS-1, RADARSAT-1, and ALOS PALSAR) via a brief proposal process.
When published in 2005, the Millennium Run was the largest ever simulation of the formation of structure within the ΛCDM cosmology. It uses 10(10) particles to follow the dark matter distribution in a cubic region 500h(−1)Mpc on a side, and has a spatial resolution of 5h−1kpc. Application of simplified modelling techniques to the stored output of this calculation allows the formation and evolution of the ~10(7) galaxies more luminous than the Small Magellanic Cloud to be simulated for a variety of assumptions about the detailed physics involved. As part of the activities of the German Astrophysical Virtual Observatory we have created relational databases to store the detailed assembly histories both of all the haloes and subhaloes resolved by the simulation, and of all the galaxies that form within these structures for two independent models of the galaxy formation physics. We have implemented a Structured Query Language (SQL) server on these databases. This allows easy access to many properties of the galaxies and halos, as well as to the spatial and temporal relations between them. Information is output in table format compatible with standard Virtual Observatory tools. With this announcement (from 1/8/2006) we are making these structures fully accessible to all users. Interested scientists can learn SQL and test queries on a small, openly accessible version of the Millennium Run (with volume 1/512 that of the full simulation). They can then request accounts to run similar queries on the databases for the full simulations. In 2008 and 2012 the simulations were repeated.
<<<!!!<<< This repository is no longer available. >>>!!!>>>The Deep Carbon Observatory (DCO) is a global community of multi-disciplinary scientists unlocking the inner secrets of Earth through investigations into life, energy, and the fundamentally unique chemistry of carbon. Deep Carbon Observatory Digital Object Registry (“DCO-VIVO”) is a centrally-managed digital object identification, object registration and metadata management service for the DCO. Digital object registration includes DCO-ID generation based on the global Handle System infrastructure and metadata collection using VIVO. Users will be able to deposit their data into the DCO Data Repository and have that data discoverable and accessible by others.