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Title: Ultrascale Visualization of Climate Data

To support interactive visualization and analysis of complex, large-scale climate data sets, UV-CDAT integrates a powerful set of scientific computing libraries and applications to foster more efficient knowledge discovery. Connected through a provenance framework, the UV-CDAT components can be loosely coupled for fast integration or tightly coupled for greater functionality and communication with other components. This framework addresses many challenges in the interactive visual analysis of distributed large-scale data for the climate community.
Authors:
 [1] ;  [1] ;  [1] ;  [2] ;  [2] ;  [3] ;  [3] ;  [3] ;  [3] ;  [3] ;  [4] ;  [4] ;  [4] ;  [5] ;  [6] ;  [7] ;  [7] ;  [8] ;  [9] ;  [9] more »;  [9] ;  [10] ;  [10] ;  [11] ;  [11] « less
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  5. New York University, New York, NY (United States). Center for Urban Sciences
  6. Universidade Federal do Ceara, Ceara (Brazil)
  7. New York University, New York, NY (United States)
  8. Polytechnic Institute of New York University, New York, NY (United States)
  9. Kitware Inc., Clifton Park, NY (United States)
  10. Tech-X Corporation, Boulder, CO (United States)
  11. National Aeronautics and Space Administration (NASA), Washington, DC (United States)
Publication Date:
OSTI Identifier:
1092271
DOE Contract Number:
AC05-00OR22725; AC02-05CH11231; AC52-07NA27344
Resource Type:
Journal Article
Resource Relation:
Journal Name: Computer; Journal Volume: 46; Journal Issue: 9
Research Org:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Center for Computational Sciences
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); USNASA
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING climate; visualization; data analysis; big data